Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Cao, Xiangyong; Zhou, Feng; Xu, Lin; Meng, Deyu; Xu, Zongben; Paisley, John

2018-05-01

This paper presents a new supervised classification algorithm for remotely sensed hyperspectral image (HSI) which integrates spectral and spatial information in a unified Bayesian framework. First, we formulate the HSI classification problem from a Bayesian perspective. Then, we adopt a convolutional neural network (CNN) to learn the posterior class distributions using a patch-wise training strategy to better use the spatial information. Next, spatial information is further considered by placing a spatial smoothness prior on the labels. Finally, we iteratively update the CNN parameters using stochastic gradient decent (SGD) and update the class labels of all pixel vectors using an alpha-expansion min-cut-based algorithm. Compared with other state-of-the-art methods, the proposed classification method achieves better performance on one synthetic dataset and two benchmark HSI datasets in a number of experimental settings.

Detecting and preventing error propagation via competitive learning.

PubMed

Silva, Thiago Christiano; Zhao, Liang

2013-05-01

Semisupervised learning is a machine learning approach which is able to employ both labeled and unlabeled samples in the training process. It is an important mechanism for autonomous systems due to the ability of exploiting the already acquired information and for exploring the new knowledge in the learning space at the same time. In these cases, the reliability of the labels is a crucial factor, because mislabeled samples may propagate wrong labels to a portion of or even the entire data set. This paper has the objective of addressing the error propagation problem originated by these mislabeled samples by presenting a mechanism embedded in a network-based (graph-based) semisupervised learning method. Such a procedure is based on a combined random-preferential walk of particles in a network constructed from the input data set. The particles of the same class cooperate among them, while the particles of different classes compete with each other to propagate class labels to the whole network. Computer simulations conducted on synthetic and real-world data sets reveal the effectiveness of the model. Copyright © 2012 Elsevier Ltd. All rights reserved.

49 CFR 172.402 - Additional labeling requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 30, 2001, such as, a label without the hazard class or division number displayed in the lower corner... this section); and (2)For other than Class 1 or Class 2 materials (for subsidiary labeling requirements for Class 1 or Class 2 materials see paragraph (e) or paragraphs (f) and (g), respectively, of this...

Automatic Classification of High Resolution Satellite Imagery - a Case Study for Urban Areas in the Kingdom of Saudi Arabia

NASA Astrophysics Data System (ADS)

Maas, A.; Alrajhi, M.; Alobeid, A.; Heipke, C.

2017-05-01

Updating topographic geospatial databases is often performed based on current remotely sensed images. To automatically extract the object information (labels) from the images, supervised classifiers are being employed. Decisions to be taken in this process concern the definition of the classes which should be recognised, the features to describe each class and the training data necessary in the learning part of classification. With a view to large scale topographic databases for fast developing urban areas in the Kingdom of Saudi Arabia we conducted a case study, which investigated the following two questions: (a) which set of features is best suitable for the classification?; (b) what is the added value of height information, e.g. derived from stereo imagery? Using stereoscopic GeoEye and Ikonos satellite data we investigate these two questions based on our research on label tolerant classification using logistic regression and partly incorrect training data. We show that in between five and ten features can be recommended to obtain a stable solution, that height information consistently yields an improved overall classification accuracy of about 5%, and that label noise can be successfully modelled and thus only marginally influences the classification results.

Facts about Microcephaly

MedlinePlus

... input class="button submit" name="commit" type="submit" value="Submit" /> Information For… Media Policy ... and Severe Microcephaly Comparison The images are in the public domain and thus free of any copyright restrictions. As a matter of ...

Review of nutrition labeling formats.

PubMed

Geiger, C J; Wyse, B W; Parent, C R; Hansen, R G

1991-07-01

This article examines nutrition labeling history as well as the findings of nine research studies of nutrition labeling formats. Nutrition labeling regulations were announced in 1973 and have been periodically amended since then. In response to requests from consumers and health care professionals for revision of the labeling system, the Food and Drug Administration initiated a three-phase plan for reform of nutrition labeling in 1990. President Bush signed the Nutrition Labeling and Education Act in November 1990. Literature analysis revealed that only nine studies with an experimental design have focused on nutrition labeling since 1971. Four were conducted before 1975, which was the year that nutrition labeling was officially implemented, two were conducted in 1980, and three were conducted after 1986. Only two of the nine studies supported the traditional label format mandated by the Code of Federal Regulations, and one study partially supported it. Four of the nine studies that evaluated graphic presentations of nutrition information found that consumer comprehension of nutrition information was improved with a graphic format for nutrition labeling: three studies supported the use of bar graphs and one study supported the use of a pie chart. Full disclosure (ie, complete nutrient and ingredient labeling) was preferred by consumers in two of the three studies that examined this variable. The third study supported three types of information disclosure dependent upon socioeconomic class. In those studies that tested graphics, a bar graph format was significantly preferred and showed better consumer comprehension than the traditional format.

An Oracle-based co-training framework for writer identification in offline handwriting

NASA Astrophysics Data System (ADS)

Porwal, Utkarsh; Rajan, Sreeranga; Govindaraju, Venu

2012-01-01

State-of-the-art techniques for writer identification have been centered primarily on enhancing the performance of the system for writer identification. Machine learning algorithms have been used extensively to improve the accuracy of such system assuming sufficient amount of data is available for training. Little attention has been paid to the prospect of harnessing the information tapped in a large amount of un-annotated data. This paper focuses on co-training based framework that can be used for iterative labeling of the unlabeled data set exploiting the independence between the multiple views (features) of the data. This paradigm relaxes the assumption of sufficiency of the data available and tries to generate labeled data from unlabeled data set along with improving the accuracy of the system. However, performance of co-training based framework is dependent on the effectiveness of the algorithm used for the selection of data points to be added in the labeled set. We propose an Oracle based approach for data selection that learns the patterns in the score distribution of classes for labeled data points and then predicts the labels (writers) of the unlabeled data point. This method for selection statistically learns the class distribution and predicts the most probable class unlike traditional selection algorithms which were based on heuristic approaches. We conducted experiments on publicly available IAM dataset and illustrate the efficacy of the proposed approach.

The influence of need for cognition and principal display panel factors on over-the-counter drug facts label comprehension.

PubMed

Catlin, Jesse R; Pechmann, Cornelia; Brass, Eric P

2012-01-01

Nearly all work aimed at optimizing the ability of labeling to communicate over-the-counter (OTC) drug information has focused on back-of-the-package characteristics, such as the Drug Facts label. The effects of front of the package, or principal display panel (PDP) factors, have largely been neglected by researchers. Similarly, heterogeneity in consumers' approach to new information has received scant attention in the context of OTC drugs. This preliminary study tested the hypothesis that display of a drug's brand name on the PDP and individuals' need for cognition influence comprehension of Drug Facts label information. University students (n = 212) that had experienced heartburn but not used the drug class being studied constituted the primary analysis cohort. Students were randomly assigned to review one of two PDPs (brand name or generic), followed by a Drug Facts label and a series of questions related to selection and usage of the drug. Participants with low need for cognition were influenced by the brand name PDP, as those exposed to a PDP featuring a brand (vs. generic) spent less time reading the Drug Facts label and demonstrated lower comprehension of the label information on proper drug selection. These findings suggest that further research is needed to understand the impact of PDP contents and cognitive characteristics of consumers on the communication of OTC drug information. Health care providers should consider communication strategies that account for the challenges patients face in using OTC drugs properly.

Approaching the axiomatic enrichment of the Gene Ontology from a lexical perspective.

PubMed

Quesada-Martínez, Manuel; Mikroyannidi, Eleni; Fernández-Breis, Jesualdo Tomás; Stevens, Robert

2015-09-01

The main goal of this work is to measure how lexical regularities in biomedical ontology labels can be used for the automatic creation of formal relationships between classes, and to evaluate the results of applying our approach to the Gene Ontology (GO). In recent years, we have developed a method for the lexical analysis of regularities in biomedical ontology labels, and we showed that the labels can present a high degree of regularity. In this work, we extend our method with a cross-products extension (CPE) metric, which estimates the potential interest of a specific regularity for axiomatic enrichment in the lexical analysis, using information on exact matches in external ontologies. The GO consortium recently enriched the GO by using so-called cross-product extensions. Cross-products are generated by establishing axioms that relate a given GO class with classes from the GO or other biomedical ontologies. We apply our method to the GO and study how its lexical analysis can identify and reconstruct the cross-products that are defined by the GO consortium. The label of the classes of the GO are highly regular in lexical terms, and the exact matches with labels of external ontologies affect 80% of the GO classes. The CPE metric reveals that 31.48% of the classes that exhibit regularities have fragments that are classes into two external ontologies that are selected for our experiment, namely, the Cell Ontology and the Chemical Entities of Biological Interest ontology, and 18.90% of them are fully decomposable into smaller parts. Our results show that the CPE metric permits our method to detect GO cross-product extensions with a mean recall of 62% and a mean precision of 28%. The study is completed with an analysis of false positives to explain this precision value. We think that our results support the claim that our lexical approach can contribute to the axiomatic enrichment of biomedical ontologies and that it can provide new insights into the engineering of biomedical ontologies. Copyright © 2014 Elsevier B.V. All rights reserved.

10 CFR 61.57 - Labeling.

Code of Federal Regulations, 2012 CFR

2012-01-01

... COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE Technical Requirements for Land Disposal Facilities § 61.57 Labeling. Each package of waste must be clearly labeled to identify whether it is Class A waste, Class B waste, or Class C waste, in accordance with § 61.55. ...

10 CFR 61.57 - Labeling.

Code of Federal Regulations, 2010 CFR

2010-01-01

... COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE Technical Requirements for Land Disposal Facilities § 61.57 Labeling. Each package of waste must be clearly labeled to identify whether it is Class A waste, Class B waste, or Class C waste, in accordance with § 61.55. ...

10 CFR 61.57 - Labeling.

Code of Federal Regulations, 2011 CFR

2011-01-01

... COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE Technical Requirements for Land Disposal Facilities § 61.57 Labeling. Each package of waste must be clearly labeled to identify whether it is Class A waste, Class B waste, or Class C waste, in accordance with § 61.55. ...

10 CFR 61.57 - Labeling.

Code of Federal Regulations, 2014 CFR

2014-01-01

... COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE Technical Requirements for Land Disposal Facilities § 61.57 Labeling. Each package of waste must be clearly labeled to identify whether it is Class A waste, Class B waste, or Class C waste, in accordance with § 61.55. ...

10 CFR 61.57 - Labeling.

Code of Federal Regulations, 2013 CFR

2013-01-01

... COMMISSION (CONTINUED) LICENSING REQUIREMENTS FOR LAND DISPOSAL OF RADIOACTIVE WASTE Technical Requirements for Land Disposal Facilities § 61.57 Labeling. Each package of waste must be clearly labeled to identify whether it is Class A waste, Class B waste, or Class C waste, in accordance with § 61.55. ...

A machine learning pipeline for automated registration and classification of 3D lidar data

NASA Astrophysics Data System (ADS)

Rajagopal, Abhejit; Chellappan, Karthik; Chandrasekaran, Shivkumar; Brown, Andrew P.

2017-05-01

Despite the large availability of geospatial data, registration and exploitation of these datasets remains a persis- tent challenge in geoinformatics. Popular signal processing and machine learning algorithms, such as non-linear SVMs and neural networks, rely on well-formatted input models as well as reliable output labels, which are not always immediately available. In this paper we outline a pipeline for gathering, registering, and classifying initially unlabeled wide-area geospatial data. As an illustrative example, we demonstrate the training and test- ing of a convolutional neural network to recognize 3D models in the OGRIP 2007 LiDAR dataset using fuzzy labels derived from OpenStreetMap as well as other datasets available on OpenTopography.org. When auxiliary label information is required, various text and natural language processing filters are used to extract and cluster keywords useful for identifying potential target classes. A subset of these keywords are subsequently used to form multi-class labels, with no assumption of independence. Finally, we employ class-dependent geometry extraction routines to identify candidates from both training and testing datasets. Our regression networks are able to identify the presence of 6 structural classes, including roads, walls, and buildings, in volumes as big as 8000 m3 in as little as 1.2 seconds on a commodity 4-core Intel CPU. The presented framework is neither dataset nor sensor-modality limited due to the registration process, and is capable of multi-sensor data-fusion.

7 CFR 201.74 - Labeling of all classes of certified seed.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 3 2011-01-01 2011-01-01 false Labeling of all classes of certified seed. 201.74... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Certified Seed § 201.74 Labeling of all classes of certified seed. (a...

7 CFR 201.74 - Labeling of all classes of certified seed.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 3 2010-01-01 2010-01-01 false Labeling of all classes of certified seed. 201.74... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Certified Seed § 201.74 Labeling of all classes of certified seed. (a...

Semantic image segmentation with fused CNN features

NASA Astrophysics Data System (ADS)

Geng, Hui-qiang; Zhang, Hua; Xue, Yan-bing; Zhou, Mian; Xu, Guang-ping; Gao, Zan

2017-09-01

Semantic image segmentation is a task to predict a category label for every image pixel. The key challenge of it is to design a strong feature representation. In this paper, we fuse the hierarchical convolutional neural network (CNN) features and the region-based features as the feature representation. The hierarchical features contain more global information, while the region-based features contain more local information. The combination of these two kinds of features significantly enhances the feature representation. Then the fused features are used to train a softmax classifier to produce per-pixel label assignment probability. And a fully connected conditional random field (CRF) is used as a post-processing method to improve the labeling consistency. We conduct experiments on SIFT flow dataset. The pixel accuracy and class accuracy are 84.4% and 34.86%, respectively.

Active Learning Framework for Non-Intrusive Load Monitoring: Preprint

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

Jin, Xin

2016-05-16

Non-Intrusive Load Monitoring (NILM) is a set of techniques that estimate the electricity usage of individual appliances from power measurements taken at a limited number of locations in a building. One of the key challenges in NILM is having too much data without class labels yet being unable to label the data manually for cost or time constraints. This paper presents an active learning framework that helps existing NILM techniques to overcome this challenge. Active learning is an advanced machine learning method that interactively queries a user for the class label information. Unlike most existing NILM systems that heuristically requestmore » user inputs, the proposed method only needs minimally sufficient information from a user to build a compact and yet highly representative load signature library. Initial results indicate the proposed method can reduce the user inputs by up to 90% while still achieving similar disaggregation performance compared to a heuristic method. Thus, the proposed method can substantially reduce the burden on the user, improve the performance of a NILM system with limited user inputs, and overcome the key market barriers to the wide adoption of NILM technologies.« less

Mining big data sets of plankton images: a zero-shot learning approach to retrieve labels without training data

NASA Astrophysics Data System (ADS)

Orenstein, E. C.; Morgado, P. M.; Peacock, E.; Sosik, H. M.; Jaffe, J. S.

2016-02-01

Technological advances in instrumentation and computing have allowed oceanographers to develop imaging systems capable of collecting extremely large data sets. With the advent of in situ plankton imaging systems, scientists must now commonly deal with "big data" sets containing tens of millions of samples spanning hundreds of classes, making manual classification untenable. Automated annotation methods are now considered to be the bottleneck between collection and interpretation. Typically, such classifiers learn to approximate a function that predicts a predefined set of classes for which a considerable amount of labeled training data is available. The requirement that the training data span all the classes of concern is problematic for plankton imaging systems since they sample such diverse, rapidly changing populations. These data sets may contain relatively rare, sparsely distributed, taxa that will not have associated training data; a classifier trained on a limited set of classes will miss these samples. The computer vision community, leveraging advances in Convolutional Neural Networks (CNNs), has recently attempted to tackle such problems using "zero-shot" object categorization methods. Under a zero-shot framework, a classifier is trained to map samples onto a set of attributes rather than a class label. These attributes can include visual and non-visual information such as what an organism is made out of, where it is distributed globally, or how it reproduces. A second stage classifier is then used to extrapolate a class. In this work, we demonstrate a zero-shot classifier, implemented with a CNN, to retrieve out-of-training-set labels from images. This method is applied to data from two continuously imaging, moored instruments: the Scripps Plankton Camera System (SPCS) and the Imaging FlowCytobot (IFCB). Results from simulated deployment scenarios indicate zero-shot classifiers could be successful at recovering samples of rare taxa in image sets. This capability will allow ecologists to identify trends in the distribution of difficult to sample organisms in their data.

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

Zhang, Guo Qiang; Luo, Lingyun; Ogbuji, Chime

The interaction of multiple types of relationships among anatomical classes in the Foundational Model of Anatomy (FMA) can provide inferred information valuable for quality assurance. This paper introduces a method called Motif Checking (MOCH) to study the effects of such multi-relation type interactions. MOCH represents patterns of multitype interaction as small labeled sub-graph motifs, whose nodes represent class variables, and labeled edges represent relational types. By representing FMA as an RDF graph and motifs as SPARQL queries, fragments of FMA are automatically obtained as auditing candidates. Leveraging the scalability and reconfigurability of Semantic Web Technology (OWL, RDF and SPARQL) andmore » Virtuoso, we performed exhaustive analyses of three 2-node motifs, resulting in 638 matching FMA configurations; twelve 3-node motifs, resulting in 202,960 configurations. Using the Principal Ideal Explorer (PIE) methodology as an extension of MOCH, we were able to identify 755 root nodes with 4,100 respective descendants with opposing antonyms in their class names for arbitrary-length motifs. With possible disjointness implied by antonyms, we performed manual inspection of a subset of the resulting FMA fragments and tracked down a source of abnormal inferred conclusions (captured by the motifs), coming from a gender-neutral class being modeled as a part of gender-specific class, such as “Urinary system” is a part of “Female human body.” Our results demonstrate that MOCH and PIE provide a unique source of valuable information for quality assurance. Since our approach is general, it is applicable to any ontological system with an OWL representation.« less

An Analysis of “Natural” Food Litigation to Build a Sesame Allergy Consumer Class Action.

PubMed

Shaker, Dana

In a world where food allergy is still an incurable disease, law and regulation stand as necessary mechanisms to provide food-allergic consumers with the information they need to protect their health. The Food Allergen Labeling and Consumer Protection Act of 2004 provided specific labeling requirements for the “Top Eight” allergens in the U.S.: milk, soy, gluten, egg, tree nut, peanut, fish, and Crustacean shellfish. Since then, sesame has become more prevalent as an allergen and remains just as dangerous, inducing anaphylactic shock in some sesame-allergic individuals. Yet sesame remains unregulated, despite advocates and congressional members arguing for its inclusion. This note entertains one solution to this problem by exploring the most strategic way to bring a sesame allergy class action against a private food company under California’s consumer protection statutes. Because this kind of class action does not have much, if any, precedent, this note analyzes the basic, preliminary issues that any litigant would have to navigate around to certify a class, including preemption, standing, and the claim itself, by focusing on how courts have examined these issues in the recent “natural” class action litigation. It also analyzes the legal, moral, and practical aspects of choosing a type of relief, as well as whom to include in the class. Finally, this note briefly considers how FDA itself can ensure sesame is regulated on the labels of food products, given that some of the legal issues may well be insurmountable for this particular class action. This note explores the potential solutions to difficult legal hurdles in constructing a sesame allergy class action, arguing that litigating a sesame allergy class action—even if it is not ultimately successful—could start a productive conversation that might lead Congress or FDA to provide greater public health and consumer protection for those with sesame allergy.

Classification of Aerial Photogrammetric 3d Point Clouds

NASA Astrophysics Data System (ADS)

Becker, C.; Häni, N.; Rosinskaya, E.; d'Angelo, E.; Strecha, C.

2017-05-01

We present a powerful method to extract per-point semantic class labels from aerial photogrammetry data. Labelling this kind of data is important for tasks such as environmental modelling, object classification and scene understanding. Unlike previous point cloud classification methods that rely exclusively on geometric features, we show that incorporating color information yields a significant increase in accuracy in detecting semantic classes. We test our classification method on three real-world photogrammetry datasets that were generated with Pix4Dmapper Pro, and with varying point densities. We show that off-the-shelf machine learning techniques coupled with our new features allow us to train highly accurate classifiers that generalize well to unseen data, processing point clouds containing 10 million points in less than 3 minutes on a desktop computer.

Classification with asymmetric label noise: Consistency and maximal denoising

DOE PAGES

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

2016-09-20

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

Classification with asymmetric label noise: Consistency and maximal denoising

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

Blanchard, Gilles; Flaska, Marek; Handy, Gregory

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

Co-clustering phenome–genome for phenotype classification and disease gene discovery

PubMed Central

Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui

2012-01-01

Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways. PMID:22735708

Automation of motor dexterity assessment.

PubMed

Heyer, Patrick; Castrejon, Luis R; Orihuela-Espina, Felipe; Sucar, Luis Enrique

2017-07-01

Motor dexterity assessment is regularly performed in rehabilitation wards to establish patient status and automatization for such routinary task is sought. A system for automatizing the assessment of motor dexterity based on the Fugl-Meyer scale and with loose restrictions on sensing technologies is presented. The system consists of two main elements: 1) A data representation that abstracts the low level information obtained from a variety of sensors, into a highly separable low dimensionality encoding employing t-distributed Stochastic Neighbourhood Embedding, and, 2) central to this communication, a multi-label classifier that boosts classification rates by exploiting the fact that the classes corresponding to the individual exercises are naturally organized as a network. Depending on the targeted therapeutic movement class labels i.e. exercises scores, are highly correlated-patients who perform well in one, tends to perform well in related exercises-; and critically no node can be used as proxy of others - an exercise does not encode the information of other exercises. Over data from a cohort of 20 patients, the novel classifier outperforms classical Naive Bayes, random forest and variants of support vector machines (ANOVA: p < 0.001). The novel multi-label classification strategy fulfills an automatic system for motor dexterity assessment, with implications for lessening therapist's workloads, reducing healthcare costs and providing support for home-based virtual rehabilitation and telerehabilitation alternatives.

Using partially labeled data for normal mixture identification with application to class definition

NASA Technical Reports Server (NTRS)

Shahshahani, Behzad M.; Landgrebe, David A.

1992-01-01

The problem of estimating the parameters of a normal mixture density when, in addition to the unlabeled samples, sets of partially labeled samples are available is addressed. The density of the multidimensional feature space is modeled with a normal mixture. It is assumed that the set of components of the mixture can be partitioned into several classes and that training samples are available from each class. Since for any training sample the class of origin is known but the exact component of origin within the corresponding class is unknown, the training samples as considered to be partially labeled. The EM iterative equations are derived for estimating the parameters of the normal mixture in the presence of partially labeled samples. These equations can be used to combine the supervised and nonsupervised learning processes.

76 FR 40377 - Agency Information Collection Activities; Proposed Collection; Comment Request; Class II Special...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-08

... Guidance Document: Labeling for Natural Rubber Latex Condoms AGENCY: Food and Drug Administration, HHS. ACTION: Notice. SUMMARY: The Food and Drug Administration (FDA) is announcing an opportunity for public... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2011-N-0492...

Feasibility of use of fatty acid and triacylglycerol profiles for the authentication of commercial labelling in Iberian dry-cured sausages.

PubMed

Horcada, Alberto; Fernández-Cabanás, Víctor M; Polvillo, Oliva; Botella, Baltasar; Cubiles, M Dolores; Pino, Rafael; Narváez-Rivas, Mónica; León-Camacho, Manuel; Acuña, Rafael Rodríguez

2013-12-15

In the present study, fatty acid and triacylglycerol profiles were used to evaluate the possibility of authenticating Iberian dry-cured sausages according to their label specifications. 42 Commercial brand 'chorizo' and 39 commercial brand 'salchichón' sausages from Iberian pigs were purchased. 36 Samples were labelled Bellota and 45 bore the generic Ibérico label. In the market, Bellota is considered to be a better class than the generic Ibérico since products with the Bellota label are manufactured with high quality fat obtained from extensively reared pigs fed on acorns and pasture. Analyses of fatty acids and triacylglycerols were carried out by gas chromatography and a flame ion detector. A CP-SIL 88 column (highly substituted cyanopropyl phase; 50 m × 0.25 mm i.d., 0.2 µm film thickness) (Varian, Palo Alto, USA) was used for fatty acid analysis and a fused silica capillary DB-17HT column (50% phenyl-50% methylpolysiloxane; 30 m × 0.25 mm i.d., 0.15 µm film thickness) was used for triacylglycerols. Twelve fatty acids and 16 triacylglycerols were identified. Various discriminant models (linear quadratic discriminant analyses, logistic regression and support vector machines) were trained to predict the sample class (Bellota or Ibérico). These models included fatty acids and triacylglycerols separately and combined fatty acid and triacylglycerol profiles. The number of correctly classified samples according to discriminant analyses can be considered low (lower than 65%). The greatest discriminant rate was obtained when triacylglycerol profiles were included in the model, whilst using a combination of fatty acid and triacylglycerol profiles did not improve the rate of correct assignation. The values that represent the reliability of prediction of the samples according to the label specification were higher for the Ibérico class than for the Bellota class. In fact, quadratic and Support Vector Machine discriminate analyses were not able to assign the Bellota class (0%) when combined fatty acids and triacylglycerols were included in the model. The use of fatty acid and triacylglycerol profiles to discriminate Iberian dry-cured sausages in the market according to their labelling information is unclear. In order to ensure the genuineness of Iberian dry-cured sausages in the market, identification of fatty acid and triacylglycerol profiles should be combined with the application of quality standard traceability techniques. © 2013 Published by Elsevier B.V.

49 CFR 177.842 - Class 7 (radioactive) material.

Code of Federal Regulations, 2010 CFR

2010-10-01

... the labels on the individual packages and overpacks in the group. This provision does not apply to... Class 7 (radioactive) material bearing “RADIOACTIVE YELLOW-II” or “RADIOACTIVE YELLOW-III” labels may... transport index number determined by adding together the transport index number on the labels on the...

Headgear Accessories Classification Using an Overhead Depth Sensor

PubMed Central

Luna, Carlos A.; Marron-Romera, Marta; Mazo, Manuel; Luengo-Sanchez, Sara; Macho-Pedroso, Roberto

2017-01-01

In this paper, we address the generation of semantic labels describing the headgear accessories carried out by people in a scene under surveillance, only using depth information obtained from a Time-of-Flight (ToF) camera placed in an overhead position. We propose a new method for headgear accessories classification based on the design of a robust processing strategy that includes the estimation of a meaningful feature vector that provides the relevant information about the people’s head and shoulder areas. This paper includes a detailed description of the proposed algorithmic approach, and the results obtained in tests with persons with and without headgear accessories, and with different types of hats and caps. In order to evaluate the proposal, a wide experimental validation has been carried out on a fully labeled database (that has been made available to the scientific community), including a broad variety of people and headgear accessories. For the validation, three different levels of detail have been defined, considering a different number of classes: the first level only includes two classes (hat/cap, and no hat/cap), the second one considers three classes (hat, cap and no hat/cap), and the last one includes the full class set with the five classes (no hat/cap, cap, small size hat, medium size hat, and large size hat). The achieved performance is satisfactory in every case: the average classification rates for the first level reaches 95.25%, for the second one is 92.34%, and for the full class set equals 84.60%. In addition, the online stage processing time is 5.75 ms per frame in a standard PC, thus allowing for real-time operation. PMID:28796177

76 FR 71575 - Agency Information Collection Activities; Submission for Office of Management and Budget Review...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-18

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2011-N-0492... Request; Class II Special Controls Guidance Document: Labeling for Natural Rubber Latex Condoms AGENCY: Food and Drug Administration, HHS. ACTION: Notice. SUMMARY: The Food and Drug Administration (FDA) is...

An analysis of multi-type relational interactions in FMA using graph motifs with disjointness constraints.

PubMed

Zhang, Guo-Qiang; Luo, Lingyun; Ogbuji, Chime; Joslyn, Cliff; Mejino, Jose; Sahoo, Satya S

2012-01-01

The interaction of multiple types of relationships among anatomical classes in the Foundational Model of Anatomy (FMA) can provide inferred information valuable for quality assurance. This paper introduces a method called Motif Checking (MOCH) to study the effects of such multi-relation type interactions for detecting logical inconsistencies as well as other anomalies represented by the motifs. MOCH represents patterns of multi-type interaction as small labeled (with multiple types of edges) sub-graph motifs, whose nodes represent class variables, and labeled edges represent relational types. By representing FMA as an RDF graph and motifs as SPARQL queries, fragments of FMA are automatically obtained as auditing candidates. Leveraging the scalability and reconfigurability of Semantic Web Technology, we performed exhaustive analyses of a variety of labeled sub-graph motifs. The quality assurance feature of MOCH comes from the distinct use of a subset of the edges of the graph motifs as constraints for disjointness, whereby bringing in rule-based flavor to the approach as well. With possible disjointness implied by antonyms, we performed manual inspection of the resulting FMA fragments and tracked down sources of abnormal inferred conclusions (logical inconsistencies), which are amendable for programmatic revision of the FMA. Our results demonstrate that MOCH provides a unique source of valuable information for quality assurance. Since our approach is general, it is applicable to any ontological system with an OWL representation.

An Analysis of Multi-type Relational Interactions in FMA Using Graph Motifs with Disjointness Constraints

PubMed Central

Zhang, Guo-Qiang; Luo, Lingyun; Ogbuji, Chime; Joslyn, Cliff; Mejino, Jose; Sahoo, Satya S

2012-01-01

The interaction of multiple types of relationships among anatomical classes in the Foundational Model of Anatomy (FMA) can provide inferred information valuable for quality assurance. This paper introduces a method called Motif Checking (MOCH) to study the effects of such multi-relation type interactions for detecting logical inconsistencies as well as other anomalies represented by the motifs. MOCH represents patterns of multi-type interaction as small labeled (with multiple types of edges) sub-graph motifs, whose nodes represent class variables, and labeled edges represent relational types. By representing FMA as an RDF graph and motifs as SPARQL queries, fragments of FMA are automatically obtained as auditing candidates. Leveraging the scalability and reconfigurability of Semantic Web Technology, we performed exhaustive analyses of a variety of labeled sub-graph motifs. The quality assurance feature of MOCH comes from the distinct use of a subset of the edges of the graph motifs as constraints for disjointness, whereby bringing in rule-based flavor to the approach as well. With possible disjointness implied by antonyms, we performed manual inspection of the resulting FMA fragments and tracked down sources of abnormal inferred conclusions (logical inconsistencies), which are amendable for programmatic revision of the FMA. Our results demonstrate that MOCH provides a unique source of valuable information for quality assurance. Since our approach is general, it is applicable to any ontological system with an OWL representation. PMID:23304382

Cell-selective metabolic labeling of biomolecules with bioorthogonal functionalities.

PubMed

Xie, Ran; Hong, Senlian; Chen, Xing

2013-10-01

Metabolic labeling of biomolecules with bioorthogonal functionalities enables visualization, enrichment, and analysis of the biomolecules of interest in their physiological environments. This versatile strategy has found utility in probing various classes of biomolecules in a broad range of biological processes. On the other hand, metabolic labeling is nonselective with respect to cell type, which imposes limitations for studies performed in complex biological systems. Herein, we review the recent methodological developments aiming to endow metabolic labeling strategies with cell-type selectivity. The cell-selective metabolic labeling strategies have emerged from protein and glycan labeling. We envision that these strategies can be readily extended to labeling of other classes of biomolecules. Copyright © 2013 Elsevier Ltd. All rights reserved.

How informative are open-label studies for youth with bipolar disorder? A meta-analysis comparing open-label versus randomized, placebo-controlled clinical trials.

PubMed

Biederman, Joseph; Petty, Carter R; Woodworth, K Yvonne; Lomedico, Alexandra; O'Connor, Katherine B; Wozniak, Janet; Faraone, Stephen V

2012-03-01

To examine the informativeness of open-label trials toward predicting results in subsequent randomized, placebo-controlled clinical trials of psychopharmacologic treatments for pediatric bipolar disorder. We searched journal articles through PubMed at the National Library of Medicine using bipolar disorder, mania, pharmacotherapy, treatment and clinical trial as keywords. This search was supplemented with scientific presentations at national and international scientific meetings and submitted manuscripts from our group. Selection criteria included (1) enrollment of children diagnosed with DSM-IV bipolar disorder; (2) prospective assessment of at least 3 weeks; (3) monotherapy of a pharmacologic treatment for bipolar disorder; (4) use of a randomized placebo-controlled design or an open-label design for the same therapeutic compound; and (5) repeated use of the Young Mania Rating Scale (YMRS) as an outcome. The following information and data were extracted from 14 studies: study design, name of medication, class of medication, dose of medication, sample size, age, sex, trial length, and YMRS mean and standard deviation baseline and follow-up scores. For both study designs, the pooled effect size was statistically significant (open-label studies, z = 8.88, P < .001; randomized placebo-controlled studies, z = 13.75, P < .001), indicating a reduction in the YMRS from baseline to endpoint in both study designs. In a meta-analysis regression, study design was not a significant predictor of mean change in the YMRS. We found similarities in the treatment effects between open-label and randomized placebo-controlled studies in youth with bipolar disorder indicating that open-label studies are useful predictors of the potential safety and efficacy of a given compound in the treatment of pediatric bipolar disorder. © Copyright 2012 Physicians Postgraduate Press, Inc.

Latent class profile of psychiatric symptoms and treatment utilization in a sample of patients with co-occurring disorders.

PubMed

Villalobos-Gallegos, Luis; Marín-Navarrete, Rodrigo; Roncero, Calos; González-Cantú, Hugo

2017-01-01

To identify symptom-based subgroups within a sample of patients with co-occurring disorders (CODs) and to analyze intersubgroup differences in mental health services utilization. Two hundred and fifteen patients with COD from an addiction clinic completed the Symptom Checklist 90-Revised. Subgroups were determined using latent class profile analysis. Services utilization data were collected from electronic records during a 3-year span. The five-class model obtained the best fit (Bayesian information criteria [BIC] = 3,546.95; adjusted BIC = 3,363.14; bootstrapped likelihood ratio test p < 0.0001). Differences between classes were quantitative, and groups were labeled according to severity: mild (26%), mild-moderate (28.8%), moderate (18.6%), moderate-severe (17.2%), and severe (9.3%). A significant time by class interaction was obtained (chi-square [χ2[15

Active learning in the presence of unlabelable examples

NASA Technical Reports Server (NTRS)

Mazzoni, Dominic; Wagstaff, Kiri

2004-01-01

We propose a new active learning framework where the expert labeler is allowed to decline to label any example. This may be necessary because the true label is unknown or because the example belongs to a class that is not part of the real training problem. We show that within this framework, popular active learning algorithms (such as Simple) may perform worse than random selection because they make so many queries to the unlabelable class. We present a method by which any active learning algorithm can be modified to avoid unlabelable examples by training a second classifier to distinguish between the labelable and unlabelable classes. We also demonstrate the effectiveness of the method on two benchmark data sets and a real-world problem.

Information science team

NASA Technical Reports Server (NTRS)

Billingsley, F.

1982-01-01

Concerns are expressed about the data handling aspects of system design and about enabling technology for data handling and data analysis. The status, contributing factors, critical issues, and recommendations for investigations are listed for data handling, rectification and registration, and information extraction. Potential supports to individual P.I., research tasks, systematic data system design, and to system operation. The need for an airborne spectrometer class instrument for fundamental research in high spectral and spatial resolution is indicated. Geographic information system formatting and labelling techniques, very large scale integration, and methods for providing multitype data sets must also be developed.

Inter-class sparsity based discriminative least square regression.

PubMed

Wen, Jie; Xu, Yong; Li, Zuoyong; Ma, Zhongli; Xu, Yuanrong

2018-06-01

Least square regression is a very popular supervised classification method. However, two main issues greatly limit its performance. The first one is that it only focuses on fitting the input features to the corresponding output labels while ignoring the correlations among samples. The second one is that the used label matrix, i.e., zero-one label matrix is inappropriate for classification. To solve these problems and improve the performance, this paper presents a novel method, i.e., inter-class sparsity based discriminative least square regression (ICS_DLSR), for multi-class classification. Different from other methods, the proposed method pursues that the transformed samples have a common sparsity structure in each class. For this goal, an inter-class sparsity constraint is introduced to the least square regression model such that the margins of samples from the same class can be greatly reduced while those of samples from different classes can be enlarged. In addition, an error term with row-sparsity constraint is introduced to relax the strict zero-one label matrix, which allows the method to be more flexible in learning the discriminative transformation matrix. These factors encourage the method to learn a more compact and discriminative transformation for regression and thus has the potential to perform better than other methods. Extensive experimental results show that the proposed method achieves the best performance in comparison with other methods for multi-class classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

Deep learning architectures for multi-label classification of intelligent health risk prediction.

PubMed

Maxwell, Andrew; Li, Runzhi; Yang, Bei; Weng, Heng; Ou, Aihua; Hong, Huixiao; Zhou, Zhaoxian; Gong, Ping; Zhang, Chaoyang

2017-12-28

Multi-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive. For medical data, patients could have symptoms of multiple different diseases at the same time and it is important to develop tools that help to identify problems early. Intelligent health risk prediction models built with deep learning architectures offer a powerful tool for physicians to identify patterns in patient data that indicate risks associated with certain types of chronic diseases. Physical examination records of 110,300 anonymous patients were used to predict diabetes, hypertension, fatty liver, a combination of these three chronic diseases, and the absence of disease (8 classes in total). The dataset was split into training (90%) and testing (10%) sub-datasets. Ten-fold cross validation was used to evaluate prediction accuracy with metrics such as precision, recall, and F-score. Deep Learning (DL) architectures were compared with standard and state-of-the-art multi-label classification methods. Preliminary results suggest that Deep Neural Networks (DNN), a DL architecture, when applied to multi-label classification of chronic diseases, produced accuracy that was comparable to that of common methods such as Support Vector Machines. We have implemented DNNs to handle both problem transformation and algorithm adaption type multi-label methods and compare both to see which is preferable. Deep Learning architectures have the potential of inferring more information about the patterns of physical examination data than common classification methods. The advanced techniques of Deep Learning can be used to identify the significance of different features from physical examination data as well as to learn the contributions of each feature that impact a patient's risk for chronic diseases. However, accurate prediction of chronic disease risks remains a challenging problem that warrants further studies.

Digital microbiology: detection and classification of unknown bacterial pathogens using a label-free laser light scatter-sensing system

NASA Astrophysics Data System (ADS)

Rajwa, Bartek; Dundar, M. Murat; Akova, Ferit; Patsekin, Valery; Bae, Euiwon; Tang, Yanjie; Dietz, J. Eric; Hirleman, E. Daniel; Robinson, J. Paul; Bhunia, Arun K.

2011-06-01

The majority of tools for pathogen sensing and recognition are based on physiological or genetic properties of microorganisms. However, there is enormous interest in devising label-free and reagentless biosensors that would operate utilizing the biophysical signatures of samples without the need for labeling and reporting biochemistry. Optical biosensors are closest to realizing this goal and vibrational spectroscopies are examples of well-established optical label-free biosensing techniques. A recently introduced forward-scatter phenotyping (FSP) also belongs to the broad class of optical sensors. However, in contrast to spectroscopies, the remarkable specificity of FSP derives from the morphological information that bacterial material encodes on a coherent optical wavefront passing through the colony. The system collects elastically scattered light patterns that, given a constant environment, are unique to each bacterial species and/or serovar. Both FSP technology and spectroscopies rely on statistical machine learning to perform recognition and classification. However, the commonly used methods utilize either simplistic unsupervised learning or traditional supervised techniques that assume completeness of training libraries. This restrictive assumption is known to be false for real-life conditions, resulting in unsatisfactory levels of accuracy, and consequently limited overall performance for biodetection and classification tasks. The presented work demonstrates preliminary studies on the use of FSP system to classify selected serotypes of non-O157 Shiga toxin-producing E. coli in a nonexhaustive framework, that is, without full knowledge about all the possible classes that can be encountered. Our study uses a Bayesian approach to learning with a nonexhaustive training dataset to allow for the automated and distributed detection of unknown bacterial classes.

Classification of Mls Point Clouds in Urban Scenes Using Detrended Geometric Features from Supervoxel-Based Local Contexts

NASA Astrophysics Data System (ADS)

Sun, Z.; Xu, Y.; Hoegner, L.; Stilla, U.

2018-05-01

In this work, we propose a classification method designed for the labeling of MLS point clouds, with detrended geometric features extracted from the points of the supervoxel-based local context. To achieve the analysis of complex 3D urban scenes, acquired points of the scene should be tagged with individual labels of different classes. Thus, assigning a unique label to the points of an object that belong to the same category plays an essential role in the entire 3D scene analysis workflow. Although plenty of studies in this field have been reported, this work is still a challenging task. Specifically, in this work: 1) A novel geometric feature extraction method, detrending the redundant and in-salient information in the local context, is proposed, which is proved to be effective for extracting local geometric features from the 3D scene. 2) Instead of using individual point as basic element, the supervoxel-based local context is designed to encapsulate geometric characteristics of points, providing a flexible and robust solution for feature extraction. 3) Experiments using complex urban scene with manually labeled ground truth are conducted, and the performance of proposed method with respect to different methods is analyzed. With the testing dataset, we have obtained a result of 0.92 for overall accuracy for assigning eight semantic classes.

"Staying in Class so No One Can Get to Him": A Case for the Institutional Reproduction of ADHD Categories and Behaviours

ERIC Educational Resources Information Center

Exley, Beryl

2008-01-01

This paper focuses a sociological lens on what two early years Australian school boys labelled as having attention deficit hyperactivity disorder (ADHD) and an early years teacher have to say about social relations within informal play environments. The boys participated in separate semi-structured interviews where they predicted the likely…

Discriminant projective non-negative matrix factorization.

PubMed

Guan, Naiyang; Zhang, Xiang; Luo, Zhigang; Tao, Dacheng; Yang, Xuejun

2013-01-01

Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers W(T) X as their coefficients, i.e., X≈WW(T) X. Since PNMF learns the natural parts-based representation Wof X, it has been widely used in many fields such as pattern recognition and computer vision. However, PNMF does not perform well in classification tasks because it completely ignores the label information of the dataset. This paper proposes a Discriminant PNMF method (DPNMF) to overcome this deficiency. In particular, DPNMF exploits Fisher's criterion to PNMF for utilizing the label information. Similar to PNMF, DPNMF learns a single non-negative basis matrix and needs less computational burden than NMF. In contrast to PNMF, DPNMF maximizes the distance between centers of any two classes of examples meanwhile minimizes the distance between any two examples of the same class in the lower-dimensional subspace and thus has more discriminant power. We develop a multiplicative update rule to solve DPNMF and prove its convergence. Experimental results on four popular face image datasets confirm its effectiveness comparing with the representative NMF and PNMF algorithms.

Discriminant Projective Non-Negative Matrix Factorization

PubMed Central

Guan, Naiyang; Zhang, Xiang; Luo, Zhigang; Tao, Dacheng; Yang, Xuejun

2013-01-01

Projective non-negative matrix factorization (PNMF) projects high-dimensional non-negative examples X onto a lower-dimensional subspace spanned by a non-negative basis W and considers WT X as their coefficients, i.e., X≈WWT X. Since PNMF learns the natural parts-based representation Wof X, it has been widely used in many fields such as pattern recognition and computer vision. However, PNMF does not perform well in classification tasks because it completely ignores the label information of the dataset. This paper proposes a Discriminant PNMF method (DPNMF) to overcome this deficiency. In particular, DPNMF exploits Fisher's criterion to PNMF for utilizing the label information. Similar to PNMF, DPNMF learns a single non-negative basis matrix and needs less computational burden than NMF. In contrast to PNMF, DPNMF maximizes the distance between centers of any two classes of examples meanwhile minimizes the distance between any two examples of the same class in the lower-dimensional subspace and thus has more discriminant power. We develop a multiplicative update rule to solve DPNMF and prove its convergence. Experimental results on four popular face image datasets confirm its effectiveness comparing with the representative NMF and PNMF algorithms. PMID:24376680

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

NASA Astrophysics Data System (ADS)

Li, Hui; Yu, Jun-Ling; Yu, Le-An; Sun, Jie

2014-05-01

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.

Comparison of Unlicensed and Off-Label Use of Antipsychotics Prescribed to Child and Adolescent Psychiatric Outpatients for Treatment of Mental and Behavioral Disorders with Different Guidelines: The China Food and Drug Administration Versus the FDA.

PubMed

Zhu, Xiuqing; Hu, Jinqing; Sun, Bin; Deng, Shuhua; Wen, Yuguan; Chen, Weijia; Qiu, Chang; Shang, Dewei; Zhang, Ming

2018-04-01

This study aims to compare the prevalence of unlicensed and off-label use of antipsychotics among child and adolescent psychiatric outpatients with guidelines proposed by the China Food and Drug Administration (CFDA) and the U.S. Food and Drug Administration (FDA), and to identify factors associated with inconsistencies between the two regulations. A retrospective analysis of 29,326 drug prescriptions for child and adolescent outpatients from the Affiliated Brain Hospital of Guangzhou Medical University was conducted. Antipsychotics were classified as "unlicensed" or "off-label use" according to the latest pediatric license information registered by the CFDA and the FDA or the package inserts of antipsychotics authorized by the CFDA or the FDA for the treatment of pediatric mental and behavioral disorders, respectively. Binary logistic regression analysis was performed to assess factors associated with inconsistencies between the two regulations. The total unlicensed use, according to the CFDA analysis, was higher than that found in the FDA analysis (74.14% vs. 22.04%, p < 0.001). However, the total off-label use, according to the FDA analysis, was higher than that found in the CFDA analysis (46.53% vs. 15.77%, p < 0.001). Antipsychotic drug classes, age group, number of diagnoses, and diagnosis of schizophrenia and schizotypal and delusional disorders were associated with inconsistent unlicensed use. Antipsychotic drug classes, age group, number of prescribed psychotropic drugs, gender, diagnosis of schizophrenia and schizotypal and delusional disorders, diagnosis of mood [affective] disorders, diagnosis of mental retardation, and diagnosis of psychological development disorders were associated with inconsistent off-label use. The difference in prevalence of total unlicensed and off-label use of antipsychotics between the two regulations was statistically significant. This inconsistency could be partly attributed to differences in pediatric license information and package inserts of antipsychotics. The results indicate a need for further clinical pediatric studies and better harmonization between agencies regarding antipsychotic used in pediatrics.

From the SAIN,LIM system to the SENS algorithm: a review of a French approach of nutrient profiling.

PubMed

Tharrey, Marion; Maillot, Matthieu; Azaïs-Braesco, Véronique; Darmon, Nicole

2017-08-01

Nutrient profiling aims to classify or rank foods according to their nutritional composition to assist policies aimed at improving the nutritional quality of foods and diets. The present paper reviews a French approach of nutrient profiling by describing the SAIN,LIM system and its evolution from its early draft to the simplified nutrition labelling system (SENS) algorithm. Considered in 2010 by WHO as the 'French model' of nutrient profiling, SAIN,LIM classifies foods into four classes based on two scores: a nutrient density score (NDS) called SAIN and a score of nutrients to limit called LIM, and one threshold on each score. The system was first developed by the French Food Standard Agency in 2008 in response to the European regulation on nutrition and health claims (European Commission (EC) 1924/2006) to determine foods that may be eligible for bearing claims. Recently, the European regulation (EC 1169/2011) on the provision of food information to consumers allowed simplified nutrition labelling to facilitate consumer information and help them make fully informed choices. In that context, the SAIN,LIM was adapted to obtain the SENS algorithm, a system able to rank foods for simplified nutrition labelling. The implementation of the algorithm followed a step-by-step, systematic, transparent and logical process where shortcomings of the SAIN,LIM were addressed by integrating specificities of food categories in the SENS, reducing the number of nutrients, ordering the four classes and introducing European reference intakes. Through the French example, this review shows how an existing nutrient profiling system can be specifically adapted to support public health nutrition policies.

Towards Automatic Semantic Labelling of 3D City Models

NASA Astrophysics Data System (ADS)

Rook, M.; Biljecki, F.; Diakité, A. A.

2016-10-01

The lack of semantic information in many 3D city models is a considerable limiting factor in their use, as a lot of applications rely on semantics. Such information is not always available, since it is not collected at all times, it might be lost due to data transformation, or its lack may be caused by non-interoperability in data integration from other sources. This research is a first step in creating an automatic workflow that semantically labels plain 3D city model represented by a soup of polygons, with semantic and thematic information, as defined in the CityGML standard. The first step involves the reconstruction of the topology, which is used in a region growing algorithm that clusters upward facing adjacent triangles. Heuristic rules, embedded in a decision tree, are used to compute a likeliness score for these regions that either represent the ground (terrain) or a RoofSurface. Regions with a high likeliness score, to one of the two classes, are used to create a decision space, which is used in a support vector machine (SVM). Next, topological relations are utilised to select seeds that function as a start in a region growing algorithm, to create regions of triangles of other semantic classes. The topological relationships of the regions are used in the aggregation of the thematic building features. Finally, the level of detail is detected to generate the correct output in CityGML. The results show an accuracy between 85 % and 99 % in the automatic semantic labelling on four different test datasets. The paper is concluded by indicating problems and difficulties implying the next steps in the research.

An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation.

PubMed

Dereymaeker, Anneleen; Pillay, Kirubin; Vervisch, Jan; Van Huffel, Sabine; Naulaers, Gunnar; Jansen, Katrien; De Vos, Maarten

2017-09-01

Sleep state development in preterm neonates can provide crucial information regarding functional brain maturation and give insight into neurological well being. However, visual labeling of sleep stages from EEG requires expertise and is very time consuming, prompting the need for an automated procedure. We present a robust method for automated detection of preterm sleep from EEG, over a wide postmenstrual age ([Formula: see text] age) range, focusing first on Quiet Sleep (QS) as an initial marker for sleep assessment. Our algorithm, CLuster-based Adaptive Sleep Staging (CLASS), detects QS if it remains relatively more discontinuous than non-QS over PMA. CLASS was optimized on a training set of 34 recordings aged 27-42 weeks PMA, and performance then assessed on a distinct test set of 55 recordings of the same age range. Results were compared to visual QS labeling from two independent raters (with inter-rater agreement [Formula: see text]), using Sensitivity, Specificity, Detection Factor ([Formula: see text] of visual QS periods correctly detected by CLASS) and Misclassification Factor ([Formula: see text] of CLASS-detected QS periods that are misclassified). CLASS performance proved optimal across recordings at 31-38 weeks (median [Formula: see text], median MF 0-0.25, median Sensitivity 0.93-1.0, and median Specificity 0.80-0.91 across this age range), with minimal misclassifications at 35-36 weeks (median [Formula: see text]). To illustrate the potential of CLASS in facilitating clinical research, normal maturational trends over PMA were derived from CLASS-estimated QS periods, visual QS estimates, and nonstate specific periods (containing QS and non-QS) in the EEG recording. CLASS QS trends agreed with those from visual QS, with both showing stronger correlations than nonstate specific trends. This highlights the benefit of automated QS detection for exploring brain maturation.

Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

2016-08-01

Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reducing Spatial Data Complexity for Classification Models

NASA Astrophysics Data System (ADS)

Ruta, Dymitr; Gabrys, Bogdan

2007-11-01

Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the comparable compression levels.

15 CFR 9.4 - Development of voluntary energy conservation specifications.

Code of Federal Regulations, 2010 CFR

2010-01-01

... efficiency characteristics of the class of appliance or equipment. (3) A prototype Label and directions for... conditions of use, and stating that any manufacturer of appliances or equipment in the class concerned desiring voluntarily to use the Label and Energy Conservation Mark with such appliances or equipment must...

Feasibility of Active Machine Learning for Multiclass Compound Classification.

PubMed

Lang, Tobias; Flachsenberg, Florian; von Luxburg, Ulrike; Rarey, Matthias

2016-01-25

A common task in the hit-to-lead process is classifying sets of compounds into multiple, usually structural classes, which build the groundwork for subsequent SAR studies. Machine learning techniques can be used to automate this process by learning classification models from training compounds of each class. Gathering class information for compounds can be cost-intensive as the required data needs to be provided by human experts or experiments. This paper studies whether active machine learning can be used to reduce the required number of training compounds. Active learning is a machine learning method which processes class label data in an iterative fashion. It has gained much attention in a broad range of application areas. In this paper, an active learning method for multiclass compound classification is proposed. This method selects informative training compounds so as to optimally support the learning progress. The combination with human feedback leads to a semiautomated interactive multiclass classification procedure. This method was investigated empirically on 15 compound classification tasks containing 86-2870 compounds in 3-38 classes. The empirical results show that active learning can solve these classification tasks using 10-80% of the data which would be necessary for standard learning techniques.

9 CFR 355.34 - Labels, approval of, by Administrator.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Labels, approval of, by Administrator..., CERTIFICATION, AND IDENTIFICATION AS TO CLASS, QUALITY, QUANTITY, AND CONDITION Labeling § 355.34 Labels, approval of, by Administrator. (a) Except as provided in paragraph (c) of this section, no label shall be...

Effect on moisture permeability of typewriting on unit dose package surfaces.

PubMed

Rackson, J T; Zellhofer, M J; Birmingham, P H

1984-10-01

The effects of typewriting on labels of two unit dose packages with respect to moisture permeability were examined. Using an electric typewriter, a standard label format was imprinted on two different types of class A unit dose packages: (1) a heat-sealed paper-backed foil and cellofilm strip pouch, and (2) a copolyester and polyethylene multiple-cup blister with a heat-sealed paper-backed foil and cellofilm cover. The labels were typed at various typing-element impact settings. The official USP test for water permeation was then performed on typed packages and untyped control packages. The original untyped packages were confirmed to be USP class A quality. The packages for which successively harder impact settings were used showed a corresponding increase in moisture permeability. This resulted in a lowering of USP package ratings from class A to class B and D, some of which would be unsuitable for use in any unit dose system under current FDA repackaging standards. Typing directly onto the label of a unit dose package before it is sealed will most likely damage the package and possibly make it unfit for use. Pharmacists who must type labels for the unit dose packages studied should use the lowest possible typewriter impact setting and test for damage using the USP moisture-permeation test.

Actively learning to distinguish suspicious from innocuous anomalies in a batch of vehicle tracks

NASA Astrophysics Data System (ADS)

Qiu, Zhicong; Miller, David J.; Stieber, Brian; Fair, Tim

2014-06-01

We investigate the problem of actively learning to distinguish between two sets of anomalous vehicle tracks, innocuous" and suspicious", starting from scratch, without any initial examples of suspicious" and with no prior knowledge of what an operator would deem suspicious. This two-class problem is challenging because it is a priori unknown which track features may characterize the suspicious class. Furthermore, there is inherent imbalance in the sizes of the labeled innocuous" and suspicious" sets, even after some suspicious examples are identified. We present a comprehensive solution wherein a classifier learns to discriminate suspicious from innocuous based on derived p-value track features. Through active learning, our classifier thus learns the types of anomalies on which to base its discrimination. Our solution encompasses: i) judicious choice of kinematic p-value based features conditioned on the road of origin, along with more explicit features that capture unique vehicle behavior (e.g. U-turns); ii) novel semi-supervised learning that exploits information in the unlabeled (test batch) tracks, and iii) evaluation of several classifier models (logistic regression, SVMs). We find that two active labeling streams are necessary in practice in order to have efficient classifier learning while also forwarding (for labeling) the most actionable tracks. Experiments on wide-area motion imagery (WAMI) tracks, extracted via a system developed by Toyon Research Corporation, demonstrate the strong ROC AUC performance of our system, with sparing use of operator-based active labeling.

A statistical approach to combining multisource information in one-class classifiers

DOE PAGES

Simonson, Katherine M.; Derek West, R.; Hansen, Ross L.; ...

2017-06-08

A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorousmore » assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.« less

A statistical approach to combining multisource information in one-class classifiers

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

Simonson, Katherine M.; Derek West, R.; Hansen, Ross L.

A new method is introduced in this paper for combining information from multiple sources to support one-class classification. The contributing sources may represent measurements taken by different sensors of the same physical entity, repeated measurements by a single sensor, or numerous features computed from a single measured image or signal. The approach utilizes the theory of statistical hypothesis testing, and applies Fisher's technique for combining p-values, modified to handle nonindependent sources. Classifier outputs take the form of fused p-values, which may be used to gauge the consistency of unknown entities with one or more class hypotheses. The approach enables rigorousmore » assessment of classification uncertainties, and allows for traceability of classifier decisions back to the constituent sources, both of which are important for high-consequence decision support. Application of the technique is illustrated in two challenge problems, one for skin segmentation and the other for terrain labeling. Finally, the method is seen to be particularly effective for relatively small training samples.« less

Thematic accuracy of the National Land Cover Database (NLCD) 2001 land cover for Alaska

USGS Publications Warehouse

Selkowitz, D.J.; Stehman, S.V.

2011-01-01

The National Land Cover Database (NLCD) 2001 Alaska land cover classification is the first 30-m resolution land cover product available covering the entire state of Alaska. The accuracy assessment of the NLCD 2001 Alaska land cover classification employed a geographically stratified three-stage sampling design to select the reference sample of pixels. Reference land cover class labels were determined via fixed wing aircraft, as the high resolution imagery used for determining the reference land cover classification in the conterminous U.S. was not available for most of Alaska. Overall thematic accuracy for the Alaska NLCD was 76.2% (s.e. 2.8%) at Level II (12 classes evaluated) and 83.9% (s.e. 2.1%) at Level I (6 classes evaluated) when agreement was defined as a match between the map class and either the primary or alternate reference class label. When agreement was defined as a match between the map class and primary reference label only, overall accuracy was 59.4% at Level II and 69.3% at Level I. The majority of classification errors occurred at Level I of the classification hierarchy (i.e., misclassifications were generally to a different Level I class, not to a Level II class within the same Level I class). Classification accuracy was higher for more abundant land cover classes and for pixels located in the interior of homogeneous land cover patches. ?? 2011.

49 CFR 172.404 - Labels for mixed and consolidated packaging.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 2 2012-10-01 2012-10-01 false Labels for mixed and consolidated packaging. 172..., TRAINING REQUIREMENTS, AND SECURITY PLANS Labeling § 172.404 Labels for mixed and consolidated packaging. (a) Mixed packaging. When compatible hazardous materials having different hazard classes are packed...

49 CFR 172.404 - Labels for mixed and consolidated packaging.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 2 2014-10-01 2014-10-01 false Labels for mixed and consolidated packaging. 172..., TRAINING REQUIREMENTS, AND SECURITY PLANS Labeling § 172.404 Labels for mixed and consolidated packaging. (a) Mixed packaging. When compatible hazardous materials having different hazard classes are packed...

49 CFR 172.404 - Labels for mixed and consolidated packaging.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 2 2011-10-01 2011-10-01 false Labels for mixed and consolidated packaging. 172..., TRAINING REQUIREMENTS, AND SECURITY PLANS Labeling § 172.404 Labels for mixed and consolidated packaging. (a) Mixed packaging. When compatible hazardous materials having different hazard classes are packed...

49 CFR 172.404 - Labels for mixed and consolidated packaging.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 2 2013-10-01 2013-10-01 false Labels for mixed and consolidated packaging. 172..., TRAINING REQUIREMENTS, AND SECURITY PLANS Labeling § 172.404 Labels for mixed and consolidated packaging. (a) Mixed packaging. When compatible hazardous materials having different hazard classes are packed...

49 CFR 172.407 - Label specifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., numbers, and border must be shown in black on a label except that— (i) White may be used on a label with a one color background of green, red or blue. (ii) White must be used for the text and class number for the CORROSIVE label. (iii) White may be used for the symbol for the ORGANIC PEROXIDE label. (3) Black...

49 CFR 172.407 - Label specifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., numbers, and border must be shown in black on a label except that— (i) White may be used on a label with a one color background of green, red or blue. (ii) White must be used for the text and class number for the CORROSIVE label. (iii) White may be used for the symbol for the ORGANIC PEROXIDE label. (3) Black...

49 CFR 172.407 - Label specifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., numbers, and border must be shown in black on a label except that— (i) White may be used on a label with a one color background of green, red or blue. (ii) White must be used for the text and class number for the CORROSIVE label. (iii) White may be used for the symbol for the ORGANIC PEROXIDE label. (3) Black...

Joint Feature Selection and Classification for Multilabel Learning.

PubMed

Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

2018-03-01

Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

27 CFR 7.24 - Class and type.

Code of Federal Regulations, 2011 CFR

2011-04-01

... OF THE TREASURY LIQUORS LABELING AND ADVERTISING OF MALT BEVERAGES Labeling Requirements for Malt... volume shall bear the class designation “malt beverage,” or “cereal beverage,” or “near beer.” If the designation “near beer” is used, both words must appear in the same size and style of type, in the same color...

27 CFR 7.24 - Class and type.

Code of Federal Regulations, 2014 CFR

2014-04-01

... OF THE TREASURY ALCOHOL LABELING AND ADVERTISING OF MALT BEVERAGES Labeling Requirements for Malt... volume shall bear the class designation “malt beverage,” or “cereal beverage,” or “near beer.” If the designation “near beer” is used, both words must appear in the same size and style of type, in the same color...

27 CFR 7.24 - Class and type.

Code of Federal Regulations, 2010 CFR

2010-04-01

... OF THE TREASURY LIQUORS LABELING AND ADVERTISING OF MALT BEVERAGES Labeling Requirements for Malt... volume shall bear the class designation “malt beverage,” or “cereal beverage,” or “near beer.” If the designation “near beer” is used, both words must appear in the same size and style of type, in the same color...

27 CFR 7.24 - Class and type.

Code of Federal Regulations, 2013 CFR

2013-04-01

... OF THE TREASURY ALCOHOL LABELING AND ADVERTISING OF MALT BEVERAGES Labeling Requirements for Malt... volume shall bear the class designation “malt beverage,” or “cereal beverage,” or “near beer.” If the designation “near beer” is used, both words must appear in the same size and style of type, in the same color...

27 CFR 7.24 - Class and type.

Code of Federal Regulations, 2012 CFR

2012-04-01

... OF THE TREASURY LIQUORS LABELING AND ADVERTISING OF MALT BEVERAGES Labeling Requirements for Malt... volume shall bear the class designation “malt beverage,” or “cereal beverage,” or “near beer.” If the designation “near beer” is used, both words must appear in the same size and style of type, in the same color...

On supervised graph Laplacian embedding CA model & kernel construction and its application

NASA Astrophysics Data System (ADS)

Zeng, Junwei; Qian, Yongsheng; Wang, Min; Yang, Yongzhong

2017-01-01

There are many methods to construct kernel with given data attribute information. Gaussian radial basis function (RBF) kernel is one of the most popular ways to construct a kernel. The key observation is that in real-world data, besides the data attribute information, data label information also exists, which indicates the data class. In order to make use of both data attribute information and data label information, in this work, we propose a supervised kernel construction method. Supervised information from training data is integrated into standard kernel construction process to improve the discriminative property of resulting kernel. A supervised Laplacian embedding cellular automaton model is another key application developed for two-lane heterogeneous traffic flow with the safe distance and large-scale truck. Based on the properties of traffic flow in China, we re-calibrate the cell length, velocity, random slowing mechanism and lane-change conditions and use simulation tests to study the relationships among the speed, density and flux. The numerical results show that the large-scale trucks will have great effects on the traffic flow, which are relevant to the proportion of the large-scale trucks, random slowing rate and the times of the lane space change.

49 CFR 172.404 - Labels for mixed and consolidated packaging.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Labels for mixed and consolidated packaging. 172..., TRAINING REQUIREMENTS, AND SECURITY PLANS Labeling § 172.404 Labels for mixed and consolidated packaging. (a) Mixed packaging. When hazardous materials having different hazard classes are packed within the...

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed ADF features can effectively improve the accuracy of urban scene classification, with a significant increase in overall accuracy (3.8-11.7%) compared to using the spectral bands alone. Furthermore, the results indicated the superiority of the proposed ADFs in distinguishing between the spectrally similar and complex man-made classes, including roads and various types of buildings (e.g., high buildings, urban villages, and residential apartments).

A Multi-Label Classification Approach for Coding Cancer Information Service Chat Transcripts

PubMed Central

Rios, Anthony; Vanderpool, Robin; Shaw, Pam

2017-01-01

National Cancer Institute's (NCI) Cancer Information Service (CIS) offers online instant messaging based information service called LiveHelp to patients, family members, friends, and other cancer information consumers. A cancer information specialist (IS) ‘chats’ with a consumer and provides information on a variety of topics including clinical trials. After a LiveHelp chat session is finished, the IS codes about 20 different elements of metadata about the session in electronic contact record forms (ECRF), which are to be later used for quality control and reporting. Besides straightforward elements like age and gender, more specific elements to be coded include the purpose of contact, the subjects of interaction, and the different responses provided to the consumer, the latter two often taking on multiple values. As such, ECRF coding is a time consuming task and automating this process could help ISs to focus more on their primary goal of helping consumers with valuable cancer related information. As a first attempt in this task, we explored multi-label and multi-class text classification approaches to code the purpose, subjects of interaction, and the responses provided based on the chat transcripts. With a sample dataset of about 673 transcripts, we achieved example-based F-scores of 0.67 (for subjects) and 0.58 (responses). We also achieved label-based micro F-scores of 0.65 (for subjects), 0.62 (for responses), and 0.61 (for purpose). To our knowledge this is the first attempt in automatic coding of Live-Help transcripts and our initial results on the smaller corpus indicate promising future directions in this task. PMID:28736775

Design of polymeric immunomicrospheres for cell labelling and cell separation

NASA Technical Reports Server (NTRS)

Rembaum, A.; Margel, S.

1978-01-01

Synthesis of several classes of hydrophylic microspheres applied to cell labeling and cell separation is described. Five classes of cross-linked microspheres with functional groups such as carboxyl, hydroxyl, amide and/or pyridine groups were synthesized. These functional groups were used to bind covalently antibodies and other proteins to the surface of the microspheres. To optimize the derivatisation technique, polyglutaraldehyde immunomicrospheres were prepared and utilized. Specific populations of human and murine lymphocytes were labelled with microspheres synthesized by the emulsion of the ionizing radiation technique. The labelling of the cells by means of microspheres containing an iron core produced successful separation of B from T lymphocytes by means of a magnetic field.

Carbon Allocation into Different Fine-Root Classes of Young Abies alba Trees Is Affected More by Phenology than by Simulated Browsing

PubMed Central

Endrulat, Tina; Buchmann, Nina; Brunner, Ivano

2016-01-01

Abies alba (European silver fir) was used to investigate possible effects of simulated browsing on C allocation belowground by 13CO2 pulse-labelling at spring, summer or autumn, and by harvesting the trees at the same time point of the labelling or at a later season for biomass and for 13C-allocation into the fine-root system. Before budburst in spring, the leader shoots and 50% of all lateral shoots of half of the investigated 5-year old Abies alba saplings were clipped to simulate browsing. At harvest, different fine-root classes were separated, and starch as an important storage compartment was analysed for concentrations. The phenology had a strong effect on the allocation of the 13C-label from shoots to roots. In spring, shoots did not supply the fine-roots with high amounts of the 13C-label, because the fine-roots contained less than 1% of the applied 13C. In summer and autumn, however, shoots allocated relatively high amounts of the 13C-label to the fine roots. The incorporation of the 13C-label as structural C or as starch into the roots is strongly dependent on the root type and the root diameter. In newly formed fine roots, 3–5% of the applied 13C was incorporated, whereas 1–3% in the ≤0.5 mm root class and 1–1.5% in the >0.5–1.0 mm root class were recorded. Highest 13C-enrichment in the starch was recorded in the newly formed fine roots in autumn. The clipping treatment had a significant positive effect on the amount of allocated 13C-label to the fine roots after the spring labelling, with high relative 13C-contents observed in the ≤0.5 mm and the >0.5–1.0 mm fine-root classes of clipped trees. No effects of the clipping were observed after summer and autumn labelling in the 13C-allocation patterns. Overall, our data imply that the season of C assimilation and, thus, the phenology of trees is the main determinant of the C allocation from shoots to roots and is clearly more important than browsing. PMID:27123860

Carbon Allocation into Different Fine-Root Classes of Young Abies alba Trees Is Affected More by Phenology than by Simulated Browsing.

PubMed

Endrulat, Tina; Buchmann, Nina; Brunner, Ivano

2016-01-01

Abies alba (European silver fir) was used to investigate possible effects of simulated browsing on C allocation belowground by 13CO2 pulse-labelling at spring, summer or autumn, and by harvesting the trees at the same time point of the labelling or at a later season for biomass and for 13C-allocation into the fine-root system. Before budburst in spring, the leader shoots and 50% of all lateral shoots of half of the investigated 5-year old Abies alba saplings were clipped to simulate browsing. At harvest, different fine-root classes were separated, and starch as an important storage compartment was analysed for concentrations. The phenology had a strong effect on the allocation of the 13C-label from shoots to roots. In spring, shoots did not supply the fine-roots with high amounts of the 13C-label, because the fine-roots contained less than 1% of the applied 13C. In summer and autumn, however, shoots allocated relatively high amounts of the 13C-label to the fine roots. The incorporation of the 13C-label as structural C or as starch into the roots is strongly dependent on the root type and the root diameter. In newly formed fine roots, 3-5% of the applied 13C was incorporated, whereas 1-3% in the ≤0.5 mm root class and 1-1.5% in the >0.5-1.0 mm root class were recorded. Highest 13C-enrichment in the starch was recorded in the newly formed fine roots in autumn. The clipping treatment had a significant positive effect on the amount of allocated 13C-label to the fine roots after the spring labelling, with high relative 13C-contents observed in the ≤0.5 mm and the >0.5-1.0 mm fine-root classes of clipped trees. No effects of the clipping were observed after summer and autumn labelling in the 13C-allocation patterns. Overall, our data imply that the season of C assimilation and, thus, the phenology of trees is the main determinant of the C allocation from shoots to roots and is clearly more important than browsing.

Contrast class cues and performance facilitation in a hypothesis-testing task: evidence for an iterative counterfactual model.

PubMed

Gale, Maggie; Ball, Linden J

2012-04-01

Hypothesis-testing performance on Wason's (Quarterly Journal of Experimental Psychology 12:129-140, 1960) 2-4-6 task is typically poor, with only around 20% of participants announcing the to-be-discovered "ascending numbers" rule on their first attempt. Enhanced solution rates can, however, readily be observed with dual-goal (DG) task variants requiring the discovery of two complementary rules, one labeled "DAX" (the standard "ascending numbers" rule) and the other labeled "MED" ("any other number triples"). Two DG experiments are reported in which we manipulated the usefulness of a presented MED exemplar, where usefulness denotes cues that can establish a helpful "contrast class" that can stand in opposition to the presented 2-4-6 DAX exemplar. The usefulness of MED exemplars had a striking facilitatory effect on DAX rule discovery, which supports the importance of contrast-class information in hypothesis testing. A third experiment ruled out the possibility that the useful MED triple seeded the correct rule from the outset and obviated any need for hypothesis testing. We propose that an extension of Oaksford and Chater's (European Journal of Cognitive Psychology 6:149-169, 1994) iterative counterfactual model can neatly capture the mechanisms by which DG facilitation arises.

Standard terminology and labeling of ocular tissue for transplantation.

PubMed

Armitage, W John; Ashford, Paul; Crow, Barbara; Dahl, Patricia; DeMatteo, Jennifer; Distler, Pat; Gopinathan, Usha; Madden, Peter W; Mannis, Mark J; Moffatt, S Louise; Ponzin, Diego; Tan, Donald

2013-06-01

To develop an internationally agreed terminology for describing ocular tissue grafts to improve the accuracy and reliability of information transfer, to enhance tissue traceability, and to facilitate the gathering of comparative global activity data, including denominator data for use in biovigilance analyses. ICCBBA, the international standards organization for terminology, coding, and labeling of blood, cells, and tissues, approached the major Eye Bank Associations to form an expert advisory group. The group met by regular conference calls to develop a standard terminology, which was released for public consultation and amended accordingly. The terminology uses broad definitions (Classes) with modifying characteristics (Attributes) to define each ocular tissue product. The terminology may be used within the ISBT 128 system to label tissue products with standardized bar codes enabling the electronic capture of critical data in the collection, processing, and distribution of tissues. Guidance on coding and labeling has also been developed. The development of a standard terminology for ocular tissue marks an important step for improving traceability and reducing the risk of mistakes due to transcription errors. ISBT 128 computer codes have been assigned and may now be used to label ocular tissues. Eye banks are encouraged to adopt this standard terminology and move toward full implementation of ISBT 128 nomenclature, coding, and labeling.

Semi-Supervised Projective Non-Negative Matrix Factorization for Cancer Classification.

PubMed

Zhang, Xiang; Guan, Naiyang; Jia, Zhilong; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Advances in DNA microarray technologies have made gene expression profiles a significant candidate in identifying different types of cancers. Traditional learning-based cancer identification methods utilize labeled samples to train a classifier, but they are inconvenient for practical application because labels are quite expensive in the clinical cancer research community. This paper proposes a semi-supervised projective non-negative matrix factorization method (Semi-PNMF) to learn an effective classifier from both labeled and unlabeled samples, thus boosting subsequent cancer classification performance. In particular, Semi-PNMF jointly learns a non-negative subspace from concatenated labeled and unlabeled samples and indicates classes by the positions of the maximum entries of their coefficients. Because Semi-PNMF incorporates statistical information from the large volume of unlabeled samples in the learned subspace, it can learn more representative subspaces and boost classification performance. We developed a multiplicative update rule (MUR) to optimize Semi-PNMF and proved its convergence. The experimental results of cancer classification for two multiclass cancer gene expression profile datasets show that Semi-PNMF outperforms the representative methods.

Translation-aware semantic segmentation via conditional least-square generative adversarial networks

NASA Astrophysics Data System (ADS)

Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min

2017-10-01

Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.

Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed.

PubMed

Eisinger, Daniel; Tsatsaronis, George; Bundschus, Markus; Wieneke, Ulrich; Schroeder, Michael

2013-04-15

Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms.Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources.

Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed

PubMed Central

2013-01-01

Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms. Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources. PMID:23734562

49 CFR 175.704 - Plutonium shipments.

Code of Federal Regulations, 2010 CFR

2010-10-01

... lower cargo compartment in the aft-most location that is possible for cargo of its size and weight, and... aboard an aircraft carrying other cargo required to bear any of the following labels: Class 1 (all Divisions), Class 2 (all Divisions), Class 3, Class 4 (all Divisions), Class 5 (all Divisions), or Class 8...

Development of High-Performance Chemical Isotope Labeling LC-MS for Profiling the Carbonyl Submetabolome.

PubMed

Zhao, Shuang; Dawe, Margot; Guo, Kevin; Li, Liang

2017-06-20

Metabolites containing a carbonyl group represent several important classes of molecules including various forms of ketones and aldehydes such as steroids and sugars. We report a high-performance chemical isotope labeling (CIL) LC-MS method for profiling the carbonyl submetabolome with high coverage and high accuracy and precision of relative quantification. This method is based on the use of dansylhydrazine (DnsHz) labeling of carbonyl metabolites to change their chemical and physical properties to such an extent that the labeled metabolites can be efficiently separated by reversed phase LC and ionized by electrospray ionization MS. In the analysis of six standards representing different carbonyl classes, acetaldehyde could be ionized only after labeling and MS signals were significantly increased for other 5 standards with an enhancement factor ranging from ∼15-fold for androsterone to ∼940-fold for 2-butanone. Differential 12 C- and 13 C-DnsHz labeling was developed for quantifying metabolic differences in comparative samples where individual samples were separately labeled with 12 C-labeling and spiked with a 13 C-labeled pooled sample, followed by LC-MS analysis, peak pair picking, and peak intensity ratio measurement. In the replicate analysis of a 1:1 12 C-/ 13 C-labeled human urine mixture (n = 6), an average of 2030 ± 39 pairs per run were detected with 1737 pairs in common, indicating the possibility of detecting a large number of carbonyl metabolites as well as high reproducibility of peak pair detection. The average RSD of the peak pair ratios was 7.6%, and 95.6% of the pairs had a RSD value of less than 20%, demonstrating high precision for peak ratio measurement. In addition, the ratios of most peak pairs were close to the expected value of 1.0 (e.g., 95.5% of them had ratios of between 0.67 and 1.5), showing the high accuracy of the method. For metabolite identification, a library of DnsHz-labeled standards was constructed, including 78 carbonyl metabolites with each containing MS, retention time (RT), and MS/MS information. This library and an online search program for labeled carbonyl metabolite identification based on MS, RT, and MS/MS matches have been implemented in a freely available Website, www.mycompoundid.org . Using this library, out of the 1737 peak pairs detected in urine, 33 metabolites were positively identified. In addition, 1333 peak pairs could be matched to the metabolome databases with most of them belonging to the carbonyl metabolites. These results show that 12 C-/ 13 C-DnsHz labeling LC-MS is a useful tool for profiling the carbonyl submetabolome of complex samples with high coverage.

The use of interactive technology in the classroom.

PubMed

Kresic, P

1999-01-01

This article discusses the benefits that clinical laboratory science students and instructors experienced through the use of and integration of computer technology, microscopes, and digitizing cameras. Patient specimens were obtained from the participating clinical affiliates, slides stained or wet mounts prepared, images viewed under the microscope, digitized, and after labeling, stored into an appropriate folder. The individual folders were labeled as Hematology, Microbiology, Chemistry, or Urinalysis. Students, after obtaining the necessary specimens and pertinent data, created case study presentations for class discussions. After two semesters of utilizing videomicroscopy/computer technology in the classroom, students and instructors realized the potential associated with the technology, namely, the vast increase in the amount of organized visual and scientific information accessible and the availability of collaborative and interactive learning to complement individualized instruction. The instructors, on the other hand, were able to provide a wider variety of visual information on individual bases. In conclusion, the appropriate use of technology can enhance students' learning and participation. Increased student involvement through the use of videomicroscopy and computer technology heightened their sense of pride and ownership in providing suitable information in case study presentations. Also, visualization provides students and educators with alternative methods of teaching/learning and increased retention of information.

Probabilistic multiple sclerosis lesion classification based on modeling regional intensity variability and local neighborhood information.

PubMed

Harmouche, Rola; Subbanna, Nagesh K; Collins, D Louis; Arnold, Douglas L; Arbel, Tal

2015-05-01

In this paper, a fully automatic probabilistic method for multiple sclerosis (MS) lesion classification is presented, whereby the posterior probability density function over healthy tissues and two types of lesions (T1-hypointense and T2-hyperintense) is generated at every voxel. During training, the system explicitly models the spatial variability of the intensity distributions throughout the brain by first segmenting it into distinct anatomical regions and then building regional likelihood distributions for each tissue class based on multimodal magnetic resonance image (MRI) intensities. Local class smoothness is ensured by incorporating neighboring voxel information in the prior probability through Markov random fields. The system is tested on two datasets from real multisite clinical trials consisting of multimodal MRIs from a total of 100 patients with MS. Lesion classification results based on the framework are compared with and without the regional information, as well as with other state-of-the-art methods against the labels from expert manual raters. The metrics for comparison include Dice overlap, sensitivity, and positive predictive rates for both voxel and lesion classifications. Statistically significant improvements in Dice values ( ), for voxel-based and lesion-based sensitivity values ( ), and positive predictive rates ( and respectively) are shown when the proposed method is compared to the method without regional information, and to a widely used method [1]. This holds particularly true in the posterior fossa, an area where classification is very challenging. The proposed method allows us to provide clinicians with accurate tissue labels for T1-hypointense and T2-hyperintense lesions, two types of lesions that differ in appearance and clinical ramifications, and with a confidence level in the classification, which helps clinicians assess the classification results.

A Coupled k-Nearest Neighbor Algorithm for Multi-Label Classification

DTIC Science & Technology

2015-05-22

classification, an image may contain several concepts simultaneously, such as beach, sunset and kangaroo . Such tasks are usually denoted as multi-label...informatics, a gene can belong to both metabolism and transcription classes; and in music categorization, a song may labeled as Mozart and sad. In the

Finding Specification Pages from the Web

NASA Astrophysics Data System (ADS)

Yoshinaga, Naoki; Torisawa, Kentaro

This paper presents a method of finding a specification page on the Web for a given object (e.g., ``Ch. d'Yquem'') and its class label (e.g., ``wine''). A specification page for an object is a Web page which gives concise attribute-value information about the object (e.g., ``county''-``Sauternes'') in well formatted structures. A simple unsupervised method using layout and symbolic decoration cues was applied to a large number of the Web pages to acquire candidate attributes for each class (e.g., ``county'' for a class ``wine''). We then filter out irrelevant words from the putative attributes through an author-aware scoring function that we called site frequency. We used the acquired attributes to select a representative specification page for a given object from the Web pages retrieved by a normal search engine. Experimental results revealed that our system greatly outperformed the normal search engine in terms of this specification retrieval.

Chemical Isotope Labeling LC-MS for High Coverage and Quantitative Profiling of the Hydroxyl Submetabolome in Metabolomics.

PubMed

Zhao, Shuang; Luo, Xian; Li, Liang

2016-11-01

A key step in metabolomics is to perform accurate relative quantification of the metabolomes in comparative samples with high coverage. Hydroxyl-containing metabolites are an important class of the metabolome with diverse structures and physical/chemical properties; however, many of them are difficult to detect with high sensitivity. We present a high-performance chemical isotope labeling liquid chromatography mass spectrometry (LC-MS) technique for in-depth profiling of the hydroxyl submetabolome, which involves the use of acidic liquid-liquid extraction to enrich hydroxyl metabolites into ethyl acetate from an aqueous sample. After drying and then redissolving in acetonitrile, the metabolite extract is labeled using a base-activated 12 C- or 13 C-dansylation reaction. A fast step-gradient LC-UV method is used to determine the total concentration of labeled metabolites. On the basis of the concentration information, a 12 C-labeled individual sample is mixed with an equal mole amount of a 13 C-labeled pool or control for relative metabolite quantification. The 12 C-/ 13 C-labeled mixtures are individually analyzed by LC-MS, and the resultant peak pairs of labeled metabolites in MS are measured for relative quantification and metabolite identification. A standard library of 85 hydroxyl compounds containing MS, retention time, and MS/MS information was constructed for positive metabolite identification based on matches of two or all three of these parameters with those of an unknown. Using human urine as an example, we analyzed samples of 1:1 12 C-/ 13 C-labeled urine in triplicate with triplicate runs per sample and detected an average of 3759 ± 45 peak pairs or metabolites per run and 3538 ± 71 pairs per sample with 3093 pairs in common (n = 9). Out of the 3093 peak pairs, 2304 pairs (75%) could be positively or putatively identified based on metabolome database searches, including 20 pairs positively identified using the dansylated hydroxyl standards library. The majority of detected metabolites were those containing hydroxyl groups. This technique opens a new avenue for the detailed characterization of the hydroxyl submetabolome in metabolomics research.

Towards Automatic Classification of Exoplanet-Transit-Like Signals: A Case Study on Kepler Mission Data

NASA Astrophysics Data System (ADS)

Valizadegan, Hamed; Martin, Rodney; McCauliff, Sean D.; Jenkins, Jon Michael; Catanzarite, Joseph; Oza, Nikunj C.

2015-08-01

Building new catalogues of planetary candidates, astrophysical false alarms, and non-transiting phenomena is a challenging task that currently requires a reviewing team of astrophysicists and astronomers. These scientists need to examine more than 100 diagnostic metrics and associated graphics for each candidate exoplanet-transit-like signal to classify it into one of the three classes. Considering that the NASA Explorer Program's TESS mission and ESA's PLATO mission survey even a larger area of space, the classification of their transit-like signals is more time-consuming for human agents and a bottleneck to successfully construct the new catalogues in a timely manner. This encourages building automatic classification tools that can quickly and reliably classify the new signal data from these missions. The standard tool for building automatic classification systems is the supervised machine learning that requires a large set of highly accurate labeled examples in order to build an effective classifier. This requirement cannot be easily met for classifying transit-like signals because not only are existing labeled signals very limited, but also the current labels may not be reliable (because the labeling process is a subjective task). Our experiments with using different supervised classifiers to categorize transit-like signals verifies that the labeled signals are not rich enough to provide the classifier with enough power to generalize well beyond the observed cases (e.g. to unseen or test signals). That motivated us to utilize a new category of learning techniques, so-called semi-supervised learning, that combines the label information from the costly labeled signals, and distribution information from the cheaply available unlabeled signals in order to construct more effective classifiers. Our study on the Kepler Mission data shows that semi-supervised learning can significantly improve the result of multiple base classifiers (e.g. Support Vector Machines, AdaBoost, and Decision Tree) and is a good technique for automatic classification of exoplanet-transit-like signal.

Culture of somatic cells isolated from frozen-thawed equine semen using fluorescence-assisted cell sorting.

PubMed

Brom-de-Luna, Joao Gatto; Canesin, Heloísa Siqueira; Wright, Gus; Hinrichs, Katrin

2018-03-01

Nuclear transfer using somatic cells from frozen semen (FzSC) would allow cloning of animals for which no other genetic material is available. Horses are one of the few species for which cloning is commercially feasible; despite this, there is no information available on the culture of equine FzSC. After preliminary trials on equine FzSC, recovered by density-gradient centrifugation, resulted in no growth, we hypothesized that sperm in the culture system negatively affected cell proliferation. Therefore, we evaluated culture of FzSC isolated using fluorescence-assisted cell sorting. In Exp. 1, sperm were labeled using antibodies to a sperm-specific antigen, SP17, and unlabeled cells were collected. This resulted in high sperm contamination. In Exp. 2, FzSC were labeled using an anti-MHC class I antibody. This resulted in an essentially pure population of FzSC, 13-25% of which were nucleated. Culture yielded no proliferation in any of nine replicates. In Exp. 3, 5 × 10 3 viable fresh, cultured horse fibroblasts were added to the frozen-thawed, washed semen, then this suspension was labeled and sorted as for Exp. 2. The enriched population had a mean of five sperm per recovered somatic cell; culture yielded formation of monolayers. In conclusion, an essentially pure population of equine FzSC could be obtained using sorting for presence of MHC class I antigens. No equine FzSC grew in culture; however, the proliferation of fibroblasts subjected to the same processing demonstrated that the labeling and sorting methods, and the presence of few sperm in culture, were compatible with cell viability. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep Learning for Automated Extraction of Primary Sites From Cancer Pathology Reports.

PubMed

Qiu, John X; Yoon, Hong-Jun; Fearn, Paul A; Tourassi, Georgia D

2018-01-01

Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this study, we investigated deep learning and a convolutional neural network (CNN), for extracting ICD-O-3 topographic codes from a corpus of breast and lung cancer pathology reports. We performed two experiments, using a CNN and a more conventional term frequency vector approach, to assess the effects of class prevalence and inter-class transfer learning. The experiments were based on a set of 942 pathology reports with human expert annotations as the gold standard. CNN performance was compared against a more conventional term frequency vector space approach. We observed that the deep learning models consistently outperformed the conventional approaches in the class prevalence experiment, resulting in micro- and macro-F score increases of up to 0.132 and 0.226, respectively, when class labels were well populated. Specifically, the best performing CNN achieved a micro-F score of 0.722 over 12 ICD-O-3 topography codes. Transfer learning provided a consistent but modest performance boost for the deep learning methods but trends were contingent on the CNN method and cancer site. These encouraging results demonstrate the potential of deep learning for automated abstraction of pathology reports.

Caregiver profiles in dementia related to quality of life, depression and perseverance time in the European Actifcare study: the importance of social health.

PubMed

Janssen, Eveline P C J; de Vugt, Marjolein; Köhler, Sebastian; Wolfs, Claire; Kerpershoek, Liselot; Handels, Ron L H; Orrell, Martin; Woods, Bob; Jelley, Hannah; Stephan, Astrid; Bieber, Anja; Meyer, Gabriele; Engedal, Knut; Selbaek, Geir; Wimo, Anders; Irving, Kate; Hopper, Louise; Gonçalves-Pereira, Manuel; Portolani, Elisa; Zanetti, Orazio; Verhey, Frans R

2017-01-01

To identify caregiver profiles of persons with mild to moderate dementia and to investigate differences between identified caregiver profiles, using baseline data of the international prospective cohort study Actifcare. A latent class analysis was used to discover different caregiver profiles based on disease related characteristics of 453 persons with dementia and their 453 informal caregivers. These profiles were compared with regard to quality of life (CarerQoL score), depressive symptoms (HADS-D score) and perseverance time. A 5-class model was identified, with the best Bayesian Information Criterion value, significant likelihood ratio test (p < 0.001), high entropy score (0.88) and substantive interpretability. The classes could be differentiated on two axes: (i) caregivers' age, relationship with persons with dementia, severity of dementia, and (ii) tendency towards stress and difficulty adapting to stress. Classes showed significant differences with all dependent variables, and were labelled 'older low strain', 'older intermediate strain', 'older high strain', 'younger low strain' and 'younger high strain'. Differences exist between types of caregivers that explain variability in quality of life, depressive symptoms and perseverance time. Our findings may give direction for tailored interventions for caregivers of persons with dementia, which may improve social health and reduce health care costs.

Features of standardized nursing terminology sets in Japan.

PubMed

Sagara, Kaoru; Abe, Akinori; Ozaku, Hiromi Itoh; Kuwahara, Noriaki; Kogure, Kiyoshi

2006-01-01

This paper reports the features and relationships between standardizes nursing terminology sets used in Japan. First, we analyzed the common parts in five standardized nursing terminology sets: the Japan Nursing Practice Standard Master (JNPSM) that includes the names of nursing activities and is built by the Medical Information Center Development Center (MEDIS-DC); the labels of the Japan Classification of Nursing Practice (JCNP), built by the term advisory committee in the Japan Academy of Nursing Science; the labels of the International Classification for Nursing Practice (ICNP) translated to Japanese; the labels, domain names, and class names of the North American Nursing Diagnosis Association (NANDA) Nursing Diagnoses 2003-2004 translated to Japanese; and the terms included in the labels of Nursing Interventions Classification (NIC) translated to Japanese. Then we compared them with terms in a thesaurus dictionary, the Bunrui Goihyo, that contains general Japanese words and is built by the National Institute for Japanese Language. 1) the level of interchangeability between four standardized nursing terminology sets is quite low; 2) abbreviations and katakana words are frequently used to express nursing activities; 3) general Japanese words are usually used to express the status or situation of patients.

Robust Framework to Combine Diverse Classifiers Assigning Distributed Confidence to Individual Classifiers at Class Level

PubMed Central

Arshad, Sannia; Rho, Seungmin

2014-01-01

We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes. PMID:25295302

Robust framework to combine diverse classifiers assigning distributed confidence to individual classifiers at class level.

PubMed

Khalid, Shehzad; Arshad, Sannia; Jabbar, Sohail; Rho, Seungmin

2014-01-01

We have presented a classification framework that combines multiple heterogeneous classifiers in the presence of class label noise. An extension of m-Mediods based modeling is presented that generates model of various classes whilst identifying and filtering noisy training data. This noise free data is further used to learn model for other classifiers such as GMM and SVM. A weight learning method is then introduced to learn weights on each class for different classifiers to construct an ensemble. For this purpose, we applied genetic algorithm to search for an optimal weight vector on which classifier ensemble is expected to give the best accuracy. The proposed approach is evaluated on variety of real life datasets. It is also compared with existing standard ensemble techniques such as Adaboost, Bagging, and Random Subspace Methods. Experimental results show the superiority of proposed ensemble method as compared to its competitors, especially in the presence of class label noise and imbalance classes.

Defense Advanced Research Projects Agency (DARPA) Agent Markup Language Computer Aided Knowledge Acquisition

DTIC Science & Technology

2005-06-01

34> <rdfs:subClassOf rdf:resource="#Condition"/> <rdfs:label>Economic Self -Sufficiency Class</rdfs:label> <cnd:categoryCode>C</cnd:categoryCode...cnd:index>3.3.4.1</cnd:index> <cnd:title>Economic Self -Sufficiency</cnd:title> <cnd:definition>The ability of a nation to...34#International_Economic_Position"/> <cnd:subCategory rdf:resource="# Self -Sufficiency_In_Food"/> <cnd:subCategory rdf:resource="# Self

Multimodal Discriminative Binary Embedding for Large-Scale Cross-Modal Retrieval.

PubMed

Wang, Di; Gao, Xinbo; Wang, Xiumei; He, Lihuo; Yuan, Bo

2016-10-01

Multimodal hashing, which conducts effective and efficient nearest neighbor search across heterogeneous data on large-scale multimedia databases, has been attracting increasing interest, given the explosive growth of multimedia content on the Internet. Recent multimodal hashing research mainly aims at learning the compact binary codes to preserve semantic information given by labels. The overwhelming majority of these methods are similarity preserving approaches which approximate pairwise similarity matrix with Hamming distances between the to-be-learnt binary hash codes. However, these methods ignore the discriminative property in hash learning process, which results in hash codes from different classes undistinguished, and therefore reduces the accuracy and robustness for the nearest neighbor search. To this end, we present a novel multimodal hashing method, named multimodal discriminative binary embedding (MDBE), which focuses on learning discriminative hash codes. First, the proposed method formulates the hash function learning in terms of classification, where the binary codes generated by the learned hash functions are expected to be discriminative. And then, it exploits the label information to discover the shared structures inside heterogeneous data. Finally, the learned structures are preserved for hash codes to produce similar binary codes in the same class. Hence, the proposed MDBE can preserve both discriminability and similarity for hash codes, and will enhance retrieval accuracy. Thorough experiments on benchmark data sets demonstrate that the proposed method achieves excellent accuracy and competitive computational efficiency compared with the state-of-the-art methods for large-scale cross-modal retrieval task.

A latent class regression analysis of men's conformity to masculine norms and psychological distress.

PubMed

Wong, Y Joel; Owen, Jesse; Shea, Munyi

2012-01-01

How are specific dimensions of masculinity related to psychological distress in specific groups of men? To address this question, the authors used latent class regression to assess the optimal number of latent classes that explained differential relationships between conformity to masculine norms and psychological distress in a racially diverse sample of 223 men. The authors identified a 2-class solution. Both latent classes demonstrated very different associations between conformity to masculine norms and psychological distress. In Class 1 (labeled risk avoiders; n = 133), conformity to the masculine norm of risk-taking was negatively related to psychological distress. In Class 2 (labeled detached risk-takers; n = 90), conformity to the masculine norms of playboy, self-reliance, and risk-taking was positively related to psychological distress, whereas conformity to the masculine norm of violence was negatively related to psychological distress. A post hoc analysis revealed that younger men and Asian American men (compared with Latino and White American men) had significantly greater odds of being in Class 2 versus Class 1. The implications of these findings for future research and clinical practice are examined. (c) 2012 APA, all rights reserved.

Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction.

PubMed

Stojanova, Daniela; Ceci, Michelangelo; Malerba, Donato; Dzeroski, Saso

2013-09-26

Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Our newly developed method for HMC takes into account network information in the learning phase: When used for gene function prediction in the context of PPI networks, the explicit consideration of network autocorrelation increases the predictive performance of the learned models. Overall, we found that this holds for different gene features/ descriptions, functional annotation schemes, and PPI networks: Best results are achieved when the PPI network is dense and contains a large proportion of function-relevant interactions.

Superposition and alignment of labeled point clouds.

PubMed

Fober, Thomas; Glinca, Serghei; Klebe, Gerhard; Hüllermeier, Eyke

2011-01-01

Geometric objects are often represented approximately in terms of a finite set of points in three-dimensional euclidean space. In this paper, we extend this representation to what we call labeled point clouds. A labeled point cloud is a finite set of points, where each point is not only associated with a position in three-dimensional space, but also with a discrete class label that represents a specific property. This type of model is especially suitable for modeling biomolecules such as proteins and protein binding sites, where a label may represent an atom type or a physico-chemical property. Proceeding from this representation, we address the question of how to compare two labeled points clouds in terms of their similarity. Using fuzzy modeling techniques, we develop a suitable similarity measure as well as an efficient evolutionary algorithm to compute it. Moreover, we consider the problem of establishing an alignment of the structures in the sense of a one-to-one correspondence between their basic constituents. From a biological point of view, alignments of this kind are of great interest, since mutually corresponding molecular constituents offer important information about evolution and heredity, and can also serve as a means to explain a degree of similarity. In this paper, we therefore develop a method for computing pairwise or multiple alignments of labeled point clouds. To this end, we proceed from an optimal superposition of the corresponding point clouds and construct an alignment which is as much as possible in agreement with the neighborhood structure established by this superposition. We apply our methods to the structural analysis of protein binding sites.

49 CFR 173.150 - Exceptions for Class 3 (flammable and combustible liquids).

Code of Federal Regulations, 2012 CFR

2012-10-01

... Class 3 (flammable and combustible liquids). (a) General. Exceptions for hazardous materials shipments... flammable liquids (Class 3) and combustible liquids are excepted from labeling requirements, unless the... aircraft, the following combination packagings are authorized: (1) For flammable liquids in Packing Group I...

Archiving Spectral Libraries in the Planetary Data System

NASA Astrophysics Data System (ADS)

Slavney, S.; Guinness, E. A.; Scholes, D.; Zastrow, A.

2017-12-01

Spectral libraries are becoming popular candidates for archiving in PDS. With the increase in the number of individual investigators funded by programs such as NASA's PDART, the PDS Geosciences Node is receiving many requests for support from proposers wishing to archive various forms of laboratory spectra. To accommodate the need for a standardized approach to archiving spectra, the Geosciences Node has designed the PDS Spectral Library Data Dictionary, which contains PDS4 classes and attributes specifically for labeling spectral data, including a classification scheme for samples. The Reflectance Experiment Laboratory (RELAB) at Brown University, which has long been a provider of spectroscopy equipment and services to the science community, has provided expert input into the design of the dictionary. Together the Geosciences Node and RELAB are preparing the whole of the RELAB Spectral Library, consisting of many thousands of spectra collected over the years, to be archived in PDS. An online interface for searching, displaying, and downloading selected spectra is planned, using the Spectral Library metadata recorded in the PDS labels. The data dictionary and online interface will be extended to include spectral libraries submitted by other data providers. The Spectral Library Data Dictionary is now available from PDS at https://pds.nasa.gov/pds4/schema/released/. It can be used in PDS4 labels for reflectance spectra as well as for Raman, XRF, XRD, LIBS, and other types of spectra. Ancillary data such as images, chemistry, and abundance data are also supported. To help generate PDS4-compliant labels for spectra, the Geosciences Node provides a label generation program called MakeLabels (http://pds-geosciences.wustl.edu/tools/makelabels.html) which creates labels from a template, and which can be used for any kind of PDS4 label. For information, contact the Geosciences Node at geosci@wunder.wustl.edu.

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2012 CFR

2012-04-01

..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I...

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2014 CFR

2014-04-01

..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I...

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2013 CFR

2013-04-01

..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I...

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2010 CFR

2010-04-01

... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL...

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2011 CFR

2011-04-01

... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL...

Towards Autonomous Agriculture: Automatic Ground Detection Using Trinocular Stereovision

PubMed Central

Reina, Giulio; Milella, Annalisa

2012-01-01

Autonomous driving is a challenging problem, particularly when the domain is unstructured, as in an outdoor agricultural setting. Thus, advanced perception systems are primarily required to sense and understand the surrounding environment recognizing artificial and natural structures, topology, vegetation and paths. In this paper, a self-learning framework is proposed to automatically train a ground classifier for scene interpretation and autonomous navigation based on multi-baseline stereovision. The use of rich 3D data is emphasized where the sensor output includes range and color information of the surrounding environment. Two distinct classifiers are presented, one based on geometric data that can detect the broad class of ground and one based on color data that can further segment ground into subclasses. The geometry-based classifier features two main stages: an adaptive training stage and a classification stage. During the training stage, the system automatically learns to associate geometric appearance of 3D stereo-generated data with class labels. Then, it makes predictions based on past observations. It serves as well to provide training labels to the color-based classifier. Once trained, the color-based classifier is able to recognize similar terrain classes in stereo imagery. The system is continuously updated online using the latest stereo readings, thus making it feasible for long range and long duration navigation, over changing environments. Experimental results, obtained with a tractor test platform operating in a rural environment, are presented to validate this approach, showing an average classification precision and recall of 91.0% and 77.3%, respectively.

Using random forest for reliable classification and cost-sensitive learning for medical diagnosis.

PubMed

Yang, Fan; Wang, Hua-zhen; Mi, Hong; Lin, Cheng-de; Cai, Wei-wen

2009-01-30

Most machine-learning classifiers output label predictions for new instances without indicating how reliable the predictions are. The applicability of these classifiers is limited in critical domains where incorrect predictions have serious consequences, like medical diagnosis. Further, the default assumption of equal misclassification costs is most likely violated in medical diagnosis. In this paper, we present a modified random forest classifier which is incorporated into the conformal predictor scheme. A conformal predictor is a transductive learning scheme, using Kolmogorov complexity to test the randomness of a particular sample with respect to the training sets. Our method show well-calibrated property that the performance can be set prior to classification and the accurate rate is exactly equal to the predefined confidence level. Further, to address the cost sensitive problem, we extend our method to a label-conditional predictor which takes into account different costs for misclassifications in different class and allows different confidence level to be specified for each class. Intensive experiments on benchmark datasets and real world applications show the resultant classifier is well-calibrated and able to control the specific risk of different class. The method of using RF outlier measure to design a nonconformity measure benefits the resultant predictor. Further, a label-conditional classifier is developed and turn to be an alternative approach to the cost sensitive learning problem that relies on label-wise predefined confidence level. The target of minimizing the risk of misclassification is achieved by specifying the different confidence level for different class.

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

NASA Astrophysics Data System (ADS)

Shin, Christian K.; Doermann, David S.

1999-12-01

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

76 FR 51257 - First-Class Package Service

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-18

... Ground, and Bound Printed Matter prices. * * * * * * * * 2.0 Additional Physical Standards by Class of... ``PRSRT'') First-Class Package'' (or ``PKG'') must be printed as part of; directly below; or to the left... follows:] b. * * * labeling: * * * * * 2. Line 2: ``FC PARCELS 3D.'' [Revise item 4.4c2 by changing ``FCM...

40 CFR 600.315-82 - Classes of comparable automobiles.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 30 2011-07-01 2011-07-01 false Classes of comparable automobiles. 600... 1977 and Later Model Year Automobiles-Labeling § 600.315-82 Classes of comparable automobiles. (a) The Secretary will classify automobiles as passenger automobiles or light trucks (nonpassenger automobiles) in...

40 CFR 600.315-82 - Classes of comparable automobiles.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 29 2010-07-01 2010-07-01 false Classes of comparable automobiles. 600... 1977 and Later Model Year Automobiles-Labeling § 600.315-82 Classes of comparable automobiles. (a) The Secretary will classify automobiles as passenger automobiles or light trucks (nonpassenger automobiles) in...

Automated Classification of Thermal Infrared Spectra Using Self-organizing Maps

NASA Technical Reports Server (NTRS)

Roush, Ted L.; Hogan, Robert

2006-01-01

Existing and planned space missions to a variety of planetary and satellite surfaces produce an ever increasing volume of spectral data. Understanding the scientific informational content in this large data volume is a daunting task. Fortunately various statistical approaches are available to assess such data sets. Here we discuss an automated classification scheme based on Kohonen Self-organizing maps (SOM) we have developed. The SUM process produces an output layer were spectra having similar properties lie in close proximity to each other. One major effort is partitioning this output layer into appropriate regions. This is prefonned by defining dosed regions based upon the strength of the boundaries between adjacent cells in the SOM output layer. We use the Davies-Bouldin index as a measure of the inter-class similarities and intra-class dissimilarities that determines the optimum partition of the output layer, and hence number of SOM clusters. This allows us to identify the natural number of clusters formed from the spectral data. Mineral spectral libraries prepared at Arizona State University (ASU) and John Hopkins University (JHU) are used to test and evaluate the classification scheme. We label the library sample spectra in a hierarchical scheme with class, subclass, and mineral group names. We use a portion of the spectra to train the SOM, i.e. produce the output layer, while the remaining spectra are used to test the SOM. The test spectra are presented to the SOM output layer and assigned membership to the appropriate cluster. We then evaluate these assignments to assess the scientific meaning and accuracy of the derived SOM classes as they relate to the labels. We demonstrate that unsupervised classification by SOMs can be a useful component in autonomous systems designed to identify mineral species from reflectance and emissivity spectra in the therrnal IR.

Evaluation of stereo-array isotope labeling (SAIL) patterns for automated structural analysis of proteins with CYANA.

PubMed

Ikeya, Teppei; Terauchi, Tsutomu; Güntert, Peter; Kainosho, Masatsune

2006-07-01

Recently we have developed the stereo-array isotope labeling (SAIL) technique to overcome the conventional molecular size limitation in NMR protein structure determination by employing complete stereo- and regiospecific patterns of stable isotopes. SAIL sharpens signals and simplifies spectra without the loss of requisite structural information, thus making large classes of proteins newly accessible to detailed solution structure determination. The automated structure calculation program CYANA can efficiently analyze SAIL-NOESY spectra and calculate structures without manual analysis. Nevertheless, the original SAIL method might not be capable of determining the structures of proteins larger than 50 kDa or membrane proteins, for which the spectra are characterized by many broadened and overlapped peaks. Here we have carried out simulations of new SAIL patterns optimized for minimal relaxation and overlap, to evaluate the combined use of SAIL and CYANA for solving the structures of larger proteins and membrane proteins. The modified approach reduces the number of peaks to nearly half of that observed with uniform labeling, while still yielding well-defined structures and is expected to enable NMR structure determinations of these challenging systems.

Flow-aggregated traffic-driven label mapping in label-switching networks

NASA Astrophysics Data System (ADS)

Nagami, Kenichi; Katsube, Yasuhiro; Esaki, Hiroshi; Nakamura, Osamu

1998-12-01

Label switching technology enables high performance, flexible, layer-3 packet forwarding based on the fixed length label information mapped to the layer-3 packet stream. A Label Switching Router (LSR) forwards layer-3 packets based on their label information mapped to the layer-3 address information as well as their layer-3 address information. This paper evaluates the required number of labels under traffic-driven label mapping policy using the real backbone traffic traces. The evaluation shows that the label mapping policy requires a large number of labels. In order to reduce the required number of labels, we propose a label mapping policy which is a traffic-driven label mapping for the traffic toward the same destination network. The evaluation shows that the proposed label mapping policy requires only about one tenth as many labels compared with the traffic-driven label mapping for the host-pair packet stream,and the topology-driven label mapping for the destination network packet stream.

Hazardous Material Packaging and Transportation

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

Hypes, Philip A.

2016-02-04

This is a student training course. Some course objectives are to: recognize and use standard international and US customary units to describe activities and exposure rates associated with radioactive material; determine whether a quantity of a single radionuclide meets the definition of a class 7 (radioactive) material; determine, for a given single radionuclide, the shipping quantity activity limits per 49 Code of Federal Regulations (CFR) 173.435; determine the appropriate radioactive material hazard class proper shipping name for a given material; determine when a single radionuclide meets the DOT definition of a hazardous substance; determine the appropriate packaging required for amore » given radioactive material; identify the markings to be placed on a package of radioactive material; determine the label(s) to apply to a given radioactive material package; identify the entry requirements for radioactive material labels; determine the proper placement for radioactive material label(s); identify the shipping paper entry requirements for radioactive material; select the appropriate placards for a given radioactive material shipment or vehicle load; and identify allowable transport limits and unacceptable transport conditions for radioactive material.« less

An incremental knowledge assimilation system (IKAS) for mine detection

NASA Astrophysics Data System (ADS)

Porway, Jake; Raju, Chaitanya; Varadarajan, Karthik Mahesh; Nguyen, Hieu; Yadegar, Joseph

2010-04-01

In this paper we present an adaptive incremental learning system for underwater mine detection and classification that utilizes statistical models of seabed texture and an adaptive nearest-neighbor classifier to identify varied underwater targets in many different environments. The first stage of processing uses our Background Adaptive ANomaly detector (BAAN), which identifies statistically likely target regions using Gabor filter responses over the image. Using this information, BAAN classifies the background type and updates its detection using background-specific parameters. To perform classification, a Fully Adaptive Nearest Neighbor (FAAN) determines the best label for each detection. FAAN uses an extremely fast version of Nearest Neighbor to find the most likely label for the target. The classifier perpetually assimilates new and relevant information into its existing knowledge database in an incremental fashion, allowing improved classification accuracy and capturing concept drift in the target classes. Experiments show that the system achieves >90% classification accuracy on underwater mine detection tasks performed on synthesized datasets provided by the Office of Naval Research. We have also demonstrated that the system can incrementally improve its detection accuracy by constantly learning from new samples.

Sample Complexity Bounds for Differentially Private Learning

PubMed Central

Chaudhuri, Kamalika; Hsu, Daniel

2013-01-01

This work studies the problem of privacy-preserving classification – namely, learning a classifier from sensitive data while preserving the privacy of individuals in the training set. In particular, the learning algorithm is required in this problem to guarantee differential privacy, a very strong notion of privacy that has gained significant attention in recent years. A natural question to ask is: what is the sample requirement of a learning algorithm that guarantees a certain level of privacy and accuracy? We address this question in the context of learning with infinite hypothesis classes when the data is drawn from a continuous distribution. We first show that even for very simple hypothesis classes, any algorithm that uses a finite number of examples and guarantees differential privacy must fail to return an accurate classifier for at least some unlabeled data distributions. This result is unlike the case with either finite hypothesis classes or discrete data domains, in which distribution-free private learning is possible, as previously shown by Kasiviswanathan et al. (2008). We then consider two approaches to differentially private learning that get around this lower bound. The first approach is to use prior knowledge about the unlabeled data distribution in the form of a reference distribution chosen independently of the sensitive data. Given such a reference , we provide an upper bound on the sample requirement that depends (among other things) on a measure of closeness between and the unlabeled data distribution. Our upper bound applies to the non-realizable as well as the realizable case. The second approach is to relax the privacy requirement, by requiring only label-privacy – namely, that the only labels (and not the unlabeled parts of the examples) be considered sensitive information. An upper bound on the sample requirement of learning with label privacy was shown by Chaudhuri et al. (2006); in this work, we show a lower bound. PMID:25285183

Deep Learning for Automated Extraction of Primary Sites from Cancer Pathology Reports

DOE PAGES

Qiu, John; Yoon, Hong-Jun; Fearn, Paul A.; ...

2017-05-03

Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. Here in this study we investigated deep learning and a convolutional neural network (CNN), for extracting ICDO- 3 topographic codes from a corpus of breast and lung cancer pathology reports. We performed two experiments, using a CNN and a more conventional term frequency vector approach, to assess the effects of class prevalence and inter-class transfer learning. The experiments were based on a set of 942 pathology reports with human expert annotations asmore » the gold standard. CNN performance was compared against a more conventional term frequency vector space approach. We observed that the deep learning models consistently outperformed the conventional approaches in the class prevalence experiment, resulting in micro and macro-F score increases of up to 0.132 and 0.226 respectively when class labels were well populated. Specifically, the best performing CNN achieved a micro-F score of 0.722 over 12 ICD-O-3 topography codes. Transfer learning provided a consistent but modest performance boost for the deep learning methods but trends were contingent on CNN method and cancer site. Finally, these encouraging results demonstrate the potential of deep learning for automated abstraction of pathology reports.« less

Deep Learning for Automated Extraction of Primary Sites from Cancer Pathology Reports

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

Qiu, John; Yoon, Hong-Jun; Fearn, Paul A.

Pathology reports are a primary source of information for cancer registries which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. Here in this study we investigated deep learning and a convolutional neural network (CNN), for extracting ICDO- 3 topographic codes from a corpus of breast and lung cancer pathology reports. We performed two experiments, using a CNN and a more conventional term frequency vector approach, to assess the effects of class prevalence and inter-class transfer learning. The experiments were based on a set of 942 pathology reports with human expert annotations asmore » the gold standard. CNN performance was compared against a more conventional term frequency vector space approach. We observed that the deep learning models consistently outperformed the conventional approaches in the class prevalence experiment, resulting in micro and macro-F score increases of up to 0.132 and 0.226 respectively when class labels were well populated. Specifically, the best performing CNN achieved a micro-F score of 0.722 over 12 ICD-O-3 topography codes. Transfer learning provided a consistent but modest performance boost for the deep learning methods but trends were contingent on CNN method and cancer site. Finally, these encouraging results demonstrate the potential of deep learning for automated abstraction of pathology reports.« less

What is prescription labeling communicating to doctors about hepatotoxic drugs? A study of FDA approved product labeling.

PubMed

Willy, Mary E; Li, Zili

2004-04-01

The objective of this study was to evaluate the informativeness and consistency of product labeling of hepatotoxic drugs marketed in the United States. We searched the Physicians' Desk Reference-2000 for prescription drugs with hepatic failure and/or hepatic necrosis listed in the labeling. We used a six-item checklist to evaluate the 'informativeness' and consistency of the labeling content. An informativeness score equaled the proportion of checklist items present in each drug's labeling. Ninety-five prescription drugs were included in the study. Eleven (12%) of the drugs had information related to hepatic failure in a Black Boxed Warning, 52 (54%) in the Warnings section and 32 (34%) in the Adverse Reactions section of the label. The mean informativeness score was 35%; the score was significantly higher, 61%, when the risk was perceived to be high. The informativeness of labeling was not affected by the time of the labeling, but differed across the Center for Drug Evaluation and Research (CDER) Review Division responsible for the labeling. The information provided in labeling is variable and affected by many factors, including the perceived level of risk and review division strategy. Product labeling may benefit from current FDA initiatives to improve the consistency of risk-related labeling.

Effect of warning placement on the information processing of college students reading an OTC drug facts panel.

PubMed

Bhansali, Archita H; Sangani, Darshan S; Mhatre, Shivani K; Sansgiry, Sujit S

2018-01-01

To compare three over-the-counter (OTC) Drug Facts panel versions for information processing optimization among college students. University of Houston students (N = 210) participated in a cross-sectional survey from January to May 2010. A current FDA label was compared to two experimental labels developed using the theory of CHREST to test information processing by re-positioning the warning information within the Drug Facts panel. Congruency was defined as placing like information together. Information processing was evaluated using the OTC medication Label Evaluation Process Model (LEPM): label comprehension, ease-of-use, attitude toward the product, product evaluation, and purchase intention. Experimental label with chunked congruent information (uses-directions-other information-warnings) was rated significantly higher than the current FDA label and had the best average scores among the LEPM information processing variables. If replications uphold these findings, the FDA label design might be revised to improve information processing.

Object class segmentation of RGB-D video using recurrent convolutional neural networks.

PubMed

Pavel, Mircea Serban; Schulz, Hannes; Behnke, Sven

2017-04-01

Object class segmentation is a computer vision task which requires labeling each pixel of an image with the class of the object it belongs to. Deep convolutional neural networks (DNN) are able to learn and take advantage of local spatial correlations required for this task. They are, however, restricted by their small, fixed-sized filters, which limits their ability to learn long-range dependencies. Recurrent Neural Networks (RNN), on the other hand, do not suffer from this restriction. Their iterative interpretation allows them to model long-range dependencies by propagating activity. This property is especially useful when labeling video sequences, where both spatial and temporal long-range dependencies occur. In this work, a novel RNN architecture for object class segmentation is presented. We investigate several ways to train such a network. We evaluate our models on the challenging NYU Depth v2 dataset for object class segmentation and obtain competitive results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Graph-Based Semi-Supervised Hyperspectral Image Classification Using Spatial Information

NASA Astrophysics Data System (ADS)

Jamshidpour, N.; Homayouni, S.; Safari, A.

2017-09-01

Hyperspectral image classification has been one of the most popular research areas in the remote sensing community in the past decades. However, there are still some problems that need specific attentions. For example, the lack of enough labeled samples and the high dimensionality problem are two most important issues which degrade the performance of supervised classification dramatically. The main idea of semi-supervised learning is to overcome these issues by the contribution of unlabeled samples, which are available in an enormous amount. In this paper, we propose a graph-based semi-supervised classification method, which uses both spectral and spatial information for hyperspectral image classification. More specifically, two graphs were designed and constructed in order to exploit the relationship among pixels in spectral and spatial spaces respectively. Then, the Laplacians of both graphs were merged to form a weighted joint graph. The experiments were carried out on two different benchmark hyperspectral data sets. The proposed method performed significantly better than the well-known supervised classification methods, such as SVM. The assessments consisted of both accuracy and homogeneity analyses of the produced classification maps. The proposed spectral-spatial SSL method considerably increased the classification accuracy when the labeled training data set is too scarce.When there were only five labeled samples for each class, the performance improved 5.92% and 10.76% compared to spatial graph-based SSL, for AVIRIS Indian Pine and Pavia University data sets respectively.

Characterizing outcome preferences in patients with psychotic disorders: a discrete choice conjoint experiment.

PubMed

Zipursky, Robert B; Cunningham, Charles E; Stewart, Bailey; Rimas, Heather; Cole, Emily; Vaz, Stephanie McDermid

2017-07-01

The majority of individuals with schizophrenia will achieve a remission of psychotic symptoms, but few will meet criteria for recovery. Little is known about what outcomes are important to patients. We carried out a discrete choice experiment to characterize the outcome preferences of patients with psychotic disorders. Participants (N=300) were recruited from two clinics specializing in psychotic disorders. Twelve outcomes were each defined at three levels and incorporated into a computerized survey with 15 choice tasks. Utility values and importance scores were calculated for each outcome level. Latent class analysis was carried out to determine whether participants were distributed into segments with different preferences. Multinomial logistic regression was used to identify predictors of segment membership. Latent class analysis revealed three segments of respondents. The first segment (48%), which we labeled "Achievement-focused," preferred to have a full-time job, to live independently, to be in a long-term relationship, and to have no psychotic symptoms. The second segment (29%), labeled "Stability-focused," preferred to not have a job, to live independently, and to have some ongoing psychotic symptoms. The third segment (23%), labeled "Health-focused," preferred to not have a job, to live in supervised housing, and to have no psychotic symptoms. Segment membership was predicted by education, socioeconomic status, psychotic symptom severity, and work status. This study has revealed that patients with psychotic disorders are distributed between segments with different outcome preferences. New approaches to improve outcomes for patients with psychotic disorders should be informed by a greater understanding of patient preferences and priorities. Copyright © 2016 Elsevier B.V. All rights reserved.

Drug utilisation profile in the neonatal unit of a university hospital: a prospective observational study in Brazil.

PubMed

Gonçalves, Adriana Cristina de Souza; Reis, Adriano Max Moreira; Gusmão, Ana Carolina Marçal; Bouzada, Maria Cândida Ferrarez

2015-08-01

Advances in neonatology have contributed to changes in the drug utilisation profile in neonates, both in the number of drugs and the pharmacotherapeutic groups. To analyse drug use in the neonatal care unit of a teaching hospital in Brazil and to evaluate the associations among perinatal, clinical care and drug use data. The neonatal care unit of a teaching hospital in Brazil. A prospective observational study was conducted. Perinatal, clinical care and pharmacotherapy data were collected from the patients' medical records. Labelling information regarding neonatal use was analysed for prescribed drugs. The data were analysed using univariate descriptive statistics and quasi-Poisson regression. Frequency of drug use by gestational age. The study included 187 patients; 157 (84.0 %) received drugs. The mean gestational age was 35.8 weeks. The mean number of drugs prescribed per patient was 6.4. The number of drugs used was inversely correlated to gestational age and birth weight. The most commonly prescribed drugs belonged to the following anatomical therapeutic chemical groups: nervous system drugs, anti-infectives for systemic use, and alimentary tract and metabolism drugs. Information regarding neonatal use was given in the labelling of only 20.5 % of the prescribed drugs. Of these, only 9.5 % had information specific for preterm infants. Drug administration to neonates is frequently and inversely correlated to gestational age and birth weight. Neonates are exposed to different therapeutic classes, reflecting scientific advances in neonatology. In Brazil, the percentage of drugs with neonate-specific labelling information is low. Consequently, there is an evident need for efforts to guarantee effective and safe pharmacotherapy for neonates.

GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation.

PubMed

Bakas, Spyridon; Zeng, Ke; Sotiras, Aristeidis; Rathore, Saima; Akbari, Hamed; Gaonkar, Bilwaj; Rozycki, Martin; Pati, Sarthak; Davatzikos, Christos

2016-01-01

We present an approach for segmenting low- and high-grade gliomas in multimodal magnetic resonance imaging volumes. The proposed approach is based on a hybrid generative-discriminative model. Firstly, a generative approach based on an Expectation-Maximization framework that incorporates a glioma growth model is used to segment the brain scans into tumor, as well as healthy tissue labels. Secondly, a gradient boosting multi-class classification scheme is used to refine tumor labels based on information from multiple patients. Lastly, a probabilistic Bayesian strategy is employed to further refine and finalize the tumor segmentation based on patient-specific intensity statistics from the multiple modalities. We evaluated our approach in 186 cases during the training phase of the BRAin Tumor Segmentation (BRATS) 2015 challenge and report promising results. During the testing phase, the algorithm was additionally evaluated in 53 unseen cases, achieving the best performance among the competing methods.

Clinical Pharmacology and Cardiovascular Safety of Naproxen.

PubMed

Angiolillo, Dominick J; Weisman, Steven M

2017-04-01

The voluntary withdrawal of Vioxx (rofecoxib) from the market in 2004, as well as the 2005 and 2014 US FDA Advisory Committee meetings about non-steroidal anti-inflammatory drugs (NSAIDs) and cardiovascular risk, have raised questions surrounding the use of NSAIDs in at-risk populations. This paper discusses the cardiovascular safety profile of naproxen in the context of the NSAID class. The balance of evidence suggests that cardiovascular risk correlates with cyclooxygenase (COX)-2 selectivity, and the low COX-2 selectivity of naproxen results in a lower cardiovascular risk than that of other NSAIDs. The over-the-counter (OTC) use of naproxen is expected to pose minimal cardiovascular risk; however, the benefit-risk ratio and appropriate use should be considered at an individual patient level, particularly to assess underlying conditions that may increase the risk of events. Likewise, regulatory authorities should revisit label information periodically to ensure labeling reflects the current understanding of benefits and risks.

21 CFR 14.27 - Determination to close portions of advisory committee meetings.

Code of Federal Regulations, 2011 CFR

2011-04-01

... protocols and procedures for a class of drugs or devices; consideration of labeling requirements for a class... brought to their attention, the person will be required to leave the meeting immediately. This inadvertent...

Five-year-olds are willing, but 4-year-olds refuse, to trust informants who offer new and unfamiliar labels for parts of the body.

PubMed

Luu, Betty; Rosnay, Marc de; Harris, Paul L

2013-10-01

This study employed the selective trust paradigm to examine how children interpret novel labels when compared with labels they already know to be accurate or inaccurate within the biological domain. The participants--3-, 4-, and 5-year-olds (N=144)--were allocated to one of three conditions. In the accurate versus inaccurate condition, one informant labeled body parts correctly, whereas the other labeled them incorrectly (e.g., calling an eye an "arm"). In the accurate versus novel condition, one informant labeled body parts accurately, whereas the other provided novel labels (e.g., calling an eye a "roke"). Finally, in the inaccurate versus novel condition, one informant labeled body parts incorrectly, whereas the other offered novel labels. In subsequent test trials, the two informants provided conflicting labels for unfamiliar internal organs. In the accurate versus inaccurate condition, children sought and endorsed labels from the accurate informant. In the accurate versus novel condition, only 4- and 5-year-olds preferred the accurate informant, whereas 3-year-olds did not selectively prefer either informant. In the inaccurate versus novel condition, only 5-year-olds preferred the novel informant, whereas 3- and 4-year-olds did not demonstrate a selective preference. Results are supportive of previous studies suggesting that 3-year-olds are sensitive to inaccuracy and that 4-year-olds privilege accuracy. However, 3- and 4-year-olds appear to be unsure as to how the novel informant should be construed. In contrast, 5-year-olds appreciate that speakers offering new information are more trustworthy than those offering inaccurate information, but they are cautious in judging such informants as being "better" at providing that information. Copyright © 2013 Elsevier Inc. All rights reserved.

An investigative model evaluating how consumers process pictorial information on nonprescription medication labels.

PubMed

Sansgiry, S S; Cady, P S

1997-01-01

Currently, marketed over-the-counter (OTC) medication labels were simulated and tested in a controlled environment to understand consumer evaluation of OTC label information. Two factors, consumers' age (younger and older adults) and label designs (picture-only, verbal-only, congruent picture-verbal, and noncongruent picture-verbal) were controlled and tested to evaluate consumer information processing. The effects exerted by the independent variables, namely, comprehension of label information (understanding) and product evaluations (satisfaction, certainty, and perceived confusion) were evaluated on the dependent variable purchase intention. Intention measured as purchase recommendation was significantly related to product evaluations and affected by the factor label design. Participants' level of perceived confusion was more important than actual understanding of information on OTC medication labels. A Label Evaluation Process Model was developed which could be used for future testing of OTC medication labels.

19 CFR 12.22 - Labels; samples.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 1 2010-04-01 2010-04-01 false Labels; samples. 12.22 Section 12.22 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY SPECIAL CLASSES OF MERCHANDISE Viruses, Serums, Toxins, Antitoxins, and Analogous Products for the...

19 CFR 12.22 - Labels; samples.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 1 2011-04-01 2011-04-01 false Labels; samples. 12.22 Section 12.22 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY SPECIAL CLASSES OF MERCHANDISE Viruses, Serums, Toxins, Antitoxins, and Analogous Products for the...

19 CFR 12.22 - Labels; samples.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 1 2013-04-01 2013-04-01 false Labels; samples. 12.22 Section 12.22 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY SPECIAL CLASSES OF MERCHANDISE Viruses, Serums, Toxins, Antitoxins, and Analogous Products for the...

Cross-label Suppression: a Discriminative and Fast Dictionary Learning with Group Regularization.

PubMed

Wang, Xiudong; Gu, Yuantao

2017-05-10

This paper addresses image classification through learning a compact and discriminative dictionary efficiently. Given a structured dictionary with each atom (columns in the dictionary matrix) related to some label, we propose crosslabel suppression constraint to enlarge the difference among representations for different classes. Meanwhile, we introduce group regularization to enforce representations to preserve label properties of original samples, meaning the representations for the same class are encouraged to be similar. Upon the cross-label suppression, we don't resort to frequently-used `0-norm or `1- norm for coding, and obtain computational efficiency without losing the discriminative power for categorization. Moreover, two simple classification schemes are also developed to take full advantage of the learnt dictionary. Extensive experiments on six data sets including face recognition, object categorization, scene classification, texture recognition and sport action categorization are conducted, and the results show that the proposed approach can outperform lots of recently presented dictionary algorithms on both recognition accuracy and computational efficiency.

Labeled Graph Kernel for Behavior Analysis.

PubMed

Zhao, Ruiqi; Martinez, Aleix M

2016-08-01

Automatic behavior analysis from video is a major topic in many areas of research, including computer vision, multimedia, robotics, biology, cognitive science, social psychology, psychiatry, and linguistics. Two major problems are of interest when analyzing behavior. First, we wish to automatically categorize observed behaviors into a discrete set of classes (i.e., classification). For example, to determine word production from video sequences in sign language. Second, we wish to understand the relevance of each behavioral feature in achieving this classification (i.e., decoding). For instance, to know which behavior variables are used to discriminate between the words apple and onion in American Sign Language (ASL). The present paper proposes to model behavior using a labeled graph, where the nodes define behavioral features and the edges are labels specifying their order (e.g., before, overlaps, start). In this approach, classification reduces to a simple labeled graph matching. Unfortunately, the complexity of labeled graph matching grows exponentially with the number of categories we wish to represent. Here, we derive a graph kernel to quickly and accurately compute this graph similarity. This approach is very general and can be plugged into any kernel-based classifier. Specifically, we derive a Labeled Graph Support Vector Machine (LGSVM) and a Labeled Graph Logistic Regressor (LGLR) that can be readily employed to discriminate between many actions (e.g., sign language concepts). The derived approach can be readily used for decoding too, yielding invaluable information for the understanding of a problem (e.g., to know how to teach a sign language). The derived algorithms allow us to achieve higher accuracy results than those of state-of-the-art algorithms in a fraction of the time. We show experimental results on a variety of problems and datasets, including multimodal data.

To See or Not to See: Do Front of Pack Nutrition Labels Affect Attention to Overall Nutrition Information?

PubMed Central

Bix, Laura; Sundar, Raghav Prashant; Bello, Nora M.; Peltier, Chad; Weatherspoon, Lorraine J.; Becker, Mark W.

2015-01-01

Background Front of pack (FOP) nutrition labels are concise labels located on the front of food packages that provide truncated nutrition information. These labels are rapidly gaining prominence worldwide, presumably because they attract attention and their simplified formats enable rapid comparisons of nutritional value. Methods Eye tracking was conducted as US consumers interacted with actual packages with and without FOP labels to (1) assess if the presence of an FOP label increases attention to nutrition information when viewers are not specifically tasked with nutrition-related goals; and (2) study the effect of FOP presence on consumer use of more comprehensive, traditional nutrition information presented in the Nutritional Facts Panel (NFP), a mandatory label for most packaged foods in the US. Results Our results indicate that colored FOP labels enhanced the probability that any nutrition information was attended, and resulted in faster detection and longer viewing of nutrition information. However, for cereal packages, these benefits were at the expense of attention to the more comprehensive NFP. Our results are consistent with a potential short cut effect of FOP labels, such that if an FOP was present, participants spent less time attending the more comprehensive NFP. For crackers, FOP labels increased time spent attending to nutrition information, but we found no evidence that their presence reduced the time spent on the nutrition information in the NFP. Conclusions The finding that FOP labels increased attention to overall nutrition information by people who did not have an explicit nutritional goal suggests that these labels may have an advantage in conveying nutrition information to a wide segment of the population. However, for some food types this benefit may come with a short-cut effect; that is, decreased attention to more comprehensive nutrition information. These results have implications for policy and warrant further research into the mechanisms by which FOP labels impact use of nutrition information by consumers for different foods. PMID:26488611

A new class of homogeneous nucleic acid probes based on specific displacement hybridization

PubMed Central

Li, Qingge; Luan, Guoyan; Guo, Qiuping; Liang, Jixuan

2002-01-01

We have developed a new class of probes for homogeneous nucleic acid detection based on the proposed displacement hybridization. Our probes consist of two complementary oligodeoxyribonucleotides of different length labeled with a fluorophore and a quencher in close proximity in the duplex. The probes on their own are quenched, but they become fluorescent upon displacement hybridization with the target. These probes display complete discrimination between a perfectly matched target and single nucleotide mismatch targets. A comparison of double-stranded probes with corresponding linear probes confirms that the presence of the complementary strand significantly enhances their specificity. Using four such probes labeled with different color fluorophores, each designed to recognize a different target, we have demonstrated that multiple targets can be distinguished in the same solution, even if they differ from one another by as little as a single nucleotide. Double-stranded probes were used in real-time nucleic acid amplifications as either probes or as primers. In addition to its extreme specificity and flexibility, the new class of probes is simple to design and synthesize, has low cost and high sensitivity and is accessible to a wide range of labels. This class of probes should find applications in a variety of areas wherever high specificity of nucleic acid hybridization is relevant. PMID:11788731

Comparisons and Selections of Features and Classifiers for Short Text Classification

NASA Astrophysics Data System (ADS)

Wang, Ye; Zhou, Zhi; Jin, Shan; Liu, Debin; Lu, Mi

2017-10-01

Short text is considerably different from traditional long text documents due to its shortness and conciseness, which somehow hinders the applications of conventional machine learning and data mining algorithms in short text classification. According to traditional artificial intelligence methods, we divide short text classification into three steps, namely preprocessing, feature selection and classifier comparison. In this paper, we have illustrated step-by-step how we approach our goals. Specifically, in feature selection, we compared the performance and robustness of the four methods of one-hot encoding, tf-idf weighting, word2vec and paragraph2vec, and in the classification part, we deliberately chose and compared Naive Bayes, Logistic Regression, Support Vector Machine, K-nearest Neighbor and Decision Tree as our classifiers. Then, we compared and analysed the classifiers horizontally with each other and vertically with feature selections. Regarding the datasets, we crawled more than 400,000 short text files from Shanghai and Shenzhen Stock Exchanges and manually labeled them into two classes, the big and the small. There are eight labels in the big class, and 59 labels in the small class.

Maximum-likelihood techniques for joint segmentation-classification of multispectral chromosome images.

PubMed

Schwartzkopf, Wade C; Bovik, Alan C; Evans, Brian L

2005-12-01

Traditional chromosome imaging has been limited to grayscale images, but recently a 5-fluorophore combinatorial labeling technique (M-FISH) was developed wherein each class of chromosomes binds with a different combination of fluorophores. This results in a multispectral image, where each class of chromosomes has distinct spectral components. In this paper, we develop new methods for automatic chromosome identification by exploiting the multispectral information in M-FISH chromosome images and by jointly performing chromosome segmentation and classification. We (1) develop a maximum-likelihood hypothesis test that uses multispectral information, together with conventional criteria, to select the best segmentation possibility; (2) use this likelihood function to combine chromosome segmentation and classification into a robust chromosome identification system; and (3) show that the proposed likelihood function can also be used as a reliable indicator of errors in segmentation, errors in classification, and chromosome anomalies, which can be indicators of radiation damage, cancer, and a wide variety of inherited diseases. We show that the proposed multispectral joint segmentation-classification method outperforms past grayscale segmentation methods when decomposing touching chromosomes. We also show that it outperforms past M-FISH classification techniques that do not use segmentation information.

Investigating substrate use efficiency across different microbial physiologies in soil-extracted, solubilized organic matter (SESOM)

NASA Astrophysics Data System (ADS)

Cyle, K. T.; Martinez, C. E.

2017-12-01

Recent experimental work has elevated the importance of microbial processing for the stabilization of fresh carbon inputs within the soil mineral matrix. Enhancing our understanding of soil carbon and nitrogen dynamics therefore requires a better understanding of how efficiently microbial metabolism can process low molecular weight carbon substrates (carbon use efficiency, CUE) under environmentally relevant conditions. One approach to better understanding microbial uptake rates and CUE is the ecophysiological study of soil isolates in liquid media culture consisting of soil-extracted solubilized organic matter (SESOM). We are using SESOM from an Oa horizon under hemlock hardwood vegetation in upstate New York as liquid media for the growth of 12 isolates from the Oa and B horizon of the same site. Here we seek to test the uptake rates as well as CUE of 5 different low molecular weight substrates spanning compound class and nominal oxidation state (glucose, acetate, formate, glycine, valine) by isolates differing in phylogeny and physiology. The use of a spike of each of the 13C-labeled substrates into SESOM, along with a 0.2 μm filtration step, allows accurate partitioning of labeled carbon between biomass, gaseous CO2 as well as the exometabolome. Coupled UHPLC-MS measurements are being used to identify and determine uptake rates of over 80 potential C substrates present in the extract as well as our labeled substrate of interest along the course of the isolate growth curve. This work seeks to utilize a gradient in substrate class as well as microbial physiologies to inform our understanding of C and N cycling under relevant soil solution conditions. Future experiments may also use labeled biomass from stationary phase to investigate the stabilization potential of anabolic products formed from each substrate with a clay fraction isolated from the same site.

An exploratory study of drinkers views of health information and warning labels on alcohol containers.

PubMed

Thomson, Lisa M; Vandenberg, Brian; Fitzgerald, John L

2012-03-01

To identify general and specific features of health information warning labels on alcohol beverage containers that could potentially inform the development and implementation of a new labelling regime in Australia. Mixed methods, including a cross-sectional population survey and a qualitative study of knowledge, attitudes and behaviours regarding alcohol beverage labelling. The population survey used computer-assisted telephone interviews of 1500 persons in Victoria, Australia to gauge the level of support for health information and warning labels. The qualitative study used six focus groups to test the suitability of 12 prototype labels that were placed in situ on a variety of alcohol beverage containers. The telephone survey found 80% to 90% support for a range of information that could potentially be mandated by government authorities for inclusion on labels (nutritional information, alcohol content, health warning, images). Focus group testing of the prototype label designs found that labels should be integrated with other alcohol-related health messages, such as government social advertising campaigns, and specific labels should be matched appropriately to specific consumer groups and beverage types. There are high levels of public support for health information and warning labels on alcohol beverages. This study contributes much needed empirical guidance for developing alcohol beverage labelling strategies in an Australian context. © 2011 Australasian Professional Society on Alcohol and other Drugs.

Active learning for solving the incomplete data problem in facial age classification by the furthest nearest-neighbor criterion.

PubMed

Wang, Jian-Gang; Sung, Eric; Yau, Wei-Yun

2011-07-01

Facial age classification is an approach to classify face images into one of several predefined age groups. One of the difficulties in applying learning techniques to the age classification problem is the large amount of labeled training data required. Acquiring such training data is very costly in terms of age progress, privacy, human time, and effort. Although unlabeled face images can be obtained easily, it would be expensive to manually label them on a large scale and getting the ground truth. The frugal selection of the unlabeled data for labeling to quickly reach high classification performance with minimal labeling efforts is a challenging problem. In this paper, we present an active learning approach based on an online incremental bilateral two-dimension linear discriminant analysis (IB2DLDA) which initially learns from a small pool of labeled data and then iteratively selects the most informative samples from the unlabeled set to increasingly improve the classifier. Specifically, we propose a novel data selection criterion called the furthest nearest-neighbor (FNN) that generalizes the margin-based uncertainty to the multiclass case and which is easy to compute, so that the proposed active learning algorithm can handle a large number of classes and large data sizes efficiently. Empirical experiments on FG-NET and Morph databases together with a large unlabeled data set for age categorization problems show that the proposed approach can achieve results comparable or even outperform a conventionally trained active classifier that requires much more labeling effort. Our IB2DLDA-FNN algorithm can achieve similar results much faster than random selection and with fewer samples for age categorization. It also can achieve comparable results with active SVM but is much faster than active SVM in terms of training because kernel methods are not needed. The results on the face recognition database and palmprint/palm vein database showed that our approach can handle problems with large number of classes. Our contributions in this paper are twofold. First, we proposed the IB2DLDA-FNN, the FNN being our novel idea, as a generic on-line or active learning paradigm. Second, we showed that it can be another viable tool for active learning of facial age range classification.

Pharmacogenomic biomarker information in drug labels approved by the United States food and drug administration: prevalence of related drug use.

PubMed

Frueh, Felix W; Amur, Shashi; Mummaneni, Padmaja; Epstein, Robert S; Aubert, Ronald E; DeLuca, Teresa M; Verbrugge, Robert R; Burckart, Gilbert J; Lesko, Lawrence J

2008-08-01

To review the labels of United States Food and Drug Administration (FDA)-approved drugs to identify those that contain pharmacogenomic biomarker information, and to collect prevalence information on the use of those drugs for which pharmacogenomic information is included in the drug labeling. Retrospective analysis. The Physicians' Desk Reference Web site, Drugs@FDA Web site, and manufacturers' Web sites were used to identify drug labels containing pharmacogenomic information, and the prescription claims database of a large pharmacy benefits manager (insuring > 55 million individuals in the United States) was used to obtain drug utilization data. Pharmacogenomic biomarkers were defined, FDA-approved drug labels containing this information were identified, and utilization of these drugs was determined. Of 1200 drug labels reviewed for the years 1945-2005, 121 drug labels contained pharmacogenomic information based on a key word search and follow-up screening. Of those, 69 labels referred to human genomic biomarkers, and 52 referred to microbial genomic biomarkers. Of the labels referring to human biomarkers, 43 (62%) pertained to polymorphisms in cytochrome P450 (CYP) enzyme metabolism, with CYP2D6 being most common. Of 36.1 million patients whose prescriptions were processed by a large pharmacy benefits manager in 2006, about 8.8 million (24.3%) received one or more drugs with human genomic biomarker information in the drug label. Nearly one fourth of all outpatients received one or more drugs that have pharmacogenomic information in the label for that drug. The incorporation and appropriate use of pharmacogenomic information in drug labels should be tested for its ability to improve drug use and safety in the United States.

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

PubMed Central

Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

2015-01-01

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

The effect of sample size and disease prevalence on supervised machine learning of narrative data.

PubMed Central

McKnight, Lawrence K.; Wilcox, Adam; Hripcsak, George

2002-01-01

This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets were constructed to define positive outcome states at 4 prevalence rates (1, 5, 10, 25, and 50%) in training set sizes of 200 and 2,000 cases. We found that the effect of outcome prevalence is significant when outcome classes drop below 10% of cases. The effect appeared independent of sample size, induction algorithm used, or class label. Work is needed to identify methods of improving classifier performance when output classes are rare. PMID:12463878

Automatic Earthquake Detection by Active Learning

NASA Astrophysics Data System (ADS)

Bergen, K.; Beroza, G. C.

2017-12-01

In recent years, advances in machine learning have transformed fields such as image recognition, natural language processing and recommender systems. Many of these performance gains have relied on the availability of large, labeled data sets to train high-accuracy models; labeled data sets are those for which each sample includes a target class label, such as waveforms tagged as either earthquakes or noise. Earthquake seismologists are increasingly leveraging machine learning and data mining techniques to detect and analyze weak earthquake signals in large seismic data sets. One of the challenges in applying machine learning to seismic data sets is the limited labeled data problem; learning algorithms need to be given examples of earthquake waveforms, but the number of known events, taken from earthquake catalogs, may be insufficient to build an accurate detector. Furthermore, earthquake catalogs are known to be incomplete, resulting in training data that may be biased towards larger events and contain inaccurate labels. This challenge is compounded by the class imbalance problem; the events of interest, earthquakes, are infrequent relative to noise in continuous data sets, and many learning algorithms perform poorly on rare classes. In this work, we investigate the use of active learning for automatic earthquake detection. Active learning is a type of semi-supervised machine learning that uses a human-in-the-loop approach to strategically supplement a small initial training set. The learning algorithm incorporates domain expertise through interaction between a human expert and the algorithm, with the algorithm actively posing queries to the user to improve detection performance. We demonstrate the potential of active machine learning to improve earthquake detection performance with limited available training data.

Predicting Drug-Target Interactions With Multi-Information Fusion.

PubMed

Peng, Lihong; Liao, Bo; Zhu, Wen; Li, Zejun; Li, Keqin

2017-03-01

Identifying potential associations between drugs and targets is a critical prerequisite for modern drug discovery and repurposing. However, predicting these associations is difficult because of the limitations of existing computational methods. Most models only consider chemical structures and protein sequences, and other models are oversimplified. Moreover, datasets used for analysis contain only true-positive interactions, and experimentally validated negative samples are unavailable. To overcome these limitations, we developed a semi-supervised based learning framework called NormMulInf through collaborative filtering theory by using labeled and unlabeled interaction information. The proposed method initially determines similarity measures, such as similarities among samples and local correlations among the labels of the samples, by integrating biological information. The similarity information is then integrated into a robust principal component analysis model, which is solved using augmented Lagrange multipliers. Experimental results on four classes of drug-target interaction networks suggest that the proposed approach can accurately classify and predict drug-target interactions. Part of the predicted interactions are reported in public databases. The proposed method can also predict possible targets for new drugs and can be used to determine whether atropine may interact with alpha1B- and beta1- adrenergic receptors. Furthermore, the developed technique identifies potential drugs for new targets and can be used to assess whether olanzapine and propiomazine may target 5HT2B. Finally, the proposed method can potentially address limitations on studies of multitarget drugs and multidrug targets.

A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

PubMed Central

Ortega-Martorell, Sandra; Ruiz, Héctor; Vellido, Alfredo; Olier, Iván; Romero, Enrique; Julià-Sapé, Margarida; Martín, José D.; Jarman, Ian H.; Arús, Carles; Lisboa, Paulo J. G.

2013-01-01

Background The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal. Methodology/Principal Findings Non-negative matrix factorization techniques have recently shown their potential for the identification of meaningful sources from brain tissue spectroscopy data. In this study, we use a convex variant of these methods that is capable of handling negatively-valued data and generating sources that can be interpreted as tumor class prototypes. A novel approach to convex non-negative matrix factorization is proposed, in which prior knowledge about class information is utilized in model optimization. Class-specific information is integrated into this semi-supervised process by setting the metric of a latent variable space where the matrix factorization is carried out. The reported experimental study comprises 196 cases from different tumor types drawn from two international, multi-center databases. The results indicate that the proposed approach outperforms a purely unsupervised process by achieving near perfect correlation of the extracted sources with the mean spectra of the tumor types. It also improves tissue type classification. Conclusions/Significance We show that source extraction by unsupervised matrix factorization benefits from the integration of the available class information, so operating in a semi-supervised learning manner, for discriminative source identification and brain tumor labeling from single-voxel spectroscopy data. We are confident that the proposed methodology has wider applicability for biomedical signal processing. PMID:24376744

Contextualizing Informal Labeling Effect on Adolescent Recidivism in South Korea.

PubMed

Lee, Jonathan

2017-08-01

Symbolic interactionism argues that the effect of informal labeling by general others, such as family and friends, on behavior depends on the social context under which labeling takes place. Despite abundant research on informal labeling, little effort has been made to contextualize its impact on adolescent reoffending. Also, compared with other theories, only a few studies have been conducted among youths in Asian population. Using three consecutive waves of self-reported survey data from a nationally representative sample of 2,406 Korean adolescents, this study examined an interactional model for the informal labeling effect. Findings suggest that informal labeling, as well as school commitment and delinquent peer association, has an independent effect on delinquency. Also supported is the symbolic interactionist hypothesis that adolescents with greater involvement in delinquent subcultures were less susceptible to informal labeling. Implications of the findings are discussed.

49 CFR 172.407 - Label specifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... one color background of green, red or blue. (ii) White must be used for the text and class number for... Hazardous Materials Safety, Office of Hazardous Materials Standards, Room 8422, Nassif Building, 400 Seventh... markings and hazard warning labels and placards: (i) For Red—Use PANTONE ® 186 U (ii) For Orange—Use...

A Label Propagation Approach for Detecting Buried Objects in Handheld GPR Data

DTIC Science & Technology

2016-04-17

regions of interest that correspond to locations with anomalous signatures. Second, a classifier (or an ensemble of classifiers ) is used to assign a...investigated for almost two decades and several classifiers have been developed. Most of these methods are based on the supervised learning paradigm where...labeled target and clutter signatures are needed to train a classifier to discriminate between the two classes. Typically, large and diverse labeled

[The influence of labeling format on use and understanding of nutrition information: results of an experiment in workplace restaurants].

PubMed

Gomez, P; Le Minous, A-E

2012-02-01

Nutrition labeling usually describes food product composition in terms of nutrients. This article aims at investigating the influence of nutrition labeling on use and understanding of nutrition information in workplace restaurants and comparing the difference between a nutrient-based labeling and an alternative labeling based on food groups. In this respect, an experiment was conducted in two workplace restaurants during 4 weeks. Then, a survey was carried out, covering 329 individuals, to assess use and understanding of nutrition information. We found that 42.9% of the sample saw the nutrient labeling and only 5.2% said they used it. Our results show that both labeling formats lead to high understanding. Nutrition labeling format was found to have no significant influence on use and understanding of nutrition information. In spite of these results, food groups labeling were perceived as easier to process than nutrient-based labeling. Understanding is more widespread than use among participants suggesting that the main hurdle to information use comes from a lack of motivation. Food groups labeling are of limited interest compared to nutrient-based labeling. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

The changes in hazard classification and product notification procedures of the new European CLP and Cosmetics Regulations.

PubMed

de Groot, Ronald; Brekelmans, Pieter; Herremans, Joke; Meulenbelt, Jan

2010-01-01

The United Nations Globally Harmonized System of Classification and Labelling of Chemicals (UN-GHS) is developed to harmonize the criteria for hazard communication worldwide. The European Regulation on classification, labeling, and packaging of substances and mixtures [CLP Regulation (European Commission, EC) No 1272/2008] will align the existing European Union (EU) legislation to the UN-GHS. This CLP Regulation entered into force on January 20, 2009, and will, after a transitional period, replace the current rules on classification, labeling, and packaging for supply and use in Europe. Both old and new classifications will exist simultaneously until 2010 for substances and until 2015 for mixtures. The new hazard classification will introduce new health hazard classes and categories, with associated new hazard pictograms, signal words, Hazard (H)-statements, and Precautionary (P)-statements as labeling elements. Furthermore, the CLP Regulation will affect the notification of product information on hazardous products to poisons information centers (PICs). At this moment product notification widely varies in procedures and requirements across EU Member States. Article 45 of the CLP Regulation contains a provision stating that the EC will (by January 20, 2012) review the possibility of harmonizing product notification. The European Association of Poisons Centres and Clinical Toxicologists (EAPCCT) is recognized as an important stakeholder. For cosmetic products, the new Cosmetics Regulation will directly implement a new procedure for electronic cosmetic product notification in all EU Member States. Both the CLP Regulation and the Cosmetics Regulation will develop their own product notification procedure within different time frames. Harmonization of notification procedures for both product groups, especially a common electronic format, would be most effective from a cost-benefit viewpoint and would be welcomed by PICs.

Axonal transport of class II and III beta-tubulin: evidence that the slow component wave represents the movement of only a small fraction of the tubulin in mature motor axons

PubMed Central

1992-01-01

Pulse-labeling studies demonstrate that tubulin synthesized in the neuron cell body (soma) moves somatofugally within the axon (at a rate of several millimeters per day) as a well-defined wave corresponding to the slow component of axonal transport. A major goal of the present study was to determine what proportion of the tubulin in mature motor axons is transported in this wave. Lumbar motor neurons in 9-wk-old rats were labeled by injecting [35S]methionine into the spinal cord 2 wk after motor axons were injured (axotomized) by crushing the sciatic nerve. Immunoprecipitation with mAbs which recognize either class II or III beta-tubulin were used to analyze the distributions of radioactivity in these isotypes in intact and axotomized motor fibers 5 d after labeling. We found that both isotypes were associated with the slow component wave, and that the leading edge of this wave was enriched in the class III isotype. Axotomy resulted in significant increases in the labeling and transport rates of both isotypes. Immunohistochemical examination of peripheral nerve fibers demonstrated that nearly all of the class II and III beta-tubulin in nerve fibers is located within axons. Although the amounts of radioactivity per millimeter of nerve in class II and III beta-tubulin were significantly greater in axotomized than in control nerves (with increases of +160% and +58%, respectively), immunoassay revealed no differences in the amounts of these isotypes in axotomized and control motor fibers. We consider several explanations for this paradox; these include the possibility that the total tubulin content is relatively insensitive to changes in the amount of tubulin transported in the slow component wave because this wave represents the movement of only a small fraction of the tubulin in these motor fibers. PMID:1383234

27 CFR 4.62 - Mandatory statements.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., type, and distinctive designation. The advertisement shall contain a conspicuous statement of the class, type, or distinctive designation to which the product belongs, corresponding with the statement of class, type, or distinctive designation which is required to appear on the label of the product. (c...

Automated segmentation of thyroid gland on CT images with multi-atlas label fusion and random classification forest

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Chang, Kevin; Kim, Lauren; Turkbey, Evrim; Lu, Le; Yao, Jianhua; Summers, Ronald

2015-03-01

The thyroid gland plays an important role in clinical practice, especially for radiation therapy treatment planning. For patients with head and neck cancer, radiation therapy requires a precise delineation of the thyroid gland to be spared on the pre-treatment planning CT images to avoid thyroid dysfunction. In the current clinical workflow, the thyroid gland is normally manually delineated by radiologists or radiation oncologists, which is time consuming and error prone. Therefore, a system for automated segmentation of the thyroid is desirable. However, automated segmentation of the thyroid is challenging because the thyroid is inhomogeneous and surrounded by structures that have similar intensities. In this work, the thyroid gland segmentation is initially estimated by multi-atlas label fusion algorithm. The segmentation is refined by supervised statistical learning based voxel labeling with a random forest algorithm. Multiatlas label fusion (MALF) transfers expert-labeled thyroids from atlases to a target image using deformable registration. Errors produced by label transfer are reduced by label fusion that combines the results produced by all atlases into a consensus solution. Then, random forest (RF) employs an ensemble of decision trees that are trained on labeled thyroids to recognize features. The trained forest classifier is then applied to the thyroid estimated from the MALF by voxel scanning to assign the class-conditional probability. Voxels from the expert-labeled thyroids in CT volumes are treated as positive classes; background non-thyroid voxels as negatives. We applied this automated thyroid segmentation system to CT scans of 20 patients. The results showed that the MALF achieved an overall 0.75 Dice Similarity Coefficient (DSC) and the RF classification further improved the DSC to 0.81.

Reconstituting the ADHD Girl: Accomplishing Exclusion and Solidifying a Biomedical Identity in an ADHD Class

ERIC Educational Resources Information Center

Hjörne, Eva; Evaldsson, Ann-Carita

2015-01-01

In this study, we explore what happens to young people labelled as having attention deficit hyperactivity disorder (ADHD) after they have been excluded from mainstream class and placed in a special class. More specifically, we focus on how a specific disability identity is locally accomplished and ascribed to a girl placed in an ADHD class…

Dietary Supplement Label Database (DSLD)

MedlinePlus

... be an educational and research tool for students, academics, and other professionals. Disclaimer: All information contained in the Dietary Supplement Label Database (DSLD) comes from product labels. Label information has ...

Structure of a class I tagatose-1,6-bisphosphate aldolase: investigation into an apparent loss of stereospecificity.

PubMed

LowKam, Clotilde; Liotard, Brigitte; Sygusch, Jurgen

2010-07-02

Tagatose-1,6-bisphosphate aldolase from Streptococcus pyogenes is a class I aldolase that exhibits a remarkable lack of chiral discrimination with respect to the configuration of hydroxyl groups at both C3 and C4 positions. The enzyme catalyzes the reversible cleavage of four diastereoisomers (fructose 1,6-bisphosphate (FBP), psicose 1,6-bisphosphate, sorbose 1,6-bisphosphate, and tagatose 1,6-bisphosphate) to dihydroxyacetone phosphate (DHAP) and d-glyceraldehyde 3-phosphate with high catalytic efficiency. To investigate its enzymatic mechanism, high resolution crystal structures were determined of both native enzyme and native enzyme in complex with dihydroxyacetone-P. The electron density map revealed a (alpha/beta)(8) fold in each dimeric subunit. Flash-cooled crystals of native enzyme soaked with dihydroxyacetone phosphate trapped a covalent intermediate with carbanionic character at Lys(205), different from the enamine mesomer bound in stereospecific class I FBP aldolase. Structural analysis indicates extensive active site conservation with respect to class I FBP aldolases, including conserved conformational responses to DHAP binding and conserved stereospecific proton transfer at the DHAP C3 carbon mediated by a proximal water molecule. Exchange reactions with tritiated water and tritium-labeled DHAP at C3 hydrogen were carried out in both solution and crystalline state to assess stereochemical control at C3. The kinetic studies show labeling at both pro-R and pro-S C3 positions of DHAP yet detritiation only at the C3 pro-S-labeled position. Detritiation of the C3 pro-R label was not detected and is consistent with preferential cis-trans isomerism about the C2-C3 bond in the carbanion as the mechanism responsible for C3 epimerization in tagatose-1,6-bisphosphate aldolase.

Structure of a Class I Tagatose-1,6-bisphosphate Aldolase

PubMed Central

LowKam, Clotilde; Liotard, Brigitte; Sygusch, Jurgen

2010-01-01

Tagatose-1,6-bisphosphate aldolase from Streptococcus pyogenes is a class I aldolase that exhibits a remarkable lack of chiral discrimination with respect to the configuration of hydroxyl groups at both C3 and C4 positions. The enzyme catalyzes the reversible cleavage of four diastereoisomers (fructose 1,6-bisphosphate (FBP), psicose 1,6-bisphosphate, sorbose 1,6-bisphosphate, and tagatose 1,6-bisphosphate) to dihydroxyacetone phosphate (DHAP) and d-glyceraldehyde 3-phosphate with high catalytic efficiency. To investigate its enzymatic mechanism, high resolution crystal structures were determined of both native enzyme and native enzyme in complex with dihydroxyacetone-P. The electron density map revealed a (α/β)8 fold in each dimeric subunit. Flash-cooled crystals of native enzyme soaked with dihydroxyacetone phosphate trapped a covalent intermediate with carbanionic character at Lys205, different from the enamine mesomer bound in stereospecific class I FBP aldolase. Structural analysis indicates extensive active site conservation with respect to class I FBP aldolases, including conserved conformational responses to DHAP binding and conserved stereospecific proton transfer at the DHAP C3 carbon mediated by a proximal water molecule. Exchange reactions with tritiated water and tritium-labeled DHAP at C3 hydrogen were carried out in both solution and crystalline state to assess stereochemical control at C3. The kinetic studies show labeling at both pro-R and pro-S C3 positions of DHAP yet detritiation only at the C3 pro-S-labeled position. Detritiation of the C3 pro-R label was not detected and is consistent with preferential cis-trans isomerism about the C2–C3 bond in the carbanion as the mechanism responsible for C3 epimerization in tagatose-1,6-bisphosphate aldolase. PMID:20427286

Rationale and evidence for menu-labeling legislation.

PubMed

Roberto, Christina A; Schwartz, Marlene B; Brownell, Kelly D

2009-12-01

Menu-labeling legislation is a proposed public health intervention for poor diet and obesity that requires chain restaurants to provide nutrition information on menus and menu boards. The restaurant industry has strongly opposed menu-labeling legislation. Using scientific evidence, this paper counters industry arguments against menu labeling by demonstrating that consumers want chain restaurant nutrition information to be disclosed; the current methods of providing nutrition information are inadequate; the expense of providing nutrition information is minimal; the government has the legal right to mandate disclosure of information; consumers have the right to know nutrition information; a lack of information reduces the efficiency of a market economy; and menu labeling has the potential to make a positive public health impact.

FDA-approved medications that impair human spermatogenesis.

PubMed

Ding, Jiayi; Shang, Xuejun; Zhang, Zhanhu; Jing, Hua; Shao, Jun; Fei, Qianqian; Rayburn, Elizabeth R; Li, Haibo

2017-02-07

We herein provide an overview of the single-ingredient U.S. Food and Drug Administration (FDA)-approved drugs that affect human spermatogenesis, potentially resulting in a negative impact on male fertility. To provide this information, we performed an in-depth search of DailyMed, the official website for FDA-approved drug labels. Not surprisingly, hormone-based agents were found to be the drugs most likely to affect human spermatogenesis. The next category of drugs most likely to have effects on spermatogenesis was the antineoplastic agents. Interestingly, the DailyMed labels indicated that several anti-inflammatory drugs affect spermatogenesis, which is not supported by the peer-reviewed literature. Overall, there were a total of 65 labels for drugs of various classes that showed that they have the potential to affect human sperm production and maturation. We identified several drugs indicated to be spermatotoxic in the drug labels that were not reported in the peer-reviewed literature. However, the details about the effects of these drugs on human spermatogenesis are largely lacking, the mechanisms are often unknown, and the clinical impact of many of the findings is currently unclear. Therefore, additional work is needed at both the basic research level and during clinical trials and post-marketing surveillance to fill the gaps in the current knowledge. The present findings will be of interest to physicians and pharmacists, researchers, and those involved in drug development and health care policy.

Learning Discriminative Binary Codes for Large-scale Cross-modal Retrieval.

PubMed

Xu, Xing; Shen, Fumin; Yang, Yang; Shen, Heng Tao; Li, Xuelong

2017-05-01

Hashing based methods have attracted considerable attention for efficient cross-modal retrieval on large-scale multimedia data. The core problem of cross-modal hashing is how to learn compact binary codes that construct the underlying correlations between heterogeneous features from different modalities. A majority of recent approaches aim at learning hash functions to preserve the pairwise similarities defined by given class labels. However, these methods fail to explicitly explore the discriminative property of class labels during hash function learning. In addition, they usually discard the discrete constraints imposed on the to-be-learned binary codes, and compromise to solve a relaxed problem with quantization to obtain the approximate binary solution. Therefore, the binary codes generated by these methods are suboptimal and less discriminative to different classes. To overcome these drawbacks, we propose a novel cross-modal hashing method, termed discrete cross-modal hashing (DCH), which directly learns discriminative binary codes while retaining the discrete constraints. Specifically, DCH learns modality-specific hash functions for generating unified binary codes, and these binary codes are viewed as representative features for discriminative classification with class labels. An effective discrete optimization algorithm is developed for DCH to jointly learn the modality-specific hash function and the unified binary codes. Extensive experiments on three benchmark data sets highlight the superiority of DCH under various cross-modal scenarios and show its state-of-the-art performance.

Factual text and emotional pictures: overcoming a false dichotomy of cigarette warning labels.

PubMed

Popova, Lucy; Owusu, Daniel; Jenson, Desmond; Neilands, Torsten B

2017-04-20

In reviewing the first set of pictorial warning labels in the USA, the courts equated textual labels with facts and information, and images with emotion. This study tested the differences in perceived informativeness and emotion between textual and pictorial cigarette warning labels. An online study with 1838 US adults who were non-smokers (n=764), transitioning smokers (quit smoking in the past 2 years or currently trying to quit, n=505) or current smokers (n=569). Each participant evaluated 9 out of 81 text and pictorial cigarette warning labels. Participants reported to what extent they perceived the label as informative and factual and the negative emotions they felt while looking at each label. We used linear mixed models to account for the nesting of multiple observations within each participant. There were no significant differences in perceived informativeness between textual (mean 6.15 on a 9-point scale) and pictorial labels (6.14, p=0.80, Cohen's d=0.003). Textual labels evoked slightly less emotion (4.21 on a 9-point scale) than pictorial labels (4.42, p<0.001, Cohen's d=0.08). Perceived informativeness and emotion were strongly correlated (Pearson r=0.53, p<0.001). Our findings contradict courts' conclusions that pictorial messages are emotional and not factual. Pictorial labels are rated as informative and factual, textual labels evoke emotion, and emotionality and informativeness are strongly correlated. These findings serve as evidence for the Food and Drug Administration (FDA) to counteract the claim that pictorial warning labels, by definition, are not 'purely factual and uncontroversial'. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Use of food labels by adolescents to make healthier choices on snacks: a cross-sectional study from Sri Lanka.

PubMed

Talagala, Ishanka A; Arambepola, Carukshi

2016-08-08

Unhealthy snacking is commonly seen among adolescents. Therefore, use of food labels is promoted for making healthier choices on packaged snacks. This study was conducted to assess the use of food labels in making choices on packaged snack and its associated factors among adolescents. A cross-sectional study was conducted in 2012 among 542 Grade 12 students in Sri Lanka. Eight classes were selected as 'clusters' for the study (two classes each from two schools that were selected randomly from each list of 'Girls only' and 'Boys only' schools in Colombo district). A self-administered questionnaire assessed their socio-demography, snacking behaviour, attitudes and nutrition knowledge related to food labels. Adolescents' use of labels was assessed by three practices (label reading frequency, attention paid to label contents and correct interpretation of six hypothetical labels of snacks). Based on total scores obtained for the three practices, 'satisfactory' (score ≥75(th) percentile mark) and 'unsatisfactory' (score <75(th) percentile mark) label users were identified. Using SPSS, associations were assessed at 0.05 significance level using Chi-square-test. Of the participants, 51 % were males; 61 % spent their pocket money at least once/week on packaged snacks; predominantly on biscuits (85 %) and cola-drinks (77 %) and 88 % selected snacks on their own. The majority (74.5 %) was frequent ('always' or 'most often') label readers with female predominance (p < 0.05). Over 74 % paid attention frequently to the brand name (75 %), price (85 %) and nutrition panel (81 %). Over 64 % were able to select the better food label when given a choice between two snacks, although some did it for reasons such as attractive label (63 %). The majority (84 %) had good knowledge (obtaining more than the 75(th) percentile mark) on interpreting labels. Although not statistically significant, 'unsatisfactory' label use was higher among males (73 %), purchasing power (70.4 %) and unhealthy snacking behaviour (73 %). In contrast, among the marketing strategies, identifying known brands (73.2 %) and imported products (75.8 %) as 'good' products were significantly associated with 'unsatisfactory' label use (p < 0.05). Despite having good knowledge and positive attitudes, food label use is unsatisfactory among adolescents. Skills in reading labels should be addressed in the 'School canteen policy' in Sri Lanka.

Image annotation by deep neural networks with attention shaping

NASA Astrophysics Data System (ADS)

Zheng, Kexin; Lv, Shaohe; Ma, Fang; Chen, Fei; Jin, Chi; Dou, Yong

2017-07-01

Image annotation is a task of assigning semantic labels to an image. Recently, deep neural networks with visual attention have been utilized successfully in many computer vision tasks. In this paper, we show that conventional attention mechanism is easily misled by the salient class, i.e., the attended region always contains part of the image area describing the content of salient class at different attention iterations. To this end, we propose a novel attention shaping mechanism, which aims to maximize the non-overlapping area between consecutive attention processes by taking into account the history of previous attention vectors. Several weighting polices are studied to utilize the history information in different manners. In two benchmark datasets, i.e., PASCAL VOC2012 and MIRFlickr-25k, the average precision is improved by up to 10% in comparison with the state-of-the-art annotation methods.

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

Amino Acid Insertion Frequencies Arising from Photoproducts Generated Using Aliphatic Diazirines

NASA Astrophysics Data System (ADS)

Ziemianowicz, Daniel S.; Bomgarden, Ryan; Etienne, Chris; Schriemer, David C.

2017-10-01

Mapping proteins with chemical reagents and mass spectrometry can generate a measure of accessible surface area, which in turn can be used to support the modeling and refinement of protein structures. Photolytically generated carbenes are a promising class of reagent for this purpose. Substituent effects appear to influence surface mapping properties, allowing for a useful measure of design control. However, to use carbene labeling data in a quantitative manner for modeling activities, we require a better understanding of their inherent amino acid reactivity, so that incorporation data can be normalized. The current study presents an analysis of the amino acid insertion frequency of aliphatic carbenes generated by the photolysis of three different diazirines: 3,3'-azibutyl-1-ammonium, 3,3'-azibutan-1-ol, and 4,4'-azipentan-1-oate. Leveraging an improved photolysis system for single-shot labeling of sub-microliter frozen samples, we used EThCD to localize insertion products in a large population of labeled peptides. Counting statistics were drawn from data-dependent LC-MS2 experiments and used to estimate the frequencies of insertion as a function of amino acid. We observed labeling of all 20 amino acids over a remarkably narrow range of insertion frequencies. However, the nature of the substituent could influence relative insertion frequencies, within a general preference for larger polar amino acids. We confirm a large (6-fold) increase in labeling yield when carbenes were photogenerated in the solid phase (77 K) relative to the liquid phase (293 K), and we suggest that carbene labeling should always be conducted in the frozen state to avoid information loss in surface mapping experiments. [Figure not available: see fulltext.

How do design features influence consumer attention when looking for nutritional information on food labels? Results from an eye-tracking study on pan bread labels.

PubMed

Antúnez, Lucía; Vidal, Leticia; Sapolinski, Alejandra; Giménez, Ana; Maiche, Alejandro; Ares, Gastón

2013-08-01

The aim of this work was to evaluate consumer visual processing of food labels when evaluating the salt content of pan bread labels and to study the influence of label design and nutritional labelling format on consumer attention. A total of 16 pan bread labels, designed according to a full factorial design, were presented to 52 participants, who were asked to decide whether the sodium content of each label was medium or low, while their eye movements were recorded using an eye tracker. Results showed that most participants looked at nutrition labels and the traffic light system to conclude on the salt content of the labels. However, the average percentage of participants who looked at the actual sodium content was much lower. Nutrition information format affected participants' processing of nutrition information. Among other effects, the inclusion of the traffic light system increased participants' attention towards some kind of nutrition information and facilitated its processing, but not its understanding.

How does consumer knowledge affect environmentally sustainable choices? Evidence from a cross-country latent class analysis of food labels.

PubMed

Peschel, Anne O; Grebitus, Carola; Steiner, Bodo; Veeman, Michele

2016-11-01

This paper examines consumers' knowledge and lifestyle profiles and preferences regarding two environmentally labeled food staples, potatoes and ground beef. Data from online choice experiments conducted in Canada and Germany are analyzed through latent class choice modeling to identify the influence of consumer knowledge (subjective and objective knowledge as well as usage experience) on environmentally sustainable choices. We find that irrespective of product or country under investigation, high subjective and objective knowledge levels drive environmentally sustainable food choices. Subjective knowledge was found to be more important in this context. Usage experience had relatively little impact on environmentally sustainable choices. Our results suggest that about 20% of consumers in both countries are ready to adopt footprint labels in their food choices. Another 10-20% could be targeted by enhancing subjective knowledge, for example through targeted marketing campaigns. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-class segmentation of neuronal electron microscopy images using deep learning

NASA Astrophysics Data System (ADS)

Khobragade, Nivedita; Agarwal, Chirag

2018-03-01

Study of connectivity of neural circuits is an essential step towards a better understanding of functioning of the nervous system. With the recent improvement in imaging techniques, high-resolution and high-volume images are being generated requiring automated segmentation techniques. We present a pixel-wise classification method based on Bayesian SegNet architecture. We carried out multi-class segmentation on serial section Transmission Electron Microscopy (ssTEM) images of Drosophila third instar larva ventral nerve cord, labeling the four classes of neuron membranes, neuron intracellular space, mitochondria and glia / extracellular space. Bayesian SegNet was trained using 256 ssTEM images of 256 x 256 pixels and tested on 64 different ssTEM images of the same size, from the same serial stack. Due to high class imbalance, we used a class-balanced version of Bayesian SegNet by re-weighting each class based on their relative frequency. We achieved an overall accuracy of 93% and a mean class accuracy of 88% for pixel-wise segmentation using this encoder-decoder approach. On evaluating the segmentation results using similarity metrics like SSIM and Dice Coefficient, we obtained scores of 0.994 and 0.886 respectively. Additionally, we used the network trained using the 256 ssTEM images of Drosophila third instar larva for multi-class labeling of ISBI 2012 challenge ssTEM dataset.

The availability and accessibility of nutrition information in fast food outlets in five states post-menu labelling legislation in New South Wales.

PubMed

Wellard, Lyndal; Havill, Michelle; Hughes, Clare; Watson, Wendy L; Chapman, Kathy

2015-12-01

1) Explore the availability and accessibility of fast food energy and nutrient information post-NSW menu labelling legislation in states with and without menu labelling legislation. 2) Determine whether availability and accessibility differed compared with pre-menu labelling legislation in NSW. We visited 210 outlets of the five largest fast food chains in five Australian states to observe the availability and accessibility of energy and nutrient information. Results were compared with 197 outlets surveyed pre-menu labelling. Most outlets (95%) provided energy values, half provided nutrient values and 3% provided information for all menu items. The total amount of information available increased post-NSW menu labelling implementation (473 versus 178 pre-implementation, p<0.001); however, fewer outlets provided nutrient values (26% versus 97% pre-implementation, p<0.001). Fast food chains surveyed had voluntarily introduced menu labelling nationally. However, more nutrient information was available in-store in 2010, showing that fast food chains are able to provide comprehensive nutrition information, yet they have stopped doing so. Menu labelling legislation should compel fast food chains to provide accessible nutrition information including nutrient values in addition to energy for all menu items in-store. Additionally, public education campaigns are needed to ensure customers can use menu labelling. © 2015 Public Health Association of Australia.

Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction mention extraction.

PubMed

Gupta, Shashank; Pawar, Sachin; Ramrakhiyani, Nitin; Palshikar, Girish Keshav; Varma, Vasudeva

2018-06-13

Social media is a useful platform to share health-related information due to its vast reach. This makes it a good candidate for public-health monitoring tasks, specifically for pharmacovigilance. We study the problem of extraction of Adverse-Drug-Reaction (ADR) mentions from social media, particularly from Twitter. Medical information extraction from social media is challenging, mainly due to short and highly informal nature of text, as compared to more technical and formal medical reports. Current methods in ADR mention extraction rely on supervised learning methods, which suffer from labeled data scarcity problem. The state-of-the-art method uses deep neural networks, specifically a class of Recurrent Neural Network (RNN) which is Long-Short-Term-Memory network (LSTM). Deep neural networks, due to their large number of free parameters rely heavily on large annotated corpora for learning the end task. But in the real-world, it is hard to get large labeled data, mainly due to the heavy cost associated with the manual annotation. To this end, we propose a novel semi-supervised learning based RNN model, which can leverage unlabeled data also present in abundance on social media. Through experiments we demonstrate the effectiveness of our method, achieving state-of-the-art performance in ADR mention extraction. In this study, we tackle the problem of labeled data scarcity for Adverse Drug Reaction mention extraction from social media and propose a novel semi-supervised learning based method which can leverage large unlabeled corpus available in abundance on the web. Through empirical study, we demonstrate that our proposed method outperforms fully supervised learning based baseline which relies on large manually annotated corpus for a good performance.

77 FR 7 - Revisions to Labeling Requirements for Blood and Blood Components, Including Source Plasma

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-03

... requirements will facilitate the use of a labeling system using machine-readable information that would be... components. Furthermore, we proposed the use of a labeling system using machine-readable information that...; Facilitates the use of a labeling system using machine- readable information that would be acceptable as a...

16 CFR 300.3 - Required label information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 16 Commercial Practices 1 2011-01-01 2011-01-01 false Required label information. 300.3 Section 300.3 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS RULES AND REGULATIONS UNDER THE WOOL PRODUCTS LABELING ACT OF 1939 Labeling § 300.3 Required label...

Equivalence Class Formation in a Trace Stimulus Pairing Two-Response Format: Effects of Response Labels and Prior Programmed Transitivity Induction

ERIC Educational Resources Information Center

Fields, Lanny; Doran, Erica; Marroquin, Michael

2009-01-01

Three experiments identified factors that did and did not enhance the formation of two-node four-member equivalence classes when training and testing were conducted with trials presented in a trace stimulus pairing two-response (SP2R) format. All trials contained two separately presented stimuli. Half of the trials, called within-class trials,…

Textural-Contextual Labeling and Metadata Generation for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Kiang, Richard K.

1999-01-01

Despite the extensive research and the advent of several new information technologies in the last three decades, machine labeling of ground categories using remotely sensed data has not become a routine process. Considerable amount of human intervention is needed to achieve a level of acceptable labeling accuracy. A number of fundamental reasons may explain why machine labeling has not become automatic. In addition, there may be shortcomings in the methodology for labeling ground categories. The spatial information of a pixel, whether textural or contextual, relates a pixel to its surroundings. This information should be utilized to improve the performance of machine labeling of ground categories. Landsat-4 Thematic Mapper (TM) data taken in July 1982 over an area in the vicinity of Washington, D.C. are used in this study. On-line texture extraction by neural networks may not be the most efficient way to incorporate textural information into the labeling process. Texture features are pre-computed from cooccurrence matrices and then combined with a pixel's spectral and contextual information as the input to a neural network. The improvement in labeling accuracy with spatial information included is significant. The prospect of automatic generation of metadata consisting of ground categories, textural and contextual information is discussed.

Bayes estimation on parameters of the single-class classifier. [for remotely sensed crop data

NASA Technical Reports Server (NTRS)

Lin, G. C.; Minter, T. C.

1976-01-01

Normal procedures used for designing a Bayes classifier to classify wheat as the major crop of interest require not only training samples of wheat but also those of nonwheat. Therefore, ground truth must be available for the class of interest plus all confusion classes. The single-class Bayes classifier classifies data into the class of interest or the class 'other' but requires training samples only from the class of interest. This paper will present a procedure for Bayes estimation on the mean vector, covariance matrix, and a priori probability of the single-class classifier using labeled samples from the class of interest and unlabeled samples drawn from the mixture density function.

Location, Location, Location: Eye-Tracking Evidence that Consumers Preferentially View Prominently Positioned Nutrition Information

PubMed Central

Graham, Dan J.; Jeffery, Robert W.

2012-01-01

Background Nutrition Facts labels can keep consumers better informed about their diets' nutritional composition, however, consumers currently do not understand these labels well or use them often. Thus, modifying existing labels may benefit public health. Objective The present study tracked the visual attention of individuals making simulated food-purchasing decisions to assess Nutrition Facts label viewing. Primary research questions were how self-reported viewing of Nutrition Facts labels and their components relates to measured viewing and whether locations of labels and specific label components relate to viewing. Design The study involved a simulated grocery shopping exercise conducted on a computer equipped with an eye-tracking camera. A post-task survey assessed self-reported nutrition information viewing, health behaviors, and demographics. Subjects/setting Individuals 18 years old and older and capable of reading English words on a computer (n=203) completed the 1-hour protocol at the University of Minnesota during Spring 2010. Statistical analyses Primary analyses included χ2, analysis of variance, and t tests comparing self-reported and measured viewing of label components in different presentation configurations. Results Self-reported viewing of Nutrition Facts label components was higher than objectively measured viewing. Label components at the top of the label were viewed more than those at the bottom, and labels positioned in the center of the screen were viewed more than those located on the sides. Conclusions Nutrition Facts label position within a viewing area and position of specific components on a label relate to viewing. Eye tracking is a valuable technology for evaluating consumers' attention to nutrition information, informing nutrition labeling policy (eg, front-of-pack labels), and designing labels that best support healthy dietary decisions. PMID:22027053

Vegetation mapping of Nowitna National Wildlife Reguge, Alaska using Landsat MSS digital data

USGS Publications Warehouse

Talbot, S. S.; Markon, Carl J.

1986-01-01

A Landsat-derived vegetation map was prepared for Nowitna National Wildlife Refuge. The refuge lies within the middle boreal subzone of north central Alaska. Seven major vegetation classes and sixteen subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, alluvial, subalpine); dwarf scrub (prostrate dwarf shrub tundra, dwarf shrub-graminoid tussock peatland); herbaceous (graminoid bog, marsh and meadow); scarcely vegetated areas (scarcely vegetated scree and floodplain); water (clear, turbid); and other areas (mountain shadow). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photointerpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is a 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

An automatic search of Alzheimer patterns using a nonnegative matrix factorization

NASA Astrophysics Data System (ADS)

Giraldo, Diana L.; García-Arteaga, Juan D.; Romero, Eduardo

2013-11-01

This paper presents a fully automatic method that condenses relevant morphometric information from a database of magnetic resonance images (MR) labeled as either normal (NC) or Alzheimer's disease (AD). The proposed method generates class templates using Nonnegative Matrix Factorization (NMF) which will be used to develop an NC/AD classi cator. It then nds regions of interest (ROI) with discerning inter-class properties. by inspecting the di erence volume of the two class templates. From these templates local probability distribution functions associated to low level features such as intensities, orientation and edges within the found ROI are calculated. A sample brain volume can then be characterized by a similarity measure in the ROI to both the normal and the pathological templates. These characteristics feed a simple binary SVM classi er which, when tested with an experimental group extracted from a public brain MR dataset (OASIS), reveals an equal error rate measure which is better than the state-of-the-art tested on the same dataset (0:9 in the former and 0:8 in the latter).

Improving the design of nutrition labels to promote healthier food choices and reasonable portion sizes.

PubMed

Roberto, C A; Khandpur, N

2014-07-01

Accurate and easy-to-understand nutrition labeling is a worthy public health goal that should be considered an important strategy among many to address obesity and poor diet. Updating the Nutrition Facts Panel on packaged foods, developing a uniform front-of-package labeling system and providing consumers with nutrition information on restaurant menus offer important opportunities to educate people about food's nutritional content, increase awareness of reasonable portion sizes and motivate consumers to make healthier choices. The aims of this paper were to identify and discuss: (1) current concerns with nutrition label communication strategies; (2) opportunities to improve the communication of nutrition information via food labels, with a specific focus on serving size information; and (3) important future areas of research on nutrition labeling as a tool to improve diet. We suggest that research on nutrition labeling should focus on ways to improve food labels' ability to capture consumer attention, reduce label complexity and convey numeric nutrition information in simpler and more meaningful ways, such as through interpretive food labels, the addition of simple text, reduced use of percentages and easy-to-understand presentation of serving size information.

A New F-18 Labeled PET Agent For Imaging Alzheimer's Plaques

NASA Astrophysics Data System (ADS)

Kulkarni, Padmakar V.; Vasdev, Neil; Hao, Guiyang; Arora, Veera; Long, Michael; Slavine, Nikolai; Chiguru, Srinivas; Qu, Bao Xi; Sun, Xiankai; Bennett, Michael; Antich, Peter P.; Bonte, Frederick J.

2011-06-01

Amyloid plaques and neurofibrillary tangles are hallmarks of Alzheimer's disease (AD). Advances in development of imaging agents have focused on targeting amyloid plaques. Notable success has been the development of C-11 labeled PIB (Pittsburgh Compound) and a number of studies have demonstrated the utility of this agent. However, the short half life of C-11 (t1/2: 20 min), is a limitation, thus has prompted the development of F-18 labeled agents. Most of these agents are derivatives of amyloid binding dyes; Congo red and Thioflavin. Some of these agents are in clinical trials with encouraging results. We have been exploring new class of agents based on 8-hydroxy quinoline, a weak metal chelator, targeting elevated levels of metals in plaques. Iodine-123 labeled clioquinol showed affinity for amyloid plaques however, it had limited brain uptake and was not successful in imaging in intact animals and humans. We have been successful in synthesizing F-18 labeled 8-hydroxy quinoline. Small animal PET/CT imaging studies with this agent showed high (7-10% ID/g), rapid brain uptake and fast washout of the agent from normal mice brains and delayed washout from transgenic Alzheimer's mice. These promising results encouraged us in further evaluation of this class of compounds for imaging AD plaques.

27 CFR 7.22 - Mandatory label information.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., DEPARTMENT OF THE TREASURY LIQUORS LABELING AND ADVERTISING OF MALT BEVERAGES Labeling Requirements for Malt Beverages § 7.22 Mandatory label information. There shall be stated: (a) On the brand label: (1) Brand name....27. (5) Alcohol content in accordance with § 7.71, for malt beverages that contain any alcohol...

Do Consumers Want More Nutritional and Health Information on Wine Labels? Insights from the EU and USA.

PubMed

Annunziata, Azzurra; Pomarici, Eugenio; Vecchio, Riccardo; Mariani, Angela

2016-07-07

The global strategy to reduce the harmful use of alcohol launched in 2010 by the World Health Organization includes, amongst several areas of recommended actions, providing consumer information about, and labelling, alcoholic beverages to indicate alcohol-related harm. Labelling requirements worldwide for alcoholic drinks are currently quite diverse and somewhat limited compared to labelling on food products and on tobacco. In this context, the current paper contributes to the academic and political debate on the inclusion of nutritional and health information on wine labelling, providing some insights into consumer interest in, and preferences for, such information in four core wine-producing and -consuming countries: Italy, France, Spain, and the United States of America. A rating-based conjoint analysis was performed in order to ascertain consumer preferences for different formats of additional information on wine labels, and a segmentation of the sample was performed to determine the existence of homogeneous groups of consumers in relation to the degrees of usefulness attached to the nutritional and health information on wine labels. Our results highlight the interest expressed by European and United States consumers for introducing nutrition and health information on wine labels. However, the results of conjoint analysis show some significant differences among stated preferences of the information delivery modes in different countries. In addition, segmentation analysis reveal the existence of significant differences between consumer groups with respect to their interest in receiving additional information on wine labels. These differences are not only linked to the geographic origin of the consumers, or to socio-demographic variables, but are also related to wine consumption habits, attitudes towards nutritional information, and the degree of involvement with wine. This heterogeneity of consumer preferences indicates a need for a careful consideration of wine labelling regulations and merits further investigation in order to identify labelling guidelines in terms of the message content and presentation method to be used.

Do Consumers Want More Nutritional and Health Information on Wine Labels? Insights from the EU and USA

PubMed Central

Annunziata, Azzurra; Pomarici, Eugenio; Vecchio, Riccardo; Mariani, Angela

2016-01-01

The global strategy to reduce the harmful use of alcohol launched in 2010 by the World Health Organization includes, amongst several areas of recommended actions, providing consumer information about, and labelling, alcoholic beverages to indicate alcohol-related harm. Labelling requirements worldwide for alcoholic drinks are currently quite diverse and somewhat limited compared to labelling on food products and on tobacco. In this context, the current paper contributes to the academic and political debate on the inclusion of nutritional and health information on wine labelling, providing some insights into consumer interest in, and preferences for, such information in four core wine-producing and -consuming countries: Italy, France, Spain, and the United States of America. A rating-based conjoint analysis was performed in order to ascertain consumer preferences for different formats of additional information on wine labels, and a segmentation of the sample was performed to determine the existence of homogeneous groups of consumers in relation to the degrees of usefulness attached to the nutritional and health information on wine labels. Our results highlight the interest expressed by European and United States consumers for introducing nutrition and health information on wine labels. However, the results of conjoint analysis show some significant differences among stated preferences of the information delivery modes in different countries. In addition, segmentation analysis reveal the existence of significant differences between consumer groups with respect to their interest in receiving additional information on wine labels. These differences are not only linked to the geographic origin of the consumers, or to socio-demographic variables, but are also related to wine consumption habits, attitudes towards nutritional information, and the degree of involvement with wine. This heterogeneity of consumer preferences indicates a need for a careful consideration of wine labelling regulations and merits further investigation in order to identify labelling guidelines in terms of the message content and presentation method to be used. PMID:27399767

Photoaffinity labelling of the active site of the rat glutathione transferases 3-3 and 1-1 and human glutathione transferase A1-1.

PubMed

Cooke, R J; Björnestedt, R; Douglas, K T; McKie, J H; King, M D; Coles, B; Ketterer, B; Mannervik, B

1994-09-01

The glutathione transferases (GSTs) form a group of enzymes responsible for a wide range of molecular detoxications. The photoaffinity label S-(2-nitro-4-azidophenyl)glutathione was used to study the hydrophobic region of the active site of the rat liver GST 1-1 and 2-2 isoenzymes (class Alpha) as well as the rat class-Mu GST 3-3. Photoaffinity labelling was carried out using a version of S-(2-nitro-4-azidophenyl)glutathione tritiated in the arylazido ring. The labelling occurred with higher levels of radioisotope incorporation for the Mu than the Alpha families. Taking rat GST 3-3, 1.18 (+/- 0.05) mol of radiolabel from S-(2-nitro-4-azidophenyl)glutathione was incorporated per mol of dimeric enzyme, which could be blocked by the presence of the strong competitive inhibitor, S-tritylglutathione (Ki = 1.4 x 10(-7) M). Radiolabelling of the protein paralleled the loss of enzyme activity. Photoaffinity labelling by tritiated S-(2-nitro-4-azidophenyl)glutathione on a preparative scale (in the presence and absence of S-tritylglutathione) followed by tryptic digestion and purification of the labelled peptides indicated that GST 3-3 was specifically photolabelled; the labelled peptides were sequenced. Similarly, preparative photoaffinity labelling by S-(2-nitro-4-azidophenyl)glutathione of the rat liver 1-1 isoenzyme, the human GST A1-1 and the human-rat chimaeric GST, H1R1/1, was carried out with subsequent sequencing of radiolabelled h.p.l.c.-purified tryptic peptides. The results were interpreted by means of molecular-graphics analysis to locate photoaffinity-labelled peptides using the X-ray-crystallographic co-ordinates of rat GST 3-3 and human GST A1-1. The molecular-graphical analysis indicated that the labelled peptides are located within the immediate vicinity of the region occupied by S-substituted glutathione derivatives bound in the active-site cavity of the GSTs investigated.

Automated cloud classification with a fuzzy logic expert system

NASA Technical Reports Server (NTRS)

Tovinkere, Vasanth; Baum, Bryan A.

1993-01-01

An unresolved problem in current cloud retrieval algorithms concerns the analysis of scenes containing overlapping cloud layers. Cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget. Most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. One promising method uses fuzzy logic to determine whether mixed cloud and/or surface types exist within a group of pixels, such as cirrus, land, and water, or cirrus and stratus. When two or more class types are present, fuzzy logic uses membership values to assign the group of pixels partially to the different class types. The strength of fuzzy logic lies in its ability to work with patterns that may include more than one class, facilitating greater information extraction from satellite radiometric data. The development of the fuzzy logic rule-based expert system involves training the fuzzy classifier with spectral and textural features calculated from accurately labeled 32x32 regions of Advanced Very High Resolution Radiometer (AVHRR) 1.1-km data. The spectral data consists of AVHRR channels 1 (0.55-0.68 mu m), 2 (0.725-1.1 mu m), 3 (3.55-3.93 mu m), 4 (10.5-11.5 mu m), and 5 (11.5-12.5 mu m), which include visible, near-infrared, and infrared window regions. The textural features are based on the gray level difference vector (GLDV) method. A sophisticated new interactive visual image Classification System (IVICS) is used to label samples chosen from scenes collected during the FIRE IFO II. The training samples are chosen from predefined classes, chosen to be ocean, land, unbroken stratiform, broken stratiform, and cirrus. The November 28, 1991 NOAA overpasses contain complex multilevel cloud situations ideal for training and validating the fuzzy logic expert system.

Physicians prefer greater detail in the biosimilar label (SmPC) - Results of a survey across seven European countries.

PubMed

Hallersten, Anna; Fürst, Walter; Mezzasalma, Riccardo

2016-06-01

In the European Union, labels (Summaries of Product Characteristics, SmPCs) of biosimilars and their reference products are in many instances almost identical (following a generic approach) despite different data requirements for the authorization of biosimilars and generics. To understand physicians' preferences on type and detail of information in the biosimilar label and their use of information sources when prescribing biologics including biosimilars, EuropaBio surveyed 210 physicians across seven European countries. Among surveyed physicians, 90.5% use the label frequently or occasionally as an information source and 87.2% deemed a clear statement on the origin of data helpful or very helpful. When comparing excerpts from the label of an authorized biosimilar and modified texts with additional information, 78.1-82.9% preferred the samples with additional information. This survey shows that the label is an appropriate vehicle for providing physicians with information about biologics and that physicians prefer more product-specific information in the biosimilar label. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Active Learning by Querying Informative and Representative Examples.

PubMed

Huang, Sheng-Jun; Jin, Rong; Zhou, Zhi-Hua

2014-10-01

Active learning reduces the labeling cost by iteratively selecting the most valuable data to query their labels. It has attracted a lot of interests given the abundance of unlabeled data and the high cost of labeling. Most active learning approaches select either informative or representative unlabeled instances to query their labels, which could significantly limit their performance. Although several active learning algorithms were proposed to combine the two query selection criteria, they are usually ad hoc in finding unlabeled instances that are both informative and representative. We address this limitation by developing a principled approach, termed QUIRE, based on the min-max view of active learning. The proposed approach provides a systematic way for measuring and combining the informativeness and representativeness of an unlabeled instance. Further, by incorporating the correlation among labels, we extend the QUIRE approach to multi-label learning by actively querying instance-label pairs. Extensive experimental results show that the proposed QUIRE approach outperforms several state-of-the-art active learning approaches in both single-label and multi-label learning.

7 CFR 201.72 - Production of all classes of certified seed.

Code of Federal Regulations, 2012 CFR

2012-01-01

... stages of certification including seeding, harvesting, processing, and labeling of the seed. (b) The unit... 7 Agriculture 3 2012-01-01 2012-01-01 false Production of all classes of certified seed. 201.72... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED...

7 CFR 201.72 - Production of all classes of certified seed.

Code of Federal Regulations, 2013 CFR

2013-01-01

... stages of certification including seeding, harvesting, processing, and labeling of the seed. (b) The unit... 7 Agriculture 3 2013-01-01 2013-01-01 false Production of all classes of certified seed. 201.72... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED...

7 CFR 201.72 - Production of all classes of certified seed.

Code of Federal Regulations, 2010 CFR

2010-01-01

... stages of certification including seeding, harvesting, processing, and labeling of the seed. (b) The unit... 7 Agriculture 3 2010-01-01 2010-01-01 false Production of all classes of certified seed. 201.72... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED...

7 CFR 201.72 - Production of all classes of certified seed.

Code of Federal Regulations, 2014 CFR

2014-01-01

... stages of certification including seeding, harvesting, processing, and labeling of the seed. (b) The unit... 7 Agriculture 3 2014-01-01 2014-01-01 false Production of all classes of certified seed. 201.72... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED...

7 CFR 201.72 - Production of all classes of certified seed.

Code of Federal Regulations, 2011 CFR

2011-01-01

... stages of certification including seeding, harvesting, processing, and labeling of the seed. (b) The unit... 7 Agriculture 3 2011-01-01 2011-01-01 false Production of all classes of certified seed. 201.72... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED...

Requirements for Access to Pesticide Labeling Information

EPA Pesticide Factsheets

Employers of pesticide handlers must make sure that the handlers are given information from the pesticide labeling and have access to the labeling itself, before they do any handling task. Learn about the information employers must provide.

Applications of pharmacogenomics in regulatory science: a product life cycle review.

PubMed

Tan-Koi, W C; Leow, P C; Teo, Y Y

2018-05-22

With rapid developments of pharmacogenomics (PGx) and regulatory science, it is important to understand the current PGx integration in product life cycle, impact on clinical practice thus far and opportunities ahead. We conducted a cross-sectional review on PGx-related regulatory documents and implementation guidelines in the United States and Europe. Our review found that although PGx-related guidance in both markets span across the entire product life cycle, the scope of implementation guidelines varies across two continents. Approximately one-third of Food and Drug Administration (FDA)-approved drugs with PGx information in drug labels and half of the European labels posted on PharmGKB website contain recommendations on genetic testing. The drugs affected 19 and 15 World Health Organization Anatomical Therapeutic Chemical drug classes (fourth level) in the United States and Europe, respectively, with protein kinase inhibitors (13 drugs in the United States and 16 drugs in Europe) being most prevalent. Topics of emerging interest were novel technologies, adaptive design in clinical trial and sample collection.

Area under precision-recall curves for weighted and unweighted data.

PubMed

Keilwagen, Jens; Grosse, Ivo; Grau, Jan

2014-01-01

Precision-recall curves are highly informative about the performance of binary classifiers, and the area under these curves is a popular scalar performance measure for comparing different classifiers. However, for many applications class labels are not provided with absolute certainty, but with some degree of confidence, often reflected by weights or soft labels assigned to data points. Computing the area under the precision-recall curve requires interpolating between adjacent supporting points, but previous interpolation schemes are not directly applicable to weighted data. Hence, even in cases where weights were available, they had to be neglected for assessing classifiers using precision-recall curves. Here, we propose an interpolation for precision-recall curves that can also be used for weighted data, and we derive conditions for classification scores yielding the maximum and minimum area under the precision-recall curve. We investigate accordances and differences of the proposed interpolation and previous ones, and we demonstrate that taking into account existing weights of test data is important for the comparison of classifiers.

Characterization of metabolic profile of honokiol in rat feces using liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and (13)C stable isotope labeling.

PubMed

Dong, Yinfeng; Tang, Minghai; Song, Hang; Li, Rong; Wang, Chunyu; Ye, Haoyu; Qiu, Neng; Zhang, Yongkui; Chen, Lijuan; Wei, Yuquan

2014-03-15

As fecal excretion is one of important routes of elimination of drugs and their metabolites, it is indispensable to investigate the metabolites in feces for more comprehensive information on biotransformation in vivo. In this study, a sensitive and reliable approach based on ultra-performance liquid chromatography/quadrupole-time-of-flight-mass spectrometry (UHPLC-Q-TOF-MS) was applied to characterize the metabolic profile of honokiol in rat feces after the administration of an equimolar mixture of honokiol and [(13)C6]-labeled honokiol. Totally 42 metabolites were discovered and tentatively identified in rat feces samples, 26 metabolites were first reported, including two novel classes of metabolites, methylated and dimeric metabolites of honokiol. Moreover, this study provided basic comparative data on the metabolites in rat plasma, feces and urine, which gave better understanding of the metabolic fate of honokiol in vivo. Copyright © 2014 Elsevier B.V. All rights reserved.

Area under Precision-Recall Curves for Weighted and Unweighted Data

PubMed Central

Grosse, Ivo

2014-01-01

Precision-recall curves are highly informative about the performance of binary classifiers, and the area under these curves is a popular scalar performance measure for comparing different classifiers. However, for many applications class labels are not provided with absolute certainty, but with some degree of confidence, often reflected by weights or soft labels assigned to data points. Computing the area under the precision-recall curve requires interpolating between adjacent supporting points, but previous interpolation schemes are not directly applicable to weighted data. Hence, even in cases where weights were available, they had to be neglected for assessing classifiers using precision-recall curves. Here, we propose an interpolation for precision-recall curves that can also be used for weighted data, and we derive conditions for classification scores yielding the maximum and minimum area under the precision-recall curve. We investigate accordances and differences of the proposed interpolation and previous ones, and we demonstrate that taking into account existing weights of test data is important for the comparison of classifiers. PMID:24651729

27 CFR 4.32 - Mandatory label information.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Mandatory label information. (a) There shall be stated on the brand label: (1) Brand name, in accordance... the bottle. (c) There shall be stated on the brand label or on a back label a statement that the... the Office of Management and Budget under Control Number 1512-0469) [T.D. 6521, 25 FR 13835, Dec. 29...

Food Labeling and Consumer Associations with Health, Safety, and Environment.

PubMed

Sax, Joanna K; Doran, Neal

2016-12-01

The food supply is complicated and consumers are increasingly calling for labeling on food to be more informative. In particular, consumers are asking for the labeling of food derived from genetically modified organisms (GMO) based on health, safety, and environmental concerns. At issue is whether the labels that are sought would accurately provide the information desired. The present study examined consumer (n = 181) perceptions of health, safety and the environment for foods labeled organic, natural, fat free or low fat, GMO, or non-GMO. Findings indicated that respondents consistently believed that foods labeled GMO are less healthy, safe and environmentally-friendly compared to all other labels (ps < .05). These results suggest that labels mean something to consumers, but that a disconnect may exist between the meaning associated with the label and the scientific consensus for GMO food. These findings may provide insight for the development of labels that provide information that consumers seek.

DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.

PubMed

Kulmanov, Maxat; Khan, Mohammed Asif; Hoehndorf, Robert; Wren, Jonathan

2018-02-15

A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40 000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, in particular for predicting cellular locations. Web server: http://deepgo.bio2vec.net, Source code: https://github.com/bio-ontology-research-group/deepgo. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Large-scale weakly supervised object localization via latent category learning.

PubMed

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

Equivalence classes of Fibonacci lattices and their similarity properties

NASA Astrophysics Data System (ADS)

Lo Gullo, N.; Vittadello, L.; Bazzan, M.; Dell'Anna, L.

2016-08-01

We investigate, theoretically and experimentally, the properties of Fibonacci lattices with arbitrary spacings. Different from periodic structures, the reciprocal lattice and the dynamical properties of Fibonacci lattices depend strongly on the lengths of their lattice parameters, even if the sequence of long and short segment, the Fibonacci string, is the same. In this work we show that by exploiting a self-similarity property of Fibonacci strings under a suitable composition rule, it is possible to define equivalence classes of Fibonacci lattices. We show that the diffraction patterns generated by Fibonacci lattices belonging to the same equivalence class can be rescaled to a common pattern of strong diffraction peaks thus giving to this classification a precise meaning. Furthermore we show that, through the gap labeling theorem, gaps in the energy spectra of Fibonacci crystals belonging to the same class can be labeled by the same momenta (up to a proper rescaling) and that the larger gaps correspond to the strong peaks of the diffraction spectra. This observation makes the definition of equivalence classes meaningful also for the spectral and therefore dynamical and thermodynamical properties of quasicrystals. Our results apply to the more general class of quasiperiodic lattices for which similarity under a suitable deflation rule is in order.

9 CFR 317.302 - Location of nutrition information.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 2 2014-01-01 2014-01-01 false Location of nutrition information. 317... INSPECTION AND CERTIFICATION LABELING, MARKING DEVICES, AND CONTAINERS Nutrition Labeling § 317.302 Location of nutrition information. (a) Nutrition information on a label of a packaged meat or meat food...

9 CFR 317.302 - Location of nutrition information.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Location of nutrition information. 317... INSPECTION AND CERTIFICATION LABELING, MARKING DEVICES, AND CONTAINERS Nutrition Labeling § 317.302 Location of nutrition information. (a) Nutrition information on a label of a packaged meat or meat food...

9 CFR 317.302 - Location of nutrition information.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 2 2013-01-01 2013-01-01 false Location of nutrition information. 317... INSPECTION AND CERTIFICATION LABELING, MARKING DEVICES, AND CONTAINERS Nutrition Labeling § 317.302 Location of nutrition information. (a) Nutrition information on a label of a packaged meat or meat food...

9 CFR 317.302 - Location of nutrition information.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 2 2012-01-01 2012-01-01 false Location of nutrition information. 317... INSPECTION AND CERTIFICATION LABELING, MARKING DEVICES, AND CONTAINERS Nutrition Labeling § 317.302 Location of nutrition information. (a) Nutrition information on a label of a packaged meat or meat food...

9 CFR 317.302 - Location of nutrition information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 2 2011-01-01 2011-01-01 false Location of nutrition information. 317... INSPECTION AND CERTIFICATION LABELING, MARKING DEVICES, AND CONTAINERS Nutrition Labeling § 317.302 Location of nutrition information. (a) Nutrition information on a label of a packaged meat or meat food...

Ontology-based literature mining and class effect analysis of adverse drug reactions associated with neuropathy-inducing drugs.

PubMed

Hur, Junguk; Özgür, Arzucan; He, Yongqun

2018-06-07

Adverse drug reactions (ADRs), also called as drug adverse events (AEs), are reported in the FDA drug labels; however, it is a big challenge to properly retrieve and analyze the ADRs and their potential relationships from textual data. Previously, we identified and ontologically modeled over 240 drugs that can induce peripheral neuropathy through mining public drug-related databases and drug labels. However, the ADR mechanisms of these drugs are still unclear. In this study, we aimed to develop an ontology-based literature mining system to identify ADRs from drug labels and to elucidate potential mechanisms of the neuropathy-inducing drugs (NIDs). We developed and applied an ontology-based SciMiner literature mining strategy to mine ADRs from the drug labels provided in the Text Analysis Conference (TAC) 2017, which included drug labels for 53 neuropathy-inducing drugs (NIDs). We identified an average of 243 ADRs per NID and constructed an ADR-ADR network, which consists of 29 ADR nodes and 149 edges, including only those ADR-ADR pairs found in at least 50% of NIDs. Comparison to the ADR-ADR network of non-NIDs revealed that the ADRs such as pruritus, pyrexia, thrombocytopenia, nervousness, asthenia, acute lymphocytic leukaemia were highly enriched in the NID network. Our ChEBI-based ontology analysis identified three benzimidazole NIDs (i.e., lansoprazole, omeprazole, and pantoprazole), which were associated with 43 ADRs. Based on ontology-based drug class effect definition, the benzimidazole drug group has a drug class effect on all of these 43 ADRs. Many of these 43 ADRs also exist in the enriched NID ADR network. Our Ontology of Adverse Events (OAE) classification further found that these 43 benzimidazole-related ADRs were distributed in many systems, primarily in behavioral and neurological, digestive, skin, and immune systems. Our study demonstrates that ontology-based literature mining and network analysis can efficiently identify and study specific group of drugs and their associated ADRs. Furthermore, our analysis of drug class effects identified 3 benzimidazole drugs sharing 43 ADRs, leading to new hypothesis generation and possible mechanism understanding of drug-induced peripheral neuropathy.

Impact of FDA Actions, DTCA, and Public Information on the Market for Pain Medication.

PubMed

Bradford, W David; Kleit, Andrew N

2015-07-01

Nonsteroidal anti-inflammatory drugs (NSAIDs) are one of the most important classes of prescription drugs used by primary care physicians to manage pain. The NSAID class of products has a somewhat controversial history, around which a complex regulatory and informational environment has developed. This history includes a boxed warning mandated by the Food and Drug Administration (FDA) for all NSAIDs in 2005. We investigate the impact that various information shocks have had on the use of prescription medications for pain in primary care in the USA. We accomplish this by extracting data on nearly 600,000 patients from a unique nationwide electronic medical record database and estimate the probability of any active prescription for the four types of pain medications as a function of FDA actions, advertising, media coverage, and patient characteristics. We find that even after accounting for multiple sources of information, the FDA label changes and boxed warnings had a significant effect on pain medication prescribing. The boxed warning did not have the same impact on the use of all NSAID inhibitors. We find that the boxed warning reduced the use of NSAID COX-2 inhibitor use, which was the focus of much of the press attention. In contrast, however, the warning actually increased the use of non-COX-2 NSAID inhibitors. Thus, the efficacy of the FDA's black box warning is clearly mixed. Copyright © 2014 John Wiley & Sons, Ltd.

BCI Competition IV – Data Set I: Learning Discriminative Patterns for Self-Paced EEG-Based Motor Imagery Detection

PubMed Central

Zhang, Haihong; Guan, Cuntai; Ang, Kai Keng; Wang, Chuanchu

2012-01-01

Detecting motor imagery activities versus non-control in brain signals is the basis of self-paced brain-computer interfaces (BCIs), but also poses a considerable challenge to signal processing due to the complex and non-stationary characteristics of motor imagery as well as non-control. This paper presents a self-paced BCI based on a robust learning mechanism that extracts and selects spatio-spectral features for differentiating multiple EEG classes. It also employs a non-linear regression and post-processing technique for predicting the time-series of class labels from the spatio-spectral features. The method was validated in the BCI Competition IV on Dataset I where it produced the lowest prediction error of class labels continuously. This report also presents and discusses analysis of the method using the competition data set. PMID:22347153

Deep neural network-based domain adaptation for classification of remote sensing images

NASA Astrophysics Data System (ADS)

Ma, Li; Song, Jiazhen

2017-10-01

We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.

Network-based stochastic semisupervised learning.

PubMed

Silva, Thiago Christiano; Zhao, Liang

2012-03-01

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

Structure of the N-linked oligosaccharides of MHC class I molecules from cells deficient in the antigenic peptide transporter. Implications for the site of peptide association.

PubMed

Hayes, B K; Esquivel, F; Bennink, J R; Yewdell, J W; Varki, A

1995-10-15

Class I molecules are N-linked glycoproteins encoded by the MHC. They carry cytosolic protein-derived peptides to the cell surface, displaying them to enable immune surveillance of cellular processes. Peptides are delivered to class I molecules by the transporter associated with Ag processing (TAP). Peptide association is known to occur before exposure of class I molecules to the medial Golgi-processing enzyme alpha-mannosidase II, but there is limited information regarding the location or timing of peptide binding within the earlier regions of the endoplasmic reticulum (ER)-Golgi pathway. A reported association of newly synthesized class I molecules with the ER chaperonin calnexin raises the possibility of persistence of the monoglycosylated N-linked oligosaccharide (NLO) Glc1Man8GlcNAc2, known to be recognized by this lectin. To explore these matters, we determined the structure of the NLOs on the subset of newly synthesized class I molecules awaiting the loading of peptide. We pulse-labeled murine MHC H-2Db class I molecules in RMA/S cells, which lack one of the TAP subunits, causing the great majority of the molecules to be retained for prolonged periods in an early secretory compartment, awaiting peptide binding. MHC molecules pulse-labeled with [3H]glucosamine were isolated, the NLOs specifically released and structurally analyzed by a variety of techniques. Within the chosen window of biosynthetic time, most Db molecules from parental RMA cells carried mature NLOs of the biantennary complex-type, with one to two sialic acid residues. In RMA/S cells, such chains were in the minority, the majority consisting of the precursor forms Man8GlcNAc2 and Man9GlcNAc2. No glucosylated forms were detected, nor were the later processing intermediates Man5-7GlcNAc2 or GlcNAc1Man4-5GlcNAc2. Thus, most Db molecules in TAP-deficient cells are retained in an early compartment of the secretory pathway, before the point of first access to the Golgi alpha-mannosidase I, which trims alpha 1-2 linked mannose residues, but beyond the point where the alpha 1-3-linked glucose residue is finally removed by the ER glucosidase II. Thus, structural analysis of NLOs on class I molecules within a defined biosynthetic window has established a biochemical measure of the timing of peptide association.

Is less always more? The effects of low-fat labeling and caloric information on food intake, calorie estimates, taste preference, and health attributions.

PubMed

Ebneter, Daria S; Latner, Janet D; Nigg, Claudio R

2013-09-01

The present study examined whether low-fat labeling and caloric information affect food intake, calorie estimates, taste preference, and health perceptions. Participants included 175 female undergraduate students who were randomly assigned to one of four experimental conditions. A 2×2 between subjects factorial design was used in which the fat content label and caloric information of chocolate candy was manipulated. The differences in food intake across conditions did not reach statistical significance. However, participants significantly underestimated the calorie content of low-fat-labeled candy. Participants also rated low-fat-labeled candy as significantly better tasting when they had caloric information available. Participants endorsed more positive health attributions for low-fat-labeled candy than for regular-labeled candy, independent of caloric information. The inclusion of eating attitudes and behaviors as covariates did not alter the results. The study findings may be related to the "health halo" associated with low-fat foods and add to the research base by examining the interaction between low-fat and calorie labeling. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simplifying healthful choices: a qualitative study of a physical activity based nutrition label format

PubMed Central

2013-01-01

Background This study used focus groups to pilot and evaluate a new nutrition label format and refine the label design. Physical activity equivalent labels present calorie information in terms of the amount of physical activity that would be required to expend the calories in a specified food item. Methods Three focus groups with a total of twenty participants discussed food choices and nutrition labeling. They provided information on comprehension, usability and acceptability of the label. A systematic coding process was used to apply descriptive codes to the data and to identify emerging themes and attitudes. Results Participants in all three groups were able to comprehend the label format. Discussion about label format focused on issues including gender of the depicted figure, physical fitness of the figure, preference for walking or running labels, and preference for information in miles or minutes. Feedback from earlier focus groups was used to refine the labels in an iterative process. Conclusions In contrast to calorie labels, participants shown physical activity labels asked and answered, “How does this label apply to me?” This shift toward personalized understanding may indicate that physical activity labels offer an advantage over currently available nutrition labels. PMID:23742678

"We Have a Right to Know": Exploring Consumer Opinions on Content, Design and Acceptability of Enhanced Alcohol Labels.

PubMed

Vallance, Kate; Romanovska, Inna; Stockwell, Tim; Hammond, David; Rosella, Laura; Hobin, Erin

2018-01-01

This study aimed to refine content and design of an enhanced alcohol label to provide information that best supports informed drinking and to gauge consumer acceptability of enhanced alcohol labels among a subset of consumers. Five focus groups (n = 45) were conducted with stakeholders and the general public (age 19+) across one jurisdiction in northern Canada. Interviews were transcribed and analyzed using NVivo software. The majority of participants showed strong support for enhanced alcohol labels with an emphasis on the consumers' right to know about the health risks related to alcohol. Participants preferred larger labels that included standard drink (SD) information, national low-risk drinking guidelines presented as a chart with pictograms, cancer health messaging and a pregnancy warning. Supporting introduction of the labels with a web resource and an educational campaign was also recommended. Displaying enhanced labels on alcohol containers that include SD information, low-risk drinking guidelines and other health messaging in an accessible format may be an effective way to better inform drinkers about their consumption and increase awareness of alcohol-related health risks. Introduction of enhanced labels shows potential for consumer support. Focus group findings indicate strong support for enhanced alcohol labels displaying SD information, national drinking guidelines, health messaging and a pregnancy warning. Introduction of enhanced alcohol labels in tandem with an educational campaign may be an effective way to better inform Canadian drinkers and shows potential for consumer support. © The Author 2017. Medical Council on Alcohol and Oxford University Press. All rights reserved.

A Locality-Constrained and Label Embedding Dictionary Learning Algorithm for Image Classification.

PubMed

Zhengming Li; Zhihui Lai; Yong Xu; Jian Yang; Zhang, David

2017-02-01

Locality and label information of training samples play an important role in image classification. However, previous dictionary learning algorithms do not take the locality and label information of atoms into account together in the learning process, and thus their performance is limited. In this paper, a discriminative dictionary learning algorithm, called the locality-constrained and label embedding dictionary learning (LCLE-DL) algorithm, was proposed for image classification. First, the locality information was preserved using the graph Laplacian matrix of the learned dictionary instead of the conventional one derived from the training samples. Then, the label embedding term was constructed using the label information of atoms instead of the classification error term, which contained discriminating information of the learned dictionary. The optimal coding coefficients derived by the locality-based and label-based reconstruction were effective for image classification. Experimental results demonstrated that the LCLE-DL algorithm can achieve better performance than some state-of-the-art algorithms.

Consumer involvement: effects on information processing from over-the-counter medication labels.

PubMed

Sansgiry, S S; Cady, P S; Sansgiry, S

2001-01-01

The objective of this study was to evaluate the effects of consumer involvement on information processing from over-the-counter (OTC) medication labels. A sample of 256 students evaluated simulated OTC product labels for two product categories (headache and cold) in random order. Each participant evaluated labels after reading a scenario to simulate high and low involvement respectively. A questionnaire was used to collect data on variables such as label comprehension, attitude-towards-product label, product evaluation, and purchase intention. The results indicate that when consumers are involved in their purchase of OTC medications they are significantly more likely to understand information from the label and evaluate it accordingly. However, involvement does not affect attitude-towards-product label nor does it enhance purchase intention.

Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness.

PubMed

Boyce, Richard D; Horn, John R; Hassanzadeh, Oktie; Waard, Anita de; Schneider, Jodi; Luciano, Joanne S; Rastegar-Mojarad, Majid; Liakata, Maria

2013-01-26

Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep current with the scientific literature. We present a novel approach to addressing this issue. The primary goal of this novel approach is to better meet the information needs of persons who consult the drug product label for information on a drug's efficacy, effectiveness, and safety. Using FDA product label regulations as a guide, the approach links drug claims present in drug information sources available on the Semantic Web with specific product label sections. Here we report on pilot work that establishes the baseline performance characteristics of a proof-of-concept system implementing the novel approach. Claims from three drug information sources were linked to the Clinical Studies, Drug Interactions, and Clinical Pharmacology sections of the labels for drug products that contain one of 29 psychotropic drugs. The resulting Linked Data set maps 409 efficacy/effectiveness study results, 784 drug-drug interactions, and 112 metabolic pathway assertions derived from three clinically-oriented drug information sources (ClinicalTrials.gov, the National Drug File - Reference Terminology, and the Drug Interaction Knowledge Base) to the sections of 1,102 product labels. Proof-of-concept web pages were created for all 1,102 drug product labels that demonstrate one possible approach to presenting information that dynamically enhances drug product labeling. We found that approximately one in five efficacy/effectiveness claims were relevant to the Clinical Studies section of a psychotropic drug product, with most relevant claims providing new information. We also identified several cases where all of the drug-drug interaction claims linked to the Drug Interactions section for a drug were potentially novel. The baseline performance characteristics of the proof-of-concept will enable further technical and user-centered research on robust methods for scaling the approach to the many thousands of product labels currently on the market.

Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness

PubMed Central

2013-01-01

Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep current with the scientific literature. We present a novel approach to addressing this issue. The primary goal of this novel approach is to better meet the information needs of persons who consult the drug product label for information on a drug’s efficacy, effectiveness, and safety. Using FDA product label regulations as a guide, the approach links drug claims present in drug information sources available on the Semantic Web with specific product label sections. Here we report on pilot work that establishes the baseline performance characteristics of a proof-of-concept system implementing the novel approach. Claims from three drug information sources were linked to the Clinical Studies, Drug Interactions, and Clinical Pharmacology sections of the labels for drug products that contain one of 29 psychotropic drugs. The resulting Linked Data set maps 409 efficacy/effectiveness study results, 784 drug-drug interactions, and 112 metabolic pathway assertions derived from three clinically-oriented drug information sources (ClinicalTrials.gov, the National Drug File – Reference Terminology, and the Drug Interaction Knowledge Base) to the sections of 1,102 product labels. Proof-of-concept web pages were created for all 1,102 drug product labels that demonstrate one possible approach to presenting information that dynamically enhances drug product labeling. We found that approximately one in five efficacy/effectiveness claims were relevant to the Clinical Studies section of a psychotropic drug product, with most relevant claims providing new information. We also identified several cases where all of the drug-drug interaction claims linked to the Drug Interactions section for a drug were potentially novel. The baseline performance characteristics of the proof-of-concept will enable further technical and user-centered research on robust methods for scaling the approach to the many thousands of product labels currently on the market. PMID:23351881

76 FR 82303 - Draft Guidance for Industry on Responding to Unsolicited Requests for Off-Label Information About...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-30

... indication and risk information, post-marketing submission requirements) in their internet and social media... requests for off-label information, including those that firms may encounter on emerging electronic media...] Draft Guidance for Industry on Responding to Unsolicited Requests for Off-Label Information About...

Tin-117m-labeled stannic (Sn.sup.4+) chelates

DOEpatents

Srivastava, Suresh C.; Meinken, George E.; Richards, Powell

1985-01-01

The radiopharmaceutical reagents of this invention and the class of Tin-117m radiopharmaceuticals are therapeutic and diagnostic agents that incorporate gamma-emitting nuclides that localize in bone after intravenous injection in mammals (mice, rats, dogs, and rabbits). Images reflecting bone structure or function can then be obtained by a scintillation camera that detects the distribution of ionizing radiation emitted by the radioactive agent. Tin-117m-labeled chelates of stannic tin localize almost exclusively in cortical bone. Upon intravenous injection of the reagent, the preferred chelates are phosphonate compounds, preferable, PYP, MDP, EHDP, and DTPA. This class of reagents is therapeutically and diagnostically useful in skeletal scintigraphy and for the radiotherapy of bone tumors and other disorders.

Sub-pixel image classification for forest types in East Texas

NASA Astrophysics Data System (ADS)

Westbrook, Joey

Sub-pixel classification is the extraction of information about the proportion of individual materials of interest within a pixel. Landcover classification at the sub-pixel scale provides more discrimination than traditional per-pixel multispectral classifiers for pixels where the material of interest is mixed with other materials. It allows for the un-mixing of pixels to show the proportion of each material of interest. The materials of interest for this study are pine, hardwood, mixed forest and non-forest. The goal of this project was to perform a sub-pixel classification, which allows a pixel to have multiple labels, and compare the result to a traditional supervised classification, which allows a pixel to have only one label. The satellite image used was a Landsat 5 Thematic Mapper (TM) scene of the Stephen F. Austin Experimental Forest in Nacogdoches County, Texas and the four cover type classes are pine, hardwood, mixed forest and non-forest. Once classified, a multi-layer raster datasets was created that comprised four raster layers where each layer showed the percentage of that cover type within the pixel area. Percentage cover type maps were then produced and the accuracy of each was assessed using a fuzzy error matrix for the sub-pixel classifications, and the results were compared to the supervised classification in which a traditional error matrix was used. The overall accuracy of the sub-pixel classification using the aerial photo for both training and reference data had the highest (65% overall) out of the three sub-pixel classifications. This was understandable because the analyst can visually observe the cover types actually on the ground for training data and reference data, whereas using the FIA (Forest Inventory and Analysis) plot data, the analyst must assume that an entire pixel contains the exact percentage of a cover type found in a plot. An increase in accuracy was found after reclassifying each sub-pixel classification from nine classes with 10 percent interval each to five classes with 20 percent interval each. When compared to the supervised classification which has a satisfactory overall accuracy of 90%, none of the sub-pixel classification achieved the same level. However, since traditional per-pixel classifiers assign only one label to pixels throughout the landscape while sub-pixel classifications assign multiple labels to each pixel, the traditional 85% accuracy of acceptance for pixel-based classifications should not apply to sub-pixel classifications. More research is needed in order to define the level of accuracy that is deemed acceptable for sub-pixel classifications.

An evaluation of the completeness of drug-drug interaction-related information in package inserts.

PubMed

Ng, Giok Qin; Sklar, Grant Edward; Chng, Hui Ting

2017-02-01

The project aimed to evaluate the completeness of drug-drug interaction (DDI)-related information in package inserts (PIs) and develop a systematic approach to conduct the evaluation. DDI-related information in the branded PIs of statins, macrolides, protease inhibitors and selected drugs of narrow therapeutic index (DNTI) were evaluated against the criteria distilled from the Food and Drug Administration (FDA) labelling recommendation guidance document. Decision trees were crafted and employed in the evaluation process. Scores were computed to give each PI an overall completeness score and individual criterion completeness score. The Kruskal-Wallis test and Dunn's multiple comparison test were used to assess the differences in the completeness scores. The mean overall completeness score of the 21 PIs was 35.7 ± 13.4 % (range 12.2-62 %). Eight out of the 11 individual evaluation criterion had a mean completeness score below 50 %. A subclass analysis conducted revealed that PIs from the different drug classes differed in the type of DDI-related information, such that they are more complete or less complete. The completeness score of DDI-related information in the PIs varied extensively amongst and within drug classes. A consensus between the authorities and drug companies on the type and quality of DDI-related information to be included could improve their completeness in PIs and make PIs a valuable source of DDI reference. Decision trees, albeit not validated yet, lay the groundwork for a valuable tool to evaluate DDI-related or other drug information.

78 FR 39736 - Agency Information Collection Activities; Announcement of Office of Management and Budget...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-02

... Labeling; Notification Procedures for Statements on Dietary Supplements AGENCY: Food and Drug... information entitled ``Food Labeling; Notification Procedures for Statements on Dietary Supplements'' to OMB... collection of information entitled ``Food Labeling; Notification Procedures for Statements on Dietary...

Assessing Attentional Prioritization of Front-of-Pack Nutrition Labels using Change Detection

PubMed Central

Becker, Mark W.; Sundar, Raghav Prashant; Bello, Nora; Alzahabi, Reem; Weatherspoon, Lorraine; Bix, Laura

2015-01-01

We used a change detection method to evaluate attentional prioritization of nutrition information that appears in the traditional “Nutrition Facts Panel” and in front-of-pack nutrition labels. Results provide compelling evidence that front-of-pack labels attract attention more readily than the Nutrition Facts Panel, even when participants are not specifically tasked with searching for nutrition information. Further, color-coding the relative nutritional value of key nutrients within the front-of-pack label resulted in increased attentional prioritization of nutrition information, but coding using facial icons did not significantly increase attention to the label. Finally, the general pattern of attentional prioritization across front-of-pack designs was consistent across a diverse sample of participants. Our results indicate that color-coded, front-of-pack nutrition labels increase attention to the nutrition information of packaged food, a finding that has implications for current policy discussions regarding labeling change. PMID:26851468

49 CFR 172.403 - Class 7 (radioactive) material.

Code of Federal Regulations, 2014 CFR

2014-10-01

...Sv/h (1,000 mrem/h) YELLOW-III (Must be shipped under exclusive use provisions; see 173.441(b) of... overpacks and freight containers required in § 172.402 to bear a FISSILE label, the CSI on the label must be the sum of the CSIs for all of the packages contained in the overpack or freight container. (f) Each...

49 CFR 172.403 - Class 7 (radioactive) material.

Code of Federal Regulations, 2011 CFR

2011-10-01

...Sv/h (1,000 mrem/h) YELLOW-III (Must be shipped under exclusive use provisions; see 173.441(b) of... overpacks and freight containers required in § 172.402 to bear a FISSILE label, the CSI on the label must be the sum of the CSIs for all of the packages contained in the overpack or freight container. (f) Each...

49 CFR 172.403 - Class 7 (radioactive) material.

Code of Federal Regulations, 2012 CFR

2012-10-01

...Sv/h (1,000 mrem/h) YELLOW-III (Must be shipped under exclusive use provisions; see 173.441(b) of... overpacks and freight containers required in § 172.402 to bear a FISSILE label, the CSI on the label must be the sum of the CSIs for all of the packages contained in the overpack or freight container. (f) Each...

49 CFR 172.403 - Class 7 (radioactive) material.

Code of Federal Regulations, 2010 CFR

2010-10-01

...Sv/h (1,000 mrem/h) YELLOW-III (Must be shipped under exclusive use provisions; see 173.441(b) of... overpacks and freight containers required in § 172.402 to bear a FISSILE label, the CSI on the label must be the sum of the CSIs for all of the packages contained in the overpack or freight container. (f) Each...

49 CFR 172.403 - Class 7 (radioactive) material.

Code of Federal Regulations, 2013 CFR

2013-10-01

...Sv/h (1,000 mrem/h) YELLOW-III (Must be shipped under exclusive use provisions; see 173.441(b) of... overpacks and freight containers required in § 172.402 to bear a FISSILE label, the CSI on the label must be the sum of the CSIs for all of the packages contained in the overpack or freight container. (f) Each...

Interaction of a vasopressin antagonist with vasopressin receptors in the septum of the rat brain

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

Dorsa, D.M.; Brot, M.D.; Shewey, L.M.

1988-01-01

The ability of d(CH2)5-Tyr(Me)-arginine-8-vasopressin, an antagonist of peripheral pressoric (V1-type) vasopressin receptors, to label vasopressin binding sites in the septum of the rat brain was evaluated. Using crude membrane preparations from the septum, /sup 3/H-arginine-8-vasopressin (AVP) specifically labels a single class of binding sites with a Kd of 2.9 nM and maximum binding site concentration of 19.8 fmole/mg protein. /sup 3/H-Antag also labels a single class of membrane sites but with higher affinity (Kd = 0.47 nM) and lower capacity (10.1 fmole/mg protein) than /sup 3/H-AVP. The rank order of potency of various competitor peptides for /sup 3/H-AVP and /supmore » 3/H-Antag binding was similar. Oxytocin was 100-1,000 fold less potent than AVP in competing for binding with both ligands. /sup 3/H-AVP and /sup 3/H-Antag showed similar labeling patterns when incubated with septal tissue slices. Unlabeled Antag also effectively antagonized vasopressin-stimulated phosphatidylinositol hydrolysis in septal tissue slices.« less

An Interactive User Interface for Drug Labeling to Improve Readability and Decision-Making

PubMed Central

Abedtash, Hamed; Duke, Jon D.

2015-01-01

FDA-approved prescribing information (also known as product labeling or labels) contain critical safety information for health care professionals. Drug labels have often been criticized, however, for being overly complex, difficult to read, and rife with overwarning, leading to high cognitive load. In this project, we aimed to improve the usability of drug labels by increasing the ‘signal-to-noise ratio’ and providing meaningful information to care providers based on patient-specific comorbidities and concomitant medications. In the current paper, we describe the design process and resulting web application, known as myDrugLabel. Using the Structured Product Label documents as a base, we describe the process of label personalization, readability improvements, and integration of diverse evidence sources, including the medical literature from PubMed, pharmacovigilance reports from FDA adverse event reporting system (FAERS), and social media signals directly into the label. PMID:26958158

An Interactive User Interface for Drug Labeling to Improve Readability and Decision-Making.

PubMed

Abedtash, Hamed; Duke, Jon D

FDA-approved prescribing information (also known as product labeling or labels) contain critical safety information for health care professionals. Drug labels have often been criticized, however, for being overly complex, difficult to read, and rife with overwarning, leading to high cognitive load. In this project, we aimed to improve the usability of drug labels by increasing the 'signal-to-noise ratio' and providing meaningful information to care providers based on patient-specific comorbidities and concomitant medications. In the current paper, we describe the design process and resulting web application, known as myDrugLabel. Using the Structured Product Label documents as a base, we describe the process of label personalization, readability improvements, and integration of diverse evidence sources, including the medical literature from PubMed, pharmacovigilance reports from FDA adverse event reporting system (FAERS), and social media signals directly into the label.

Acquiring Taxonomic Relations in Lexical Memory: The Role of Superordinate Category Labels.

ERIC Educational Resources Information Center

Blewitt, Pamela; Krackow, Elisa

1992-01-01

On picture matching and word recall tasks, children performed better on slot-fillers, or items classed in a superordinate category (such as food) and in the same event context (such as eating breakfast), than on coordinates, or items classed in a superordinate category but in different event contexts. (BC)

Effect of Training Different Classes of Verbal Behavior to Decrease Aberrant Verbal Behavior

ERIC Educational Resources Information Center

Vandbakk, Monica; Arntzen, Erik; Gisnaas, Arnt; Antonsen, Vidar; Gundhus, Terje

2012-01-01

Inappropriate verbal behavior that is labeled "psychotic" is often described as insensitive to environmental contingencies. The purpose of the current study was to establish different classes of rational or appropriate verbal behavior in a woman with developmental disabilities and evaluate the effects on her psychotic or aberrant vocal verbal…

Defining the "like" in "begetting the like": The development of inductive inference in the domain of biology

NASA Astrophysics Data System (ADS)

Lo, Ya-Fen

There are evidences that very young children consider linguistic labels when making similarity judgment and inductive inferences. However, it remains unclear how labels contribute to young children's similarity judgment and inductive inferences. It has been demonstrated that labels facilitate categorical memberships about objects in young children's similarity judgment and inductive inferences. It is also suggested that young children should rely on several sources of information when making similarity judgment and inductive inferences. Three experiments were conducted to examine these interpretations, in which biological information, labeling information, and perceptual similarity information were varied in a systematic manner. Three- to eleven-year-old children were asked to judge which of two Test animals a baby animals would share biological properties with. In Experiment 1, preschool children demonstrated a basic understanding of the importance of biological information for generalizing biological properties. In Experiment 2, when the labeling information became available, young children relied on linguistic labels rather than on biological information when generalizing biological properties. At the same time, 9- to 11-year-old children relied consistently on biological information. Experiment 3 supported the results of Experiment 2 and suggested that in addition to labels, perceptual similarity also contributed to children's inductive inferences.

Evaluating Varied Label Designs for Use with Medical Devices: Optimized Labels Outperform Existing Labels in the Correct Selection of Devices and Time to Select.

PubMed

Bix, Laura; Seo, Do Chan; Ladoni, Moslem; Brunk, Eric; Becker, Mark W

2016-01-01

Effective standardization of medical device labels requires objective study of varied designs. Insufficient empirical evidence exists regarding how practitioners utilize and view labeling. Measure the effect of graphic elements (boxing information, grouping information, symbol use and color-coding) to optimize a label for comparison with those typical of commercial medical devices. Participants viewed 54 trials on a computer screen. Trials were comprised of two labels that were identical with regard to graphics, but differed in one aspect of information (e.g., one had latex, the other did not). Participants were instructed to select the label along a given criteria (e.g., latex containing) as quickly as possible. Dependent variables were binary (correct selection) and continuous (time to correct selection). Eighty-nine healthcare professionals were recruited at Association of Surgical Technologists (AST) conferences, and using a targeted e-mail of AST members. Symbol presence, color coding and grouping critical pieces of information all significantly improved selection rates and sped time to correct selection (α = 0.05). Conversely, when critical information was graphically boxed, probability of correct selection and time to selection were impaired (α = 0.05). Subsequently, responses from trials containing optimal treatments (color coded, critical information grouped with symbols) were compared to two labels created based on a review of those commercially available. Optimal labels yielded a significant positive benefit regarding the probability of correct choice ((P<0.0001) LSM; UCL, LCL: 97.3%; 98.4%, 95.5%)), as compared to the two labels we created based on commercial designs (92.0%; 94.7%, 87.9% and 89.8%; 93.0%, 85.3%) and time to selection. Our study provides data regarding design factors, namely: color coding, symbol use and grouping of critical information that can be used to significantly enhance the performance of medical device labels.

Relationships among Behavioral Profiles, Reading Performance, and Disability Labels: A Latent Class Analysis of Students in the ED, LD, and OHI Special Education Categories

ERIC Educational Resources Information Center

Weingarten, Zachary

2018-01-01

The aim of this study was to explore the variation in student behavior across the ED, LD, and OHI disability categories and to examine demographic, behavioral, and academic factors that may place students at risk for negative outcomes. This study used teachers' rating of students' in-class behavior to identify latent classes of students in the ED,…

Physiological and morphological characterization of local interneurons in the Drosophila antennal lobe.

PubMed

Seki, Yoichi; Rybak, Jürgen; Wicher, Dieter; Sachse, Silke; Hansson, Bill S

2010-08-01

The Drosophila antennal lobe (AL) has become an excellent model for studying early olfactory processing mechanisms. Local interneurons (LNs) connect a large number of glomeruli and are ideally positioned to increase computational capabilities of odor information processing in the AL. Although the neural circuit of the Drosophila AL has been intensively studied at both the input and the output level, the internal circuit is not yet well understood. An unambiguous characterization of LNs is essential to remedy this lack of knowledge. We used whole cell patch-clamp recordings and characterized four classes of LNs in detail using electrophysiological and morphological properties at the single neuron level. Each class of LN displayed unique characteristics in intrinsic electrophysiological properties, showing differences in firing patterns, degree of spike adaptation, and amplitude of spike afterhyperpolarization. Notably, one class of LNs had characteristic burst firing properties, whereas the others were tonically active. Morphologically, neurons from three classes innervated almost all glomeruli, while LNs from one class innervated a specific subpopulation of glomeruli. Three-dimensional reconstruction analyses revealed general characteristics of LN morphology and further differences in dendritic density and distribution within specific glomeruli between the different classes of LNs. Additionally, we found that LNs labeled by a specific enhancer trap line (GAL4-Krasavietz), which had previously been reported as cholinergic LNs, were mostly GABAergic. The current study provides a systematic characterization of olfactory LNs in Drosophila and demonstrates that a variety of inhibitory LNs, characterized by class-specific electrophysiological and morphological properties, construct the neural circuit of the AL.

16 CFR 1500.123 - Condensation of label information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 16 Commercial Practices 2 2011-01-01 2011-01-01 false Condensation of label information. 1500.123 Section 1500.123 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL HAZARDOUS SUBSTANCES ACT... Condensation of label information. Whenever the statement of the principal hazard or hazards itself provides...

16 CFR 1500.123 - Condensation of label information.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 16 Commercial Practices 2 2014-01-01 2014-01-01 false Condensation of label information. 1500.123 Section 1500.123 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL HAZARDOUS SUBSTANCES ACT... Condensation of label information. Whenever the statement of the principal hazard or hazards itself provides...

16 CFR 1500.123 - Condensation of label information.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 2 2010-01-01 2010-01-01 false Condensation of label information. 1500.123 Section 1500.123 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL HAZARDOUS SUBSTANCES ACT... Condensation of label information. Whenever the statement of the principal hazard or hazards itself provides...

16 CFR 1500.123 - Condensation of label information.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 16 Commercial Practices 2 2012-01-01 2012-01-01 false Condensation of label information. 1500.123 Section 1500.123 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL HAZARDOUS SUBSTANCES ACT... Condensation of label information. Whenever the statement of the principal hazard or hazards itself provides...

Quantum dot bioconjugates for ultrasensitive nonisotopic detection.

PubMed

Chan, W C; Nie, S

1998-09-25

Highly luminescent semiconductor quantum dots (zinc sulfide-capped cadmium selenide) have been covalently coupled to biomolecules for use in ultrasensitive biological detection. In comparison with organic dyes such as rhodamine, this class of luminescent labels is 20 times as bright, 100 times as stable against photobleaching, and one-third as wide in spectral linewidth. These nanometer-sized conjugates are water-soluble and biocompatible. Quantum dots that were labeled with the protein transferrin underwent receptor-mediated endocytosis in cultured HeLa cells, and those dots that were labeled with immunomolecules recognized specific antibodies or antigens.

27 CFR 5.32 - Mandatory label information.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2014-04-01 2014-04-01 false Mandatory label information. 5.32 Section 5.32 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF THE TREASURY ALCOHOL LABELING AND ADVERTISING OF DISTILLED SPIRITS Labeling Requirements for...

Protein migration from transplanted nuclei in Amoeba proteus. I. The relation to the cell cycle and RNA migration, as studied by autoradiography

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

Mills, K.I.; Bell, L.G.

1982-11-01

Autoradiography has been used to examine the migration of proteins from a radioactivity labelled amoeba nucleus following transplantation into an unlabelled homophasic amoeba. Nuclei were transferred at three times in the cell cycle coinciding with DNA synthesis (4 h post-division); a peak of RNA synthesis (25 h); and a relative lull in synthetic activity (43 h). Six amino acids were added individually to the culture medium to label the nuclear proteins. Migration of the proteins from the donor nucleui and least with proteins labelled with the basic amino acids. All amino acids exhibited the greatest extent of migration following themore » 25-h transfers, i.e., coinciding with a peak of RNA synthesis at 26-27.5 h. Actinomycin D (actD) inhibition of RNA synthesis reduced, but did not eliminate the extent of protein migration from the transplanted nucleus, thus indicating the existence of two classes of migratory proteins. Firstly, proteins, associated with RNA transport, which migrated mainly into the host cytoplasm. The second class migrated into the host nucleus from the transplanted nucleus, irrespective of RNA synthesis. The shuttling character of the latter class of proteins is consistent with a role of regulation of nuclear activity.« less

Transportation of Hazardous Evidentiary Material.

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

Osborn, Douglas.

2005-06-01

This document describes the specimen and transportation containers currently available for use with hazardous and infectious materials. A detailed comparison of advantages, disadvantages, and costs of the different technologies is included. Short- and long-term recommendations are also provided.3 DraftDraftDraftExecutive SummaryThe Federal Bureau of Investigation's Hazardous Materials Response Unit currently has hazardous material transport containers for shipping 1-quart paint cans and small amounts of contaminated forensic evidence, but the containers may not be able to maintain their integrity under accident conditions or for some types of hazardous materials. This report provides guidance and recommendations on the availability of packages for themore » safe and secure transport of evidence consisting of or contaminated with hazardous chemicals or infectious materials. Only non-bulk containers were considered because these are appropriate for transport on small aircraft. This report will addresses packaging and transportation concerns for Hazardous Classes 3, 4, 5, 6, 8, and 9 materials. If the evidence is known or suspected of belonging to one of these Hazardous Classes, it must be packaged in accordance with the provisions of 49 CFR Part 173. The anthrax scare of several years ago, and less well publicized incidents involving unknown and uncharacterized substances, has required that suspicious substances be sent to appropriate analytical laboratories for analysis and characterization. Transportation of potentially hazardous or infectious material to an appropriate analytical laboratory requires transport containers that maintain both the biological and chemical integrity of the substance in question. As a rule, only relatively small quantities will be available for analysis. Appropriate transportation packaging is needed that will maintain the integrity of the substance, will not allow biological alteration, will not react chemically with the substance being shipped, and will otherwise maintain it as nearly as possible in its original condition.The recommendations provided are short-term solutions to the problems of shipping evidence, and have considered only currently commercially available containers. These containers may not be appropriate for all cases. Design, testing, and certification of new transportation containers would be necessary to provide a container appropriate for all cases.Table 1 provides a summary of the recommendations for each class of hazardous material.Table 1: Summary of RecommendationsContainerCost1-quart paint can with ArmlockTM seal ringLabelMaster(r)%242.90 eachHazard Class 3, 4, 5, 8, or 9 Small ContainersTC Hazardous Material Transport ContainerCurrently in Use4 DraftDraftDraftTable 1: Summary of Recommendations (continued)ContainerCost55-gallon open or closed-head steel drumsAll-Pak, Inc.%2458.28 - %2473.62 eachHazard Class 3, 4, 5, 8, or 9 Large Containers95-gallon poly overpack LabelMaster(r)%24194.50 each1-liter glass container with plastic coatingLabelMaster(r)%243.35 - %243.70 eachHazard Class 6 Division 6.1 Poisonous by Inhalation (PIH) Small ContainersTC Hazardous Material Transport ContainerCurrently in Use20 to 55-gallon PIH overpacksLabelMaster(r)%24142.50 - %24170.50 eachHazard Class 6 Division 6.1 Poisonous by Inhalation (PIH) Large Containers65 to 95-gallon poly overpacksLabelMaster(r)%24163.30 - %24194.50 each1-liter transparent containerCurrently in UseHazard Class 6 Division 6.2 Infectious Material Small ContainersInfectious Substance ShipperSource Packaging of NE, Inc.%24336.00 eachNone Commercially AvailableN/AHazard Class 6 Division 6.2 Infectious Material Large ContainersNone Commercially Available N/A5« less

Consumer use and understanding of labelling information on edible marijuana products sold for recreational use in the states of Colorado and Washington.

PubMed

Kosa, Katherine M; Giombi, Kristen C; Rains, Caroline B; Cates, Sheryl C

2017-05-01

In 2014, the states of Colorado and Washington began allowing retail sales of marijuana for recreational use. The regulatory agencies in these states have implemented specific labelling requirements for edible marijuana products sold for recreational use to help address concerns such as delayed activation time, accidental ingestion, and proper dosing. We conducted 12 focus groups with 94 adult consumers and nonconsumers of edibles in Denver and Seattle to collect information on their use and understanding of labelling information on edible marijuana products sold for recreational use. Specifically, we asked participants about the usefulness, attractiveness, ease of comprehension, relevancy, and acceptability of the label information. Some focus group participants look for and read specific information, such as the potency profile and serving size statement, but do not read or were unfamiliar with other labelling features. The focus groups revealed that participants have some concerns about the current labelling of edibles. In particular, participants were concerned that there is too much information on the labels so consumers may not read the label, there is no obvious indication that the product contains marijuana (e.g., a Universal Symbol), and the information on consumption advice is not clear. Participants in both locations suggested that education in a variety of formats, such as web- and video-based education, would be useful in informing consumers about the possible risks of edibles. The focus group findings suggest that improvements are needed in the labelling of edibles to prevent unintentional ingestion among adult nonusers and help ensure proper dosing and safe consumption among adult users. These findings, along with lessons learned from Colorado and Washington, can help inform the labelling of edibles as additional states allow the sale of edibles for recreational use. Copyright © 2017 Elsevier B.V. All rights reserved.

Joint deconvolution and classification with applications to passive acoustic underwater multipath.

PubMed

Anderson, Hyrum S; Gupta, Maya R

2008-11-01

This paper addresses the problem of classifying signals that have been corrupted by noise and unknown linear time-invariant (LTI) filtering such as multipath, given labeled uncorrupted training signals. A maximum a posteriori approach to the deconvolution and classification is considered, which produces estimates of the desired signal, the unknown channel, and the class label. For cases in which only a class label is needed, the classification accuracy can be improved by not committing to an estimate of the channel or signal. A variant of the quadratic discriminant analysis (QDA) classifier is proposed that probabilistically accounts for the unknown LTI filtering, and which avoids deconvolution. The proposed QDA classifier can work either directly on the signal or on features whose transformation by LTI filtering can be analyzed; as an example a classifier for subband-power features is derived. Results on simulated data and real Bowhead whale vocalizations show that jointly considering deconvolution with classification can dramatically improve classification performance over traditional methods over a range of signal-to-noise ratios.

Best practices for developmental toxicity assessment for classification and labeling.

PubMed

Daston, George; Piersma, Aldert; Attias, Leonello; Beekhuijzen, Manon; Chen, Connie; Foreman, Jennifer; Hallmark, Nina; Leconte, Isabelle

2018-05-14

Many chemicals are going through a hazard-based classification and labeling process in Europe. Because of the significant public health implications, the best science must be applied in assessing developmental toxicity data. The European Teratology Society and Health and Environmental Sciences Institute co-organized a workshop to consider best practices, including data quality and consistency, interpretation of developmental effects in the presence of maternal toxicity, human relevance of animal data, and limits of chemical classes. Recommendations included larger historical control databases, more pharmacokinetic studies in pregnant animals for dose setting and study interpretation, generation of mechanistic data to resolve questions about whether maternal toxicity is causative of developmental toxicity, and more rigorous specifications for what constitutes a chemical class. It is our hope that these recommendations will form the basis for subsequent consensus workshops and other scientific activities designed to improve the scientific robustness of data interpretation for classification and labeling. Copyright © 2018 Elsevier Inc. All rights reserved.

Weight information labels on media models reduce body dissatisfaction in adolescent girls.

PubMed

Veldhuis, Jolanda; Konijn, Elly A; Seidell, Jacob C

2012-06-01

To examine how weight information labels on variously sized media models affect (pre)adolescent girls' body perceptions and how they compare themselves with media models. We used a three (body shape: extremely thin vs. thin vs. normal weight) × three (information label: 6-kg underweight vs. 3-kg underweight vs. normal weight) experimental design in three age-groups (9-10 years, 12-13 years, and 15-16 years; n = 184). The girls completed questionnaires after exposure to media models. Weight information labels affected girls' body dissatisfaction, social comparison with media figures, and objectified body consciousness. Respondents exposed to an extremely thin body shape labeled to be of "normal weight" were most dissatisfied with their own bodies and showed highest levels of objectified body consciousness and comparison with media figures. An extremely thin body shape combined with a corresponding label (i.e., 6-kg underweight), however, induced less body dissatisfaction and less comparison with the media model. Age differences were also found to affect body perceptions: adolescent girls showed more negative body perceptions than preadolescents. Weight information labels may counteract the generally media-induced thin-body ideal. That is, when the weight labels appropriately informed the respondents about the actual thinness of the media model's body shape, girls were less affected. Weight information labels also instigated a normalization effect when a "normal-weight" label was attached to underweight-sized media models. Presenting underweight as a normal body shape, clearly increased body dissatisfaction in girls. Results also suggest age between preadolescence and adolescence as a critical criterion in responding to media models' body shape. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

16 CFR 300.10 - Disclosure of information on labels.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 16 Commercial Practices 1 2011-01-01 2011-01-01 false Disclosure of information on labels. 300.10 Section 300.10 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS RULES AND REGULATIONS UNDER THE WOOL PRODUCTS LABELING ACT OF 1939 Labeling § 300.10 Disclosure of...

27 CFR 4.32 - Mandatory label information.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2014-04-01 2014-04-01 false Mandatory label information. 4.32 Section 4.32 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF THE TREASURY ALCOHOL LABELING AND ADVERTISING OF WINE Labeling Requirements for Wine § 4.32...

27 CFR 4.32 - Mandatory label information.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 27 Alcohol, Tobacco Products and Firearms 1 2013-04-01 2013-04-01 false Mandatory label information. 4.32 Section 4.32 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF THE TREASURY ALCOHOL LABELING AND ADVERTISING OF WINE Labeling Requirements for Wine § 4.32...

77 FR 74827 - Working Group on Access to Information on Prescription Drug Container Labels

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-18

... on Prescription Drug Container Labels AGENCY: Architectural and Transportation Barriers Compliance... information on prescription drug container labels accessible to people who are blind or visually impaired. The... stakeholder working group to develop best practices for making information on prescription drug container...

27 CFR 4.38 - General requirements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... mandatory information required on labels by this part, except the alcoholic content statement, shall be in... OF THE TREASURY LIQUORS LABELING AND ADVERTISING OF WINE Labeling Requirements for Wine § 4.38... descriptive or explanatory information, the script, type, or printing of the mandatory information shall be of...

Dissemination of information on the off-label (unapproved) use of medication: a comparative analysis.

PubMed

Jansen, Rita-Marié

2011-03-01

"Off-label" in relation to the use of medication means that a medicine is used in another way or for indications other than those specified in its conditions of registration and reflected in its labelling. The off-label use of medication accounts for an estimated 21 per cent of drug use overall and is an important part of mainstream, legitimate medical practice worldwide. In South Africa, legislation prohibits the dissemination of information regarding the off-label use of medication. There are diverging views on whether pharmaceutical companies should be allowed to distribute scientific publications on off-label uses of approved drugs. Current policy in the United States of America (USA) eases restrictions on the dissemination of information of this nature. The prohibitions existing in South Africa, however, are more comparable with those in European countries. After analysing the different legal positions on the issue, it is submitted that pharmaceutical companies should not be allowed to disseminate information on off-label uses, but that the regulatory authority play an active and leading role in providing the latest, objective medical and scientific information, as well as guidelines on the off-label use of medication. Other related recommendations are also made.

Do nutrition labels improve dietary outcomes?

PubMed

Variyam, Jayachandran N

2008-06-01

The disclosure of nutritional characteristics of most packaged foods became mandatory in the United States with the implementation of the Nutrition Labeling and Education Act (NLEA) in 1994. Under the NLEA regulations, a 'Nutrition Facts' panel displays information on nutrients such as calories, total and saturated fats, cholesterol, and sodium in a standardized format. By providing nutrition information in a credible, distinctive, and easy-to-read format, the new label was expected to help consumers choose healthier, more nutritious diets. This paper examines whether the disclosure of nutrition information through the mandatory labels impacted consumer diets. Assessing the dietary effects of labeling is problematic due to the confounding of the label effect with unobserved label user characteristics. This self-selection problem is addressed by exploiting the fact that the NLEA exempts away-from-home foods from mandatory labeling. Difference-in-differences models that account for zero away-from-home intakes suggest that the labels increase fiber and iron intakes of label users compared with label nonusers. In comparison, a model that does not account for self-selection implies significant label effects for all but two of the 13 nutrients that are listed on the label.

Latent typologies of posttraumatic stress disorder in World Trade Center responders.

PubMed

Horn, Sarah R; Pietrzak, Robert H; Schechter, Clyde; Bromet, Evelyn J; Katz, Craig L; Reissman, Dori B; Kotov, Roman; Crane, Michael; Harrison, Denise J; Herbert, Robin; Luft, Benjamin J; Moline, Jacqueline M; Stellman, Jeanne M; Udasin, Iris G; Landrigan, Philip J; Zvolensky, Michael J; Southwick, Steven M; Feder, Adriana

2016-12-01

Posttraumatic stress disorder (PTSD) is a debilitating and often chronic psychiatric disorder. Following the 9/11/2001 World Trade Center (WTC) attacks, thousands of individuals were involved in rescue, recovery and clean-up efforts. While a growing body of literature has documented the prevalence and correlates of PTSD in WTC responders, no study has evaluated predominant typologies of PTSD in this population. Participants were 4352 WTC responders with probable WTC-related DSM-IV PTSD. Latent class analyses were conducted to identify predominant typologies of PTSD symptoms and associated correlates. A 3-class solution provided the optimal representation of latent PTSD symptom typologies. The first class, labeled "High-Symptom (n = 1,973, 45.3%)," was characterized by high probabilities of all PTSD symptoms. The second class, "Dysphoric (n = 1,371, 31.5%)," exhibited relatively high probabilities of emotional numbing and dysphoric arousal (e.g., sleep disturbance). The third class, "Threat (n = 1,008, 23.2%)," was characterized by high probabilities of re-experiencing, avoidance and anxious arousal (e.g., hypervigilance). Compared to the Threat class, the Dysphoric class reported a greater number of life stressors after 9/11/2001 (OR = 1.06). The High-Symptom class was more likely than the Threat class to have a positive psychiatric history before 9/11/2001 (OR = 1.7) and reported a greater number of life stressors after 9/11/2001 (OR = 1.1). The High-Symptom class was more likely than the Dysphoric class, which was more likely than the Threat class, to screen positive for depression (83% > 74% > 53%, respectively), and to report greater functional impairment (High-Symptom > Dysphoric [Cohen d = 0.19], Dysphoric > Threat [Cohen d = 0.24]). These results may help inform assessment, risk stratification, and treatment approaches for PTSD in WTC and disaster responders. Copyright © 2016 Elsevier Ltd. All rights reserved.

Inferring product healthfulness from nutrition labelling. The influence of reference points.

PubMed

van Herpen, Erica; Hieke, Sophie; van Trijp, Hans C M

2014-01-01

Despite considerable research on nutrition labelling, it has proven difficult to find a front-of-pack label which is informative about product healthfulness across various situations. This study examines the ability of different types of nutrition labelling schemes (multiple traffic light label, nutrition table, GDA, logo) to communicate product healthfulness (a) across different product categories, (b) between options from the same product category, and (c) when viewed in isolation and in comparison with another product. Results of two experiments in Germany and The Netherlands show that a labelling scheme with reference point information at the nutrient level (e.g., the traffic light label) can achieve all three objectives. Although other types of labelling schemes are also capable of communicating healthfulness, labelling schemes lacking reference point information (e.g., nutrition tables) are less effective when no comparison product is available, and labelling schemes based on overall product healthfulness within the category (e.g., logos) can diminish consumers' ability to differentiate between categories, leading to a potential misinterpretation of product healthfulness. None of the labels affected food preferences.

Inferring Product Healthfulness from Nutrition Labelling: The Influence of Reference Points.

PubMed

Herpen, Erica van; Hieke, Sophie; van Trijp, Hans C M

2013-10-25

Despite considerable research on nutrition labelling, it has proven difficult to find a front-of-pack label which is informative about product healthfulness across various situations. This study examines the ability of different types of nutrition labelling schemes (multiple traffic light label, nutrition table, GDA, logo) to communicate product healthfulness (a) across different product categories, (b) between options from the same product category, and (c) when viewed in isolation and in comparison with another product. Results of two experiments in Germany and The Netherlands show that a labelling scheme with reference point information at the nutrient level (e.g., the traffic light label) can achieve all three objectives. Although other types of labelling schemes are also capable of communicating healthfulness, labelling schemes lacking reference point information (e.g., nutrition tables) are less effective when no comparison product is available, and labelling schemes based on overall product healthfulness within the category (e.g., logos) can diminish consumers' ability to differentiate between categories, leading to a potential misinterpretation of product healthfulness. None of the labels affected food preferences. Copyright © 2013. Published by Elsevier Ltd.

A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data.

PubMed

Zheng, Yin; Zhang, Yu-Jin; Larochelle, Hugo

2016-06-01

Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to deal with multimodal data, such as in image annotation tasks. Another popular approach to model the multimodal data is through deep neural networks, such as the deep Boltzmann machine (DBM). Recently, a new type of topic model called the Document Neural Autoregressive Distribution Estimator (DocNADE) was proposed and demonstrated state-of-the-art performance for text document modeling. In this work, we show how to successfully apply and extend this model to multimodal data, such as simultaneous image classification and annotation. First, we propose SupDocNADE, a supervised extension of DocNADE, that increases the discriminative power of the learned hidden topic features and show how to employ it to learn a joint representation from image visual words, annotation words and class label information. We test our model on the LabelMe and UIUC-Sports data sets and show that it compares favorably to other topic models. Second, we propose a deep extension of our model and provide an efficient way of training the deep model. Experimental results show that our deep model outperforms its shallow version and reaches state-of-the-art performance on the Multimedia Information Retrieval (MIR) Flickr data set.

A Generalized Mixture Framework for Multi-label Classification

PubMed Central

Hong, Charmgil; Batal, Iyad; Hauskrecht, Milos

2015-01-01

We develop a novel probabilistic ensemble framework for multi-label classification that is based on the mixtures-of-experts architecture. In this framework, we combine multi-label classification models in the classifier chains family that decompose the class posterior distribution P(Y1, …, Yd|X) using a product of posterior distributions over components of the output space. Our approach captures different input–output and output–output relations that tend to change across data. As a result, we can recover a rich set of dependency relations among inputs and outputs that a single multi-label classification model cannot capture due to its modeling simplifications. We develop and present algorithms for learning the mixtures-of-experts models from data and for performing multi-label predictions on unseen data instances. Experiments on multiple benchmark datasets demonstrate that our approach achieves highly competitive results and outperforms the existing state-of-the-art multi-label classification methods. PMID:26613069

Dietary Supplement Label Database (DSLD)

Science.gov Websites

Intakes (DRIs) Definitions Frequently Asked Questions (FAQ) Information Sources Release Notes Help Search full label derived information from dietary supplement products marketed in the U.S. with a Web-based user interface that provides ready access to label information. It was developed to serve the research

16 CFR § 1500.123 - Condensation of label information.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 16 Commercial Practices 2 2013-01-01 2013-01-01 false Condensation of label information. § 1500.123 Section § 1500.123 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL HAZARDOUS... § 1500.123 Condensation of label information. Whenever the statement of the principal hazard or hazards...

77 FR 42502 - Agency Information Collection Activities; Announcement of Office of Management and Budget...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-19

...; Survey of ``Health Care Providers' Responses to Medical Device Labeling'' AGENCY: Food and Drug... collection of information entitled Survey of ``Health Care Providers' Responses to Medical Device Labeling... of information entitled Survey of ``Health Care Providers' Responses to Medical Device Labeling'' to...

Label Review Training: Module 1: Label Basics, Page 21

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Learn about types of labels.

A Multi-modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling.

PubMed

Asif, Umar; Bennamoun, Mohammed; Sohel, Ferdous

2017-08-30

While deep convolutional neural networks have shown a remarkable success in image classification, the problems of inter-class similarities, intra-class variances, the effective combination of multimodal data, and the spatial variability in images of objects remain to be major challenges. To address these problems, this paper proposes a novel framework to learn a discriminative and spatially invariant classification model for object and indoor scene recognition using multimodal RGB-D imagery. This is achieved through three postulates: 1) spatial invariance - this is achieved by combining a spatial transformer network with a deep convolutional neural network to learn features which are invariant to spatial translations, rotations, and scale changes, 2) high discriminative capability - this is achieved by introducing Fisher encoding within the CNN architecture to learn features which have small inter-class similarities and large intra-class compactness, and 3) multimodal hierarchical fusion - this is achieved through the regularization of semantic segmentation to a multi-modal CNN architecture, where class probabilities are estimated at different hierarchical levels (i.e., imageand pixel-levels), and fused into a Conditional Random Field (CRF)- based inference hypothesis, the optimization of which produces consistent class labels in RGB-D images. Extensive experimental evaluations on RGB-D object and scene datasets, and live video streams (acquired from Kinect) show that our framework produces superior object and scene classification results compared to the state-of-the-art methods.

Competition-based cellular peptide binding assays for 13 prevalent HLA class I alleles using fluorescein-labeled synthetic peptides.

PubMed

Kessler, Jan H; Mommaas, Bregje; Mutis, Tuna; Huijbers, Ivo; Vissers, Debby; Benckhuijsen, Willemien E; Schreuder, Geziena M Th; Offringa, Rienk; Goulmy, Els; Melief, Cornelis J M; van der Burg, Sjoerd H; Drijfhout, Jan W

2003-02-01

We report the development, validation, and application of competition-based peptide binding assays for 13 prevalent human leukocyte antigen (HLA) class I alleles. The assays are based on peptide binding to HLA molecules on living cells carrying the particular allele. Competition for binding between the test peptide of interest and a fluorescein-labeled HLA class I binding peptide is used as read out. The use of cell membrane-bound HLA class I molecules circumvents the need for laborious biochemical purification of these molecules in soluble form. Previously, we have applied this principle for HLA-A2 and HLA-A3. We now describe the assays for HLA-A1, HLA-A11, HLA-A24, HLA-A68, HLA-B7, HLA-B8, HLA-B14, HLA-B35, HLA-B60, HLA-B61, and HLA-B62. Together with HLA-A2 and HLA-A3, these alleles cover more than 95% of the Caucasian population. Several allele-specific parameters were determined for each assay. Using these assays, we identified novel HLA class I high-affinity binding peptides from HIVpol, p53, PRAME, and minor histocompatibility antigen HA-1. Thus these convenient and accurate peptide-binding assays will be useful for the identification of putative cytotoxic T lymphocyte epitopes presented on a diverse array of HLA class I molecules.

Automated grading of lumbar disc degeneration via supervised distance metric learning

NASA Astrophysics Data System (ADS)

He, Xiaoxu; Landis, Mark; Leung, Stephanie; Warrington, James; Shmuilovich, Olga; Li, Shuo

2017-03-01

Lumbar disc degeneration (LDD) is a commonly age-associated condition related to low back pain, while its consequences are responsible for over 90% of spine surgical procedures. In clinical practice, grading of LDD by inspecting MRI is a necessary step to make a suitable treatment plan. This step purely relies on physicians manual inspection so that it brings the unbearable tediousness and inefficiency. An automated method for grading of LDD is highly desirable. However, the technical implementation faces a big challenge from class ambiguity, which is typical in medical image classification problems with a large number of classes. This typical challenge is derived from the complexity and diversity of medical images, which lead to a serious class overlapping and brings a great challenge in discriminating different classes. To solve this problem, we proposed an automated grading approach, which is based on supervised distance metric learning to classify the input discs into four class labels (0: normal, 1: slight, 2: marked, 3: severe). By learning distance metrics from labeled instances, an optimal distance metric is modeled and with two attractive advantages: (1) keeps images from the same classes close, and (2) keeps images from different classes far apart. The experiments, performed in 93 subjects, demonstrated the superiority of our method with accuracy 0.9226, sensitivity 0.9655, specificity 0.9083, F-score 0.8615. With our approach, physicians will be free from the tediousness and patients will be provided an effective treatment.

Label Review Training: Module 1: Label Basics, Page 20

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. This section focuses on supplemental labeling.

Label Review Training: Module 1: Label Basics, Page 22

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Learn about what labels require review.

Label Review Training: Module 1: Label Basics, Page 18

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. This section discusses the types of labels.

Label Review Training: Module 1: Label Basics, Page 26

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Learn about mandatory and advisory label statements.

Label Review Training: Module 1: Label Basics, Page 19

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. This section covers supplemental distributor labeling.

Label Review Training: Module 1: Label Basics, Page 15

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Learn about the consequences of improper labeling.

Label Review Training: Module 1: Label Basics, Page 14

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Learn about positive effects from proper labeling.

College Students Must Overcome Barriers to Use Calorie Labels in Fast-Food Restaurants.

PubMed

Stran, Kimberly A; Knol, Linda L; Turner, Lori W; Severt, Kimberly; McCallum, Debra M; Lawrence, Jeannine C

2016-02-01

To explore predictors of intention of college students to use calorie labels on fast-food menus and differences in calories ordered after viewing calorie information. Quasi-experimental design. Participants selected a meal from a menu without calorie labels, selected a meal from the same menu with calorie labels, and completed a survey that assessed demographics, dietary habits, Theory of Planned Behavior constructs, and potential barriers to use of calorie labeling. A southern university. Undergraduate university students (n = 97). Predictors of intention to use calorie labels and whether calories selected from the nonlabeled menu differed from the labeled menu. Confirmatory factor analysis, exploratory factor analysis, multiple regression, and paired t tests. Participants ordered significantly fewer calories (P = .02) when selecting from the labeled menu vs the menu without labels. Attitudes (P = .006), subjective norms (P < .001), and perceived behavioral control (P = .01) predicted intention to use calorie information but did not predict a difference in the calories ordered. Hunger (P = .03) and cost (P = .04) were barriers to using the calorie information. If students can overcome barriers, calorie labeling could provide information that college students need to select lower-calorie items at fast-food restaurants. Copyright © 2016 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Data Mining and Visualization of Twin-Cities Traffic Data

DTIC Science & Technology

2001-03-08

Ramsey I W Q Ramsey Table The...using the n attributes in the data set The class models are then used to classify test set which the class labels are not provided A decisiontree...interval for January while the testing set is the trac ow on January The training accuracy is and testing accuracy is The

27 CFR 5.35 - Class and type.

Code of Federal Regulations, 2010 CFR

2010-04-01

... of whiskies in mixtures. In the case of any of the types of whisky defined in § 5.22(b), Class 2, which contains any whisky or whiskies produced in a country other than that indicated by the type designation, there shall be stated on the brand label the percentage of such whisky and the country or origin...

27 CFR 5.35 - Class and type.

Code of Federal Regulations, 2011 CFR

2011-04-01

... of whiskies in mixtures. In the case of any of the types of whisky defined in § 5.22(b), Class 2, which contains any whisky or whiskies produced in a country other than that indicated by the type designation, there shall be stated on the brand label the percentage of such whisky and the country or origin...

Clinically relevant safety issues associated with St. John's wort product labels.

PubMed

Clauson, Kevin A; Santamarina, Marile L; Rutledge, Jennifer C

2008-07-17

St. John's wort (SJW), used to treat depression, is popular in the USA, Canada, and parts of Europe. However, there are documented interactions between SJW and prescription medications including warfarin, cyclosporine, indinavir, and oral contraceptives. One source of information about these safety considerations is the product label. The aim of this study was to evaluate the clinically relevant safety information included on labeling in a nationally representative sample of SJW products from the USA. Eight clinically relevant safety issues were identified: drug interactions (SJW-HIV medications, SJW-immunosupressants, SJW-oral contraceptives, and SJW-warfarin), contraindications (bipolar disorder), therapeutic duplication (antidepressants), and general considerations (phototoxicity and advice to consult a healthcare professional (HCP)). A list of SJW products was identified to assess their labels. Percentages and totals were used to present findings. Of the seventy-four products evaluated, no product label provided information for all 8 evaluation criteria. Three products (4.1%) provided information on 7 of the 8 criteria. Four products provided no safety information whatsoever. Percentage of products with label information was: SJW-HIV (8.1%), SJW-immunosupressants (5.4%), SJW-OCPs (8.1%), SJW-warfarin (5.4%), bipolar (1.4%), antidepressants (23.0%), phototoxicity (51.4%), and consult HCP (87.8%). Other safety-related information on labels included warnings about pregnancy (74.3%), lactation (64.9%), discontinue if adverse reaction (23.0%), and not for use in patients under 18 years old (13.5%). The average number of a priori safety issues included on a product label was 1.91 (range 0-8) for 23.9% completeness. The vast majority of SJW products fail to adequately address clinically relevant safety issues on their labeling. A few products do provide an acceptable amount of information on clinically relevant safety issues which could enhance the quality of counseling by HCPs and health store clerks. HCPs and consumers may benefit if the FDA re-examined labeling requirements for dietary supplements.

Clinically relevant safety issues associated with St. John's wort product labels

PubMed Central

Clauson, Kevin A; Santamarina, Marile L; Rutledge, Jennifer C

2008-01-01

Background St. John's wort (SJW), used to treat depression, is popular in the USA, Canada, and parts of Europe. However, there are documented interactions between SJW and prescription medications including warfarin, cyclosporine, indinavir, and oral contraceptives. One source of information about these safety considerations is the product label. The aim of this study was to evaluate the clinically relevant safety information included on labeling in a nationally representative sample of SJW products from the USA. Methods Eight clinically relevant safety issues were identified: drug interactions (SJW-HIV medications, SJW-immunosupressants, SJW-oral contraceptives, and SJW-warfarin), contraindications (bipolar disorder), therapeutic duplication (antidepressants), and general considerations (phototoxicity and advice to consult a healthcare professional (HCP)). A list of SJW products was identified to assess their labels. Percentages and totals were used to present findings. Results Of the seventy-four products evaluated, no product label provided information for all 8 evaluation criteria. Three products (4.1%) provided information on 7 of the 8 criteria. Four products provided no safety information whatsoever. Percentage of products with label information was: SJW-HIV (8.1%), SJW-immunosupressants (5.4%), SJW-OCPs (8.1%), SJW-warfarin (5.4%), bipolar (1.4%), antidepressants (23.0%), phototoxicity (51.4%), and consult HCP (87.8%). Other safety-related information on labels included warnings about pregnancy (74.3%), lactation (64.9%), discontinue if adverse reaction (23.0%), and not for use in patients under 18 years old (13.5%). The average number of a priori safety issues included on a product label was 1.91 (range 0–8) for 23.9% completeness. Conclusion The vast majority of SJW products fail to adequately address clinically relevant safety issues on their labeling. A few products do provide an acceptable amount of information on clinically relevant safety issues which could enhance the quality of counseling by HCPs and health store clerks. HCPs and consumers may benefit if the FDA re-examined labeling requirements for dietary supplements. PMID:18637192

Assessment of self-reporting reading of medicine's labels and the resources of information about medicines in general public in Malaysia.

PubMed

Dawood, Omar T; Hassali, Mohamed A; Saleem, Fahad; Ibrahim, Inas R

2018-04-01

This study was undertaken to assess the people's self-reported reading of medicine labels and its associated factors and to assess the sources of information about medicines among general public. A cross-sectional study was carried out among general public in the State of Penang, Malaysia. A total of 888 participants were conveniently selected and completed the survey. A self-administered questionnaire was used to obtain the data from all the participants. Most of the participants (74.2%) reported that they have adequate information about medicines provided on their medicine labels. In addition, 86.9% of them reported that they read their medicine's label for the directions of usage and 84.3% for the dosage instruction. However, 42.1% of the participants do not read their medicine's label for the active ingredients, and 33% of them do not read their medicine's label for the safety information. In addition, 36.5% of the respondents did not read the label of medicine for the symptoms which can be used for. However, females, Malay respondents, and higher education level (college/university) were more likely to self-reported the reading medicine's label. Females were more likely to read the labels of medicines compared with males (OR = 1.6, 95% CI 1.20-2.13, P  = .001). The reading of medicine labels was predicted by females, Malay respondents, and higher educated people. Health educational programs are needed to clarify label's information that can help in concept of patient safety.

The influence of calorie and physical activity labelling on snack and beverage choices.

PubMed

Masic, U; Christiansen, P; Boyland, E J

2017-05-01

Much research suggests nutrition labelling does not influence lower energy food choice. This study aimed to assess the impact of physical activity based and kilocalorie (Kcal) based labels on the energy content of snack food and beverage choices made. An independent-groups design, utilizing an online questionnaire platform tested 458 UK adults (87 men), aged 18-64 years (mean: 30 years) whose BMI ranged from 16 to 41 kg/m 2 (mean: 24 kg/m 2 ). Participants were randomized to one of four label information conditions (no label, Kcal label, physical activity label [duration of walking required to burn the Kcal in the product], Kcal and physical activity label) and were asked to choose from higher and lower energy options for a series of items. Label condition significantly affected low vs. high-energy product selection of snack foods (p < 0.001) and beverages (p < 0.001). The physical activity label condition resulted in significantly lower energy snack and beverage choices than the Kcal label condition (p < 0.001). This effect was found across the full sample and persisted even when participants' dietary restraint, BMI, gender, socioeconomic status, habitual physical activity, calorie and numerical literacy were controlled. The provision of physical activity information appeared most effective in influencing the selection of lower Kcal snack food and beverage items, when compared with no information or Kcal information. These findings could inform the debate around potential legislative policies to facilitate healthier nutritional choices at a population level. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Penetration of nutrition information on food labels across the EU-27 plus Turkey

PubMed Central

Storcksdieck genannt Bonsmann, S; Celemín, L Fernández; Larrañaga, A; Egger, S; Wills, J M; Hodgkins, C; Raats, M M

2010-01-01

Objectives: The European Union (EU)-funded project Food Labelling to Advance Better Education for Life (FLABEL) aims to understand how nutrition information on food labels affects consumers' dietary choices and shopping behaviour. The first phase of this study consisted of assessing the penetration of nutrition labelling and related information on various food products in all 27 EU Member States and Turkey. Methods: In each country, food products were audited in three different types of retailers to cover as many different products as possible within five food and beverage categories: sweet biscuits, breakfast cereals, pre-packed chilled ready meals, carbonated soft drinks and yoghurts. Results: More than 37 000 products were audited in a total of 84 retail stores. On average, 85% of the products contained back-of-pack (BOP) nutrition labelling or related information (from 70% in Slovenia to 97% in Ireland), versus 48% for front-of-pack (FOP) information (from 24% in Turkey to 82% in the UK). The most widespread format was the BOP tabular or linear listing of nutrition content. Guideline daily amounts labelling was the most prevalent form of FOP information, showing an average penetration of 25% across all products audited. Among categories, breakfast cereals showed the highest penetration of nutrition-related information, with 94% BOP penetration and 70% FOP penetration. Conclusions: Nutrition labelling and related information was found on a large majority of products audited. These findings provide the basis for subsequent phases of FLABEL involving attention, reading, liking, understanding and use by consumers of different nutrition labelling formats. PMID:20808336

Know thy enemy: Education about terrorism improves social attitudes toward terrorists.

PubMed

Theriault, Jordan; Krause, Peter; Young, Liane

2017-03-01

Hatred of terrorists is an obstacle to the implementation of effective counterterrorism policies-it invites indiscriminate retaliation, whereas many of the greatest successes in counterterrorism have come from understanding terrorists' personal and political motivations. Drawing from psychological research, traditional prejudice reduction strategies are generally not well suited to the task of reducing hatred of terrorists. Instead, in 2 studies, we explored education's potential ability to reduce extreme negative attitudes toward terrorists. Study 1 compared students in a college course on terrorism (treatment) with wait-listed students, measuring prosocial attitudes toward a hypothetical terrorist. Initially, all students reported extremely negative attitudes; however, at the end of the semester, treatment students' attitudes were significantly improved. Study 2 replicated the effect within a sample of treatment and control classes drawn from universities across the United States. The present work was part of an ongoing research project, focusing on foreign policy and the perceived threat of terrorism; thus classes did not explicitly aim to reduce prejudice, making the effect of treatment somewhat surprising. One possibility is that learning about terrorists "crowds out" the initial pejorative associations-that is, the label terrorism may ultimately call more information to mind, diluting its initial negative associative links. Alternatively, students may learn to challenge how the label terrorist is being applied. In either case, learning about terrorism can decrease the extreme negative reactions it evokes, which is desirable if one wishes to implement effective counterterrorism policies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An Improvement To The k-Nearest Neighbor Classifier For ECG Database

NASA Astrophysics Data System (ADS)

Jaafar, Haryati; Hidayah Ramli, Nur; Nasir, Aimi Salihah Abdul

2018-03-01

The k nearest neighbor (kNN) is a non-parametric classifier and has been widely used for pattern classification. However, in practice, the performance of kNN often tends to fail due to the lack of information on how the samples are distributed among them. Moreover, kNN is no longer optimal when the training samples are limited. Another problem observed in kNN is regarding the weighting issues in assigning the class label before classification. Thus, to solve these limitations, a new classifier called Mahalanobis fuzzy k-nearest centroid neighbor (MFkNCN) is proposed in this study. Here, a Mahalanobis distance is applied to avoid the imbalance of samples distribition. Then, a surrounding rule is employed to obtain the nearest centroid neighbor based on the distributions of training samples and its distance to the query point. Consequently, the fuzzy membership function is employed to assign the query point to the class label which is frequently represented by the nearest centroid neighbor Experimental studies from electrocardiogram (ECG) signal is applied in this study. The classification performances are evaluated in two experimental steps i.e. different values of k and different sizes of feature dimensions. Subsequently, a comparative study of kNN, kNCN, FkNN and MFkCNN classifier is conducted to evaluate the performances of the proposed classifier. The results show that the performance of MFkNCN consistently exceeds the kNN, kNCN and FkNN with the best classification rates of 96.5%.

Spectral-Spatial Classification of Hyperspectral Images Using Hierarchical Optimization

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new spectral-spatial method for hyperspectral data classification is proposed. For a given hyperspectral image, probabilistic pixelwise classification is first applied. Then, hierarchical step-wise optimization algorithm is performed, by iteratively merging neighboring regions with the smallest Dissimilarity Criterion (DC) and recomputing class labels for new regions. The DC is computed by comparing region mean vectors, class labels and a number of pixels in the two regions under consideration. The algorithm is converged when all the pixels get involved in the region merging procedure. Experimental results are presented on two remote sensing hyperspectral images acquired by the AVIRIS and ROSIS sensors. The proposed approach improves classification accuracies and provides maps with more homogeneous regions, when compared to previously proposed classification techniques.

Pharmacogenomic Biomarkers: an FDA Perspective on Utilization in Biological Product Labeling.

PubMed

Schuck, Robert N; Grillo, Joseph A

2016-05-01

Precision medicine promises to improve both the efficacy and safety of therapeutic products by better informing why some patients respond well to a drug, and some experience adverse reactions, while others do not. Pharmacogenomics is a key component of precision medicine and can be utilized to select optimal doses for patients, more precisely identify individuals who will respond to a treatment and avoid serious drug-related toxicities. Since pharmacogenomic biomarker information can help inform drug dosing, efficacy, and safety, pharmacogenomic data are critically reviewed by FDA staff to ensure effective use of pharmacogenomic strategies in drug development and appropriate incorporation into product labels. Pharmacogenomic information may be provided in drug or biological product labeling to inform health care providers about the impact of genotype on response to a drug through description of relevant genomic markers, functional effects of genomic variants, dosing recommendations based on genotype, and other applicable genomic information. The format and content of labeling for biologic drugs will generally follow that of small molecule drugs; however, there are notable differences in pharmacogenomic information that might be considered useful for biologic drugs in comparison to small molecule drugs. Furthermore, the rapid entry of biologic drugs for treatment of rare genetic diseases and molecularly defined subsets of common diseases will likely lead to increased use of pharmacogenomic information in biologic drug labels in the near future. In this review, we outline the general principles of therapeutic product labeling and discuss the utilization of pharmacogenomic information in biologic drug labels.

Building rooftop classification using random forests for large-scale PV deployment

NASA Astrophysics Data System (ADS)

Assouline, Dan; Mohajeri, Nahid; Scartezzini, Jean-Louis

2017-10-01

Large scale solar Photovoltaic (PV) deployment on existing building rooftops has proven to be one of the most efficient and viable sources of renewable energy in urban areas. As it usually requires a potential analysis over the area of interest, a crucial step is to estimate the geometric characteristics of the building rooftops. In this paper, we introduce a multi-layer machine learning methodology to classify 6 roof types, 9 aspect (azimuth) classes and 5 slope (tilt) classes for all building rooftops in Switzerland, using GIS processing. We train Random Forests (RF), an ensemble learning algorithm, to build the classifiers. We use (2 × 2) [m2 ] LiDAR data (considering buildings and vegetation) to extract several rooftop features, and a generalised footprint polygon data to localize buildings. The roof classifier is trained and tested with 1252 labeled roofs from three different urban areas, namely Baden, Luzern, and Winterthur. The results for roof type classification show an average accuracy of 67%. The aspect and slope classifiers are trained and tested with 11449 labeled roofs in the Zurich periphery area. The results for aspect and slope classification show different accuracies depending on the classes: while some classes are well identified, other under-represented classes remain challenging to detect.

Segments and segmental properties in cross-language perception: Korean perception of English obstruents in various prosodic locations

NASA Astrophysics Data System (ADS)

de Jong, Kenneth; Silbert, Noah; Park, Hanyong

2004-05-01

Experimental models of cross-language perception and second-language acquisition (such as PAM and SLM) typically treat language differences in terms of whether the two languages share phonological segmental categories. Linguistic models, by contrast, generally examine properties which cross classify segments, such as features, rules, or prosodic constraints. Such models predict that perceptual patterns found for one segment will generalize to other segments of the same class. This paper presents perceptual identifications of Korean listeners to a set of voiced and voiceless English stops and fricatives in various prosodic locations to determine the extent to which such generality occurs. Results show some class-general effects; for example, voicing identification patterns generalize from stops, which occur in Korean, to nonsibilant fricatives, which are new to Korean listeners. However, when identification is poor, there are clear differences between segments within the same class. For example, in identifying stops and fricatives, both point of articulation and prosodic position bias perceptions; coronals are more often labeled fricatives, and syllable initial obstruents are more often labeled stops. These results suggest that class-general perceptual patterns are not a simple consequence of the structure of the perceptual system, but need to be acquired by factoring out within-class differences.

Landsat-faciliated vegetation classification of the Kenai National Wildlife Refuge and adjacent areas, Alaska

USGS Publications Warehouse

Talbot, S. S.; Shasby, M.B.; Bailey, T.N.

1985-01-01

A Landsat-based vegetation map was prepared for Kenai National Wildlife Refuge and adjacent lands, 2 million and 2.5 million acres respectively. The refuge lies within the middle boreal sub zone of south central Alaska. Seven major classes and sixteen subclasses were recognized: forest (closed needleleaf, needleleaf woodland, mixed); deciduous scrub (lowland and montane, subalpine); dwarf scrub (dwarf shrub tundra, lichen tundra, dwarf shrub and lichen tundra, dwarf shrub peatland, string bog/wetlands); herbaceous (graminoid meadows and marshes); scarcely vegetated areas ; water (clear, moderately turbid, highly turbid); and glaciers. The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo interpretation, and digital Landsat data. Major steps in the Landsat analysis involved: preprocessing (geometric connection), spectral class labeling of sample areas, derivation of statistical parameters for spectral classes, preliminary classification of the entree study area using a maximum-likelihood algorithm, and final classification through ancillary information such as digital elevation data. The vegetation map (scale 1:250,000) was a pioneering effort since there were no intermediate-sclae maps of the area. Representative of distinctive regional patterns, the map was suitable for use in comprehensive conservation planning and wildlife management.

Intermediate-scale vegetation mapping of Innoko National Wildlife Refuge, Alaska using Landsat MSS digital data

USGS Publications Warehouse

Talbot, Stephen S.; Markon, Carl J.

1988-01-01

A Landsat-derived vegetation map was prepared for lnnoko National Wildlife Refuge. The refuge lies within the northern boreal subzone of northwestern central Alaska. Six major vegetation classes and 21 subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, upland burn regeneration, subalpine); dwarf scrub (prostrate dwarf shrub tundra, erect dwarf shrub heath, dwarf shrub-graminoid peatland, dwarf shrub-graminoid tussock peatland, dwarf shrub raised bog with scattered trees, dwarf shrub-graminoid marsh); herbaceous (graminoid bog, graminoid marsh, graminoid tussock-dwarf shrub peatland); scarcely vegetated areas (scarcely vegetated scree and floodplain); and water (clear, sedimented). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo-interpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Nonparametric, Coupled ,Bayesian ,Dictionary ,and Classifier Learning for Hyperspectral Classification.

PubMed

Akhtar, Naveed; Mian, Ajmal

2017-10-03

We present a principled approach to learn a discriminative dictionary along a linear classifier for hyperspectral classification. Our approach places Gaussian Process priors over the dictionary to account for the relative smoothness of the natural spectra, whereas the classifier parameters are sampled from multivariate Gaussians. We employ two Beta-Bernoulli processes to jointly infer the dictionary and the classifier. These processes are coupled under the same sets of Bernoulli distributions. In our approach, these distributions signify the frequency of the dictionary atom usage in representing class-specific training spectra, which also makes the dictionary discriminative. Due to the coupling between the dictionary and the classifier, the popularity of the atoms for representing different classes gets encoded into the classifier. This helps in predicting the class labels of test spectra that are first represented over the dictionary by solving a simultaneous sparse optimization problem. The labels of the spectra are predicted by feeding the resulting representations to the classifier. Our approach exploits the nonparametric Bayesian framework to automatically infer the dictionary size--the key parameter in discriminative dictionary learning. Moreover, it also has the desirable property of adaptively learning the association between the dictionary atoms and the class labels by itself. We use Gibbs sampling to infer the posterior probability distributions over the dictionary and the classifier under the proposed model, for which, we derive analytical expressions. To establish the effectiveness of our approach, we test it on benchmark hyperspectral images. The classification performance is compared with the state-of-the-art dictionary learning-based classification methods.

Label Review Training: Module 1: Label Basics, Page 24

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. This page is about which labels require review.

Label Review Training: Module 1: Label Basics, Page 17

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. See an overview of the importance of labels.

Label Review Training: Module 1: Label Basics, Page 27

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. See examples of mandatory and advisory label statements.

Label Review Training: Module 1: Label Basics, Page 23

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Lists types of labels that do not require review.

Information search behaviour, understanding and use of nutrition labeling by residents of Madrid, Spain.

PubMed

Prieto-Castillo, L; Royo-Bordonada, M A; Moya-Geromini, A

2015-03-01

To describe the information search behaviour, comprehension level, and use of nutritional labeling by consumers according to sociodemographic characteristics. Cross-sectional study of consumers recruited in five stores of the main supermarket chains in Madrid: a random sample of 299 consumers (response rate: 80.6%). Interviewers collected information about the information search behaviour, comprehension, and use of nutritional labeling using a questionnaire designed for this purpose. Analyses examined the frequency of the variables of interest. Differences were tested using the Chi-square statistic. In this sample, 38.8% of consumers regularly read the nutritional labeling before making a purchase (45% of women vs 30% in men; P = 0.03) and the most common reason reported was choosing healthier products (81.3%). The proportion of people who were interested in additives and fats was the higher, (55% and 50%, respectively). Lack of time (38.9%), lack of interest (27.1%), and reading difficulties (18.1%) were the most common reasons given for not reading labels. Over half (52.4%) of consumers reported completely understanding the nutritional information on labels and 20.5% reported using such information for dietary planning. Reported information search behaviour, comprehension, and use of nutritional labeling were relatively high among consumers of the study, and their main goal was picking healthier products. However, not only are there still barriers to reading the information, but also the information most relevant to health is not always read or understood. Thus, interventions to increase nutritional labeling comprehension and use are required in order to facilitate the making of healthier choices by consumers. Copyright © 2014 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

The helpfulness of category labels in semi-supervised learning depends on category structure.

PubMed

Vong, Wai Keen; Navarro, Daniel J; Perfors, Amy

2016-02-01

The study of semi-supervised category learning has generally focused on how additional unlabeled information with given labeled information might benefit category learning. The literature is also somewhat contradictory, sometimes appearing to show a benefit to unlabeled information and sometimes not. In this paper, we frame the problem differently, focusing on when labels might be helpful to a learner who has access to lots of unlabeled information. Using an unconstrained free-sorting categorization experiment, we show that labels are useful to participants only when the category structure is ambiguous and that people's responses are driven by the specific set of labels they see. We present an extension of Anderson's Rational Model of Categorization that captures this effect.

Adding self-management of chronic conditions to fall prevention: A feasibility study.

PubMed

Wurzer, Birgit Maria; Waters, Debra Lynn; Robertson, Linda; Hale, Beatrice; Hale, Leigh Anne

2017-03-01

Assess feasibility and impact of adding a long-term condition self-management program (Living a Healthy Life, LHL) into Steady as You Go (SAYGO) fall prevention exercise classes. Four-day LHL leader training workshop to deliver six weekly program. Focus groups explored feasibility and acceptability. Chronic disease self-efficacy, balance confidence, health behaviours and status were measured at 6 weeks, 3, 6 and 12 months. Four leaders and 17 participants volunteered. Focus groups revealed that becoming a leader was considered stressful. Participants valued discussions about managing health, strategies for better communication with doctors, keeping track of medications, action plans and nutrition labels. Between 6-week and 12-month follow-up, self-rated health increased. Although participants valued LHL information, the low participation rates, time commitment and stress of becoming a leader and leading classes suggest that adding LHL to other fall prevention programs will need further consideration around integration of the programs. © 2016 AJA Inc.

Learning to Recognize Actions From Limited Training Examples Using a Recurrent Spiking Neural Model

PubMed Central

Panda, Priyadarshini; Srinivasa, Narayan

2018-01-01

A fundamental challenge in machine learning today is to build a model that can learn from few examples. Here, we describe a reservoir based spiking neural model for learning to recognize actions with a limited number of labeled videos. First, we propose a novel encoding, inspired by how microsaccades influence visual perception, to extract spike information from raw video data while preserving the temporal correlation across different frames. Using this encoding, we show that the reservoir generalizes its rich dynamical activity toward signature action/movements enabling it to learn from few training examples. We evaluate our approach on the UCF-101 dataset. Our experiments demonstrate that our proposed reservoir achieves 81.3/87% Top-1/Top-5 accuracy, respectively, on the 101-class data while requiring just 8 video examples per class for training. Our results establish a new benchmark for action recognition from limited video examples for spiking neural models while yielding competitive accuracy with respect to state-of-the-art non-spiking neural models. PMID:29551962

Automated cell-type classification in intact tissues by single-cell molecular profiling

PubMed Central

2018-01-01

A major challenge in biology is identifying distinct cell classes and mapping their interactions in vivo. Tissue-dissociative technologies enable deep single cell molecular profiling but do not provide spatial information. We developed a proximity ligation in situ hybridization technology (PLISH) with exceptional signal strength, specificity, and sensitivity in tissue. Multiplexed data sets can be acquired using barcoded probes and rapid label-image-erase cycles, with automated calculation of single cell profiles, enabling clustering and anatomical re-mapping of cells. We apply PLISH to expression profile ~2900 cells in intact mouse lung, which identifies and localizes known cell types, including rare ones. Unsupervised classification of the cells indicates differential expression of ‘housekeeping’ genes between cell types, and re-mapping of two sub-classes of Club cells highlights their segregated spatial domains in terminal airways. By enabling single cell profiling of various RNA species in situ, PLISH can impact many areas of basic and medical research. PMID:29319504

Learning a Taxonomy of Predefined and Discovered Activity Patterns

PubMed Central

Krishnan, Narayanan; Cook, Diane J.; Wemlinger, Zachary

2013-01-01

Many intelligent systems that focus on the needs of a human require information about the activities that are being performed by the human. At the core of this capability is activity recognition. Activity recognition techniques have become robust but rarely scale to handle more than a few activities. They also rarely learn from more than one smart home data set because of inherent differences between labeling techniques. In this paper we investigate a data-driven approach to creating an activity taxonomy from sensor data found in disparate smart home datasets. We investigate how the resulting taxonomy can help analyze the relationship between classes of activities. We also analyze how the taxonomy can be used to scale activity recognition to a large number of activity classes and training datasets. We describe our approach and evaluate it on 34 smart home datasets. The results of the evaluation indicate that the hierarchical modeling can reduce training time while maintaining accuracy of the learned model. PMID:25302084

How to Read a Nutrition Facts Label

MedlinePlus Videos and Cool Tools

... label. These labels have a lot of important information — on fat and calories, serving sizes, sodium content, ... Nondiscrimination Visit the Nemours Web site. Note: All information on KidsHealth® is for educational purposes only. For ...

Label Review Training: Module 1: Label Basics, Page 16

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. Learn about the importance of labels and the role in enforcement.

Addressing multi-label imbalance problem of surgical tool detection using CNN.

PubMed

Sahu, Manish; Mukhopadhyay, Anirban; Szengel, Angelika; Zachow, Stefan

2017-06-01

A fully automated surgical tool detection framework is proposed for endoscopic video streams. State-of-the-art surgical tool detection methods rely on supervised one-vs-all or multi-class classification techniques, completely ignoring the co-occurrence relationship of the tools and the associated class imbalance. In this paper, we formulate tool detection as a multi-label classification task where tool co-occurrences are treated as separate classes. In addition, imbalance on tool co-occurrences is analyzed and stratification techniques are employed to address the imbalance during convolutional neural network (CNN) training. Moreover, temporal smoothing is introduced as an online post-processing step to enhance runtime prediction. Quantitative analysis is performed on the M2CAI16 tool detection dataset to highlight the importance of stratification, temporal smoothing and the overall framework for tool detection. The analysis on tool imbalance, backed by the empirical results, indicates the need and superiority of the proposed framework over state-of-the-art techniques.

Methods of visualizing graphs

DOEpatents

Wong, Pak C.; Mackey, Patrick S.; Perrine, Kenneth A.; Foote, Harlan P.; Thomas, James J.

2008-12-23

Methods for visualizing a graph by automatically drawing elements of the graph as labels are disclosed. In one embodiment, the method comprises receiving node information and edge information from an input device and/or communication interface, constructing a graph layout based at least in part on that information, wherein the edges are automatically drawn as labels, and displaying the graph on a display device according to the graph layout. In some embodiments, the nodes are automatically drawn as labels instead of, or in addition to, the label-edges.

The power of putting a label on it: green labels weigh heavier than contradicting product information for consumers' purchase decisions and post-purchase behavior.

PubMed

Hahnel, Ulf J J; Arnold, Oliver; Waschto, Michael; Korcaj, Liridon; Hillmann, Karen; Roser, Damaris; Spada, Hans

2015-01-01

Green products are appealing. Thus, labeling products as environmentally friendly is an effective strategy to increase sales. However, the labels often promise more than the products can actually deliver. In the present research, we examined the expectation that consumers with high ecological motivation have strong preferences for green-labeled products - even when presented product information contradicts the label's image. This unsettling hypothesis is grounded in the labels' potential to create a cognitive match between the labeled product and consumers' motives. For labels indicating environmental friendliness (green product labels), this link should be strongest when consumers' ecological motivation is high. Findings in a series of three experiments support our assumption, showing that consumers with high ecological motivation had strong preferences (i.e., product evaluations, purchase intentions, and simulated purchase decisions) for green-labeled products as compared to consumers with low ecological motivation (Studies 1-3). Crucially, these preferences were robust, despite contradicting environmental product information (Studies 1 and 2). We extended our findings by additionally examining the impact of product labels and motivation on moral self-regulation processes. This was established by assessing participants' pro-social behavior after the purchase task: participants with high ecological motivation acted, consistent with their motives, more pro-socially in post-decision occasions. In accordance with moral cleansing effects, pro-social behavior was intensified after purchasing conventional products (Studies 2 and 3). Green labels protected participants with high ecological motivation from moral threats due to the purchase, thus making pro-social behavior less likely. Findings suggest that highly ecologically motivated consumers are most susceptible to green labels, which may override detailed product information.

Information Measures of Degree Distributions with an Application to Labeled Graphs

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

Joslyn, Cliff A.; Purvine, Emilie AH

2016-01-11

The problem of describing the distribution of labels over a set of objects is relevant to many domains. For example: cyber security, social media, and protein interactions all care about the manner in which labels are distributed among different objects. In this paper we present three interacting statistical measures on label distributions, inspired by entropy and information theory. Labeled graphs are discussed as a specific case of labels distributed over a set of edges. We describe a use case in cyber security using a labeled directed multi-graph of IPFLOW. Finally we show how these measures respond when labels are updatedmore » in certain ways.« less

Patterns of Alcohol Use Among Canadian Military Personnel and Their Associations With Health and Well-Being.

PubMed

Richer, Isabelle; Lee, Jennifer E C; Born, Jennifer

2016-04-07

Heavy drinking increases the risk of injury, adverse physical and mental health outcomes, and loss of productivity. Nonetheless, patterns of alcohol use and related symptomatology among military personnel remain poorly understood. A latent class analysis (LCA) was used to explore the presence of subgroups of alcohol users among Canadian Armed Forces (CAF) Regular Forces members. Correlates of empirically derived subgroups were further explored. Analyses were performed on a subsample of alcohol users who participated in a 2008/09 cross-sectional survey of a stratified random sample of currently serving CAF Regular Force members (N = 1980). Multinomial logistic regression models were conducted to verify physical and mental health differences across subgroups of alcohol users. All analyses were adjusted for complex survey design. A 4-class solution was considered the best fit for the data. Subgroups were labeled as follows: Class 1 - Infrequent drinkers (27.2%); Class 2 - Moderate drinkers (41.5%); Class 3 - Regular binge drinkers with minimal problems (14.8%); and Class 4 - Problem drinkers (16.6%). Significant differences by age, sex, marital status, element, rank, recent serious injuries, chronic conditions, psychological distress, posttraumatic stress disorder, and depression symptoms were found across the subgroups. Problem drinkers demonstrated the most degraded physical and mental health. Findings highlight the heterogeneity of alcohol users and heavy drinkers among CAF members and the need for tailored interventions addressing high-risk alcohol use. Results have the potential to inform prevention strategies and screening efforts. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Introduction to Pesticide Labels

EPA Pesticide Factsheets

Pesticide product labels provide critical information about how to safely and legally handle and use pesticide products. Unlike most other types of product labels, pesticide labels are legally enforceable. Learn about pesticide product labels.

Nutrition labels in bar graph format deemed most useful for consumer purchase decisions using adaptive conjoint analysis.

PubMed

Geiger, C J; Wyse, B W; Parent, C R; Hansen, R G

1991-07-01

This study estimated the effects of changing multiple levels and combinations of nutrition information format, load, expression, and order on consumers' perceptions of label usefulness in purchase decisions using adaptive conjoint analysis. A shopping mall intercept survey, which was administered by a marketing research firm, assessed consumer preferences for 12 label alternatives produced on Campbell's soup cans to portray nutrition information realistically; 252 of 258 respondents completed the computer interactive interview. Consumers significantly preferred the bar graph format to the bar graph/nutrient density and traditional label formats. Consumers considered the bar graph/nutrient density format to be as useful as the traditional label format. There was a highly significant difference among the three levels of information load; the most information load was preferred regardless of nutrient importance. Consumers significantly preferred nutrition information stated in absolute numbers and percentages vs in absolute numbers only in traditional, or in percentages only expressions. There was a significant difference between consumer preferences for the two types of information order. The findings indicate that consumers clearly preferred the nutrition label that displayed all nutrient values using a bar graph format, offered the most information load, and expressed nutrient values using both absolute numbers and percentages. Consumers also preferred nutrition information rearranged in an order that grouped nutrients that should be consumed in adequate amounts on the top, calories in the middle, and nutrients that should be consumed in lesser amounts on the bottom of the label.

Computationally efficient target classification in multispectral image data with Deep Neural Networks

NASA Astrophysics Data System (ADS)

Cavigelli, Lukas; Bernath, Dominic; Magno, Michele; Benini, Luca

2016-10-01

Detecting and classifying targets in video streams from surveillance cameras is a cumbersome, error-prone and expensive task. Often, the incurred costs are prohibitive for real-time monitoring. This leads to data being stored locally or transmitted to a central storage site for post-incident examination. The required communication links and archiving of the video data are still expensive and this setup excludes preemptive actions to respond to imminent threats. An effective way to overcome these limitations is to build a smart camera that analyzes the data on-site, close to the sensor, and transmits alerts when relevant video sequences are detected. Deep neural networks (DNNs) have come to outperform humans in visual classifications tasks and are also performing exceptionally well on other computer vision tasks. The concept of DNNs and Convolutional Networks (ConvNets) can easily be extended to make use of higher-dimensional input data such as multispectral data. We explore this opportunity in terms of achievable accuracy and required computational effort. To analyze the precision of DNNs for scene labeling in an urban surveillance scenario we have created a dataset with 8 classes obtained in a field experiment. We combine an RGB camera with a 25-channel VIS-NIR snapshot sensor to assess the potential of multispectral image data for target classification. We evaluate several new DNNs, showing that the spectral information fused together with the RGB frames can be used to improve the accuracy of the system or to achieve similar accuracy with a 3x smaller computation effort. We achieve a very high per-pixel accuracy of 99.1%. Even for scarcely occurring, but particularly interesting classes, such as cars, 75% of the pixels are labeled correctly with errors occurring only around the border of the objects. This high accuracy was obtained with a training set of only 30 labeled images, paving the way for fast adaptation to various application scenarios.

Requirements for the admission of medical products made of NiTinol according to the German Medical Products Act (MPG).

PubMed

Frey-Köppel

2004-08-01

This paper describes the procedure in placing a medical product on the market. Since June 1998, medical products must have the CE label according to the directive 93/42 EEC. This means that all medical products must fulfill the essential requirements according to Annex I of this directive. Assessments and certifications are made by so-called Notified Bodies. Medical products are classified into four classes: Classes I, IIa, IIb, and III. There exist 18 classification rules. Biocompatibility of a product must be demonstrated. The standard EN ISO 10993-1 Biological Assessment of Medical Products informs about the type and scope of the tests. The place of application and body contact time are criteria for the tests to be performed. Biocompatibility of NiTinol may be assessed on the basis of clinical data/literature. Clinical suitability of a medical product must also be demonstrated. This can be done by assessing scientific literature or performing clinical tests or by combining both methods. The prerequisites for a clinical test of medical products are outlined among others by Article 20, MPG (General Prerequisites for Clinical Testing). MEDDEV 2.7.1, Evaluation of Clinical Data, represents the guideline for the processing of clinical data. Custom-made products are products intended for a specific patient and manufactured especially for this patient according to a given specification. Custom-made products may be used without a CE label and, hence, are not subjected to assessing by a Notified Body but have to fulfill the essential requirements and must also be documented accordingly. According to the directive 93/42 EEC, the person responsible for placing the product on the market under its own name and CE-label is deemed the manufacturer, even if the product has been manufactured completely by another company.

Accounting for control mislabeling in case-control biomarker studies.

PubMed

Rantalainen, Mattias; Holmes, Chris C

2011-12-02

In biomarker discovery studies, uncertainty associated with case and control labels is often overlooked. By omitting to take into account label uncertainty, model parameters and the predictive risk can become biased, sometimes severely. The most common situation is when the control set contains an unknown number of undiagnosed, or future, cases. This has a marked impact in situations where the model needs to be well-calibrated, e.g., when the prediction performance of a biomarker panel is evaluated. Failing to account for class label uncertainty may lead to underestimation of classification performance and bias in parameter estimates. This can further impact on meta-analysis for combining evidence from multiple studies. Using a simulation study, we outline how conventional statistical models can be modified to address class label uncertainty leading to well-calibrated prediction performance estimates and reduced bias in meta-analysis. We focus on the problem of mislabeled control subjects in case-control studies, i.e., when some of the control subjects are undiagnosed cases, although the procedures we report are generic. The uncertainty in control status is a particular situation common in biomarker discovery studies in the context of genomic and molecular epidemiology, where control subjects are commonly sampled from the general population with an established expected disease incidence rate.

Exploring enhanced menu labels' influence on fast food selections and exercise-related attitudes, perceptions, and intentions.

PubMed

Lee, Morgan S; Thompson, Joel Kevin

2016-10-01

Labeling restaurant menus with calorie counts is a popular public health intervention, but research shows these labels have small, inconsistent effects on behavior. Supplementing calorie counts with physical activity equivalents may produce stronger results, but few studies of these enhanced labels have been conducted, and the labels' potential to influence exercise-related outcomes remains unexplored. This online study evaluated the impact of no information, calories-only, and calories plus equivalent miles of walking labels on fast food item selection and exercise-related attitudes, perceptions, and intentions. Participants (N = 643) were randomly assigned to a labeling condition and completed a menu ordering task followed by measures of exercise-related outcomes. The labels had little effect on ordering behavior, with no significant differences in total calories ordered and counterintuitive increases in calories ordered in the two informational conditions in some item categories. The labels also had little impact on the exercise-related outcomes, though participants in the two informational conditions perceived exercise as less enjoyable than did participants in the no information condition, and trends following the same pattern were found for other exercise-related outcomes. The present findings concur with literature demonstrating small, inconsistent effects of current menu labeling strategies and suggest that alternatives such as traffic light systems should be explored. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relationships among food label use, motivation, and dietary quality.

PubMed

Miller, Lisa M Soederberg; Cassady, Diana L; Applegate, Elizabeth A; Beckett, Laurel A; Wilson, Machelle D; Gibson, Tanja N; Ellwood, Kathleen

2015-02-05

Nutrition information on packaged foods supplies information that aids consumers in meeting the recommendations put forth in the US Dietary Guidelines for Americans such as reducing intake of solid fats and added sugars. It is important to understand how food label use is related to dietary intake. However, prior work is based only on self-reported use of food labels, making it unclear if subjective assessments are biased toward motivational influences. We assessed food label use using both self-reported and objective measures, the stage of change, and dietary quality in a sample of 392 stratified by income. Self-reported food label use was assessed using a questionnaire. Objective use was assessed using a mock shopping task in which participants viewed food labels and decided which foods to purchase. Eye movements were monitored to assess attention to nutrition information on the food labels. Individuals paid attention to nutrition information when selecting foods to buy. Self-reported and objective measures of label use showed some overlap with each other (r=0.29, p<0.001), and both predicted dietary quality (p<0.001 for both). The stage of change diminished the predictive power of subjective (p<0.09), but not objective (p<0.01), food label use. These data show both self-reported and objective measures of food label use are positively associated with dietary quality. However, self-reported measures appear to capture a greater motivational component of food label use than do more objective measures.

Label free measurement of retinal blood cell flux, velocity, hematocrit and capillary width in the living mouse eye

PubMed Central

Guevara-Torres, A.; Joseph, A.; Schallek, J. B.

2016-01-01

Measuring blood cell dynamics within the capillaries of the living eye provides crucial information regarding the health of the microvascular network. To date, the study of single blood cell movement in this network has been obscured by optical aberrations, hindered by weak optical contrast, and often required injection of exogenous fluorescent dyes to perform measurements. Here we present a new strategy to non-invasively image single blood cells in the living mouse eye without contrast agents. Eye aberrations were corrected with an adaptive optics camera coupled with a fast, 15 kHz scanned beam orthogonal to a capillary of interest. Blood cells were imaged as they flowed past a near infrared imaging beam to which the eye is relatively insensitive. Optical contrast of cells was optimized using differential scatter of blood cells in the split-detector imaging configuration. Combined, these strategies provide label-free, non-invasive imaging of blood cells in the retina as they travel in single file in capillaries, enabling determination of cell flux, morphology, class, velocity, and rheology at the single cell level. PMID:27867728

Cyclobutanone Mimics of Intermediates in Metallo-β-Lactamase Catalysis.

PubMed

Abboud, Martine I; Kosmopoulou, Magda; Krismanich, Anthony P; Johnson, Jarrod W; Hinchliffe, Philip; Brem, Jürgen; Claridge, Timothy D W; Spencer, James; Schofield, Christopher J; Dmitrienko, Gary I

2018-04-17

The most important resistance mechanism to β-lactam antibiotics involves hydrolysis by two β-lactamase categories: the nucleophilic serine and the metallo-β-lactamases (SBLs and MBLs, respectively). Cyclobutanones are hydrolytically stable β-lactam analogues with potential to inhibit both SBLs and MBLs. We describe solution and crystallographic studies on the interaction of a cyclobutanone penem analogue with the clinically important MBL SPM-1. NMR experiments using 19 F-labeled SPM-1 imply the cyclobutanone binds to SPM-1 with micromolar affinity. A crystal structure of the SPM-1:cyclobutanone complex reveals binding of the hydrated cyclobutanone through interactions with one of the zinc ions, stabilisation of the hydrate by hydrogen bonding to zinc-bound water, and hydrophobic contacts with aromatic residues. NMR analyses using a 13 C-labeled cyclobutanone support assignment of the bound species as the hydrated ketone. The results inform on how MBLs bind substrates and stabilize tetrahedral intermediates. They support further investigations on the use of transition-state and/or intermediate analogues as inhibitors of all β-lactamase classes. © 2018 Die Autoren. Veröffentlicht von Wiley-VCH Verlag GmbH & Co. KGaA.

Are there different types of female orgasm?

PubMed

King, Robert; Belsky, Jay; Mah, Kenneth; Binik, Yitzchak

2011-10-01

In attempt to identify and validate different types of orgasms which females have during sex with a partner, data collected by Mah and Binik (2002) on the dimensional phenomenology of female orgasm were subjected to a typological analysis. A total of 503 women provided adjectival descriptions of orgasms experienced either with a partner (n = 276) or while alone (n = 227). Latent-class analysis revealed four orgasm types which varied systematically in terms of pleasure and sensations engendered. Two types, collectively labelled "good-sex orgasms," received higher pleasure and sensation ratings than solitary-masturbatory ones, whereas two other types, collectively labelled "not-as-good-sex orgasms," received lower ratings. These two higher-order groupings differed on a number of psychological, physical and relationship factors examined for purposes of validating the typology. Evolutionary thinking regarding the function of female orgasm informed discussion of the findings. Future research directions were outlined, especially the need to examine whether the same individual experiences different types of orgasms with partners with different characteristics, as evolutionary theorizing predicts should be the case.

Cyclobutanone Mimics of Intermediates in Metallo‐β‐Lactamase Catalysis

PubMed Central

Abboud, Martine I.; Kosmopoulou, Magda; Krismanich, Anthony P.; Johnson, Jarrod W.; Hinchliffe, Philip; Brem, Jürgen; Claridge, Timothy D. W.

2018-01-01

Abstract The most important resistance mechanism to β‐lactam antibiotics involves hydrolysis by two β‐lactamase categories: the nucleophilic serine and the metallo‐β‐lactamases (SBLs and MBLs, respectively). Cyclobutanones are hydrolytically stable β‐lactam analogues with potential to inhibit both SBLs and MBLs. We describe solution and crystallographic studies on the interaction of a cyclobutanone penem analogue with the clinically important MBL SPM‐1. NMR experiments using 19F‐labeled SPM‐1 imply the cyclobutanone binds to SPM‐1 with micromolar affinity. A crystal structure of the SPM‐1:cyclobutanone complex reveals binding of the hydrated cyclobutanone through interactions with one of the zinc ions, stabilisation of the hydrate by hydrogen bonding to zinc‐bound water, and hydrophobic contacts with aromatic residues. NMR analyses using a 13C‐labeled cyclobutanone support assignment of the bound species as the hydrated ketone. The results inform on how MBLs bind substrates and stabilize tetrahedral intermediates. They support further investigations on the use of transition‐state and/or intermediate analogues as inhibitors of all β‐lactamase classes. PMID:29250863

Label free measurement of retinal blood cell flux, velocity, hematocrit and capillary width in the living mouse eye.

PubMed

Guevara-Torres, A; Joseph, A; Schallek, J B

2016-10-01

Measuring blood cell dynamics within the capillaries of the living eye provides crucial information regarding the health of the microvascular network. To date, the study of single blood cell movement in this network has been obscured by optical aberrations, hindered by weak optical contrast, and often required injection of exogenous fluorescent dyes to perform measurements. Here we present a new strategy to non-invasively image single blood cells in the living mouse eye without contrast agents. Eye aberrations were corrected with an adaptive optics camera coupled with a fast, 15 kHz scanned beam orthogonal to a capillary of interest. Blood cells were imaged as they flowed past a near infrared imaging beam to which the eye is relatively insensitive. Optical contrast of cells was optimized using differential scatter of blood cells in the split-detector imaging configuration. Combined, these strategies provide label-free, non-invasive imaging of blood cells in the retina as they travel in single file in capillaries, enabling determination of cell flux, morphology, class, velocity, and rheology at the single cell level.

Labelling fashion magazine advertisements: Effectiveness of different label formats on social comparison and body dissatisfaction.

PubMed

Tiggemann, Marika; Brown, Zoe

2018-06-01

The experiment investigated the impact on women's body dissatisfaction of different forms of label added to fashion magazine advertisements. Participants were 340 female undergraduate students who viewed 15 fashion advertisements containing a thin and attractive model. They were randomly allocated to one of five label conditions: no label, generic disclaimer label (indicating image had been digitally altered), consequence label (indicating that viewing images might make women feel bad about themselves), informational label (indicating the model in the advertisement was underweight), or a graphic label (picture of a paint brush). Although exposure to the fashion advertisements resulted in increased body dissatisfaction, there was no significant effect of label type on body dissatisfaction; no form of label demonstrated any ameliorating effect. In addition, the consequence and informational labels resulted in increased perceived realism and state appearance comparison. Yet more extensive research is required before the effective implementation of any form of label. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Influence of Nutrition Labeling and Point-of-Purchase Information on Food Behaviours.

PubMed

Volkova, Ekaterina; Ni Mhurchu, Cliona

2015-03-01

Point-of-purchase information on packaged food has been a highly debated topic. Various types of nutrition labels and point-of-purchase information have been studied to determine their ability to attract consumers' attention, be well understood and promote healthy food choices. Country-specific regulatory and monitoring frameworks have been implemented to ensure reliability and accuracy of such information. However, the impact of such information on consumers' behaviour remains contentious. This review summarizes recent evidence on the real-world effectiveness of nutrition labels and point-of-purchase information.

Automatic classification of retinal vessels into arteries and veins

NASA Astrophysics Data System (ADS)

Niemeijer, Meindert; van Ginneken, Bram; Abràmoff, Michael D.

2009-02-01

Separating the retinal vascular tree into arteries and veins is important for quantifying vessel changes that preferentially affect either the veins or the arteries. For example the ratio of arterial to venous diameter, the retinal a/v ratio, is well established to be predictive of stroke and other cardiovascular events in adults, as well as the staging of retinopathy of prematurity in premature infants. This work presents a supervised, automatic method that can determine whether a vessel is an artery or a vein based on intensity and derivative information. After thinning of the vessel segmentation, vessel crossing and bifurcation points are removed leaving a set of vessel segments containing centerline pixels. A set of features is extracted from each centerline pixel and using these each is assigned a soft label indicating the likelihood that it is part of a vein. As all centerline pixels in a connected segment should be the same type we average the soft labels and assign this average label to each centerline pixel in the segment. We train and test the algorithm using the data (40 color fundus photographs) from the DRIVE database1 with an enhanced reference standard. In the enhanced reference standard a fellowship trained retinal specialist (MDA) labeled all vessels for which it was possible to visually determine whether it was a vein or an artery. After applying the proposed method to the 20 images of the DRIVE test set we obtained an area under the receiver operator characteristic (ROC) curve of 0.88 for correctly assigning centerline pixels to either the vein or artery classes.

Evaluation of adverse drug event information in US manufacturer labels.

PubMed

Harrington, Catherine A; Garcia, Angela S; Sircar-Ramsewak, Feroza

2011-02-01

Pharmaceutical manufacturer labels are an important source of adverse drug event (ADE) information. The study objective was to determine the sufficiency of ADE reporting in US drug labels. A sample of 50 labels was evaluated from the top 200 drugs dispensed in the US. Electronic copies of labels were obtained and reviewed by 2 pharmacists for ADE incidence and discontinuation data. ADE incidence data were provided in 86% of labels. However, discontinuation rates due to ADEs and ADE incidence by dose were only reported in 60%. ADE incidence reporting by age (46%) or gender (18%) was also low. ADEs that occurred in less than 2% of the population were rarely reported. Incidence rates were based on small populations (median of 794) and short term studies (median of 84 days for chronic conditions). Labels for 19 drugs used chronically had no long term study data. Methods for collecting ADE data were stated in only 12% of labels. Adverse drug event and drug discontinuation data is under-reported in US labels. More information on adverse events causing discontinuation (especially serious events) and those related to dose, age, and gender is needed in labels to ensure safe prescribing and dispensing of drugs.

Label Review Training: Module 1: Label Basics, Page 25

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review: clarity, accuracy, consistency with EPA policy, and enforceability.

Label Review Training: Module 1: Label Basics, Page 29

EPA Pesticide Factsheets

This module of the pesticide label review training provides basic information about pesticides, their labeling and regulation, and the core principles of pesticide label review. This page is a quiz on Module 1.

An evaluation of open set recognition for FLIR images

NASA Astrophysics Data System (ADS)

Scherreik, Matthew; Rigling, Brian

2015-05-01

Typical supervised classification algorithms label inputs according to what was learned in a training phase. Thus, test inputs that were not seen in training are always given incorrect labels. Open set recognition algorithms address this issue by accounting for inputs that are not present in training and providing the classifier with an option to reject" unknown samples. A number of such techniques have been developed in the literature, many of which are based on support vector machines (SVMs). One approach, the 1-vs-set machine, constructs a slab" in feature space using the SVM hyperplane. Inputs falling on one side of the slab or within the slab belong to a training class, while inputs falling on the far side of the slab are rejected. We note that rejection of unknown inputs can be achieved by thresholding class posterior probabilities. Another recently developed approach, the Probabilistic Open Set SVM (POS-SVM), empirically determines good probability thresholds. We apply the 1-vs-set machine, POS-SVM, and closed set SVMs to FLIR images taken from the Comanche SIG dataset. Vehicles in the dataset are divided into three general classes: wheeled, armored personnel carrier (APC), and tank. For each class, a coarse pose estimate (front, rear, left, right) is taken. In a closed set sense, we analyze these algorithms for prediction of vehicle class and pose. To test open set performance, one or more vehicle classes are held out from training. By considering closed and open set performance separately, we may closely analyze both inter-class discrimination and threshold effectiveness.

Self-organizing maps for learning the edit costs in graph matching.

PubMed

Neuhaus, Michel; Bunke, Horst

2005-06-01

Although graph matching and graph edit distance computation have become areas of intensive research recently, the automatic inference of the cost of edit operations has remained an open problem. In the present paper, we address the issue of learning graph edit distance cost functions for numerically labeled graphs from a corpus of sample graphs. We propose a system of self-organizing maps (SOMs) that represent the distance measuring spaces of node and edge labels. Our learning process is based on the concept of self-organization. It adapts the edit costs in such a way that the similarity of graphs from the same class is increased, whereas the similarity of graphs from different classes decreases. The learning procedure is demonstrated on two different applications involving line drawing graphs and graphs representing diatoms, respectively.

Tin-117m-labeled stannic (Sn/sup 4 +/) chelate of diethylenetriamine pentaacetic acid (DTPA) for application in diagnosis and therapy

DOEpatents

Srivastava, S.C.; Meinken, G.E.; Richards, P.

1983-08-25

The radiopharmaceutical reagents of this invention and the class of Tin-117m radiopharmaceuticals are therapeutic and diagnostic agents that incorporate gamma-emitting nuclides that localize in bone after intravenous injection in mammals (mice, rats, dogs, and rabbits). Images reflecting bone structure or function can then be obtained by a scintillation camera that detects the distribution of ionizing radiation emitted by the radioactive agent. Tin-117m-labeled chelates of stannic tin localize almost exclusively in cortical bone. Upon intravenous injection of the reagent, the preferred chelates are phosphonate compounds, preferable, PYP, MDP, EHDP, and DTPA. This class of reagents is therapeutically and diagnostically useful in skeletal scintigraphy and for the radiotherapy of bone tumors and other disorders.

Data set of the protein expression profiles of Luminal A, Claudin-low and overexpressing HER2+ breast cancer cell lines by iTRAQ labelling and tandem mass spectrometry

PubMed Central

Calderón-González, Karla Grisel; Valero Rustarazo, Ma Luz; Labra-Barrios, Maria Luisa; Bazán-Méndez, César Isaac; Tavera-Tapia, Alejandra; Herrera-Aguirre, Marí;aEsther; Sánchez del Pino, Manuel M.; Gallegos-Pérez, José Luis; González-Márquez, Humberto; Hernández-Hernández, Jose Manuel; León-Ávila, Gloria; Rodríguez-Cuevas, Sergio; Guisa-Hohenstein, Fernando; Luna-Arias, Juan Pedro

2015-01-01

Breast cancer is the most common and the leading cause of mortality in women worldwide. There is a dire necessity of the identification of novel molecules useful in diagnosis and prognosis. In this work we determined the differentially expression profiles of four breast cancer cell lines compared to a control cell line. We identified 1020 polypeptides labelled with iTRAQ with more than 95% in confidence. We analysed the common proteins in all breast cancer cell lines through IPA software (IPA core and Biomarkers). In addition, we selected the specific overexpressed and subexpressed proteins of the different molecular classes of breast cancer cell lines, and classified them according to protein class and biological process. Data in this article is related to the research article “Determination of the protein expression profiles of breast cancer cell lines by Quantitative Proteomics using iTRAQ Labelling and Tandem Mass Spectrometry” (Calderón-González et al. [1] in press). PMID:26217805

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.

Incorporating prior knowledge induced from stochastic differential equations in the classification of stochastic observations.

PubMed

Zollanvari, Amin; Dougherty, Edward R

2016-12-01

In classification, prior knowledge is incorporated in a Bayesian framework by assuming that the feature-label distribution belongs to an uncertainty class of feature-label distributions governed by a prior distribution. A posterior distribution is then derived from the prior and the sample data. An optimal Bayesian classifier (OBC) minimizes the expected misclassification error relative to the posterior distribution. From an application perspective, prior construction is critical. The prior distribution is formed by mapping a set of mathematical relations among the features and labels, the prior knowledge, into a distribution governing the probability mass across the uncertainty class. In this paper, we consider prior knowledge in the form of stochastic differential equations (SDEs). We consider a vector SDE in integral form involving a drift vector and dispersion matrix. Having constructed the prior, we develop the optimal Bayesian classifier between two models and examine, via synthetic experiments, the effects of uncertainty in the drift vector and dispersion matrix. We apply the theory to a set of SDEs for the purpose of differentiating the evolutionary history between two species.

Understanding the local public health workforce: labels versus substance.

PubMed

Merrill, Jacqueline A; Keeling, Jonathan W

2014-11-01

The workforce is a key component of the nation's public health (PH) infrastructure, but little is known about the skills of local health department (LHD) workers to guide policy and planning. To profile a sample of LHD workers using classification schemes for PH work (the substance of what is done) and PH job titles (the labeling of what is done) to determine if work content is consistent with job classifications. A secondary analysis was conducted on data collected from 2,734 employees from 19 LHDs using a taxonomy of 151 essential tasks performed, knowledge possessed, and resources available. Each employee was classified by job title using a schema developed by PH experts. The inter-rater agreement was calculated within job classes and congruence on tasks, knowledge, and resources for five exemplar classes was examined. The average response rate was 89%. Overall, workers exhibited moderate agreement on tasks and poor agreement on knowledge and resources. Job classes with higher agreement included agency directors and community workers; those with lower agreement were mid-level managers such as program directors. Findings suggest that local PH workers within a job class perform similar tasks but vary in training and access to resources. Job classes that are specific and focused have higher agreement whereas job classes that perform in many roles show less agreement. The PH worker classification may not match employees' skill sets or how LHDs allocate resources, which may be a contributor to unexplained fluctuation in public health system performance. Copyright © 2014. Published by Elsevier Inc.

Semantic 3d City Model to Raster Generalisation for Water Run-Off Modelling

NASA Astrophysics Data System (ADS)

Verbree, E.; de Vries, M.; Gorte, B.; Oude Elberink, S.; Karimlou, G.

2013-09-01

Water run-off modelling applied within urban areas requires an appropriate detailed surface model represented by a raster height grid. Accurate simulations at this scale level have to take into account small but important water barriers and flow channels given by the large-scale map definitions of buildings, street infrastructure, and other terrain objects. Thus, these 3D features have to be rasterised such that each cell represents the height of the object class as good as possible given the cell size limitations. Small grid cells will result in realistic run-off modelling but with unacceptable computation times; larger grid cells with averaged height values will result in less realistic run-off modelling but fast computation times. This paper introduces a height grid generalisation approach in which the surface characteristics that most influence the water run-off flow are preserved. The first step is to create a detailed surface model (1:1.000), combining high-density laser data with a detailed topographic base map. The topographic map objects are triangulated to a set of TIN-objects by taking into account the semantics of the different map object classes. These TIN objects are then rasterised to two grids with a 0.5m cell-spacing: one grid for the object class labels and the other for the TIN-interpolated height values. The next step is to generalise both raster grids to a lower resolution using a procedure that considers the class label of each cell and that of its neighbours. The results of this approach are tested and validated by water run-off model runs for different cellspaced height grids at a pilot area in Amersfoort (the Netherlands). Two national datasets were used in this study: the large scale Topographic Base map (BGT, map scale 1:1.000), and the National height model of the Netherlands AHN2 (10 points per square meter on average). Comparison between the original AHN2 height grid and the semantically enriched and then generalised height grids shows that water barriers are better preserved with the new method. This research confirms the idea that topographical information, mainly the boundary locations and object classes, can enrich the height grid for this hydrological application.

Weighted Discriminative Dictionary Learning based on Low-rank Representation

NASA Astrophysics Data System (ADS)

Chang, Heyou; Zheng, Hao

2017-01-01

Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods.

Superpixel-based structure classification for laparoscopic surgery

NASA Astrophysics Data System (ADS)

Bodenstedt, Sebastian; Görtler, Jochen; Wagner, Martin; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

2016-03-01

Minimally-invasive interventions offers multiple benefits for patients, but also entails drawbacks for the surgeon. The goal of context-aware assistance systems is to alleviate some of these difficulties. Localizing and identifying anatomical structures, maligned tissue and surgical instruments through endoscopic image analysis is paramount for an assistance system, making online measurements and augmented reality visualizations possible. Furthermore, such information can be used to assess the progress of an intervention, hereby allowing for a context-aware assistance. In this work, we present an approach for such an analysis. First, a given laparoscopic image is divided into groups of connected pixels, so-called superpixels, using the SEEDS algorithm. The content of a given superpixel is then described using information regarding its color and texture. Using a Random Forest classifier, we determine the class label of each superpixel. We evaluated our approach on a publicly available dataset for laparoscopic instrument detection and achieved a DICE score of 0.69.

Carbon "Quantum" Dots for Fluorescence Labeling of Cells.

PubMed

Liu, Jia-Hui; Cao, Li; LeCroy, Gregory E; Wang, Ping; Meziani, Mohammed J; Dong, Yiyang; Liu, Yuanfang; Luo, Pengju G; Sun, Ya-Ping

2015-09-02

The specifically synthesized and selected carbon dots of relatively high fluorescence quantum yields were evaluated in their fluorescence labeling of cells. For the cancer cell lines, the cellular uptake of the carbon dots was generally efficient, resulting in the labeling of the cells with bright fluorescence emissions for both one- and two-photon excitations from predominantly the cell membrane and cytoplasm. In the exploration on labeling the live stem cells, the cellular uptake of the carbon dots was relatively less efficient, though fluorescence emissions could still be adequately detected in the labeled cells, with the emissions again predominantly from the cell membrane and cytoplasm. This combined with the observed more efficient internalization of the same carbon dots by the fixed stem cells might suggest some significant selectivity of the stem cells toward surface functionalities of the carbon dots. The needs and possible strategies for more systematic and comparative studies on the fluorescence labeling of different cells, including especially live stem cells, by carbon dots as a new class of brightly fluorescent probes are discussed.

Maximum likelihood estimation of label imperfections and its use in the identification of mislabeled patterns

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of estimating label imperfections and the use of the estimation in identifying mislabeled patterns is presented. Expressions for the maximum likelihood estimates of classification errors and a priori probabilities are derived from the classification of a set of labeled patterns. Expressions also are given for the asymptotic variances of probability of correct classification and proportions. Simple models are developed for imperfections in the labels and for classification errors and are used in the formulation of a maximum likelihood estimation scheme. Schemes are presented for the identification of mislabeled patterns in terms of threshold on the discriminant functions for both two-class and multiclass cases. Expressions are derived for the probability that the imperfect label identification scheme will result in a wrong decision and are used in computing thresholds. The results of practical applications of these techniques in the processing of remotely sensed multispectral data are presented.

The synthesis of tritium, carbon-14 and stable isotope labelled selective estrogen receptor degraders.

PubMed

Bragg, Ryan A; Bushby, Nick; Ericsson, Cecilia; Kingston, Lee P; Ji, Hailong; Elmore, Charles S

2016-09-01

As part of a Medicinal Chemistry program aimed at developing an orally bioavailable selective estrogen receptor degrader, a number of tritium, carbon-14, and stable isotope labelled (E)-3-[4-(2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indol-1-yl)phenyl]prop-2-enoic acids were required. This paper discusses 5 synthetic approaches to this compound class. Copyright © 2016 John Wiley & Sons, Ltd.

Evaluating the Impact of Menu Labeling on Food Choices and Intake

PubMed Central

Larsen, Peter D.; Agnew, Henry; Baik, Jenny; Brownell, Kelly D.

2010-01-01

Objectives. We assessed the impact of restaurant menu calorie labels on food choices and intake. Methods. Participants in a study dinner (n = 303) were randomly assigned to either (1) a menu without calorie labels (no calorie labels), (2) a menu with calorie labels (calorie labels), or (3) a menu with calorie labels and a label stating the recommended daily caloric intake for an average adult (calorie labels plus information). Food choices and intake during and after the study dinner were measured. Results. Participants in both calorie label conditions ordered fewer calories than those in the no calorie labels condition. When calorie label conditions were combined, that group consumed 14% fewer calories than the no calorie labels group. Individuals in the calorie labels condition consumed more calories after the study dinner than those in both other conditions. When calories consumed during and after the study dinner were combined, participants in the calorie labels plus information group consumed an average of 250 fewer calories than those in the other groups. Conclusions. Calorie labels on restaurant menus impacted food choices and intake; adding a recommended daily caloric requirement label increased this effect, suggesting menu label legislation should require such a label. Future research should evaluate menu labeling's impact on children's food choices and consumption. PMID:20019307

Ergotamine and Caffeine

MedlinePlus

... and caffeine is used to prevent and treat migraine headaches. Ergotamine is in a class of medications ... usually taken at the first sign of a migraine headache. Follow the directions on your prescription label ...

Identification and quantification of human kidney atrial natriuretic peptide receptors.

PubMed

Kahana, L; Yechiely, H; Mecz, Y; Lurie, A

1995-04-01

The present study determined 125I-label atrial natriuretic peptide (ANP) binding sites in human kidney glomerular and papillary membranes. The membranes were prepared from non-malignant renal tissue obtained at nephrectomy of patients with renal carcinoma. To evaluate the proportion of ANP receptor classes ANP-R1 (ANPR-A, -B) versus ANP-R2 (ANPR-C), competitive binding studies were performed using [125I]-ANP in the presence of increasing concentrations of ANP or an internally ring-deleted analog, des(Gln116, Ser117, Gly118, Leu119, Gly120)ANP(102-121), called C-ANP, which binds selectively to ANPR-C receptors. Analysis of the competitive binding curve with ANP in glomerular membranes suggested the presence of one group of high-affinity receptors with dissociation constant Kd = 26 +/- 12 pmol/l and density Bmax = 101 +/- 47 nmol/kg protein. A decrease of 10-30% in Bmax with no change in Kd was obtained in the presence of excess (10(-6) mol/l) C-ANP, suggesting the existence of a small amount of a second class of receptors, the ANPR-C class. The densities of ANPR-A, -B versus ANPR-C receptors in human glomeruli, calculated from competitive inhibition experiments, were 75 +/- 42 and 22 +/- 16 nmol/kg protein (N = 8). Autoradiography of the sodium dodecyl sulfate polyacrylamide gel electrophoresis under reducing conditions showed two bands: a highly labeled 130kD band and a weakly labeled 66 kD band, both displaced by ANP. Only the 66-kD band was displaced by the C-ANP analog. Human papilla membrane, as shown by competition binding studies and SDS gel electrophoresis, presented only one class of receptors with Kd = 40 +/- 23 pmol/l (mean +/- SD, N = 3) and Bmax = 17 +/- 6.3 nmol/kg protein.(ABSTRACT TRUNCATED AT 250 WORDS)

Restaurant menu labelling: Is it worth adding sodium to the label?

PubMed

Scourboutakos, Mary J; Corey, Paul N; Mendoza, Julio; Henson, Spencer J; L'Abbe, Mary R

2014-07-31

Several provincial and federal bills have recommended various forms of menu labelling that would require information beyond just calories; however, the additional benefit of including sodium information is unknown. The objective of this study was to determine whether sodium information on menus helps consumers make lower-sodium choices and to understand what other factors influence the effect of menu labelling on consumers' meal choices. A total of 3,080 Canadian consumers completed an online survey that included a repeated measures experiment in which consumers were asked to select what they would typically order from four mock-restaurant menus. Subsequently, consumers were randomly allocated to see one of three menu-labelling treatments (calories; calories and sodium; or calories, sodium and serving size) and were given the option to change their order. There was a significant difference in the proportion of consumers who changed their order, varying from 17% to 30%, depending on the restaurant type. After participants had seen menu labelling, sodium levels decreased in all treatments (p<0.0001). However, in three of the four restaurant types, consumers who saw calorie and sodium information ordered meals with significantly less sodium than consumers who saw only calorie information (p<0.01). Consumers who saw sodium labelling decreased the sodium level of their meal by an average of 171-384 mg, depending on the restaurant. In the subset of consumers who saw sodium information and chose to change their order, sodium levels decreased by an average of 681-1,360 mg, depending on the restaurant. Sex, intent to lose weight and the amount of calories ordered at baseline were the most important predictors of who used menu labelling. Eighty percent of survey panelists wanted to see nutrition information when dining out. Including sodium information alongside calorie information may result in a larger decrease in the amount of sodium ordered by restaurant-goers.

The power of putting a label on it: green labels weigh heavier than contradicting product information for consumers’ purchase decisions and post-purchase behavior

PubMed Central

Hahnel, Ulf J. J.; Arnold, Oliver; Waschto, Michael; Korcaj, Liridon; Hillmann, Karen; Roser, Damaris; Spada, Hans

2015-01-01

Green products are appealing. Thus, labeling products as environmentally friendly is an effective strategy to increase sales. However, the labels often promise more than the products can actually deliver. In the present research, we examined the expectation that consumers with high ecological motivation have strong preferences for green-labeled products – even when presented product information contradicts the label’s image. This unsettling hypothesis is grounded in the labels’ potential to create a cognitive match between the labeled product and consumers’ motives. For labels indicating environmental friendliness (green product labels), this link should be strongest when consumers’ ecological motivation is high. Findings in a series of three experiments support our assumption, showing that consumers with high ecological motivation had strong preferences (i.e., product evaluations, purchase intentions, and simulated purchase decisions) for green-labeled products as compared to consumers with low ecological motivation (Studies 1–3). Crucially, these preferences were robust, despite contradicting environmental product information (Studies 1 and 2). We extended our findings by additionally examining the impact of product labels and motivation on moral self-regulation processes. This was established by assessing participants’ pro-social behavior after the purchase task: participants with high ecological motivation acted, consistent with their motives, more pro-socially in post-decision occasions. In accordance with moral cleansing effects, pro-social behavior was intensified after purchasing conventional products (Studies 2 and 3). Green labels protected participants with high ecological motivation from moral threats due to the purchase, thus making pro-social behavior less likely. Findings suggest that highly ecologically motivated consumers are most susceptible to green labels, which may override detailed product information. PMID:26441767

Desired and Undesired Effects of Energy Labels--An Eye-Tracking Study.

PubMed

Waechter, Signe; Sütterlin, Bernadette; Siegrist, Michael

2015-01-01

Saving energy is an important pillar for the mitigation of climate change. Electric devices (e.g., freezer and television) are an important player in the residential sector in the final demand for energy. Consumers' purchase decisions are therefore crucial to successfully reach the energy-efficiency goals. Putting energy labels on products is often considered an adequate way of empowering consumers to make informed purchase decisions. Consequently, this approach should contribute to reducing overall energy consumption. The effectiveness of its measurement depends on consumers' use and interpretation of the information provided. Despite advances in energy efficiency and a mandatory labeling policy, final energy consumption per capita is in many countries still increasing. This paper provides a systematic analysis of consumers' reactions to one of the most widely used eco-labels, the European Union (EU) energy label, by using eye-tracking methodology as an objective measurement. The study's results partially support the EU's mandatory policy, showing that the energy label triggers attention toward energy information in general. However, the energy label's effect on consumers' actual product choices seems to be rather low. The study's results show that the currently used presentation format on the label is insufficient. The findings suggest that it does not facilitate the integration of energy-related information. Furthermore, the current format can attract consumers to focus more on energy-efficiency information, leading them to disregard information about actual energy consumption. As a result, the final energy consumption may increase because excellent ratings on energy efficiency (e.g., A++) do not automatically imply little consumption. Finally, implications for policymakers and suggestions for further research are discussed.

Use of food label information by urban consumers in India - a study among supermarket shoppers.

PubMed

Vemula, Sudershan R; Gavaravarapu, SubbaRao M; Mendu, Vishnu Vardhana Rao; Mathur, Pulkit; Avula, Laxmaiah

2014-09-01

To study consumer knowledge and use of food labels. A cross-sectional study employing both quantitative and qualitative methods. Intercept interviews were conducted with 1832 consumers at supermarket sites selected using a stratified random sampling procedure. This information was triangulated with twenty-one focus group discussions. New Delhi and Hyderabad, two metro-cities from north and south India. Adolescent (10-19 years), adult (20-59 years) and elderly (≥60 years) consumers. While the national urban literacy rate is 84 %, about 99 % of the study participants were educated. About 45 % reported that they buy pre-packaged foods once weekly and about a fifth buy them every day. Taste, quality, convenience and ease of use are the main reasons for buying pre-packaged foods. Although 90 % of consumers across the age groups read food labels, the majority (81 %) looked only for the manufacturing date or expiry/best before date. Of those who read labels, only a third checked nutrition information and ingredients. Nutrient information on labels was not often read because most consumers either lacked nutrition knowledge or found the information too technical to understand. About 60 % read quality symbols. A positive association was found between education level and checking various aspects of food labels. Women and girls concerned about 'fat' and 'sugar' intake read the nutrition facts panel. The intention of promoting healthy food choices through use of food labels is not being completely met. Since a majority of people found it difficult to comprehend nutrition information, there is a need to take up educational activities and/or introduce new forms of labelling.

Enhanced labelling on alcoholic drinks: reviewing the evidence to guide alcohol policy.

PubMed

Martin-Moreno, Jose M; Harris, Meggan E; Breda, Joao; Møller, Lars; Alfonso-Sanchez, Jose L; Gorgojo, Lydia

2013-12-01

Consumer and public health organizations have called for better labelling on alcoholic drinks. However, there is a lack of consensus about the best elements to include. This review summarizes alcohol labelling policy worldwide and examines available evidence to support enhanced labelling. A literature review was carried out in June-July 2012 on Scopus using the key word 'alcohol' combined with 'allergens', 'labels', 'nutrition information', 'ingredients', 'consumer information' and/or 'warning'. Articles discussing advertising and promotion of alcohol were excluded. A search through Google and the System for Grey Literature in Europe (SIGLE) identified additional sources on alcohol labelling policies, mainly from governmental and organizational websites. Five elements were identified as potentially useful to consumers: (i) a list of ingredients, (ii) nutritional information, (iii) serving size and servings per container, (iv) a definition of 'moderate' intake and (v) a health warning. Alcohol labelling policy with regard to these aspects is quite rudimentary in most countries, with few requiring a list of ingredients or health warnings, and none requiring basic nutritional information. Only one country (Australia) requires serving size and servings per container to be displayed. Our study suggests that there are both potential advantages and disadvantages to providing consumers with more information about alcohol products. Current evidence seems to support prompt inclusion of a list of ingredients, nutritional information (usually only kcal) and health warnings on labels. Standard drink and serving size is useful only when combined with other health education efforts. A definition of 'moderate intake' and recommended drinking guidelines are best suited to other contexts.

Patient-Reported Outcomes Labeling for Products Approved by the Office of Hematology and Oncology Products of the US Food and Drug Administration (2010-2014).

PubMed

Gnanasakthy, Ari; DeMuro, Carla; Clark, Marci; Haydysch, Emily; Ma, Esprit; Bonthapally, Vijayveer

2016-06-01

To review the use of patient-reported outcome (PRO) data in medical product labeling granted by the US Food and Drug Administration (FDA) for new molecular entities and biologic license applications by the FDA Office of Hematology and Oncology Products (OHOP) between January 2010 and December 2014, to elucidate challenges faced by OHOP for approving PRO labeling, and to understand challenges faced by drug manufacturers to include PRO end points in oncology clinical trials. FDA Drug Approval Reports by Month were reviewed to obtain the number of new molecular entities and biologic license applications approved from 2010 to 2014. Drugs approved by the FDA OHOP during this period were selected for further review, focusing on brand and generic name; approval date; applicant; indication; PRO labeling describing treatment benefit, measures, end point status, and significant results; FDA reviewer feedback on PRO end points; and study design of registration trials. First in class, priority review, fast track, orphan drug, or accelerated approval status was retrieved for selected oncology drugs from 2011 to 2014. Descriptive analyses were performed by using Microsoft Excel 2010. Of 160 drugs approved by the FDA (2010-2014), 40 were approved by OHOP. Three (7.5%) of the 40 received PRO-related labeling (abiraterone acetate, ruxolitinib phosphate, and crizotinib). Compared with nononcology drugs (2011-2014), oncology drugs were more likely to be orphan and first in class. The majority of oncology drug reviews by FDA were fast track, priority, or accelerated. Although symptoms and functional decrements are common among patients with cancer, PRO labeling is rare in the United States, likely because of logistical hurdles and oncology study design. Recent developments within the FDA OHOP to capture PROs in oncology studies for the purpose of product labeling are encouraging. © 2016 by American Society of Clinical Oncology.

Vagus nerve stimulation for the treatment of depression and other neuropsychiatric disorders.

PubMed

George, Mark S; Nahas, Ziad; Borckardt, Jeffrey J; Anderson, Berry; Burns, Carol; Kose, Samet; Short, E Baron

2007-01-01

Vagus nerve stimulation is an interesting new approach to treating neuropsychiatric diseases within the class of brain-stimulation devices sometimes labeled 'neuromodulators'. With vagus nerve stimulation, a battery-powered generator implanted in the chest wall connects to a wire wrapped around the vagus nerve in the neck, and sends intermittent pulses of electricity along the nerve directly into the brain. This mechanism takes advantage of the natural role of the vagus nerve in conveying information into the brain concerning homeostatic information (e.g., hunger, chest pain and respirations). Vagus nerve stimulation therapy is US FDA approved for the adjunctive treatment of epilepsy and has recently been FDA approved for the treatment of medication-resistant depression. Owing to its novel route into the brain, it has no drug-drug interactions or systemic side effects. This treatment also appears to have high long-term tolerability in patients, with low rates of patients relapsing on vagus nerve stimulation or becoming tolerant. However, alongside the excitement and enthusiasm for this new treatment, a lack of Class I evidence of efficacy in treating depression is currently slowing down adoption by psychiatrists. Much more research is needed regarding exactly how to refine and deliver the electrical pulses and how this differentially affects brain function in health and disease.

A novel Bayesian framework for discriminative feature extraction in Brain-Computer Interfaces.

PubMed

Suk, Heung-Il; Lee, Seong-Whan

2013-02-01

As there has been a paradigm shift in the learning load from a human subject to a computer, machine learning has been considered as a useful tool for Brain-Computer Interfaces (BCIs). In this paper, we propose a novel Bayesian framework for discriminative feature extraction for motor imagery classification in an EEG-based BCI in which the class-discriminative frequency bands and the corresponding spatial filters are optimized by means of the probabilistic and information-theoretic approaches. In our framework, the problem of simultaneous spatiospectral filter optimization is formulated as the estimation of an unknown posterior probability density function (pdf) that represents the probability that a single-trial EEG of predefined mental tasks can be discriminated in a state. In order to estimate the posterior pdf, we propose a particle-based approximation method by extending a factored-sampling technique with a diffusion process. An information-theoretic observation model is also devised to measure discriminative power of features between classes. From the viewpoint of classifier design, the proposed method naturally allows us to construct a spectrally weighted label decision rule by linearly combining the outputs from multiple classifiers. We demonstrate the feasibility and effectiveness of the proposed method by analyzing the results and its success on three public databases.

Potential effect of physical activity based menu labels on the calorie content of selected fast food meals.

PubMed

Dowray, Sunaina; Swartz, Jonas J; Braxton, Danielle; Viera, Anthony J

2013-03-01

In this study we examined the effect of physical activity based labels on the calorie content of meals selected from a sample fast food menu. Using a web-based survey, participants were randomly assigned to one of four menus which differed only in their labeling schemes (n=802): (1) a menu with no nutritional information, (2) a menu with calorie information, (3) a menu with calorie information and minutes to walk to burn those calories, or (4) a menu with calorie information and miles to walk to burn those calories. There was a significant difference in the mean number of calories ordered based on menu type (p=0.02), with an average of 1020 calories ordered from a menu with no nutritional information, 927 calories ordered from a menu with only calorie information, 916 calories ordered from a menu with both calorie information and minutes to walk to burn those calories, and 826 calories ordered from the menu with calorie information and the number of miles to walk to burn those calories. The menu with calories and the number of miles to walk to burn those calories appeared the most effective in influencing the selection of lower calorie meals (p=0.0007) when compared to the menu with no nutritional information provided. The majority of participants (82%) reported a preference for physical activity based menu labels over labels with calorie information alone and no nutritional information. Whether these labels are effective in real-life scenarios remains to be tested. Copyright © 2012 Elsevier Ltd. All rights reserved.

Consumer knowledge and attitudes to salt intake and labelled salt information.

PubMed

Grimes, Carley A; Riddell, Lynn J; Nowson, Caryl A

2009-10-01

The objective of this study was to investigate consumers' knowledge of health risks of high salt intake and frequency of use and understanding of labelled salt information. We conducted a cross-sectional survey in shopping centres within Metropolitan Melbourne. A sample of 493 subjects was recruited. The questionnaire assessed salt related shopping behaviours, attitudes to salt intake and health and their ability to interpret labelled sodium information. Four hundred and seventy four valid surveys were collected (65% female, 64% being the main shopper). Most participants knew of the relationship between salt intake and high blood pressure (88%). Sixty five percent of participants were unable to correctly identify the relationship between salt and sodium. Sixty nine percent reported reading the salt content of food products when shopping. Salt label usage was significantly related to shoppers concern about the amount of salt in their diet and the belief that their health could improve by lowering salt intake. Approximately half of the sample was unable to accurately use labelled sodium information to pick low salt options. Raising consumer awareness of the health risks associated with high salt consumption may increase salt label usage and purchases of low salt foods. However, for food labels to be effective in helping consumers select low salt foods a more 'user friendly' labelling format is needed.

Medical-device risk management and public safety: using cost-benefit as a measurement of effectiveness

NASA Astrophysics Data System (ADS)

Hughes, Allen A.

1994-12-01

Public safety can be enhanced through the development of a comprehensive medical device risk management. This can be accomplished through case studies using a framework that incorporates cost-benefit analysis in the evaluation of risk management attributes. This paper presents a framework for evaluating the risk management system for regulatory Class III medical devices. The framework consists of the following sixteen attributes of a comprehensive medical device risk management system: fault/failure analysis, premarket testing/clinical trials, post-approval studies, manufacturer sponsored hospital studies, product labeling, establishment inspections, problem reporting program, mandatory hospital reporting, medical literature surveillance, device/patient registries, device performance monitoring, returned product analysis, autopsy program, emergency treatment funds/interim compensation, product liability, and alternative compensation mechanisms. Review of performance histories for several medical devices can reveal the value of information for many attributes, and also the inter-dependencies of the attributes in generating risk information flow. Such an information flow network is presented as a starting point for enhancing medical device risk management by focusing on attributes with high net benefit values and potential to spur information dissemination.

Malaria rapid diagnostic kits: quality of packaging, design and labelling of boxes and components and readability and accuracy of information inserts.

PubMed

Gillet, Philippe; Maltha, Jessica; Hermans, Veerle; Ravinetto, Raffaella; Bruggeman, Cathrien; Jacobs, Jan

2011-02-13

The present study assessed malaria RDT kits for adequate and correct packaging, design and labelling of boxes and components. Information inserts were studied for readability and accuracy of information. Criteria for packaging, design, labelling and information were compiled from Directive 98/79 of the European Community (EC), relevant World Health Organization (WHO) documents and studies on end-users' performance of RDTs. Typography and readability level (Flesch-Kincaid grade level) were assessed. Forty-two RDT kits from 22 manufacturers were assessed, 35 of which had evidence of good manufacturing practice according to available information (i.e. CE-label affixed or inclusion in the WHO list of ISO13485:2003 certified manufacturers). Shortcomings in devices were (i) insufficient place for writing sample identification (n=40) and (ii) ambiguous labelling of the reading window (n=6). Buffer vial labels were lacking essential information (n=24) or were of poor quality (n=16). Information inserts had elevated readability levels (median Flesch Kincaid grade 8.9, range 7.1-12.9) and user-unfriendly typography (median font size 8, range 5-10). Inadequacies included (i) no referral to biosafety (n=18), (ii) critical differences between depicted and real devices (n=8), (iii) figures with unrealistic colours (n=4), (iv) incomplete information about RDT line interpretations (n=31) and no data on test characteristics (n=8). Other problems included (i) kit names that referred to Plasmodium vivax although targeting a pan-species Plasmodium antigen (n=4), (ii) not stating the identity of the pan-species antigen (n=2) and (iii) slight but numerous differences in names displayed on boxes, device packages and information inserts. Three CE labelled RDT kits produced outside the EC had no authorized representative affixed and the shape and relative dimensions of the CE symbol affixed did not comply with the Directive 98/79/EC. Overall, RDTs with evidence of GMP scored better compared to those without but inadequacies were observed in both groups. Overall, malaria RDTs showed shortcomings in quality of construction, design and labelling of boxes, device packages, devices and buffers. Information inserts were difficult to read and lacked relevant information.

77 FR 49818 - Agency Information Collection Activities; Proposed Collection; Comment Request; Bar Code Label...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-17

...] Agency Information Collection Activities; Proposed Collection; Comment Request; Bar Code Label... allow 60 days for public comment in response to the notice. This notice solicits comments on the bar... technology. Bar Code Label Requirement for Human Drug and Biological Products--(OMB Control Number 0910-0537...

16 CFR 1633.12 - Labeling.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 2 2010-01-01 2010-01-01 false Labeling. 1633.12 Section 1633.12 Commercial... (OPEN FLAME) OF MATTRESS SETS Rules and Regulations § 1633.12 Labeling. (a) Each mattress set subject to... information (and no other information) in English: (1) Name of the manufacturer, or for imported mattress sets...

78 FR 57394 - Draft Guidance for Industry on Patient Counseling Information Section of Labeling for Human...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-18

...The Food and Drug Administration (FDA) is announcing the availability of a draft guidance for industry entitled ``Patient Counseling Information Section of Labeling for Human Prescription Drug and Biological Products--Content and Format.'' The recommendations in the draft guidance are intended to help ensure that the labeling is clear, useful, informative, and to the extent possible, consistent in content and format.

75 FR 80823 - Agency Information Collection Activities: Proposed Collection; Comment Request; Guidance for...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-23

...] Agency Information Collection Activities: Proposed Collection; Comment Request; Guidance for Industry on Updating Labeling for Susceptibility Test Information in Systemic Antibacterial Drug Products and... Industry on Updating Labeling for Susceptibility Test Information in Systemic Antibacterial Drug Products...

21 CFR 101.56 - Nutrient content claims for “light” or “lite.”

Code of Federal Regulations, 2013 CFR

2013-04-01

...) Quantitative information comparing the level of calories and fat content in the product per labeled serving... information panel, the quantitative information may be located elsewhere on the information panel in... sauce); and (B) Quantitative information comparing the level of sodium per labeled serving size with...

21 CFR 101.56 - Nutrient content claims for “light” or “lite.”

Code of Federal Regulations, 2011 CFR

2011-04-01

...) Quantitative information comparing the level of calories and fat content in the product per labeled serving... information panel, the quantitative information may be located elsewhere on the information panel in... sauce); and (B) Quantitative information comparing the level of sodium per labeled serving size with...

21 CFR 101.56 - Nutrient content claims for “light” or “lite.”

Code of Federal Regulations, 2014 CFR

2014-04-01

...) Quantitative information comparing the level of calories and fat content in the product per labeled serving... information panel, the quantitative information may be located elsewhere on the information panel in... sauce); and (B) Quantitative information comparing the level of sodium per labeled serving size with...

21 CFR 101.56 - Nutrient content claims for “light” or “lite.”

Code of Federal Regulations, 2012 CFR

2012-04-01

...) Quantitative information comparing the level of calories and fat content in the product per labeled serving... information panel, the quantitative information may be located elsewhere on the information panel in... sauce); and (B) Quantitative information comparing the level of sodium per labeled serving size with...

21 CFR 101.56 - Nutrient content claims for “light” or “lite.”

Code of Federal Regulations, 2010 CFR

2010-04-01

...) Quantitative information comparing the level of calories and fat content in the product per labeled serving... information panel, the quantitative information may be located elsewhere on the information panel in... sauce); and (B) Quantitative information comparing the level of sodium per labeled serving size with...

Automated egg grading system using computer vision: Investigation on weight measure versus shape parameters

NASA Astrophysics Data System (ADS)

Nasir, Ahmad Fakhri Ab; Suhaila Sabarudin, Siti; Majeed, Anwar P. P. Abdul; Ghani, Ahmad Shahrizan Abdul

2018-04-01

Chicken egg is a source of food of high demand by humans. Human operators cannot work perfectly and continuously when conducting egg grading. Instead of an egg grading system using weight measure, an automatic system for egg grading using computer vision (using egg shape parameter) can be used to improve the productivity of egg grading. However, early hypothesis has indicated that more number of egg classes will change when using egg shape parameter compared with using weight measure. This paper presents the comparison of egg classification by the two above-mentioned methods. Firstly, 120 images of chicken eggs of various grades (A–D) produced in Malaysia are captured. Then, the egg images are processed using image pre-processing techniques, such as image cropping, smoothing and segmentation. Thereafter, eight egg shape features, including area, major axis length, minor axis length, volume, diameter and perimeter, are extracted. Lastly, feature selection (information gain ratio) and feature extraction (principal component analysis) are performed using k-nearest neighbour classifier in the classification process. Two methods, namely, supervised learning (using weight measure as graded by egg supplier) and unsupervised learning (using egg shape parameters as graded by ourselves), are conducted to execute the experiment. Clustering results reveal many changes in egg classes after performing shape-based grading. On average, the best recognition results using shape-based grading label is 94.16% while using weight-based label is 44.17%. As conclusion, automated egg grading system using computer vision is better by implementing shape-based features since it uses image meanwhile the weight parameter is more suitable by using weight grading system.

Voxel-based plaque classification in coronary intravascular optical coherence tomography images using decision trees

NASA Astrophysics Data System (ADS)

Kolluru, Chaitanya; Prabhu, David; Gharaibeh, Yazan; Wu, Hao; Wilson, David L.

2018-02-01

Intravascular Optical Coherence Tomography (IVOCT) is a high contrast, 3D microscopic imaging technique that can be used to assess atherosclerosis and guide stent interventions. Despite its advantages, IVOCT image interpretation is challenging and time consuming with over 500 image frames generated in a single pullback volume. We have developed a method to classify voxel plaque types in IVOCT images using machine learning. To train and test the classifier, we have used our unique database of labeled cadaver vessel IVOCT images accurately registered to gold standard cryoimages. This database currently contains 300 images and is growing. Each voxel is labeled as fibrotic, lipid-rich, calcified or other. Optical attenuation, intensity and texture features were extracted for each voxel and were used to build a decision tree classifier for multi-class classification. Five-fold cross-validation across images gave accuracies of 96 % +/- 0.01 %, 90 +/- 0.02% and 90 % +/- 0.01 % for fibrotic, lipid-rich and calcified classes respectively. To rectify performance degradation seen in left out vessel specimens as opposed to left out images, we are adding data and reducing features to limit overfitting. Following spatial noise cleaning, important vascular regions were unambiguous in display. We developed displays that enable physicians to make rapid determination of calcified and lipid regions. This will inform treatment decisions such as the need for devices (e.g., atherectomy or scoring balloon in the case of calcifications) or extended stent lengths to ensure coverage of lipid regions prone to injury at the edge of a stent.

Can front-of-pack labelling schemes guide healthier food choices? Australian shoppers' responses to seven labelling formats.

PubMed

Watson, Wendy L; Kelly, Bridget; Hector, Debra; Hughes, Clare; King, Lesley; Crawford, Jennifer; Sergeant, John; Chapman, Kathy

2014-01-01

There is evidence that easily accessible, comprehensible and consistent nutrient information on the front of packaged foods could assist shoppers to make healthier food choices. This study used an online questionnaire of 4357 grocery shoppers to examine Australian shoppers' ability to use a range of front-of-pack labels to identify healthier food products. Seven different front-of-pack labelling schemes comprising variants of the Traffic Light labelling scheme and the Percentage Daily Intake scheme, and a star rating scheme, were applied to nine pairs of commonly purchased food products. Participants could also access a nutrition information panel for each product. Participants were able to identify the healthier product in each comparison over 80% of the time using any of the five schemes that provided information on multiple nutrients. No individual scheme performed significantly better in terms of shoppers' ability to determine the healthier product, shopper reliance on the 'back-of-pack' nutrition information panel, and speed of use. The scheme that provided information about energy only and a scheme with limited numerical information of nutrient type or content performed poorly, as did the nutrition information panel alone (control). Further consumer testing is necessary to determine the optimal format and content of an interpretive front-of-pack nutrition labelling scheme. Copyright © 2013 Elsevier Ltd. All rights reserved.

A qualitative study of consumer perceptions and use of traffic light food labelling in Ecuador.

PubMed

Freire, Wilma B; Waters, William F; Rivas-Mariño, Gabriela; Nguyen, Tien; Rivas, Patricio

2017-04-01

To analyse patterns of knowledge, comprehension, attitudes and practices regarding the traffic light label placed on processed food packages to inform Ecuadorian consumers about levels of added fat, sugar and salt. Twenty-one focus group discussions organized by age group, sex and place of residence. Interviews with representatives of companies that manufacture or market processed foods. Analysis of regulations and structured observations of processed food labels. Cities and towns in Ecuador's coastal, highland and eastern lowland regions. One hundred and seventy-eight participants in twenty-one focus group discussions and nine key informants. Focus group participants knew about the traffic light label and understood the information it conveys, but not all changed their attitudes and practices related to the purchase and consumption of processed foods. Children, adolescents and adult males reported using the information infrequently; adolescents interested in health and adult women used the label the most to select products. Representatives of companies that manufacture or market processed foods generally opposed the policy, stating that the information is misleading. Nevertheless, some companies have reduced levels of added fat, sugar or salt in their products. The traffic light label is an effective tool for conveying complex information. Its potential contribution to reduce consumption of products with high levels of fat, sugar and salt could be enhanced by promoting healthy diets among consumers who have not changed purchasing and consumption behaviour, by placing the label on front panels and by monitoring the production and marketing of processed foods.

Holographic Labeling And Reading Machine For Authentication And Security Appications

DOEpatents

Weber, David C.; Trolinger, James D.

1999-07-06

A holographic security label and automated reading machine for marking and subsequently authenticating any object such as an identification badge, a pass, a ticket, a manufactured part, or a package is described. The security label is extremely difficult to copy or even to read by unauthorized persons. The system comprises a holographic security label that has been created with a coded reference wave, whose specification can be kept secret. The label contains information that can be extracted only with the coded reference wave, which is derived from a holographic key, which restricts access of the information to only the possessor of the key. A reading machine accesses the information contained in the label and compares it with data stored in the machine through the application of a joint transform correlator, which is also equipped with a reference hologram that adds additional security to the procedure.

Synthesis of Cryptophycin Affinity Labels and Tubulin Labeling

DTIC Science & Technology

2006-05-01

Nostoc sp.), are a new and potent tumor-selective class of tubulin-binding antimitotic agents1 that show excellent activity against MDR cancer cell...lines and were exceptionally active against mammary derived tumors.2,3 Cryptophycin-1 (1, Fig. 1) is the major cytotoxin in Nostoc sp.4,5 and...arenastatin A), isolated from the Okinawan marine sponge Dysidea arenaria6 and later from Nostoc sp. strain GSV 224,7 is also a potent inhibitor of tubulin

Synthesis of Cryptophycin Affinity Labels and Tubulin Labeling

DTIC Science & Technology

2004-05-01

isolated from blue-green algae ( Nostoc sp.), are a new and potent tumor-selective class of tubulin-binding antimitotic agents that show excellent activity... Nostoc sp.3𔃾 and displays IC 50 values in the pM range. Of special importance is the reduced susceptibility of the cryptophycins to P-glycoprotein...also named arenastatin A), isolated from the Okinawan marine sponge Dysidea arenaria5 and later from Nostoc sp. strain GSV 224,6 is also a potent

Synthesis of Cryptophycin Affinity Labels and Tubulin Labeling

DTIC Science & Technology

2005-05-01

isolated from blue-green algae ( Nostoc sp.), are a new and potent tumor-selective class of tubulin-binding antimitotic agents’ that show excellent activity... Nostoc sp. 4𔃿 and displays IC 5 0 values in the pM range. Of special importance is the reduced susceptibility of the cryptophycins to P-glycoprotein...also named arenastatin A), isolated from the Okinawan marine sponge Dysidea arenaria6 and later from Nostoc sp. strain GSV 224,7 is also a potent

Chromosome-encoded beta-lactamases of Citrobacter diversus. Interaction with beta-iodopenicillanate and labelling of the active site.

PubMed Central

Amicosante, G; Oratore, A; Joris, B; Galleni, M; Frère, J M; Van Beeumen, J

1988-01-01

Both forms of the chromosome-encoded beta-lactamase of Citrobacter diversus react with beta-iodopenicillanate at a rate characteristic of class A beta-lactamases. The active site of form I was labelled with the same reagent. The sequence of the peptide obtained after trypsin hydrolysis is identical with that of a peptide obtained in a similar manner from the chromosome-encoded beta-lactamase of Klebsiella pneumoniae. PMID:2848500

GEO Label Web Services for Dynamic and Effective Communication of Geospatial Metadata Quality

NASA Astrophysics Data System (ADS)

Lush, Victoria; Nüst, Daniel; Bastin, Lucy; Masó, Joan; Lumsden, Jo

2014-05-01

We present demonstrations of the GEO label Web services and their integration into a prototype extension of the GEOSS portal (http://scgeoviqua.sapienzaconsulting.com/web/guest/geo_home), the GMU portal (http://gis.csiss.gmu.edu/GADMFS/) and a GeoNetwork catalog application (http://uncertdata.aston.ac.uk:8080/geonetwork/srv/eng/main.home). The GEO label is designed to communicate, and facilitate interrogation of, geospatial quality information with a view to supporting efficient and effective dataset selection on the basis of quality, trustworthiness and fitness for use. The GEO label which we propose was developed and evaluated according to a user-centred design (UCD) approach in order to maximise the likelihood of user acceptance once deployed. The resulting label is dynamically generated from producer metadata in ISO or FDGC format, and incorporates user feedback on dataset usage, ratings and discovered issues, in order to supply a highly informative summary of metadata completeness and quality. The label was easily incorporated into a community portal as part of the GEO Architecture Implementation Programme (AIP-6) and has been successfully integrated into a prototype extension of the GEOSS portal, as well as the popular metadata catalog and editor, GeoNetwork. The design of the GEO label was based on 4 user studies conducted to: (1) elicit initial user requirements; (2) investigate initial user views on the concept of a GEO label and its potential role; (3) evaluate prototype label visualizations; and (4) evaluate and validate physical GEO label prototypes. The results of these studies indicated that users and producers support the concept of a label with drill-down interrogation facility, combining eight geospatial data informational aspects, namely: producer profile, producer comments, lineage information, standards compliance, quality information, user feedback, expert reviews, and citations information. These are delivered as eight facets of a wheel-like label, which are coloured according to metadata availability and are clickable to allow a user to engage with the original metadata and explore specific aspects in more detail. To support this graphical representation and allow for wider deployment architectures we have implemented two Web services, a PHP and a Java implementation, that generate GEO label representations by combining producer metadata (from standard catalogues or other published locations) with structured user feedback. Both services accept encoded URLs of publicly available metadata documents or metadata XML files as HTTP POST and GET requests and apply XPath and XSLT mappings to transform producer and feedback XML documents into clickable SVG GEO label representations. The label and services are underpinned by two XML-based quality models. The first is a producer model that extends ISO 19115 and 19157 to allow fuller citation of reference data, presentation of pixel- and dataset- level statistical quality information, and encoding of 'traceability' information on the lineage of an actual quality assessment. The second is a user quality model (realised as a feedback server and client) which allows reporting and query of ratings, usage reports, citations, comments and other domain knowledge. Both services are Open Source and are available on GitHub at https://github.com/lushv/geolabel-service and https://github.com/52North/GEO-label-java. The functionality of these services can be tested using our GEO label generation demos, available online at http://www.geolabel.net/demo.html and http://geoviqua.dev.52north.org/glbservice/index.jsf.

The effects of calorie information on food selection and intake.

PubMed

Girz, L; Polivy, J; Herman, C P; Lee, H

2012-10-01

To examine the effects of calorie labeling on food selection and intake in dieters and non-dieters, and to explore whether expectations about food healthfulness moderate these effects. Participants were presented with a menu containing two items, a salad and a pasta dish. The menu had (a) no calorie information, (b) information that the salad was low in calories and the pasta was high in calories, (c) information that the salad was high in calories and the pasta was low in calories or (d) information that both were high in calories (study 2 only). Calorie labels influenced food selection for dieters, but not for non-dieters. Dieters were more likely to order salad when the salad was labeled as low in calories and more likely to order pasta, even high-calorie pasta, when the salad was labeled as high in calories. Participants who chose high-calorie foods over low-calorie foods did not eat less in response to calorie information, although non-dieters reduced their intake somewhat when calorie labels were put in the context of recommended daily calories. The results suggest that the rush to provide calorie information may not prove to be the best approach to fighting the obesity epidemic.

Probabilistic atlas based labeling of the cerebral vessel tree

NASA Astrophysics Data System (ADS)

Van de Giessen, Martijn; Janssen, Jasper P.; Brouwer, Patrick A.; Reiber, Johan H. C.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

2015-03-01

Preoperative imaging of the cerebral vessel tree is essential for planning therapy on intracranial stenoses and aneurysms. Usually, a magnetic resonance angiography (MRA) or computed tomography angiography (CTA) is acquired from which the cerebral vessel tree is segmented. Accurate analysis is helped by the labeling of the cerebral vessels, but labeling is non-trivial due to anatomical topological variability and missing branches due to acquisition issues. In recent literature, labeling the cerebral vasculature around the Circle of Willis has mainly been approached as a graph-based problem. The most successful method, however, requires the definition of all possible permutations of missing vessels, which limits application to subsets of the tree and ignores spatial information about the vessel locations. This research aims to perform labeling using probabilistic atlases that model spatial vessel and label likelihoods. A cerebral vessel tree is aligned to a probabilistic atlas and subsequently each vessel is labeled by computing the maximum label likelihood per segment from label-specific atlases. The proposed method was validated on 25 segmented cerebral vessel trees. Labeling accuracies were close to 100% for large vessels, but dropped to 50-60% for small vessels that were only present in less than 50% of the set. With this work we showed that using solely spatial information of the vessel labels, vessel segments from stable vessels (>50% presence) were reliably classified. This spatial information will form the basis for a future labeling strategy with a very loose topological model.

Cryopreservation of MHC multimers: Recommendations for quality assurance in detection of antigen specific T cells.

PubMed

Hadrup, Sine Reker; Maurer, Dominik; Laske, Karoline; Frøsig, Thomas Mørch; Andersen, Sofie Ramskov; Britten, Cedrik M; van der Burg, Sjoerd H; Walter, Steffen; Gouttefangeas, Cécile

2015-01-01

Fluorescence-labeled peptide-MHC class I multimers serve as ideal tools for the detection of antigen-specific T cells by flow cytometry, enabling functional and phenotypical characterization of specific T cells at the single cell level. While this technique offers a number of unique advantages, MHC multimer reagents can be difficult to handle in terms of stability and quality assurance. The stability of a given fluorescence-labeled MHC multimer complex depends on both the stability of the peptide-MHC complex itself and the stability of the fluorochrome. Consequently, stability is difficult to predict and long-term storage is generally not recommended. We investigated here the possibility of cryopreserving MHC multimers, both in-house produced and commercially available, using a wide range of peptide-MHC class I multimers comprising virus and cancer-associated epitopes of different affinities presented by various HLA-class I molecules. Cryopreservation of MHC multimers was feasible for at least 6 months, when they were dissolved in buffer containing 5-16% glycerol (v/v) and 0.5% serum albumin (w/v). The addition of cryoprotectants was tolerated across three different T-cell staining protocols for all fluorescence labels tested (PE, APC, PE-Cy7 and Quantum dots). We propose cryopreservation as an easily implementable method for stable storage of MHC multimers and recommend the use of cryopreservation in long-term immunomonitoring projects, thereby eliminating the variability introduced by different batches and inconsistent stability. © 2014 International Society for Advancement of Cytometry.

A combined analysis of the Frost Multidimensional Perfectionism Scale (FMPS), Child and Adolescent Perfectionism Scale (CAPS), and Almost Perfect Scale-Revised (APS-R): Different perfectionist profiles in adolescent high school students.

PubMed

Sironic, Amanda; Reeve, Robert A

2015-12-01

To investigate differences and similarities in the dimensional constructs of the Frost Multidimensional Perfectionism Scale (FMPS; Frost, Marten, Lahart, & Rosenblate, 1990), Child and Adolescent Perfectionism Scale (CAPS; Flett, Hewitt, Boucher, Davidson, & Munro, 2000), and Almost Perfect Scale-Revised (APS-R; Slaney, Rice, Mobley, Trippi, & Ashby, 2001), 938 high school students completed the 3 perfectionism questionnaires, as well as the Depression Anxiety Stress Scales (DASS; Lovibond & Lovibond, 1995). Preliminary analyses revealed commonly observed factor structures for each perfectionism questionnaire. Exploratory factor analysis of item responses from the questionnaires (combined) yielded a 4-factor solution (factors were labeled High Personal Standards, Concerns, Doubts and Discrepancy, Externally Motivated Perfectionism, and Organization and Order). A latent class analysis of individuals' mean ratings on each of the 4 factors yielded a 6-class solution. Three of the 6 classes represented perfectionist subgroups (labeled adaptive perfectionist, externally motivated maladaptive perfectionist, and mixed maladaptive perfectionist), and 3 represented nonperfectionist subgroups (labeled nonperfectionist A, nonperfectionist B, and order and organization nonperfectionist). Each of the 6 subgroups was meaningfully associated with the DASS. Findings showed that 3 out of 10 students were classified as maladaptive perfectionists, and maladaptive perfectionists were more prevalent than adaptive perfectionists. In sum, it is evident that combined ratings from the FMPS, CAPS, and APS-R offer a meaningful characterization of perfectionism. (c) 2015 APA, all rights reserved).

Cryopreservation of MHC Multimers: Recommendations for Quality Assurance in Detection of Antigen Specific T Cells

PubMed Central

Hadrup, Sine Reker; Maurer, Dominik; Laske, Karoline; Frøsig, Thomas Mørch; Andersen, Sofie Ramskov; Britten, Cedrik M; van der Burg, Sjoerd H; Walter, Steffen; Gouttefangeas, Cécile

2015-01-01

Fluorescence-labeled peptide-MHC class I multimers serve as ideal tools for the detection of antigen-specific T cells by flow cytometry, enabling functional and phenotypical characterization of specific T cells at the single cell level. While this technique offers a number of unique advantages, MHC multimer reagents can be difficult to handle in terms of stability and quality assurance. The stability of a given fluorescence-labeled MHC multimer complex depends on both the stability of the peptide-MHC complex itself and the stability of the fluorochrome. Consequently, stability is difficult to predict and long-term storage is generally not recommended. We investigated here the possibility of cryopreserving MHC multimers, both in-house produced and commercially available, using a wide range of peptide-MHC class I multimers comprising virus and cancer-associated epitopes of different affinities presented by various HLA-class I molecules. Cryopreservation of MHC multimers was feasible for at least 6 months, when they were dissolved in buffer containing 5–16% glycerol (v/v) and 0.5% serum albumin (w/v). The addition of cryoprotectants was tolerated across three different T-cell staining protocols for all fluorescence labels tested (PE, APC, PE-Cy7 and Quantum dots). We propose cryopreservation as an easily implementable method for stable storage of MHC multimers and recommend the use of cryopreservation in long-term immunomonitoring projects, thereby eliminating the variability introduced by different batches and inconsistent stability. © 2014 International Society for Advancement of Cytometry PMID:25297339

Current Status of Pediatric Labeling in China and the near Future Efforts Needed for the Country

PubMed Central

Li, Zhiping; Wang, Yi; Wu, Dan; Gao, Xuan; Wang, Zhiyun

2014-01-01

Background: Children are recognized as “therapeutic orphan” in many parts of the world, one expression of this is the lack of adequate pediatric labeling information. Some research studies have been done to investigate the pediatric labeling condition in the U.S. and other countries, but no national studies had been carried out in China. This survey was conducted aiming to inquire the current situation of pediatric labeling in China. Methods: We investigated 6020 child-applied medicines from 15 representative Chinese hospitals, and analyzed the information according to the dosage forms, therapeutic category, and label information integrity. Results: Among all these medicines, only 238 (3.95%) are pediatric products, the rest are adult formulations with an extended use in children. The major pediatric formulations were injection (45.95%), tablet (23.69%), and capsule (4.93%), respectively. Alimentary tract/metabolism medicine (24.70%) and infections medicines (20.60%) had the most species. In prescription drugs, only 210 of 5187 (4%) medicines had adequate pediatric labeling information. The main cause of this deficiency was lack of evidence derived from pediatric clinical trials. Conclusion: The dilemma of “therapeutic orphan” requires significant attention. Inadequate labeling information and lack of pediatric clinical trials were two prominent issues in China. It calls for more efforts from pharmaceutical industries, regulatory agencies, and legislature in China to collaborate and find solution to improve the situation. PMID:24724075

Recognition and Quantification of Area Damaged by Oligonychus Perseae in Avocado Leaves

NASA Astrophysics Data System (ADS)

Díaz, Gloria; Romero, Eduardo; Boyero, Juan R.; Malpica, Norberto

The measure of leaf damage is a basic tool in plant epidemiology research. Measuring the area of a great number of leaves is subjective and time consuming. We investigate the use of machine learning approaches for the objective segmentation and quantification of leaf area damaged by mites in avocado leaves. After extraction of the leaf veins, pixels are labeled with a look-up table generated using a Support Vector Machine with a polynomial kernel of degree 3, on the chrominance components of YCrCb color space. Spatial information is included in the segmentation process by rating the degree of membership to a certain class and the homogeneity of the classified region. Results are presented on real images with different degrees of damage.

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

PubMed Central

Wang, Yun; Huang, Fangzhou

2018-01-01

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible. PMID:29666661

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

PubMed

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

2018-01-01

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

A Bayesian Approach to a Multiple-Group Latent Class-Profile Analysis: The Timing of Drinking Onset and Subsequent Drinking Behaviors among U.S. Adolescents

ERIC Educational Resources Information Center

Chung, Hwan; Anthony, James C.

2013-01-01

This article presents a multiple-group latent class-profile analysis (LCPA) by taking a Bayesian approach in which a Markov chain Monte Carlo simulation is employed to achieve more robust estimates for latent growth patterns. This article describes and addresses a label-switching problem that involves the LCPA likelihood function, which has…

30 CFR 47.43 - Label alternatives.

Code of Federal Regulations, 2010 CFR

2010-07-01

... COMMUNICATION (HazCom) Container Labels and Other Forms of Warning § 47.43 Label alternatives. The operator may... container to which it applies, (b) Communicates the same information as required on the label, and (c) Is...

The Drug Facts Box: Improving the communication of prescription drug information.

PubMed

Schwartz, Lisa M; Woloshin, Steven

2013-08-20

Communication about prescription drugs ought to be a paragon of public science communication. Unfortunately, it is not. Consumers see $4 billion of direct-to-consumer advertising annually, which typically fails to present data about how well drugs work. The professional label--the Food and Drug Administration's (FDA) mechanism to get physicians information needed for appropriate prescribing--may also fail to present benefit data. FDA labeling guidance, in fact, suggests that industry omit benefit data for new drugs in an existing class and for drugs approved on the basis of unfamiliar outcomes (such as depression rating scales). The medical literature is also problematic: there is selective reporting of favorable trials, favorable outcomes within trials, and "spinning" unfavorable results to maximize benefit and minimize harm. In contrast, publicly available FDA reviews always include the phase 3 trial data on benefit and harm, which are the basis of drug approval. However, these reviews are practically inaccessible: lengthy, poorly organized, and weakly summarized. To improve accessibility, we developed the Drug Facts Box: a one-page summary of benefit and harm data for each indication of a drug. A series of studies--including national randomized trials--demonstrates that most consumers understand the Drug Facts Box and that it improves decision-making. Despite calls from their own Risk Communication Advisory Committee and Congress (in the Affordable Care Act) to consider implementing boxes, the FDA announced it needs at least 3-5 y more to make a decision. Given its potential public health impact, physicians and the public should not have to wait that long for better drug information.

Nutritional supplement products: Does the label information influence purchasing decisions for the physically active?

PubMed

Gabriels, Gary; Lambert, Mike

2013-10-02

The increase in sales of nutritional supplement globally can be attributed, in part, to aggressive marketing by manufacturers, rather than because the nutritional supplements have become more effective. Furthermore, the accuracy of the labelling often goes unchallenged. Therefore, any effects of the supplement, may be due to contaminants or adulterants in these products not reflected on the label. A self-administered questionnaire was used to determine how consumers of nutritional supplements acquired information to assist their decision-making processes, when purchasing a product. The study was approved by the University of Cape Town, Faculty of Health Sciences Human Research Ethics Committee. The questionnaire consisted of seven, closed and open-ended questions. The participants were asked to respond to the questions according to a defined list of statements. A total of 259 participants completed and returned questionnaires. The data and processing of the returned questionnaires was captured using Windows-based Microsoft® Office Excel 2003 SP 1 (Excel © 1985-2003 Microsoft Corporation). Statistica Version 10 (copyright © Stat Soft, Inc. 1984-2011) was used to calculate the descriptive statistics. The main finding of the study was that nearly 70% of the respondents who purchased supplements were strongly influenced by container label information that stipulated that the nutritional supplement product is free of banned substances. The second finding was that just over 50% of the respondents attached importance to the quality of the nutritional supplement product information on the container label. The third finding was that about 40% of the respondents were strongly influenced by the ingredients on the labels when they purchased nutritional supplements. This study, (i) identifies short-comings in current labelling information practices, (ii) provides opportunities to improve label and non-label information and communication, and, (iii) presents the case for quality assurance laboratory "screening testing" of declared and undeclared contaminants and/or adulterants, that could have negative consequences to the consumer.

Nutritional supplement products: does the label information influence purchasing decisions for the physically active?

PubMed Central

2013-01-01

Background The increase in sales of nutritional supplement globally can be attributed, in part, to aggressive marketing by manufacturers, rather than because the nutritional supplements have become more effective. Furthermore, the accuracy of the labelling often goes unchallenged. Therefore, any effects of the supplement, may be due to contaminants or adulterants in these products not reflected on the label. Methods A self-administered questionnaire was used to determine how consumers of nutritional supplements acquired information to assist their decision-making processes, when purchasing a product. The study was approved by the University of Cape Town, Faculty of Health Sciences Human Research Ethics Committee. The questionnaire consisted of seven, closed and open-ended questions. The participants were asked to respond to the questions according to a defined list of statements. A total of 259 participants completed and returned questionnaires. The data and processing of the returned questionnaires was captured using Windows-based Microsoft® Office Excel 2003 SP 1 (Excel © 1985–2003 Microsoft Corporation). Statistica Version 10 (copyright © Stat Soft, Inc. 1984–2011) was used to calculate the descriptive statistics. Results The main finding of the study was that nearly 70% of the respondents who purchased supplements were strongly influenced by container label information that stipulated that the nutritional supplement product is free of banned substances. The second finding was that just over 50% of the respondents attached importance to the quality of the nutritional supplement product information on the container label. The third finding was that about 40% of the respondents were strongly influenced by the ingredients on the labels when they purchased nutritional supplements. Conclusion This study, (i) identifies short-comings in current labelling information practices, (ii) provides opportunities to improve label and non-label information and communication, and, (iii) presents the case for quality assurance laboratory “screening testing” of declared and undeclared contaminants and/or adulterants, that could have negative consequences to the consumer. PMID:24088193

Menu labeling: the unintended consequences to the consumer.

PubMed

Black, Ellen A

2014-01-01

The Affordable Care Act requires certain restaurants to provide nutritional information on their menus and menu boards, which is referred to as menu labeling. Menu labeling presupposes that providing consumers with the nutritional information about their food will cause them to reconsider their food choices by picking healthier food options over less healthy options, thereby reducing the nation's high obesity rate. However, several studies have shown that consumers do not make healthier food choices even when armed with menu labeling. The issue then becomes whether menu labeling provides a correlative benefit to consumers or whether there are unintended consequences that ultimately harm consumers.

Prioritising lexical patterns to increase axiomatisation in biomedical ontologies. The role of localisation and modularity.

PubMed

Quesada-Martínez, M; Fernández-Breis, J T; Stevens, R; Mikroyannidi, E

2015-01-01

This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". In previous work, we have defined methods for the extraction of lexical patterns from labels as an initial step towards semi-automatic ontology enrichment methods. Our previous findings revealed that many biomedical ontologies could benefit from enrichment methods using lexical patterns as a starting point.Here, we aim to identify which lexical patterns are appropriate for ontology enrichment, driving its analysis by metrics to prioritised the patterns. We propose metrics for suggesting which lexical regularities should be the starting point to enrich complex ontologies. Our method determines the relevance of a lexical pattern by measuring its locality in the ontology, that is, the distance between the classes associated with the pattern, and the distribution of the pattern in a certain module of the ontology. The methods have been applied to four significant biomedical ontologies including the Gene Ontology and SNOMED CT. The metrics provide information about the engineering of the ontologies and the relevance of the patterns. Our method enables the suggestion of links between classes that are not made explicit in the ontology. We propose a prioritisation of the lexical patterns found in the analysed ontologies. The locality and distribution of lexical patterns offer insights into the further engineering of the ontology. Developers can use this information to improve the axiomatisation of their ontologies.

Explicit Versus Implicit "Halal" Information: Influence of the Halal Label and the Country-of-Origin Information on Product Perceptions in Indonesia.

PubMed

Maison, Dominika; Marchlewska, Marta; Syarifah, Dewi; Zein, Rizqy A; Purba, Herison P

2018-01-01

Halal refers to what is permissible in traditional Islamic law. Food that meets halal requirements is marked by a halal label on the packaging and should be especially attractive to those Muslims who follow the set of dietary laws outlined in the Quran. This research examines the role of the halal label (explicit cue) and the country-of-origin (COO) (implicit cue) in predicting positive product perceptions among Muslim consumers. We hypothesized that when an explicit sign of "halalness" (i.e., halal label) relating to a particular product is accompanied by an implicit sign of anti - "halalness" (i.e., non-Islamic COO information), Muslim consumers who pay attention to the dietary laws of Islam would have negative perceptions of such a product. We tested our assumptions in an experiment conducted among Indonesian participants who declared themselves as Muslims ( n = 444). We manipulated: (a) exposure to the halal label, and (b) the COO information. Religion-based purchase behavior was measured as a moderator variable. Positive product perceptions were measured as a dependent variable. The results showed that the halal label itself had limited influence on product perceptions. However, we found that positive product perceptions significantly decreased among people who were high in religion-based purchase behavior in response to exposure to non-Islamic COO information accompanied by a halal label. In conclusion, people who are high (vs. low) in religion-based purchase behavior do not seem to trust halal-labeled food produced in a country with other than an Islamic tradition.

Explicit Versus Implicit “Halal” Information: Influence of the Halal Label and the Country-of-Origin Information on Product Perceptions in Indonesia

PubMed Central

Maison, Dominika; Marchlewska, Marta; Syarifah, Dewi; Zein, Rizqy A.; Purba, Herison P.

2018-01-01

Halal refers to what is permissible in traditional Islamic law. Food that meets halal requirements is marked by a halal label on the packaging and should be especially attractive to those Muslims who follow the set of dietary laws outlined in the Quran. This research examines the role of the halal label (explicit cue) and the country-of-origin (COO) (implicit cue) in predicting positive product perceptions among Muslim consumers. We hypothesized that when an explicit sign of “halalness” (i.e., halal label) relating to a particular product is accompanied by an implicit sign of anti-“halalness” (i.e., non-Islamic COO information), Muslim consumers who pay attention to the dietary laws of Islam would have negative perceptions of such a product. We tested our assumptions in an experiment conducted among Indonesian participants who declared themselves as Muslims (n = 444). We manipulated: (a) exposure to the halal label, and (b) the COO information. Religion-based purchase behavior was measured as a moderator variable. Positive product perceptions were measured as a dependent variable. The results showed that the halal label itself had limited influence on product perceptions. However, we found that positive product perceptions significantly decreased among people who were high in religion-based purchase behavior in response to exposure to non-Islamic COO information accompanied by a halal label. In conclusion, people who are high (vs. low) in religion-based purchase behavior do not seem to trust halal-labeled food produced in a country with other than an Islamic tradition. PMID:29623061

Developing alternative over-the-counter medicine label formats: How do they compare when evaluated by consumers?

PubMed

Tong, Vivien; Raynor, David K; Aslani, Parisa

2018-03-01

In recent years, the Australian Therapeutic Goods Administration (TGA) has proposed implementing a standardized over-the-counter (OTC) medicine label. However, there were mixed consumer opinions regarding a label proposed in 2012 and limited evidence demonstrating the usability of the revised (2014) format. To develop and examine the usability of alternative OTC medicine label formats for standardization, and explore consumer perspectives on the labels. Four alternative labels were developed for the exemplar medicine diclofenac. One was based on the Medicine Information label proposed by the TGA ('Medicine Information'), one was based on the U.S. Drug Facts label ('Drug Facts'), and two were based on suggestions proposed by consumers in the earlier needs analysis phase of this research (referred to as the 'Medicine Facts' and 'Consumer Desires' label formats). Five cohorts of 10 participants were recruited. Each cohort was assigned to user test one of the alternative labels or an existing label for a proprietary diclofenac product (which acted as a comparator) for diagnostic purposes. Each participant then provided feedback on all 5 labels. Each interview consisted of the administration of a user testing questionnaire, measuring consumers' ability to find and understand key points of information, and a semi-structured interview exploring consumer perspectives. Overall, all 4 alternative label formats supported consumers' ability to find and understand key points. The existing comparator label was the poorer label with respect to participants' ability to find and understand key points. Factors such as perceived usability, color, design, content, and/or content ordering impacted consumer preferences. The 'Consumer Desires' or 'Drug Facts' label formats were most often preferred by consumers for use as the standardized OTC label over the TGA proposed format. All alternative label formats demonstrated satisfactory usability and could be considered for use in OTC label standardization. User testing of OTC labels and consumer feedback received as part of the testing process can assist in the refinement of OTC labeling to ensure that implemented policies are evidence-based. Copyright © 2017 Elsevier Inc. All rights reserved.

75 FR 32953 - Guidance for Industry and Food and Drug Administration Staff; Use of “Light,” “Mild,” “Low,” or...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-10

... Similar Descriptors in the Label, Labeling, or Advertising of Tobacco Products; Availability AGENCY: Food... in the Label, Labeling, or Advertising of Tobacco Products.'' This guidance provides information on... the use of ``light,'' ``mild,'' ``low,'' or similar descriptors in the label, labeling, or advertising...

The US FDA pregnancy lactation and labeling rule - Implications for maternal immunization.

PubMed

Gruber, Marion F

2015-11-25

The FDA has responsibility for ensuring that prescription drug and biological products including vaccines are accompanied by labeling that summarizes scientific information concerning their safe and effective use. As part of a broader effort to improve the content and format of prescription drug labeling FDA published a final rule, the Content and Format of Labeling for Human Prescription Drug and Biological Products; Requirements for Pregnancy and Lactation Labeling, referred to as the "Pregnancy and Lactation Labeling Rule (PLLR)." The most significant change to be implemented by this Rule is the removal of the letter risk categories A, B, C, D and X from all labeling, replacing them with a narrative summary of the risks of using a drug or biological product including vaccines during pregnancy. The PLLR requires an evaluation of available information about a product's use in pregnancy and provides an opportunity to update labeling when new information about use of a vaccine in pregnancy becomes available. Implementation of the provisions articulated in the PLLR, as they apply to vaccine product labeling, will require close collaboration between FDA and the vaccine manufacturer for both currently licensed vaccines and those in development. Copyright © 2015 The Author. Published by Elsevier Ltd.. All rights reserved.

9 CFR 381.402 - Location of nutrition information.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Location of nutrition information. 381... INSPECTION AND CERTIFICATION POULTRY PRODUCTS INSPECTION REGULATIONS Nutrition Labeling § 381.402 Location of nutrition information. (a) Nutrition information on a label of a packaged poultry product shall appear on...

9 CFR 381.402 - Location of nutrition information.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 2 2014-01-01 2014-01-01 false Location of nutrition information. 381... INSPECTION AND CERTIFICATION POULTRY PRODUCTS INSPECTION REGULATIONS Nutrition Labeling § 381.402 Location of nutrition information. (a) Nutrition information on a label of a packaged poultry product shall appear on...

9 CFR 381.402 - Location of nutrition information.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 2 2012-01-01 2012-01-01 false Location of nutrition information. 381... INSPECTION AND CERTIFICATION POULTRY PRODUCTS INSPECTION REGULATIONS Nutrition Labeling § 381.402 Location of nutrition information. (a) Nutrition information on a label of a packaged poultry product shall appear on...

9 CFR 381.402 - Location of nutrition information.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 2 2011-01-01 2011-01-01 false Location of nutrition information. 381... INSPECTION AND CERTIFICATION POULTRY PRODUCTS INSPECTION REGULATIONS Nutrition Labeling § 381.402 Location of nutrition information. (a) Nutrition information on a label of a packaged poultry product shall appear on...

9 CFR 381.402 - Location of nutrition information.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 2 2013-01-01 2013-01-01 false Location of nutrition information. 381... INSPECTION AND CERTIFICATION POULTRY PRODUCTS INSPECTION REGULATIONS Nutrition Labeling § 381.402 Location of nutrition information. (a) Nutrition information on a label of a packaged poultry product shall appear on...

NOVEL HERBICIDES

EPA Science Inventory

Low-dose, high-potency herbicides are defined as those herbicides with a maximum label application rate of 0.5 pounds of active ingredient per acre. Several classes of chemicals fall into this category, including the acetolactate synthase (ALSase) inhibitor herbicides, imidazoli...

PRN 93-5: Labeling Requirements of the Clean Air Act

EPA Pesticide Factsheets

A regulation under the Clean Air Act requires a warning statement on products (including pesticide products) manufactured with or containing Class I ozone-depleting substances, including chlorofluorocarbons, methyl chloroform and carbon tetrachloride.

A Geo-Label for Geo-Referenced Information as a Service for Data Users and a Tool for Facilitating Societal Benefits of Earth Observations

NASA Astrophysics Data System (ADS)

Plag, H.-P.

2012-04-01

Geo-referenced information is increasingly important for many scientific and societal applications. The availability of reliable and applicable spatial data and information is fundamental for addressing pressing problems such as food, water, and energy security; disaster risk reduction; climate change; environmental quality; pandemics; economic crises and wars; population migration; and, in a general sense, sustainability. Today, more than 70% of societal activities in developed countries depend directly or indirectly on geo-referenced information. The rapid development of analysis tools, such as Geographic Information Systems and web-based tools for viewing, accessing, and analyzing of geo-referenced information, and the growing abundance of openly available Earth observations (e.g., through the Global Earth Observation System of Systems, GEOSS) likely will increase the dependency of science and society on geo-referenced information. Increasingly, the tools allow the combination of data sets from various sources. Improvements of interoperability, promoted particularly by GEOSS, will strengthen this trend and lead to more tools for the combinations of data from different sources. What is currently lacking is a service-oriented infrastructure helping to ensure that data quality and applicability are not compromised through modifications and combinations. Most geo-referenced information comes without sufficient information on quality and applicability. The Group on Earth Observations (GEO) has embarked on establishing a so-called GEO Label that would provide easy-to-understand, globally available information on aspects of quality, user rating, relevance, and fit-for-usage of the products and services accessible through GEOSS (with the responsibility for the concept development delegated to Work Plan Task ID-03). In designing a service-oriented architecture that could support a GEO Label, it is important to understand the impact of the goals for the label on the design of the infrastructure. Design, concept, implementation, and success of a label depend on the goals, and these goals need to be well-defined and widely accepted. Strong labels are generally those that are unique in their field and accepted by an authoritative body in this field. A label requires time to get accepted, and once established the key characteristics normally can not be changed. Therefore, an informed decision on a labeling for geo-referenced data is crucial for success. GEO is in a position to make this decision. There is a wide range of potential goals for the GEO Label including: (1) an attractive incentive for involvement of S&T communities by giving recognition for contributions; enabling credits for providers (attribution); and supporting forward traceability (usage); (2) promote data sharing by signaling data availability and conditions; (3) inform users by increasing trustworthiness; characterizing quality; characterizing applicability; ensuring backward traceability (data sources); (4) inform providers (and their funders) by providing information on relevance (meeting user needs); and provide information on usage. GEO will have to decide on which of these goals to choose for the GEO Label. Input from GEOSS users and S&T communities would help to reach a decision that would serve best all those depending on geo-referenced information.

Reactions of Chinese adults to warning labels on cigarette packages: A survey in Jiangsu Province

PubMed Central

2011-01-01

Background To compare reactions to warning labels presented on cigarette packages with a specific focus on whether the new Chinese warning labels are better than the old labels and international labels. Methods Participants aged 18 and over were recruited in two cities of Jiangsu Province in 2008, and 876 face-to-face interviews were completed. Participants were shown six types of warning labels found on cigarette packages. They comprised one old Chinese label, one new label used within the Chinese market, and one Chinese overseas label and three foreign brand labels. Participants were asked about the impact of the warning labels on: their knowledge of harm from smoking, giving cigarettes as a gift, and quitting smoking. Results Compared with the old Chinese label, a higher proportion of participants said the new label provided clear information on harm caused by smoking (31.2% vs 18.3%). Participants were less likely to give cigarettes with the new label on the package compared with the old label (25.2% vs 20.8%). These proportions were higher when compared to the international labels. Overall, 26.8% of participants would quit smoking based on information from the old label and 31.5% from the new label. When comparing the Chinese overseas label and other foreign labels to the new Chinese label with regard to providing knowledge of harm warning, impact of quitting smoking and giving cigarettes as a gift, the overseas labels were more effective. Conclusion Both the old and the new Chinese warning label are not effective in this target population. PMID:21349205

[Information perceived by consumers through food labeling on fats: a systematic review].

PubMed

Sebastian-Ponce, Miren Itxaso; Sanz-Valero, Javier; Wanden-Berghe, Carmina

2014-11-22

To review the scientific literature related to the information given to consumers about different types of fats in foods through food labeling. Systematic review of the data found in MEDLINE (via PubMed), EMBASE, CINAHL, FSTA, Web of Science, Cochrane Library, SCOPUS and LILACS databasis, until September 2013. The terms used as descriptors and free text were "dietary fats", "dietary fats, unsaturated" and "food labeling". The limit "human" was used. 549 references were retrieved, of which 36 articles were selected after applying the inclusion and exclusion criteria. The main effects related to labeling information were linked to the price and place of purchase/ consumption, sensory dimensions, dietary habits, interpretation and education logo. Food labeling on fat content helps when making consumption decisions. Nutrition education and the meanings of food labels are essential and were effective although the "informed consumer" is yet to be achieved. Training activities should be directed towards prior beliefs and attitudes of consumers in order to make the health and nutrition message consistent. Food labels should be homogeneous and truthful in terms of expressing composition or presenting logos, and messages included in the packaging should be clear and not misleading. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Technological advances in site-directed spin labeling of proteins.

PubMed

Hubbell, Wayne L; López, Carlos J; Altenbach, Christian; Yang, Zhongyu

2013-10-01

Molecular flexibility over a wide time range is of central importance to the function of many proteins, both soluble and membrane. Revealing the modes of flexibility, their amplitudes, and time scales under physiological conditions is the challenge for spectroscopic methods, one of which is site-directed spin labeling EPR (SDSL-EPR). Here we provide an overview of some recent technological advances in SDSL-EPR related to investigation of structure, structural heterogeneity, and dynamics of proteins. These include new classes of spin labels, advances in measurement of long range distances and distance distributions, methods for identifying backbone and conformational fluctuations, and new strategies for determining the kinetics of protein motion. Copyright © 2013 Elsevier Ltd. All rights reserved.

.sup.123m Te-Labeled biochemicals and method of preparation

DOEpatents

Knapp, Jr., Furn F.

1980-01-01

A novel class of .sup.123m Te-labeled steroids and amino acids is provided by the method of reacting a .sup.123m Te symmetric diorgano ditelluride with a hydride reducing agent and a source of alkali metal ions to form an alkali metal organo telluride. The alkali metal organo telluride is reacted with a primary halogenated steroidal side chain, amino acid, or amino acid precursor such as hydantoin. The novel compounds are useful as biological tracers and as organal imaging agents.

Looks Aren't Everything: 24-Month-Olds' Willingness to Accept Unexpected Labels

ERIC Educational Resources Information Center

Jaswal, Vikram K.; Markman, Ellen M.

2007-01-01

A label can efficiently convey nonobvious information about category membership, but this information can sometimes conflict with one's own expectations. Two studies explored whether 24-month-olds (N = 56) would be willing to accept a category label indicating that an animal (Study 1) or artifact (Study 2) that looked like a member of one familiar…

49 CFR 575.302 - Vehicle labeling of safety rating information (compliance required for model year 2012 and later...

Code of Federal Regulations, 2011 CFR

2011-10-01

... this section is to aid potential purchasers in the selection of new passenger motor vehicles by providing them with safety rating information developed by NHTSA in its New Car Assessment Program (NCAP... and rating program. (c) Definitions. (1) Monroney label means the label placed on new automobiles with...

Age differences in the use of serving size information on food labels: numeracy or attention?

PubMed

Miller, Lisa M Soederberg; Applegate, Elizabeth; Beckett, Laurel A; Wilson, Machelle D; Gibson, Tanja N

2017-04-01

The ability to use serving size information on food labels is important for managing age-related chronic conditions such as diabetes, obesity and cancer. Past research suggests that older adults are at risk for failing to accurately use this portion of the food label due to numeracy skills. However, the extent to which older adults pay attention to serving size information on packages is unclear. We compared the effects of numeracy and attention on age differences in accurate use of serving size information while individuals evaluated product healthfulness. Accuracy and attention were assessed across two tasks in which participants compared nutrition labels of two products to determine which was more healthful if they were to consume the entire package. Participants' eye movements were monitored as a measure of attention while they compared two products presented side-by-side on a computer screen. Numeracy as well as food label habits and nutrition knowledge were assessed using questionnaires. Sacramento area, California, USA, 2013-2014. Stratified sample of 358 adults, aged 20-78 years. Accuracy declined with age among those older adults who paid less attention to serving size information. Although numeracy, nutrition knowledge and self-reported food label use supported accuracy, these factors did not influence age differences in accuracy. The data suggest that older adults are less accurate than younger adults in their use of serving size information. Age differences appear to be more related to lack of attention to serving size information than to numeracy skills.

SOCIAL ENVIRONMENTAL RISK AND PROTECTION: A TYPOLOGY WITH IMPLICATIONS FOR PRACTICE IN ELEMENTARY SCHOOLS.

PubMed

Bowen, Natasha K; Lee, Jung-Sook; Weller, Bridget E

2007-01-01

Social environmental assessments can play a critical role in prevention planning in schools. The purpose of this study was to describe the importance of conducting social environmental assessments, demonstrate that complex social environmental data can be simplified into a useful and valid typology, and illustrate how the typology can guide prevention planning in schools. Data collected from 532 3(rd) through 5(th) graders using the Elementary School Success Profile were analyzed in the study. A latent profile analysis based on eight child-report social environmental dimensions identified five patterns of social environmental risk and protection. The classes were labeled High Protection, Moderate Protection, Moderate Protection/Peer Risk, Little Protection/Family Risk, and No Protection//School Risk. Class membership was significantly associated with measures of well-being, social behavior and academic performance. The article illustrates how the typology can be used to guide decisions about who to target in school-based preventions, which features of the social environment to target, and how much change to seek. Information is provided about online resources for selecting prevention strategies once these decisions are made.

Labelling of household products and prevention of unintentional poisoning.

PubMed

de Presgrave, Rosaura Farias; Alves, Eloisa Nunes; Camacho, Luiz Antônio Bastos; Bôas, Maria Helena Simões Villas

2008-04-01

Unintentional poisoning occurs mainly in childhood due to ingestion of common household products. A decisive factor is the lack of knowledge concerning the potential toxicity of these products. A random study of 158 labels of cleaning products was conducted at the National Institute of Quality Control in Health--Brazil. Health hazard warnings, first aid in case of poisoning and storage instructions were evaluated to assess the quality of information provided to the consumer regarding the risks inherent in these products. Among these labels, 75% were considered inadequate since they did not provide all cautionary information necessary to avoid the health hazards associated with these products. First aid instructions in the case of inhalation were missing on more than 50% of labels studied and 47% did not recommend taking the label to a health professional in case of accident. Furthermore, the labels did not provide other important warnings such as "read before use" and "keep in original container': The results indicate that the labelling of cleaning products does not provide all safety information recommended for consumers.

Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning.

PubMed

Mei, Suyu

2012-10-07

Recent years have witnessed much progress in computational modeling for protein subcellular localization. However, there are far few computational models for predicting plant protein subcellular multi-localization. In this paper, we propose a multi-label multi-kernel transfer learning model for predicting multiple subcellular locations of plant proteins (MLMK-TLM). The method proposes a multi-label confusion matrix and adapts one-against-all multi-class probabilistic outputs to multi-label learning scenario, based on which we further extend our published work MK-TLM (multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization) for plant protein subcellular multi-localization. By proper homolog knowledge transfer, MLMK-TLM is applicable to novel plant protein subcellular localization in multi-label learning scenario. The experiments on plant protein benchmark dataset show that MLMK-TLM outperforms the baseline model. Unlike the existing models, MLMK-TLM also reports its misleading tendency, which is important for comprehensive survey of model's multi-labeling performance. Copyright © 2012 Elsevier Ltd. All rights reserved.

HPSLPred: An Ensemble Multi-Label Classifier for Human Protein Subcellular Location Prediction with Imbalanced Source.

PubMed

Wan, Shixiang; Duan, Yucong; Zou, Quan

2017-09-01

Predicting the subcellular localization of proteins is an important and challenging problem. Traditional experimental approaches are often expensive and time-consuming. Consequently, a growing number of research efforts employ a series of machine learning approaches to predict the subcellular location of proteins. There are two main challenges among the state-of-the-art prediction methods. First, most of the existing techniques are designed to deal with multi-class rather than multi-label classification, which ignores connections between multiple labels. In reality, multiple locations of particular proteins imply that there are vital and unique biological significances that deserve special focus and cannot be ignored. Second, techniques for handling imbalanced data in multi-label classification problems are necessary, but never employed. For solving these two issues, we have developed an ensemble multi-label classifier called HPSLPred, which can be applied for multi-label classification with an imbalanced protein source. For convenience, a user-friendly webserver has been established at http://server.malab.cn/HPSLPred. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Food labelling: Regulations and Public Health implications.

PubMed

Marcotrigiano, V; Lanzilotti, C; Rondinone, D; De Giglio, O; Caggiano, G; Diella, G; Orsi, G B; Montagna, M T; Napoli, C

2018-01-01

Legislators have implemented policies to improve food labelling to protect consumers and to make the presentation of ingredients and nutritional information more transparent. Proper food labelling allows consumers who may suffer from food allergies or intolerances to know exactly what ingredients a product contains, and it also helps them make more informed health and nutrition choices. This paper deals with the most current European and Italian legislation on food labelling, actions taken in non-EU countries to increase health choices, and the expected impact on Public Health.

Deep Hashing for Scalable Image Search.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

2017-05-01

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.

An experimental Investigation of the Impact of Personality Disorder Diagnosis on Clinicians: Can We See Past the Borderline?

PubMed

Lam, Danny C K; Poplavskaya, Elena V; Salkovskis, Paul M; Hogg, Lorna I; Panting, Holly

2016-05-01

There is concern that diagnostic labels for psychiatric disorders may invoke damaging stigma, stereotypes and misunderstanding. This study investigated clinicians' reactions to diagnostic labelling by examining their positive and negative reactions to the label borderline personality disorder (BPD). Mental health professionals (n = 265) viewed a videotape of a patient suffering from panic disorder and agoraphobia undergoing assessment. Prior to viewing the videotape, participants were randomly allocated to one of three conditions and were given the following information about the patient: (a) general background information; (b) additional descriptive information about behaviour corresponding to BPD; and (c) additional descriptive information about behaviour corresponding to BPD, but explicitly adding BPD as a possible comorbid diagnostic label. All participants were then asked to note things they had seen in the videotape that made them feel optimistic or pessimistic about treatment outcome. Participants in the group that were explicitly informed that the patient had a BPD diagnostic label reported significantly fewer reasons to be optimistic than the other two groups. Diagnostic labels may negatively impact on clinicians' judgments and perceptions of individuals and therefore clinicians should think carefully about whether, and how, they use diagnoses and efforts should be made to destigmatize diagnostic terms.

Malaria rapid diagnostic kits: quality of packaging, design and labelling of boxes and components and readability and accuracy of information inserts

PubMed Central

2011-01-01

Background The present study assessed malaria RDT kits for adequate and correct packaging, design and labelling of boxes and components. Information inserts were studied for readability and accuracy of information. Methods Criteria for packaging, design, labelling and information were compiled from Directive 98/79 of the European Community (EC), relevant World Health Organization (WHO) documents and studies on end-users' performance of RDTs. Typography and readability level (Flesch-Kincaid grade level) were assessed. Results Forty-two RDT kits from 22 manufacturers were assessed, 35 of which had evidence of good manufacturing practice according to available information (i.e. CE-label affixed or inclusion in the WHO list of ISO13485:2003 certified manufacturers). Shortcomings in devices were (i) insufficient place for writing sample identification (n = 40) and (ii) ambiguous labelling of the reading window (n = 6). Buffer vial labels were lacking essential information (n = 24) or were of poor quality (n = 16). Information inserts had elevated readability levels (median Flesch Kincaid grade 8.9, range 7.1 - 12.9) and user-unfriendly typography (median font size 8, range 5 - 10). Inadequacies included (i) no referral to biosafety (n = 18), (ii) critical differences between depicted and real devices (n = 8), (iii) figures with unrealistic colours (n = 4), (iv) incomplete information about RDT line interpretations (n = 31) and no data on test characteristics (n = 8). Other problems included (i) kit names that referred to Plasmodium vivax although targeting a pan-species Plasmodium antigen (n = 4), (ii) not stating the identity of the pan-species antigen (n = 2) and (iii) slight but numerous differences in names displayed on boxes, device packages and information inserts. Three CE labelled RDT kits produced outside the EC had no authorized representative affixed and the shape and relative dimensions of the CE symbol affixed did not comply with the Directive 98/79/EC. Overall, RDTs with evidence of GMP scored better compared to those without but inadequacies were observed in both groups. Conclusion Overall, malaria RDTs showed shortcomings in quality of construction, design and labelling of boxes, device packages, devices and buffers. Information inserts were difficult to read and lacked relevant information. PMID:21314992

An Adiabatic Quantum Algorithm for Determining Gracefulness of a Graph

NASA Astrophysics Data System (ADS)

Hosseini, Sayed Mohammad; Davoudi Darareh, Mahdi; Janbaz, Shahrooz; Zaghian, Ali

2017-07-01

Graph labelling is one of the noticed contexts in combinatorics and graph theory. Graceful labelling for a graph G with e edges, is to label the vertices of G with 0, 1, ℒ, e such that, if we specify to each edge the difference value between its two ends, then any of 1, 2, ℒ, e appears exactly once as an edge label. For a given graph, there are still few efficient classical algorithms that determine either it is graceful or not, even for trees - as a well-known class of graphs. In this paper, we introduce an adiabatic quantum algorithm, which for a graceful graph G finds a graceful labelling. Also, this algorithm can determine if G is not graceful. Numerical simulations of the algorithm reveal that its time complexity has a polynomial behaviour with the problem size up to the range of 15 qubits. A general sufficient condition for a combinatorial optimization problem to have a satisfying adiabatic solution is also derived.

Cancer illustrations and warning labels on cigarette packs: perceptions of teenagers from high socioeconomic status in Lahore.

PubMed

Zil-E-Ali, Ahsan; Ahsen, Noor Fatima; Iqbal, Humaira

2015-06-01

Smoking is linked with adverse health outcomes and multi-organ diseases with six million deaths every year. The smoking population includes both genders and the habit is seen in minors as well. The cross-sectional study was conducted in Lahore among teenagers belonging to high socioeconomic class. A sample of 191 students was recruited by convenience sampling. The teenagers were questioned on their perceptions relating to prohibition labels, factors that led them to smoke, and ideas to make health warnings more effective. Overall, 66(34.55%) teenagers were smokers, and of them, 50(75.75%) were boys and 16(24.24%) were girls. Besides, 25(37.9%) smokers were of the view that smoking is a bad habit; 40(60.6%) said prohibition labels would not change the mindset of the smoker; 35(53%)believed that a smoker is completely uninfluenced by prohibition labels. Results suggest that the warning labels on cigarette packs should be made more comprehensible and alarming for smokers.

Calorie estimation accuracy and menu labeling perceptions among individuals with and without binge eating and/or purging disorders.

PubMed

Roberto, Christina A; Haynos, Ann F; Schwartz, Marlene B; Brownell, Kelly D; White, Marney A

2013-09-01

Menu labeling is a public health policy that requires chain restaurants in the USA to post kilocalorie information on their menus to help consumers make informed choices. However, there is concern that such a policy might promote disordered eating. This web-based study compared individuals with self-reported binge eating disorder (N = 52), bulimia nervosa (N = 25), and purging disorder (N = 17) and those without eating disorders (No ED) (N = 277) on restaurant calorie information knowledge and perceptions of menu labeling legislation. On average, people answered 1.46 ± 1.08 questions correctly (out of 6) (25%) on a calorie information quiz and 92% of the sample was in favor of menu labeling. The findings did not differ based on eating disorder, dieting, or weight status, or race/ethnicity. The results indicated that people have difficulty estimating the calories in restaurant meals and individuals with and without eating disorders are largely in favor of menu labeling laws.

JPRS Report, East Europe.

DTIC Science & Technology

1988-04-04

The provincial party organization showed differently, in a more modern way than before, how it perceives its role as the inspirer of change and...the working class are aware of the special interest of this class. Siber, however, asks how it is that one-half of those holding executive...34centralism," of "unitarism," and of "hegemonism" (labels for all the enemies and friends of Yugoslavia which have become rather trite), one gets a

A Discussion of Aerodynamic Control Effectors (ACEs) for Unmanned Air Vehicles (UAVs)

NASA Technical Reports Server (NTRS)

Wood, Richard M.

2002-01-01

A Reynolds number based, unmanned air vehicle classification structure has been developed which identifies four classes of unmanned air vehicle concepts. The four unmanned air vehicle (UAV) classes are; Micro UAV, Meso UAV, Macro UAV, and Mega UAV. In a similar fashion a labeling scheme for aerodynamic control effectors (ACE) was developed and eleven types of ACE concepts were identified. These eleven types of ACEs were laid out in a five (5) layer scheme. The final section of the paper correlated the various ACE concepts to the four UAV classes and ACE recommendations are offered for future design activities.

Entanglement of a class of non-Gaussian states in disordered harmonic oscillator systems

NASA Astrophysics Data System (ADS)

Abdul-Rahman, Houssam

2018-03-01

For disordered harmonic oscillator systems over the d-dimensional lattice, we consider the problem of finding the bipartite entanglement of the uniform ensemble of the energy eigenstates associated with a particular number of modes. Such an ensemble defines a class of mixed, non-Gaussian entangled states that are labeled, by the energy of the system, in an increasing order. We develop a novel approach to find the exact logarithmic negativity of this class of states. We also prove entanglement bounds and demonstrate that the low energy states follow an area law.

Seismic classification through sparse filter dictionaries

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

Hickmann, Kyle Scott; Srinivasan, Gowri

We tackle a multi-label classi cation problem involving the relation between acoustic- pro le features and the measured seismogram. To isolate components of the seismo- grams unique to each class of acoustic pro le we build dictionaries of convolutional lters. The convolutional- lter dictionaries for the individual classes are then combined into a large dictionary for the entire seismogram set. A given seismogram is classi ed by computing its representation in the large dictionary and then comparing reconstruction accuracy with this representation using each of the sub-dictionaries. The sub-dictionary with the minimal reconstruction error identi es the seismogram class.

Characterizing monoclonal antibody structure by carbodiimide/GEE footprinting

PubMed Central

Kaur, Parminder; Tomechko, Sara; Kiselar, Janna; Shi, Wuxian; Deperalta, Galahad; Wecksler, Aaron T; Gokulrangan, Giridharan; Ling, Victor; Chance, Mark R

2014-01-01

Amino acid-specific covalent labeling is well suited to probe protein structure and macromolecular interactions, especially for macromolecules and their complexes that are difficult to examine by alternative means, due to size, complexity, or instability. Here we present a detailed account of carbodiimide-based covalent labeling (with GEE tagging) applied to a glycosylated monoclonal antibody therapeutic, which represents an important class of biologic drugs. Characterization of such proteins and their antigen complexes is essential to development of new biologic-based medicines. In this study, the experiments were optimized to preserve the structural integrity of the protein, and experimental conditions were varied and replicated to establish the reproducibility and precision of the technique. Homology-based models were generated and used to compare the solvent accessibility of the labeled residues, which include D, E, and the C-terminus, against the experimental surface accessibility data in order to understand the accuracy of the approach in providing an unbiased assessment of structure. Data from the protein were also compared to reactivity measures of several model peptides to explain sequence or structure-based variations in reactivity. The results highlight several advantages of this approach. These include: the ease of use at the bench top, the linearity of the dose response plots at high levels of labeling (indicating that the label does not significantly perturb the structure of the protein), the high reproducibility of replicate experiments (<2 % variation in modification extent), the similar reactivity of the 3 target probe residues (as suggested by analysis of model peptides), and the overall positive and significant correlation of reactivity and solvent accessible surface area (the latter values predicted by the homology modeling). Attenuation of reactivity, in otherwise solvent accessible probes, is documented as arising from the effects of positive charge or bond formation between adjacent amine and carboxyl groups, the latter accompanied by observed water loss. The results are also compared with data from hydroxyl radical-mediated oxidative footprinting on the same protein, showing that complementary information is gained from the 2 approaches, although the number of target residues in carbodiimide/GEE labeling is fewer. Overall, this approach is an accurate and precise method for assessing protein structure of biologic drugs. PMID:25484052

Developmental and Individual Differences in Preschoolers' Recognition Memories: The Influences of Gender Schematization and Verbal Labeling of Information.

ERIC Educational Resources Information Center

Levy, Gary D.

1989-01-01

Examines developmental and individual differences in the effects of gender schematization on young children's memories for gender-typed information, and investigates the interactive effects of children's age, gender schematization, and verbal labeling of information on preschoolers' memories for gender typed information. (JS)

Conditional High-Order Boltzmann Machines for Supervised Relation Learning.

PubMed

Huang, Yan; Wang, Wei; Wang, Liang; Tan, Tieniu

2017-09-01

Relation learning is a fundamental problem in many vision tasks. Recently, high-order Boltzmann machine and its variants have shown their great potentials in learning various types of data relation in a range of tasks. But most of these models are learned in an unsupervised way, i.e., without using relation class labels, which are not very discriminative for some challenging tasks, e.g., face verification. In this paper, with the goal to perform supervised relation learning, we introduce relation class labels into conventional high-order multiplicative interactions with pairwise input samples, and propose a conditional high-order Boltzmann Machine (CHBM), which can learn to classify the data relation in a binary classification way. To be able to deal with more complex data relation, we develop two improved variants of CHBM: 1) latent CHBM, which jointly performs relation feature learning and classification, by using a set of latent variables to block the pathway from pairwise input samples to output relation labels and 2) gated CHBM, which untangles factors of variation in data relation, by exploiting a set of latent variables to multiplicatively gate the classification of CHBM. To reduce the large number of model parameters generated by the multiplicative interactions, we approximately factorize high-order parameter tensors into multiple matrices. Then, we develop efficient supervised learning algorithms, by first pretraining the models using joint likelihood to provide good parameter initialization, and then finetuning them using conditional likelihood to enhance the discriminant ability. We apply the proposed models to a series of tasks including invariant recognition, face verification, and action similarity labeling. Experimental results demonstrate that by exploiting supervised relation labels, our models can greatly improve the performance.

49 CFR 172.446 - CLASS 9 label.

Code of Federal Regulations, 2012 CFR

2012-10-01

... top half. The black vertical stripes must be spaced, so that, visually, they appear equal in width to...” underlined and centered at the bottom. The solid horizontal line dividing the lower and upper half of the...

49 CFR 172.446 - CLASS 9 label.

Code of Federal Regulations, 2011 CFR

2011-10-01

... top half. The black vertical stripes must be spaced, so that, visually, they appear equal in width to...” underlined and centered at the bottom. The solid horizontal line dividing the lower and upper half of the...

49 CFR 172.446 - CLASS 9 label.

Code of Federal Regulations, 2013 CFR

2013-10-01

... top half. The black vertical stripes must be spaced, so that, visually, they appear equal in width to...” underlined and centered at the bottom. The solid horizontal line dividing the lower and upper half of the...

49 CFR 172.446 - CLASS 9 label.

Code of Federal Regulations, 2014 CFR

2014-10-01

... top half. The black vertical stripes must be spaced, so that, visually, they appear equal in width to...” underlined and centered at the bottom. The solid horizontal line dividing the lower and upper half of the...

New MPLS network management techniques based on adaptive learning.

PubMed

Anjali, Tricha; Scoglio, Caterina; de Oliveira, Jaudelice Cavalcante

2005-09-01

The combined use of the differentiated services (DiffServ) and multiprotocol label switching (MPLS) technologies is envisioned to provide guaranteed quality of service (QoS) for multimedia traffic in IP networks, while effectively using network resources. These networks need to be managed adaptively to cope with the changing network conditions and provide satisfactory QoS. An efficient strategy is to map the traffic from different DiffServ classes of service on separate label switched paths (LSPs), which leads to distinct layers of MPLS networks corresponding to each DiffServ class. In this paper, three aspects of the management of such a layered MPLS network are discussed. In particular, an optimal technique for the setup of LSPs, capacity allocation of the LSPs and LSP routing are presented. The presented techniques are based on measurement of the network state to adapt the network configuration to changing traffic conditions.

40 CFR 211.104 - Label content.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 26 2012-07-01 2011-07-01 true Label content. 211.104 Section 211.104 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) NOISE ABATEMENT PROGRAMS PRODUCT NOISE LABELING General Provisions § 211.104 Label content. The following data and information must be on the label of all products for which...

40 CFR 211.104 - Label content.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 26 2013-07-01 2013-07-01 false Label content. 211.104 Section 211.104 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) NOISE ABATEMENT PROGRAMS PRODUCT NOISE LABELING General Provisions § 211.104 Label content. The following data and information must be on the label of all products for which...

40 CFR 211.104 - Label content.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 25 2014-07-01 2014-07-01 false Label content. 211.104 Section 211.104 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) NOISE ABATEMENT PROGRAMS PRODUCT NOISE LABELING General Provisions § 211.104 Label content. The following data and information must be on the label of all products for which...

40 CFR 211.104 - Label content.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Label content. 211.104 Section 211.104 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) NOISE ABATEMENT PROGRAMS PRODUCT NOISE LABELING General Provisions § 211.104 Label content. The following data and information must be on the label of all products for which...

40 CFR 211.104 - Label content.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 25 2011-07-01 2011-07-01 false Label content. 211.104 Section 211.104 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) NOISE ABATEMENT PROGRAMS PRODUCT NOISE LABELING General Provisions § 211.104 Label content. The following data and information must be on the label of all products for which...

76 FR 35678 - SPF Labeling and Testing Requirements and Drug Facts Labeling for Over-the-Counter Sunscreen Drug...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-17

... [Docket No. FDA-2011-N-0449] SPF Labeling and Testing Requirements and Drug Facts Labeling for Over-the... testing requirements for over-the-counter (OTC) sunscreen products containing specified ingredients and... techniques, when appropriate, and other forms of information technology. SPF Labeling and Testing...

75 FR 13766 - Guidance for Industry on the Content and Format of the Dosage and Administration Section of...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-23

...The Food and Drug Administration (FDA) is announcing the availability of a guidance for industry entitled ``Dosage and Administration Section of Labeling for Human Prescription Drug and Biological Products--Content and Format.'' This guidance is one of a series of guidance documents intended to assist applicants in drafting prescription drug labeling in which prescribing information is clear and accessible and in complying with the requirements in the final rule on the content and format of labeling for prescription drug and biological products. This guidance is intended to help applicants select information for inclusion in the ``Dosage and Administration'' section of labeling and to help them organize that information.

49 CFR 575.301 - Vehicle labeling of safety rating information (applicable unless a vehicle is subject to § 575.302).

Code of Federal Regulations, 2011 CFR

2011-10-01

.... The purpose of this section is to aid potential purchasers in the selection of new passenger motor vehicles by providing them with safety rating information developed by NHTSA in its New Car Assessment... label means the label placed on new automobiles with the manufacturer's suggested retail price and other...

Nutrition knowledge, and use and understanding of nutrition information on food labels among consumers in the UK.

PubMed

Grunert, Klaus G; Wills, Josephine M; Fernández-Celemín, Laura

2010-10-01

Based on in-store observations in three major UK retailers, in-store interviews (2019) and questionnaires filled out at home and returned (921), use of nutrition information on food labels and its understanding were investigated. Respondents' nutrition knowledge was also measured, using a comprehensive instrument covering knowledge of expert recommendations, nutrient content in different food products, and calorie content in different food products. Across six product categories, 27% of shoppers were found to have looked at nutrition information on the label, with guideline daily amount (GDA) labels and the nutrition grid/table as the main sources consulted. Respondents' understanding of major front-of-pack nutrition labels was measured using a variety of tasks dealing with conceptual understanding, substantial understanding and health inferences. Understanding was high, with up to 87.5% of respondents being able to identify the healthiest product in a set of three. Differences between level of understanding and level of usage are explained by different causal mechanisms. Regression analysis showed that usage is mainly related to interest in healthy eating, whereas understanding of nutrition information on food labels is mainly related to nutrition knowledge. Both are in turn affected by demographic variables, but in different ways.

Automated 3D Phenotype Analysis Using Data Mining

PubMed Central

Plyusnin, Ilya; Evans, Alistair R.; Karme, Aleksis; Gionis, Aristides; Jernvall, Jukka

2008-01-01

The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases. PMID:18320060

Volatile pollutants emitted from selected liquid household products.

PubMed

Kwon, Ki-Dong; Jo, Wan-Kuen; Lim, Ho-Jin; Jeong, Woo-Sik

2008-09-01

To identify household products that may be potential sources of indoor air pollution, the chemical composition emitted from the products should be surveyed. Although this kind of survey has been conducted by certain research groups in Western Europe and the USA, there is still limited information in scientific literature. Moreover, chemical components and their proportions of household products are suspected to be different with different manufacturers. Consequently, the current study evaluated the emission composition for 42 liquid household products sold in Korea, focusing on five product classes (deodorizers, household cleaners, color removers, pesticides, and polishes). The present study included two phase experiments. First, the chemical components and their proportions in household products were determined using a gas chromatograph and mass spectrometer system. For the 19 target compounds screened by the first phase of the experiment and other selection criteria, the second phase was done to identify their proportions in the purged-gas phase. The number of chemicals in the household products surveyed ranged from 9 to 113. Eight (product class of pesticides) to 17 (product class of cleaning products) compounds were detected in the purged-gas phase of each product class. Several compounds were identified in more than one product class. Six chemicals (acetone, ethanol, limonene, perchloroethylene (PCE), phenol, and 1-propanol) were identified in all five product classes. There were 13 analytes occurring with a frequency of more than 10% in the household products: limonene (76.2%), ethanol (71.4%), PCE (66.7%), phenol (40.5%), 1-propanol (35.7%), decane (33%), acetone (28.6%), toluene (19.0%), 2-butoxy ethanol (16.7%), o-xylene (16.7%), chlorobenzene (14.3%), ethylbenzene (11.9%), and hexane (11.9%). All of the 42 household products analyzed were found to contain one or more of the 19 compounds. The chemical composition varied broadly along with the product classes or product categories, and it was different from that reported in other studies abroad, although certain target chemicals were identified in both studies. This finding supports an assertion that chemical components emitted from household products may be different in different products and with different manufacturers. The chlorinated pollutants identified in the present study have not been reported to be components of cleaning products in papers published since the early 1990s. Limonene was identified as having the highest occurrence in the household products in the present study, although it was not detected in any of 67 household products sold in the U.S. The emission composition of selected household products was successfully examined by purge-and-trap analysis. Along with other exposure information such as use pattern of household products and the indoor climate, this composition data can be used to estimate personal exposure levels of building occupants. This exposure data can be employed to link environmental exposure to health risk. It is noteworthy that many liquid household products sold in Korea emitted several toxic aromatic and chlorinated organic compounds. Moreover, the current finding suggests that product types and manufacturers should be considered, when evaluating building occupants' exposure to chemical components emitted from household products. The current findings can provide valuable information for the semiquantitative estimation of the population inhalation exposure to these compounds in indoor environments and for the selection of safer household products. However, although the chemical composition is known, the emissions of household products might include compounds formed during the use of the product or compounds not identified as ingredients by this study. Accordingly, further studies are required, and testing must be done to determine the actual composition being emitted. Similar to eco-labeling of shampoos, shower gels, and foam baths proposed by a previous study, eco-labeling of other household products is suggested.

Analyzing temozolomide medication errors: potentially fatal.

PubMed

Letarte, Nathalie; Gabay, Michael P; Bressler, Linda R; Long, Katie E; Stachnik, Joan M; Villano, J Lee

2014-10-01

The EORTC-NCIC regimen for glioblastoma requires different dosing of temozolomide (TMZ) during radiation and maintenance therapy. This complexity is exacerbated by the availability of multiple TMZ capsule strengths. TMZ is an alkylating agent and the major toxicity of this class is dose-related myelosuppression. Inadvertent overdose can be fatal. The websites of the Institute for Safe Medication Practices (ISMP), and the Food and Drug Administration (FDA) MedWatch database were reviewed. We searched the MedWatch database for adverse events associated with TMZ and obtained all reports including hematologic toxicity submitted from 1st November 1997 to 30th May 2012. The ISMP describes errors with TMZ resulting from the positioning of information on the label of the commercial product. The strength and quantity of capsules on the label were in close proximity to each other, and this has been changed by the manufacturer. MedWatch identified 45 medication errors. Patient errors were the most common, accounting for 21 or 47% of errors, followed by dispensing errors, which accounted for 13 or 29%. Seven reports or 16% were errors in the prescribing of TMZ. Reported outcomes ranged from reversible hematological adverse events (13%), to hospitalization for other adverse events (13%) or death (18%). Four error reports lacked detail and could not be categorized. Although the FDA issued a warning in 2003 regarding fatal medication errors and the product label warns of overdosing, errors in TMZ dosing occur for various reasons and involve both healthcare professionals and patients. Overdosing errors can be fatal.

78 FR 76841 - Agency Information Collection Activities; Announcement of Office of Management and Budget...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-19

...; Guidance for Industry on Hypertension Indication: Drug Labeling for Cardiovascular Outcome Claims AGENCY... announcing that a collection of information entitled ``Guidance for Industry on Hypertension Indication: Drug... information entitled ``Guidance for Industry on Hypertension Indication: Drug Labeling for Cardiovascular...

Soil Fumigant Labels - Dazomet

EPA Pesticide Factsheets

Updated labels include new safety requirements for buffer zones and related measures. Find information from the Pesticide Product Labeling System (PPLS) for products such as Basamid G, manufactured by Amvac.

76 FR 41265 - Agency Information Collection Activities; Announcement of Office of Management and Budget...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-13

...; Restaurant Menu and Vending Machine Labeling: Recordkeeping and Mandatory Third Party Disclosure Under... collection of information entitled ``Restaurant Menu and Vending Machine Labeling: Recordkeeping and...

Alcohol consumers' attention to warning labels and brand information on alcohol packaging: Findings from cross-sectional and experimental studies.

PubMed

Kersbergen, Inge; Field, Matt

2017-01-26

Alcohol warning labels have a limited effect on drinking behavior, potentially because people devote minimal attention to them. We report findings from two studies in which we measured the extent to which alcohol consumers attend to warning labels on alcohol packaging, and aimed to identify if increased attention to warning labels is associated with motivation to change drinking behavior. Study 1 (N = 60) was an exploratory cross-sectional study in which we used eye-tracking to measure visual attention to brand and health information on alcohol and soda containers. In study 2 (N = 120) we manipulated motivation to reduce drinking using an alcohol brief intervention (vs control intervention) and measured heavy drinkers' attention to branding and warning labels with the same eye-tracking paradigm as in study 1. Then, in a separate task we experimentally manipulated attention by drawing a brightly colored border around health (or brand) information before measuring participants' self-reported drinking intentions for the subsequent week. Study 1 showed that participants paid minimal attention to warning labels (7% of viewing time). Participants who were motivated to reduce drinking paid less attention to alcohol branding and alcohol warning labels. Results from study 2 showed that the alcohol brief intervention decreased attention to branding compared to the control condition, but it did not affect attention to warning labels. Furthermore, the experimental manipulation of attention to health or brand information did not influence drinking intentions for the subsequent week. Alcohol consumers allocate minimal attention to warning labels on alcohol packaging and even if their attention is directed to these warning labels, this has no impact on their drinking intentions. The lack of attention to warning labels, even among people who actively want to cut down, suggests that there is room for improvement in the content of health warnings on alcohol packaging.

Explaining and inducing savant skills: privileged access to lower level, less-processed information

PubMed Central

Snyder, Allan

2009-01-01

I argue that savant skills are latent in us all. My hypothesis is that savants have privileged access to lower level, less-processed information, before it is packaged into holistic concepts and meaningful labels. Owing to a failure in top-down inhibition, they can tap into information that exists in all of our brains, but is normally beyond conscious awareness. This suggests why savant skills might arise spontaneously in otherwise normal people, and why such skills might be artificially induced by low-frequency repetitive transcranial magnetic stimulation. It also suggests why autistic savants are atypically literal with a tendency to concentrate more on the parts than on the whole and why this offers advantages for particular classes of problem solving, such as those that necessitate breaking cognitive mindsets. A strategy of building from the parts to the whole could form the basis for the so-called autistic genius. Unlike the healthy mind, which has inbuilt expectations of the world (internal order), the autistic mind must simplify the world by adopting strict routines (external order). PMID:19528023

An ant colony optimization based feature selection for web page classification.

PubMed

Saraç, Esra; Özel, Selma Ayşe

2014-01-01

The increased popularity of the web has caused the inclusion of huge amount of information to the web, and as a result of this explosive information growth, automated web page classification systems are needed to improve search engines' performance. Web pages have a large number of features such as HTML/XML tags, URLs, hyperlinks, and text contents that should be considered during an automated classification process. The aim of this study is to reduce the number of features to be used to improve runtime and accuracy of the classification of web pages. In this study, we used an ant colony optimization (ACO) algorithm to select the best features, and then we applied the well-known C4.5, naive Bayes, and k nearest neighbor classifiers to assign class labels to web pages. We used the WebKB and Conference datasets in our experiments, and we showed that using the ACO for feature selection improves both accuracy and runtime performance of classification. We also showed that the proposed ACO based algorithm can select better features with respect to the well-known information gain and chi square feature selection methods.

Consumer knowledge and attitudes toward nutritional labels.

PubMed

Cannoosamy, Komeela; Pugo-Gunsam, Prity; Jeewon, Rajesh

2014-01-01

To determine Mauritian consumers' attitudes toward nutritional labels based on the Kano model and to identify determinants of the use and understanding of nutrition labels. The researchers also used a Kano model questionnaire to determine consumers' attitudes toward nutrition labeling. Four hundred consumers residing in Mauritius. Information was elicited via a questionnaire that assessed nutritional knowledge and information about the use and understanding of nutritional labels and demographic factors. Nutritional label use and understanding, nutrition knowledge, and association of demographic factors with label use. Statistical tests performed included 1-way ANOVA and independent samples t tests. Statistically significant relationships (P < .05) were found for nutritional knowledge and nutritional label usage with demographic factors. All demographic factors with the exception of gender were significantly associated (P < .05) with nutritional label understanding. Based on the outcome of the Kano survey, calorie content, trans fat content, protein content, and cholesterol content were found to be must-be attributes: that is, attributes that, when not present, result in consumer dissatisfaction. Age, education, income, household size, and nutrition knowledge had an impact on nutritional label use. Health promoters should aim to increase the use of nutritional labels. Copyright © 2014 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

A test of different menu labeling presentations.

PubMed

Liu, Peggy J; Roberto, Christina A; Liu, Linda J; Brownell, Kelly D

2012-12-01

Chain restaurants will soon need to disclose calorie information on menus, but research on the impact of calorie labels on food choices is mixed. This study tested whether calorie information presented in different formats influenced calories ordered and perceived restaurant healthfulness. Participants in an online survey were randomly assigned to a menu with either (1) no calorie labels (No Calories); (2) calorie labels (Calories); (3) calorie labels ordered from low to high calories (Rank-Ordered Calories); or (4) calorie labels ordered from low to high calories that also had red/green circles indicating higher and lower calorie choices (Colored Calories). Participants ordered items for dinner, estimated calories ordered, and rated restaurant healthfulness. Participants in the Rank-Ordered Calories condition and those in the Colored Calories condition ordered fewer calories than the No Calories group. There was no significant difference in calories ordered between the Calories and No Calories groups. Participants in each calorie label condition were significantly more accurate in estimating calories ordered compared to the No Calories group. Those in the Colored Calories group perceived the restaurant as healthier. The results suggest that presenting calorie information in the modified Rank-Ordered or Colored Calories formats may increase menu labeling effectiveness. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effect of different children's menu labeling designs on family purchases.

PubMed

Holmes, Ashley S; Serrano, Elena L; Machin, Jane E; Duetsch, Thomas; Davis, George C

2013-03-01

The majority of labeling studies at restaurants have focused on adults, not children, and utilized cross-sectional data with one menu labeling design, typically calorie information. The aim of this longitudinal study was to examine the effect of three different menu labeling designs for children's meals on total calories and fat selected by families. Each menu was implemented for 2months. Patrons' purchases were tracked from a control menu (with no nutrition information) through all three theoretically-based designs: calorie and fat information; followed by symbols denoting healthier choices; then nutrition bargain price. All menus were created specifically for the study. They featured six combination meals (pre-determined entrees and side items) and a la carte items (entrees and side items that could be ordered separately). Only combination meals contained labeling. Fixed effects models were estimated to detect changes in sales for each menu labeling design compared to the control. Overall, menu labeling did not result in a positive net effect on total calories or fat purchased by families, but resulted in significant shifts in purchases of combination and a la carte meals and healthy and unhealthy options. The most significant impact was seen for nutrition bargain price labeling, the last design. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Management of chemical products and European standards: new classification criteria according to the 1272/2008 (CLP) regulation].

PubMed

Fanghella, Paola Di Prospero; Aliberti, Ludovica Malaguti

2013-01-01

The European Union adopted regulations (EC) 1907/2006 REACH e (EC)1272/2008 CLP, to manage chemicals. REACH requires for evaluation and management of risks connected to the use of chemical substances, while o CLP provides for the classification, labelling and packagings of dangerous substances and mixtures by implementing in the EU the UN Globally Harmonised System of Classification and Labelling applying the building block approach, that is taking on board the hazard classes and categories which are close to the existing EU system in order to maintain the level of protection of human health and environment. This regulation provides also for the notification of the classification and labelling of substances to the Classification & Labelling Inventory established by the European Chemicals Agency (ECHA). Some european downstream regulations making reference to the classification criteria, as the health and safety laws at workplace, need to be adapted to these regulations.

Incremental Transductive Learning Approaches to Schistosomiasis Vector Classification

NASA Astrophysics Data System (ADS)

Fusco, Terence; Bi, Yaxin; Wang, Haiying; Browne, Fiona

2016-08-01

The key issues pertaining to collection of epidemic disease data for our analysis purposes are that it is a labour intensive, time consuming and expensive process resulting in availability of sparse sample data which we use to develop prediction models. To address this sparse data issue, we present the novel Incremental Transductive methods to circumvent the data collection process by applying previously acquired data to provide consistent, confidence-based labelling alternatives to field survey research. We investigated various reasoning approaches for semi-supervised machine learning including Bayesian models for labelling data. The results show that using the proposed methods, we can label instances of data with a class of vector density at a high level of confidence. By applying the Liberal and Strict Training Approaches, we provide a labelling and classification alternative to standalone algorithms. The methods in this paper are components in the process of reducing the proliferation of the Schistosomiasis disease and its effects.

Patterns of free amino acids in German convenience food products: marked mismatch between label information and composition.

PubMed

Hermanussen, M; Gonder, U; Jakobs, C; Stegemann, D; Hoffmann, G

2010-01-01

Free amino acids affect food palatability. As information on amino acids in frequently purchased pre-packaged food is virtually absent, we analyzed free amino acid patterns of 17 frequently purchased ready-to-serve convenience food products, and compared them with the information obtained from the respective food labels. Quantitative amino acid analysis was performed using ion-exchange chromatography. gamma-Aminobutyric acid (GABA) concentrations were verified using a stable isotope dilution gas chromatography/mass spectrometry (GC-MS) method. The patterns of free amino acids were compared with information obtained from food labels. An obvious mismatch between free amino acid patterns and food label information was detected. Even on considering that tomatoes and cereal proteins are naturally rich in glutamate, the concentrations of free glutamate outranged the natural concentration of this amino acid in several products, and strongly suggested artificial enrichment. Free glutamate was found to be elevated even in dishes that explicitly state 'no glutamate added'. Arginine was markedly elevated in lentils. Free cysteine was generally low, possibly reflecting thermal destruction of this amino acid during food processing. The meat and brain-specific dipeptide carnosine (CARN) was present in most meat-containing products. Some products did not contain detectable amounts of CARN in spite of meat content being claimed on the food labels. We detected GABA at concentrations that contribute significantly to the taste sensation. This investigation highlights a marked mismatch between food label information and food composition.

EnzML: multi-label prediction of enzyme classes using InterPro signatures

PubMed Central

2012-01-01

Background Manual annotation of enzymatic functions cannot keep up with automatic genome sequencing. In this work we explore the capacity of InterPro sequence signatures to automatically predict enzymatic function. Results We present EnzML, a multi-label classification method that can efficiently account also for proteins with multiple enzymatic functions: 50,000 in UniProt. EnzML was evaluated using a standard set of 300,747 proteins for which the manually curated Swiss-Prot and KEGG databases have agreeing Enzyme Commission (EC) annotations. EnzML achieved more than 98% subset accuracy (exact match of all correct Enzyme Commission classes of a protein) for the entire dataset and between 87 and 97% subset accuracy in reannotating eight entire proteomes: human, mouse, rat, mouse-ear cress, fruit fly, the S. pombe yeast, the E. coli bacterium and the M. jannaschii archaebacterium. To understand the role played by the dataset size, we compared the cross-evaluation results of smaller datasets, either constructed at random or from specific taxonomic domains such as archaea, bacteria, fungi, invertebrates, plants and vertebrates. The results were confirmed even when the redundancy in the dataset was reduced using UniRef100, UniRef90 or UniRef50 clusters. Conclusions InterPro signatures are a compact and powerful attribute space for the prediction of enzymatic function. This representation makes multi-label machine learning feasible in reasonable time (30 minutes to train on 300,747 instances with 10,852 attributes and 2,201 class values) using the Mulan Binary Relevance Nearest Neighbours algorithm implementation (BR-kNN). PMID:22533924

75 FR 67978 - Agency Information Collection Activities; Proposed Collection; Comment Request; Restaurant Menu...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-04

...] Agency Information Collection Activities; Proposed Collection; Comment Request; Restaurant Menu Labeling... appropriate, and other forms of information technology. Restaurant Menu Labeling: Registration for Small... restaurants and similar retail food establishments (SRFE) with 20 or more locations, as well as operators of...

Content and format of labeling for human prescription drug and biological products; requirements for pregnancy and lactation labeling. Final rule.

PubMed

2014-12-04

The Food and Drug Administration (FDA) is amending its regulations governing the content and format of the "Pregnancy," "Labor and delivery," and "Nursing mothers" subsections of the "Use in Specific Populations" section of the labeling for human prescription drug and biological products. The final rule requires the removal of the pregnancy categories A, B, C, D, and X from all human prescription drug and biological product labeling. For human prescription drug and biological products subject to the Agency's 2006 Physician Labeling Rule, the final rule requires that the labeling include a summary of the risks of using a drug during pregnancy and lactation, a discussion of the data supporting that summary, and relevant information to help health care providers make prescribing decisions and counsel women about the use of drugs during pregnancy and lactation. The final rule eliminates the "Labor and delivery" subsection because information about labor and delivery is included in the "Pregnancy" subsection. The final rule requires that the labeling include relevant information about pregnancy testing, contraception, and infertility for health care providers prescribing for females and males of reproductive potential. The final rule creates a consistent format for providing information about the risks and benefits of prescription drug and/or biological product use during pregnancy and lactation and by females and males of reproductive potential. These revisions will facilitate prescriber counseling for these populations.

Active Learning with Irrelevant Examples

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; Mazzoni, Dominic

2009-01-01

An improved active learning method has been devised for training data classifiers. One example of a data classifier is the algorithm used by the United States Postal Service since the 1960s to recognize scans of handwritten digits for processing zip codes. Active learning algorithms enable rapid training with minimal investment of time on the part of human experts to provide training examples consisting of correctly classified (labeled) input data. They function by identifying which examples would be most profitable for a human expert to label. The goal is to maximize classifier accuracy while minimizing the number of examples the expert must label. Although there are several well-established methods for active learning, they may not operate well when irrelevant examples are present in the data set. That is, they may select an item for labeling that the expert simply cannot assign to any of the valid classes. In the context of classifying handwritten digits, the irrelevant items may include stray marks, smudges, and mis-scans. Querying the expert about these items results in wasted time or erroneous labels, if the expert is forced to assign the item to one of the valid classes. In contrast, the new algorithm provides a specific mechanism for avoiding querying the irrelevant items. This algorithm has two components: an active learner (which could be a conventional active learning algorithm) and a relevance classifier. The combination of these components yields a method, denoted Relevance Bias, that enables the active learner to avoid querying irrelevant data so as to increase its learning rate and efficiency when irrelevant items are present. The algorithm collects irrelevant data in a set of rejected examples, then trains the relevance classifier to distinguish between labeled (relevant) training examples and the rejected ones. The active learner combines its ranking of the items with the probability that they are relevant to yield a final decision about which item to present to the expert for labeling. Experiments on several data sets have demonstrated that the Relevance Bias approach significantly decreases the number of irrelevant items queried and also accelerates learning speed.

Revisions to labeling requirements for blood and blood components, including source plasma. Final rule.

PubMed

2012-01-03

The Food and Drug Administration (FDA) is revising the labeling requirements for blood and blood components intended for use in transfusion or for further manufacture by combining, simplifying, and updating specific regulations applicable to labeling and circulars of information. These requirements will facilitate the use of a labeling system using machine-readable information that would be acceptable as a replacement for the ``ABC Codabar'' system for the labeling of blood and blood components. FDA is taking this action as a part of its efforts to comprehensively review and, as necessary, revise its regulations, policies, guidances, and procedures related to the regulation of blood and blood components. This final rule is intended to help ensure the continued safety of the blood supply and facilitate consistency in labeling.

Detecting experimental techniques and selecting relevant documents for protein-protein interactions from biomedical literature.

PubMed

Wang, Xinglong; Rak, Rafal; Restificar, Angelo; Nobata, Chikashi; Rupp, C J; Batista-Navarro, Riza Theresa B; Nawaz, Raheel; Ananiadou, Sophia

2011-10-03

The selection of relevant articles for curation, and linking those articles to experimental techniques confirming the findings became one of the primary subjects of the recent BioCreative III contest. The contest's Protein-Protein Interaction (PPI) task consisted of two sub-tasks: Article Classification Task (ACT) and Interaction Method Task (IMT). ACT aimed to automatically select relevant documents for PPI curation, whereas the goal of IMT was to recognise the methods used in experiments for identifying the interactions in full-text articles. We proposed and compared several classification-based methods for both tasks, employing rich contextual features as well as features extracted from external knowledge sources. For IMT, a new method that classifies pair-wise relations between every text phrase and candidate interaction method obtained promising results with an F1 score of 64.49%, as tested on the task's development dataset. We also explored ways to combine this new approach and more conventional, multi-label document classification methods. For ACT, our classifiers exploited automatically detected named entities and other linguistic information. The evaluation results on the BioCreative III PPI test datasets showed that our systems were very competitive: one of our IMT methods yielded the best performance among all participants, as measured by F1 score, Matthew's Correlation Coefficient and AUC iP/R; whereas for ACT, our best classifier was ranked second as measured by AUC iP/R, and also competitive according to other metrics. Our novel approach that converts the multi-class, multi-label classification problem to a binary classification problem showed much promise in IMT. Nevertheless, on the test dataset the best performance was achieved by taking the union of the output of this method and that of a multi-class, multi-label document classifier, which indicates that the two types of systems complement each other in terms of recall. For ACT, our system exploited a rich set of features and also obtained encouraging results. We examined the features with respect to their contributions to the classification results, and concluded that contextual words surrounding named entities, as well as the MeSH headings associated with the documents were among the main contributors to the performance.

Recognition Memory for Hue: Prototypical Bias and the Role of Labeling

ERIC Educational Resources Information Center

Kelly, Laura Jane; Heit, Evan

2017-01-01

How does the concurrent use of language affect perception and memory for exemplars? Labels cue more general category information than a specific exemplar. Applying labels can affect the resulting memory for an exemplar. Here 3 alternative hypotheses are proposed for the role of labeling an exemplar at encoding: (a) labels distort memory toward the…