Co-Labeling for Multi-View Weakly Labeled Learning.

PubMed

Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

2016-06-01

It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi-view datasets clearly demonstrate that our proposed co-labeling approach achieves state-of-the-art performance for various multi-view weakly labeled learning problems including multi-view SSL, multi-view MIL and multi-view ROD.

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

NASA Astrophysics Data System (ADS)

Feng, Shou; Fu, Ping; Zheng, Wenbin

2018-03-01

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

The association between flavor labeling and flavor recall ability in children.

PubMed

Lumeng, Julie C; Zuckerman, Matthew D; Cardinal, Tiffany; Kaciroti, Niko

2005-09-01

This study sought to determine if the ability to label a flavor is associated with an improved ability to recall having tasted the flavor in preschool-aged children. A total of 120 3- to 6-year-old English-speaking children tasted and labeled 20 different flavors, blinded to color. Children's labels for the flavors were scored for consistency and accuracy. Recall for having tasted the flavor was tested. Both labeling ability and recall ability improved rapidly between the ages of 3 and 6 years in this cohort. Regression analysis indicated that independent of the child's age, consistent accurate labeling was positively associated with recall ability. Higher maternal education was an independent and marginal contributor to greater recall ability. The combination of consistent and accurate labeling, age, and maternal education accounted for 28% of the variance in flavor recall ability. Consistent but inaccurate labeling alone contributed little to the variance in flavor recall ability. We conclude from these findings that children's ability to recall having tasted a flavor develops rapidly during the preschool age range and that improved recall ability is associated with the ability to consistently and accurately label the flavor. We conclude that language mediates memory for flavors in young children.

Statistical label fusion with hierarchical performance models

PubMed Central

Asman, Andrew J.; Dagley, Alexander S.; Landman, Bennett A.

2014-01-01

Label fusion is a critical step in many image segmentation frameworks (e.g., multi-atlas segmentation) as it provides a mechanism for generalizing a collection of labeled examples into a single estimate of the underlying segmentation. In the multi-label case, typical label fusion algorithms treat all labels equally – fully neglecting the known, yet complex, anatomical relationships exhibited in the data. To address this problem, we propose a generalized statistical fusion framework using hierarchical models of rater performance. Building on the seminal work in statistical fusion, we reformulate the traditional rater performance model from a multi-tiered hierarchical perspective. This new approach provides a natural framework for leveraging known anatomical relationships and accurately modeling the types of errors that raters (or atlases) make within a hierarchically consistent formulation. Herein, we describe several contributions. First, we derive a theoretical advancement to the statistical fusion framework that enables the simultaneous estimation of multiple (hierarchical) performance models within the statistical fusion context. Second, we demonstrate that the proposed hierarchical formulation is highly amenable to the state-of-the-art advancements that have been made to the statistical fusion framework. Lastly, in an empirical whole-brain segmentation task we demonstrate substantial qualitative and significant quantitative improvement in overall segmentation accuracy. PMID:24817809

Diagnostic labels assigned to patients with orthopedic conditions and the influence of the label on selection of interventions: a qualitative study of orthopaedic clinical specialists.

PubMed

Miller-Spoto, Marcia; Gombatto, Sara P

2014-06-01

A variety of diagnostic classification systems are used by physical therapists, but little information about how therapists assign diagnostic labels and how the labels are used to direct intervention is available. The purposes of this study were: (1) to examine the diagnostic labels assigned to patient problems by physical therapists who are board-certified Orthopaedic Clinical Specialists (OCSs) and (2) to determine whether the label influences selection of interventions. A cross-sectional survey was conducted. Two written cases were developed for patients with low back and shoulder pain. A survey was used to evaluate the diagnostic label assigned and the interventions considered important for each case. The cases and survey were sent to therapists who are board-certified OCSs. Respondents assigned a diagnostic label and rated the importance of intervention categories for each case. Each diagnostic label was coded based on the construct it represented. Percentage responses for each diagnostic label code and intervention category were calculated. Relative importance of intervention category based on diagnostic label was examined. For the low back pain and shoulder pain cases, respectively, "Combination" (48.5%, 34.9%) and "Pathology/Pathophysiology" (32.7%, 57.3%) diagnostic labels were most common. Strengthening (85.9%, 98.1%), stretching (86.8%, 84.9%), neuromuscular re-education (87.6%, 93.4%), functional training (91.4%, 88.6%), and mobilization/manipulation (85.1%, 86.8%) were considered the most important interventions. Relative importance of interventions did not differ based on diagnostic label (χ2=0.050-1.263, P=.261-.824). The low response rate may limit the generalizability of the findings. Also, examples provided for labels may have influenced responses, and some of the label codes may have represented overlapping constructs. There is little consistency with which OCS therapists assign diagnostic labels, and the label does not seem to influence selection of interventions. © 2014 American Physical Therapy Association.

Manifold regularized matrix completion for multi-label learning with ADMM.

PubMed

Liu, Bin; Li, Yingming; Xu, Zenglin

2018-05-01

Multi-label learning is a common machine learning problem arising from numerous real-world applications in diverse fields, e.g, natural language processing, bioinformatics, information retrieval and so on. Among various multi-label learning methods, the matrix completion approach has been regarded as a promising approach to transductive multi-label learning. By constructing a joint matrix comprising the feature matrix and the label matrix, the missing labels of test samples are regarded as missing values of the joint matrix. With the low-rank assumption of the constructed joint matrix, the missing labels can be recovered by minimizing its rank. Despite its success, most matrix completion based approaches ignore the smoothness assumption of unlabeled data, i.e., neighboring instances should also share a similar set of labels. Thus they may under exploit the intrinsic structures of data. In addition, the matrix completion problem can be less efficient. To this end, we propose to efficiently solve the multi-label learning problem as an enhanced matrix completion model with manifold regularization, where the graph Laplacian is used to ensure the label smoothness over it. To speed up the convergence of our model, we develop an efficient iterative algorithm, which solves the resulted nuclear norm minimization problem with the alternating direction method of multipliers (ADMM). Experiments on both synthetic and real-world data have shown the promising results of the proposed approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

Transformation of general binary MRF minimization to the first-order case.

PubMed

Ishikawa, Hiroshi

2011-06-01

We introduce a transformation of general higher-order Markov random field with binary labels into a first-order one that has the same minima as the original. Moreover, we formalize a framework for approximately minimizing higher-order multi-label MRF energies that combines the new reduction with the fusion-move and QPBO algorithms. While many computer vision problems today are formulated as energy minimization problems, they have mostly been limited to using first-order energies, which consist of unary and pairwise clique potentials, with a few exceptions that consider triples. This is because of the lack of efficient algorithms to optimize energies with higher-order interactions. Our algorithm challenges this restriction that limits the representational power of the models so that higher-order energies can be used to capture the rich statistics of natural scenes. We also show that some minimization methods can be considered special cases of the present framework, as well as comparing the new method experimentally with other such techniques.

Ultrarelativistic bound states in the spherical well

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

Żaba, Mariusz; Garbaczewski, Piotr

2016-07-15

We address an eigenvalue problem for the ultrarelativistic (Cauchy) operator (−Δ){sup 1/2}, whose action is restricted to functions that vanish beyond the interior of a unit sphere in three spatial dimensions. We provide high accuracy spectral data for lowest eigenvalues and eigenfunctions of this infinite spherical well problem. Our focus is on radial and orbital shapes of eigenfunctions. The spectrum consists of an ordered set of strictly positive eigenvalues which naturally splits into non-overlapping, orbitally labelled E{sub (k,l)} series. For each orbital label l = 0, 1, 2, …, the label k = 1, 2, … enumerates consecutive lth seriesmore » eigenvalues. Each of them is 2l + 1-degenerate. The l = 0 eigenvalues series E{sub (k,0)} are identical with the set of even labeled eigenvalues for the d = 1 Cauchy well: E{sub (k,0)}(d = 3) = E{sub 2k}(d = 1). Likewise, the eigenfunctions ψ{sub (k,0)}(d = 3) and ψ{sub 2k}(d = 1) show affinity. We have identified the generic functional form of eigenfunctions of the spherical well which appear to be composed of a product of a solid harmonic and of a suitable purely radial function. The method to evaluate (approximately) the latter has been found to follow the universal pattern which effectively allows to skip all, sometimes involved, intermediate calculations (those were in usage, while computing the eigenvalues for l ≤ 3).« less

Classification of holter registers by dynamic clustering using multi-dimensional particle swarm optimization.

PubMed

Kiranyaz, Serkan; Ince, Turker; Pulkkinen, Jenni; Gabbouj, Moncef

2010-01-01

In this paper, we address dynamic clustering in high dimensional data or feature spaces as an optimization problem where multi-dimensional particle swarm optimization (MD PSO) is used to find out the true number of clusters, while fractional global best formation (FGBF) is applied to avoid local optima. Based on these techniques we then present a novel and personalized long-term ECG classification system, which addresses the problem of labeling the beats within a long-term ECG signal, known as Holter register, recorded from an individual patient. Due to the massive amount of ECG beats in a Holter register, visual inspection is quite difficult and cumbersome, if not impossible. Therefore the proposed system helps professionals to quickly and accurately diagnose any latent heart disease by examining only the representative beats (the so called master key-beats) each of which is representing a cluster of homogeneous (similar) beats. We tested the system on a benchmark database where the beats of each Holter register have been manually labeled by cardiologists. The selection of the right master key-beats is the key factor for achieving a highly accurate classification and the proposed systematic approach produced results that were consistent with the manual labels with 99.5% average accuracy, which basically shows the efficiency of the system.

A Simple Label Switching Algorithm for Semisupervised Structural SVMs.

PubMed

Balamurugan, P; Shevade, Shirish; Sundararajan, S

2015-10-01

In structured output learning, obtaining labeled data for real-world applications is usually costly, while unlabeled examples are available in abundance. Semisupervised structured classification deals with a small number of labeled examples and a large number of unlabeled structured data. In this work, we consider semisupervised structural support vector machines with domain constraints. The optimization problem, which in general is not convex, contains the loss terms associated with the labeled and unlabeled examples, along with the domain constraints. We propose a simple optimization approach that alternates between solving a supervised learning problem and a constraint matching problem. Solving the constraint matching problem is difficult for structured prediction, and we propose an efficient and effective label switching method to solve it. The alternating optimization is carried out within a deterministic annealing framework, which helps in effective constraint matching and avoiding poor local minima, which are not very useful. The algorithm is simple and easy to implement. Further, it is suitable for any structured output learning problem where exact inference is available. Experiments on benchmark sequence labeling data sets and a natural language parsing data set show that the proposed approach, though simple, achieves comparable generalization performance.

a Comparison of Two Strategies for Avoiding Negative Transfer in Domain Adaptation Based on Logistic Regression

NASA Astrophysics Data System (ADS)

Paul, A.; Vogt, K.; Rottensteiner, F.; Ostermann, J.; Heipke, C.

2018-05-01

In this paper we deal with the problem of measuring the similarity between training and tests datasets in the context of transfer learning (TL) for image classification. TL tries to transfer knowledge from a source domain, where labelled training samples are abundant but the data may follow a different distribution, to a target domain, where labelled training samples are scarce or even unavailable, assuming that the domains are related. Thus, the requirements w.r.t. the availability of labelled training samples in the target domain are reduced. In particular, if no labelled target data are available, it is inherently difficult to find a robust measure of relatedness between the source and target domains. This is of crucial importance for the performance of TL, because the knowledge transfer between unrelated data may lead to negative transfer, i.e. to a decrease of classification performance after transfer. We address the problem of measuring the relatedness between source and target datasets and investigate three different strategies to predict and, consequently, to avoid negative transfer in this paper. The first strategy is based on circular validation. The second strategy relies on the Maximum Mean Discrepancy (MMD) similarity metric, whereas the third one is an extension of MMD which incorporates the knowledge about the class labels in the source domain. Our method is evaluated using two different benchmark datasets. The experiments highlight the strengths and weaknesses of the investigated methods. We also show that it is possible to reduce the amount of negative transfer using these strategies for a TL method and to generate a consistent performance improvement over the whole dataset.

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

NASA Astrophysics Data System (ADS)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

Efficient FPT Algorithms for (Strict) Compatibility of Unrooted Phylogenetic Trees.

PubMed

Baste, Julien; Paul, Christophe; Sau, Ignasi; Scornavacca, Celine

2017-04-01

In phylogenetics, a central problem is to infer the evolutionary relationships between a set of species X; these relationships are often depicted via a phylogenetic tree-a tree having its leaves labeled bijectively by elements of X and without degree-2 nodes-called the "species tree." One common approach for reconstructing a species tree consists in first constructing several phylogenetic trees from primary data (e.g., DNA sequences originating from some species in X), and then constructing a single phylogenetic tree maximizing the "concordance" with the input trees. The obtained tree is our estimation of the species tree and, when the input trees are defined on overlapping-but not identical-sets of labels, is called "supertree." In this paper, we focus on two problems that are central when combining phylogenetic trees into a supertree: the compatibility and the strict compatibility problems for unrooted phylogenetic trees. These problems are strongly related, respectively, to the notions of "containing as a minor" and "containing as a topological minor" in the graph community. Both problems are known to be fixed parameter tractable in the number of input trees k, by using their expressibility in monadic second-order logic and a reduction to graphs of bounded treewidth. Motivated by the fact that the dependency on k of these algorithms is prohibitively large, we give the first explicit dynamic programming algorithms for solving these problems, both running in time [Formula: see text], where n is the total size of the input.

Semisupervised kernel marginal Fisher analysis for face recognition.

PubMed

Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

2013-01-01

Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

78 FR 6804 - Codex Alimentarius Commission: Meeting of the Codex Committee on Food Labeling

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-31

...; (c) Studying specific labeling problems assigned to it by Codex; and (d) Studying problems associated... the Production, Processing, Labeling and Marketing of Organically Produced Foods. (a) Use of ethylene... Washington, DC on January 24, 2013. Mary Frances Lowe, U.S. Manager for Codex Alimentarius. [FR Doc. 2013...

A linear programming approach to max-sum problem: a review.

PubMed

Werner, Tomás

2007-07-01

The max-sum labeling problem, defined as maximizing a sum of binary (i.e., pairwise) functions of discrete variables, is a general NP-hard optimization problem with many applications, such as computing the MAP configuration of a Markov random field. We review a not widely known approach to the problem, developed by Ukrainian researchers Schlesinger et al. in 1976, and show how it contributes to recent results, most importantly, those on the convex combination of trees and tree-reweighted max-product. In particular, we review Schlesinger et al.'s upper bound on the max-sum criterion, its minimization by equivalent transformations, its relation to the constraint satisfaction problem, the fact that this minimization is dual to a linear programming relaxation of the original problem, and the three kinds of consistency necessary for optimality of the upper bound. We revisit problems with Boolean variables and supermodular problems. We describe two algorithms for decreasing the upper bound. We present an example application for structural image analysis.

Development of cadmium-free quantum dot for intracellular labelling through electroporation or lipid-calcium-phosphate

NASA Astrophysics Data System (ADS)

Liu, Ying-Feng; Hung, Wei-Ling; Hou, Tzh-Yin; Huang, Hsiu-Ying; Lin, Cheng-An J.

2016-04-01

Traditional fluorescent labelling techniques has severe photo-bleaching problem such as organic dyes and fluorescent protein. Quantum dots made up of traditional semiconductor (CdSe/ZnS) material has sort of biological toxicity. This research has developed novel Cd-free quantum dots divided into semiconductor (Indium phosphide, InP) and noble metal (Gold). Former has lower toxicity compared to traditional quantum dots. Latter consisting of gold (III) chloride (AuCl3) and toluene utilizes sonochemical preparation and different stimulus to regulate fluorescent wavelength. Amphoteric macromolecule surface technology and ligand Exchange in self-Assembled are involved to develop hydrophilic nanomaterials which can regulate the number of grafts per molecule of surface functional groups. Calcium phosphate (CaP) nanoparticle (NP) with an asymmetric lipid bilayer coating technology developed for intracellular delivery and labelling has synthesized Cd-free quantum dots possessing high brightness and multi-fluorescence successfully. Then, polymer coating and ligand exchange transfer to water-soluble materials to produce liposome nanomaterials as fluorescent probes and enhancing medical applications of nanotechnology.

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.

Reliable Multi-Label Learning via Conformal Predictor and Random Forest for Syndrome Differentiation of Chronic Fatigue in Traditional Chinese Medicine

PubMed Central

Wang, Huazhen; Liu, Xin; Lv, Bing; Yang, Fan; Hong, Yanzhu

2014-01-01

Objective Chronic Fatigue (CF) still remains unclear about its etiology, pathophysiology, nomenclature and diagnostic criteria in the medical community. Traditional Chinese medicine (TCM) adopts a unique diagnostic method, namely ‘bian zheng lun zhi’ or syndrome differentiation, to diagnose the CF with a set of syndrome factors, which can be regarded as the Multi-Label Learning (MLL) problem in the machine learning literature. To obtain an effective and reliable diagnostic tool, we use Conformal Predictor (CP), Random Forest (RF) and Problem Transformation method (PT) for the syndrome differentiation of CF. Methods and Materials In this work, using PT method, CP-RF is extended to handle MLL problem. CP-RF applies RF to measure the confidence level (p-value) of each label being the true label, and then selects multiple labels whose p-values are larger than the pre-defined significance level as the region prediction. In this paper, we compare the proposed CP-RF with typical CP-NBC(Naïve Bayes Classifier), CP-KNN(K-Nearest Neighbors) and ML-KNN on CF dataset, which consists of 736 cases. Specifically, 95 symptoms are used to identify CF, and four syndrome factors are employed in the syndrome differentiation, including ‘spleen deficiency’, ‘heart deficiency’, ‘liver stagnation’ and ‘qi deficiency’. The Results CP-RF demonstrates an outstanding performance beyond CP-NBC, CP-KNN and ML-KNN under the general metrics of subset accuracy, hamming loss, one-error, coverage, ranking loss and average precision. Furthermore, the performance of CP-RF remains steady at the large scale of confidence levels from 80% to 100%, which indicates its robustness to the threshold determination. In addition, the confidence evaluation provided by CP is valid and well-calibrated. Conclusion CP-RF not only offers outstanding performance but also provides valid confidence evaluation for the CF syndrome differentiation. It would be well applicable to TCM practitioners and facilitate the utilities of objective, effective and reliable computer-based diagnosis tool. PMID:24918430

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234

Automatic prevention of label overlap

DOT National Transportation Integrated Search

1976-03-01

The project comprised a number of simulation exercises : designed to evaluate methods of either preventing or : resolving the problems likely to be caused by label overlap on : Labelled Plan Displays (LPD). The automatic prevention of : label overlap...

Quantifying immunogold labelling patterns of cellular compartments when they comprise mixtures of membranes (surface-occupying) and organelles (volume-occupying).

PubMed

Mayhew, Terry M; Lucocq, John M

2008-03-01

In quantitative immunoelectron microscopy, subcellular compartments that are preferentially labelled with colloidal gold particles can be identified by estimating labelling densities (LDs) and relative labelling indices (RLIs). Hitherto, this approach has been limited to compartments which are either surface occupying (membranes) or volume occupying (organelles) but not a mixture of both (membranes and organelles). However, some antigens are known to translocate between membrane and organelle compartments and the problem then arises of expressing gold particle LDs in a consistent manner (e.g., as number per compartment profile area). Here, we present one possible solution to tackle this problem. With this method, each membrane is treated as a volume-occupying compartment and this is achieved by creating an acceptance zone at a fixed distance on each side of membrane images. Gold signal intensity is then expressed as an LD within the membrane profile area so created and this LD can be compared to LDs found in volume-occupying compartments. Acceptance zone width is determined largely by the expected dispersion of gold labelling. In some cases, the zone can be applied to all visible membrane images but there is a potential problem when image loss occurs due to the fact that membranes are not cut orthogonal to their surface but are tilted within the section. The solution presented here is to select a subset of clear images representing orthogonally sectioned membranes (so-called local vertical windows, LVWs). The fraction of membrane images forming LVWs can be estimated in two ways: goniometrically (by determining the angle at which images become unclear) or stereologically (by counting intersections with test lines). The fraction obtained by either method can then be used to calculate a factor correcting for membrane image loss. In turn, this factor is used to estimate the total gold labelling associated with the acceptance zone of the entire (volume-occupying) membrane. However calculated, the LDs over the chosen (membrane and organelle) compartments are used to obtain observed and expected gold particle counts. The observed distribution is determined simply by counting gold particles associated with each compartment. Next, an expected distribution is created by randomly superimposing test points and counting those hitting each compartment. LDs of the chosen compartments are used to calculate RLI and chi-squared values and these serve to identify those compartments in which there is preferential labelling. The methods are illustrated by synthetic and real data.

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.

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.

Tanglegrams: A Reduction Tool for Mathematical Phylogenetics.

PubMed

Matsen, Frederick A; Billey, Sara C; Kas, Arnold; Konvalinka, Matjaz

2018-01-01

Many discrete mathematics problems in phylogenetics are defined in terms of the relative labeling of pairs of leaf-labeled trees. These relative labelings are naturally formalized as tanglegrams, which have previously been an object of study in coevolutionary analysis. Although there has been considerable work on planar drawings of tanglegrams, they have not been fully explored as combinatorial objects until recently. In this paper, we describe how many discrete mathematical questions on trees "factor" through a problem on tanglegrams, and how understanding that factoring can simplify analysis. Depending on the problem, it may be useful to consider a unordered version of tanglegrams, and/or their unrooted counterparts. For all of these definitions, we show how the isomorphism types of tanglegrams can be understood in terms of double cosets of the symmetric group, and we investigate their automorphisms. Understanding tanglegrams better will isolate the distinct problems on leaf-labeled pairs of trees and reveal natural symmetries of spaces associated with such problems.

Homography-based multiple-camera person-tracking

NASA Astrophysics Data System (ADS)

Turk, Matthew R.

2009-01-01

Multiple video cameras are cheaply installed overlooking an area of interest. While computerized single-camera tracking is well-developed, multiple-camera tracking is a relatively new problem. The main multi-camera problem is to give the same tracking label to all projections of a real-world target. This is called the consistent labelling problem. Khan and Shah (2003) introduced a method to use field of view lines to perform multiple-camera tracking. The method creates inter-camera meta-target associations when objects enter at the scene edges. They also said that a plane-induced homography could be used for tracking, but this method was not well described. Their homography-based system would not work if targets use only one side of a camera to enter the scene. This paper overcomes this limitation and fully describes a practical homography-based tracker. A new method to find the feet feature is introduced. The method works especially well if the camera is tilted, when using the bottom centre of the target's bounding-box would produce inaccurate results. The new method is more accurate than the bounding-box method even when the camera is not tilted. Next, a method is presented that uses a series of corresponding point pairs "dropped" by oblivious, live human targets to find a plane-induced homography. The point pairs are created by tracking the feet locations of moving targets that were associated using the field of view line method. Finally, a homography-based multiple-camera tracking algorithm is introduced. Rules governing when to create the homography are specified. The algorithm ensures that homography-based tracking only starts after a non-degenerate homography is found. The method works when not all four field of view lines are discoverable; only one line needs to be found to use the algorithm. To initialize the system, the operator must specify pairs of overlapping cameras. Aside from that, the algorithm is fully automatic and uses the natural movement of live targets for training. No calibration is required. Testing shows that the algorithm performs very well in real-world sequences. The consistent labelling problem is solved, even for targets that appear via in-scene entrances. Full occlusions are handled. Although implemented in Matlab, the multiple-camera tracking system runs at eight frames per second. A faster implementation would be suitable for real-world use at typical video frame rates.

Matching by linear programming and successive convexification.

PubMed

Jiang, Hao; Drew, Mark S; Li, Ze-Nian

2007-06-01

We present a novel convex programming scheme to solve matching problems, focusing on the challenging problem of matching in a large search range and with cluttered background. Matching is formulated as metric labeling with L1 regularization terms, for which we propose a novel linear programming relaxation method and an efficient successive convexification implementation. The unique feature of the proposed relaxation scheme is that a much smaller set of basis labels is used to represent the original label space. This greatly reduces the size of the searching space. A successive convexification scheme solves the labeling problem in a coarse to fine manner. Importantly, the original cost function is reconvexified at each stage, in the new focus region only, and the focus region is updated so as to refine the searching result. This makes the method well-suited for large label set matching. Experiments demonstrate successful applications of the proposed matching scheme in object detection, motion estimation, and tracking.

Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system.

PubMed

Crown, Scott B; Long, Christopher P; Antoniewicz, Maciek R

2016-11-01

13 C-Metabolic flux analysis ( 13 C-MFA) is a widely used approach in metabolic engineering for quantifying intracellular metabolic fluxes. The precision of fluxes determined by 13 C-MFA depends largely on the choice of isotopic tracers and the specific set of labeling measurements. A recent advance in the field is the use of parallel labeling experiments for improved flux precision and accuracy. However, as of today, no systemic methods exist for identifying optimal tracers for parallel labeling experiments. In this contribution, we have addressed this problem by introducing a new scoring system and evaluating thousands of different isotopic tracer schemes. Based on this extensive analysis we have identified optimal tracers for 13 C-MFA. The best single tracers were doubly 13 C-labeled glucose tracers, including [1,6- 13 C]glucose, [5,6- 13 C]glucose and [1,2- 13 C]glucose, which consistently produced the highest flux precision independent of the metabolic flux map (here, 100 random flux maps were evaluated). Moreover, we demonstrate that pure glucose tracers perform better overall than mixtures of glucose tracers. For parallel labeling experiments the optimal isotopic tracers were [1,6- 13 C]glucose and [1,2- 13 C]glucose. Combined analysis of [1,6- 13 C]glucose and [1,2- 13 C]glucose labeling data improved the flux precision score by nearly 20-fold compared to widely use tracer mixture 80% [1- 13 C]glucose +20% [U- 13 C]glucose. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

The Stigma of Mental Illness as a Barrier to Self Labeling as Having a Mental Illness.

PubMed

Stolzenburg, Susanne; Freitag, Simone; Evans-Lacko, Sara; Muehlan, Holger; Schmidt, Silke; Schomerus, Georg

2017-12-01

The aim of this study was to investigate whether personal stigma decreases self-identification as having a mental illness in individuals with untreated mental health problems. We interviewed 207 persons with a currently untreated mental health problem as confirmed by a structured diagnostic interview. Measures included symptom appraisal, self-identification as having a mental illness (SELFI), self-labeling (open-ended question on the nature of their problem) stigma-related variables (explicit and implicit), as well as sociodemographics, current symptom severity, and previous treatment. Support for discrimination and implicit stigmatizing attitude were both associated with lower likelihood of self-identification. More social distance and support for discrimination were associated with less self-labeling. Previous treatment was the strongest predictor of symptom appraisal, SELFI, and self-labeling. Destigmatizing mental illness could increase awareness of personal mental health problems, potentially leading to lower rates of untreated mental illness.

Adolescent peer group identification and characteristics: A review of the literature

PubMed Central

Sussman, Steve; Pokhrel, Pallav; Ashmore, Richard D.; Brown, B. Bradford

2011-01-01

This study provides an exhaustive review of 44 peer-reviewed quantitative or qualitative data-based peer-reviewed studies completed on adolescent peer group identification. Adolescent peer group identification is one’s self-perceived or other-perceived membership in discrete teenage peer groups. The studies reviewed suggest that adolescent peer groups consist of five general categories differentiable by lifestyle characteristics: Elites, Athletes, Academics, Deviants, and Others. We found that the Deviant adolescent group category reported relatively greater participation in drug use and other problem behaviors across studies, whereas Academics and Athletes exhibited the least participation in these problem behaviors. Additional research is needed in this arena to better understand the operation of adolescent group labels. PMID:17188815

Digital autonomous terminal access communications

NASA Technical Reports Server (NTRS)

Novacki, S.

1987-01-01

A significant problem for the Bus Monitor Unit is to identify the source of a given transmission. This problem arises from the fact that the label which identifies the source of the transmission as it is put into the bus is intercepted by the Digital Autonomous Terminal Access Communications (DATAC) terminal and removed from the transmission. Thus, a given subsystem will see only data associated with a label and never the identifying label itself. The Bus Monitor must identify the source of the transmission so as to be able to provide some type of error identification/location in the event that some problem with the data transmission occurs. Steps taken to alleviate this problem by modifications to the DATAC terminal are discussed.

Tyrosinase autoactivation and the problem of the lag period.

PubMed

Naish-Byfield, S; Riley, P A

1998-06-01

Evidence is presented for the binding of the quinone oxidation product of the monohydric phenol substrate, 4-hydroxyanisole, to mushroom tyrosinase. Column chromatography and SDS-PAGE separation showed labelling of the enzyme when incubated with 14C ring-labelled 4-hydroxyanisole. It is proposed that covalent binding to the enzyme and other proteins is through reaction of accessible nucleophilic groups, including thiols and amino groups, with the anisylquinone. This reductive addition enables the indirect generation of the catecholic substrate, which acts as an electron donor for the bicupric active site of met-tyrosinase and explains the lag kinetics of tyrosinase oxidation of non-cyclizing substrates. The effects of diluting the enzyme or the addition of amino acids on the lag period was consistent with a mechanism involving indirect generation of the dihydric phenol, which acts as the met-enzyme-recruiting substrate.

A path following algorithm for the graph matching problem.

PubMed

Zaslavskiy, Mikhail; Bach, Francis; Vert, Jean-Philippe

2009-12-01

We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the weighted graph matching problem as a least-square problem on the set of permutation matrices and relaxing it to two different optimization problems: a quadratic convex and a quadratic concave optimization problem on the set of doubly stochastic matrices. The concave relaxation has the same global minimum as the initial graph matching problem, but the search for its global minimum is also a hard combinatorial problem. We, therefore, construct an approximation of the concave problem solution by following a solution path of a convex-concave problem obtained by linear interpolation of the convex and concave formulations, starting from the convex relaxation. This method allows to easily integrate the information on graph label similarities into the optimization problem, and therefore, perform labeled weighted graph matching. The algorithm is compared with some of the best performing graph matching methods on four data sets: simulated graphs, QAPLib, retina vessel images, and handwritten Chinese characters. In all cases, the results are competitive with the state of the art.

101 Labeled Brain Images and a Consistent Human Cortical Labeling Protocol

PubMed Central

Klein, Arno; Tourville, Jason

2012-01-01

We introduce the Mindboggle-101 dataset, the largest and most complete set of free, publicly accessible, manually labeled human brain images. To manually label the macroscopic anatomy in magnetic resonance images of 101 healthy participants, we created a new cortical labeling protocol that relies on robust anatomical landmarks and minimal manual edits after initialization with automated labels. The “Desikan–Killiany–Tourville” (DKT) protocol is intended to improve the ease, consistency, and accuracy of labeling human cortical areas. Given how difficult it is to label brains, the Mindboggle-101 dataset is intended to serve as brain atlases for use in labeling other brains, as a normative dataset to establish morphometric variation in a healthy population for comparison against clinical populations, and contribute to the development, training, testing, and evaluation of automated registration and labeling algorithms. To this end, we also introduce benchmarks for the evaluation of such algorithms by comparing our manual labels with labels automatically generated by probabilistic and multi-atlas registration-based approaches. All data and related software and updated information are available on the http://mindboggle.info/data website. PMID:23227001

[Not quite the same: illness beliefs regarding burnout and depression among the general population].

PubMed

Bahlmann, Johannes; Schomerus, Georg; Angermeyer, Matthias C

2015-11-01

This study examined illness beliefs of the lay public associated with the diagnostic labels burnout and depression. Representative population survey in Germany 2011, using unlabelled case vignettes of a person suffering from depression. Following presentation of the vignette, respondents were asked openly how they would call the problem described. Agreement with various illness beliefs was elicited with Likert-scaled items. Seeing the problem as inherited predicted use of the label depression (OR 1.29, p < 0.001), while stress at work as a perceived cause was associated with use of the label burnout (OR 1.56, p < 0.001). Belief that the problem described resembled everyday experiences (belief in a symptom continuum) also predicted using the label burnout instead of depression (OR 1.31, p < 0.05). Although overlapping with beliefs about depression, the diagnostic label burnout is also associated with specific illness beliefs among the general public. © Georg Thieme Verlag KG Stuttgart · New York.

Classifying syndromes in Chinese medicine using multi-label learning algorithm with relevant features for each label.

PubMed

Xu, Jin; Xu, Zhao-Xia; Lu, Ping; Guo, Rui; Yan, Hai-Xia; Xu, Wen-Jie; Wang, Yi-Qin; Xia, Chun-Ming

2016-11-01

To develop an effective Chinese Medicine (CM) diagnostic model of coronary heart disease (CHD) and to confifirm the scientifific validity of CM theoretical basis from an algorithmic viewpoint. Four types of objective diagnostic data were collected from 835 CHD patients by using a self-developed CM inquiry scale for the diagnosis of heart problems, a tongue diagnosis instrument, a ZBOX-I pulse digital collection instrument, and the sound of an attending acquisition system. These diagnostic data was analyzed and a CM diagnostic model was established using a multi-label learning algorithm (REAL). REAL was employed to establish a Xin (Heart) qi defificiency, Xin yang defificiency, Xin yin defificiency, blood stasis, and phlegm fifive-card CM diagnostic model, which had recognition rates of 80.32%, 89.77%, 84.93%, 85.37%, and 69.90%, respectively. The multi-label learning method established using four diagnostic models based on mutual information feature selection yielded good recognition results. The characteristic model parameters were selected by maximizing the mutual information for each card type. The four diagnostic methods used to obtain information in CM, i.e., observation, auscultation and olfaction, inquiry, and pulse diagnosis, can be characterized by these parameters, which is consistent with CM theory.

Application of Multilabel Learning Using the Relevant Feature for Each Label in Chronic Gastritis Syndrome Diagnosis

PubMed Central

Liu, Guo-Ping; Yan, Jian-Jun; Wang, Yi-Qin; Fu, Jing-Jing; Xu, Zhao-Xia; Guo, Rui; Qian, Peng

2012-01-01

Background. In Traditional Chinese Medicine (TCM), most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs). Methods. We employed a multilabel learning using the relevant feature for each label (REAL) algorithm to construct a syndrome diagnostic model for chronic gastritis (CG) in TCM. REAL combines feature selection methods to select the significant symptoms (signs) of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL), whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs) for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice. PMID:22719781

Label consistent K-SVD: learning a discriminative dictionary for recognition.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2013-11-01

A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discriminability in sparse codes during the dictionary learning process. More specifically, we introduce a new label consistency constraint called "discriminative sparse-code error" and combine it with the reconstruction error and the classification error to form a unified objective function. The optimal solution is efficiently obtained using the K-SVD algorithm. Our algorithm learns a single overcomplete dictionary and an optimal linear classifier jointly. The incremental dictionary learning algorithm is presented for the situation of limited memory resources. It yields dictionaries so that feature points with the same class labels have similar sparse codes. Experimental results demonstrate that our algorithm outperforms many recently proposed sparse-coding techniques for face, action, scene, and object category recognition under the same learning conditions.

16 CFR 309.21 - Labeling requirements for used covered vehicles.

Code of Federal Regulations, 2010 CFR

2010-01-01

... visible surface of each such vehicle. (b) Layout. Figure 6 of appendix A is the prototype label that... consistent with the prototype label. The label required by this section is one-sided and rectangular in shape... label. Specific type sizes and faces to be used are indicated on the prototype label (Figure 6 of...

Two-photon in vivo flow cytometry using a fiber probe

NASA Astrophysics Data System (ADS)

Chang, Yu-Chung; Ye, Jing Yong; Thomas, Thommey P.; Cao, Zhengyi; Kotlyar, Alina; Tkaczyk, Eric R.; Baker, James R., Jr.; Norris, Theodore B.

2009-02-01

We have demonstrated the use of a double-clad fiber probe to conduct two-photon excited flow cytometry in vitro and in vivo. We conducted two-channel detection to measure fluorescence at two distinct wavelengths simultaneously. Because the scattering and absorption problems from whole blood were circumvented by the fiber probe, the detected signal strength from the cells were found to be similar in PBS and in whole blood. We achieved the same detection efficiency of the membrane-binding lipophilic dye DiD labeled cells in PBS and in whole blood. High detection efficiency of green fluorescent protein (GFP)-expressing cells in whole blood was demonstrated. DiD-labeled untransfected and GFP-transfected cells were injected into live mice and the circulation dynamics of the externally injected cells were monitored. The detection efficiency of GFP-expressing cells in vivo was consistent with that observed in whole blood.

A Spacecraft Electrical Characteristics Multi-Label Classification Method Based on Off-Line FCM Clustering and On-Line WPSVM

PubMed Central

Li, Ke; Liu, Yi; Wang, Quanxin; Wu, Yalei; Song, Shimin; Sun, Yi; Liu, Tengchong; Wang, Jun; Li, Yang; Du, Shaoyi

2015-01-01

This paper proposes a novel multi-label classification method for resolving the spacecraft electrical characteristics problems which involve many unlabeled test data processing, high-dimensional features, long computing time and identification of slow rate. Firstly, both the fuzzy c-means (FCM) offline clustering and the principal component feature extraction algorithms are applied for the feature selection process. Secondly, the approximate weighted proximal support vector machine (WPSVM) online classification algorithms is used to reduce the feature dimension and further improve the rate of recognition for electrical characteristics spacecraft. Finally, the data capture contribution method by using thresholds is proposed to guarantee the validity and consistency of the data selection. The experimental results indicate that the method proposed can obtain better data features of the spacecraft electrical characteristics, improve the accuracy of identification and shorten the computing time effectively. PMID:26544549

Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions.

PubMed

Chen, Ke; Wang, Shihai

2011-01-01

Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learning with various strategies. To our knowledge, however, none of them takes all three semi-supervised assumptions, i.e., smoothness, cluster, and manifold assumptions, together into account during boosting learning. In this paper, we propose a novel cost functional consisting of the margin cost on labeled data and the regularization penalty on unlabeled data based on three fundamental semi-supervised assumptions. Thus, minimizing our proposed cost functional with a greedy yet stagewise functional optimization procedure leads to a generic boosting framework for semi-supervised learning. Extensive experiments demonstrate that our algorithm yields favorite results for benchmark and real-world classification tasks in comparison to state-of-the-art semi-supervised learning algorithms, including newly developed boosting algorithms. Finally, we discuss relevant issues and relate our algorithm to the previous work.

An overview of four studies of a continuous oral contraceptive (levonorgestrel 90 mcg/ethinyl estradiol 20 mcg) on premenstrual dysphoric disorder and premenstrual syndrome.

PubMed

Freeman, Ellen W; Halbreich, Uriel; Grubb, Gary S; Rapkin, Andrea J; Skouby, Sven O; Smith, Lynne; Mirkin, Sebastian; Constantine, Ginger D

2012-05-01

This article presents an overview of four studies that evaluated a continuous oral contraceptive (OC) containing levonorgestrel (90 mcg) and ethinyl estradiol (20 mcg; LNG/EE) for managing premenstrual dysphoric disorder (PMDD) and premenstrual syndrome (PMS). Three randomized, double-blind, placebo-controlled trials and one open-label, single-treatment substudy examined mean changes from baseline in the Daily Record of Severity of Problems (DRSP) or Penn Daily Symptom Rating (DSR). Improvements from baseline in mean DRSP and DSR scores were observed, but results were not consistent among the studies. Mean percent improvement of premenstrual symptoms ranged from 30% to 59% in controlled trials and 56% to 81% in an open-label substudy. A large placebo effect was also observed in the placebo-controlled studies. Continuous LNG/EE yielded a favorable safety profile. These data, although not consistent, indicate that continuous LNG/EE may reduce the symptoms of PMDD and PMS, providing an option for women who are appropriate candidates for a continuous OC as a contraceptive, the approved indication for this medication. Copyright © 2012 Elsevier Inc. All rights reserved.

Pictorial Prescription Labels.

ERIC Educational Resources Information Center

Bratt, Jeremy

1978-01-01

Describes an experimental system which uses pictorial representation for labeling prescribed medicines in the United Kingdom. Since the pictorial approach breaks the language barrier, the labels should present no problems either to illiterates or minority groups who have difficulty in understanding English. (JEG)

After the "At-Risk" Label: Reorienting Educational Policy and Practice. Disability, Culture, and Equity Series

ERIC Educational Resources Information Center

Brown, Keffrelyn D.

2016-01-01

This book examines how the use of the "at-risk" category and label creates problems for students and teachers. Drawing from research across various education sites, the author illustrates how educators recognize the label's potential to redress issues of equity, but warns that it can also stigmatize the students so labeled. Brown…

Some approaches to optimal cluster labeling of aerospace imagery

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1980-01-01

Some approaches are presented to the problem of labeling clusters using information from a given set of labeled and unlabeled aerospace imagery patterns. The assignment of class labels to the clusters is formulated as the determination of the best assignment over all possible ones with respect to some criterion. Cluster labeling is also viewed as the probability of correct labeling with a maximization of likelihood function. Results of the application of these techniques in the processing of remotely sensed multispectral scanner imagery data are presented.

Estimating Classifier Accuracy Using Noisy Expert Labels

DTIC Science & Technology

estimators to real -world problems is limited. We applythe estimators to labels simulated from three models of the expert labeling process and also four real ...thatconditional dependence between experts negatively impacts estimator performance. On two of the real datasets, the estimatorsclearly outperformed the

A mechanistic model for bromodeoxyuridine dilution naturally explains labelling data of self-renewing T cell populations

PubMed Central

Ganusov, Vitaly V.; De Boer, Rob J.

2013-01-01

Bromodeoxyuridine (BrdU) is widely used in immunology to detect cell division, and several mathematical models have been proposed to estimate proliferation and death rates of lymphocytes from BrdU labelling and de-labelling curves. One problem in interpreting BrdU data is explaining the de-labelling curves. Because shortly after label withdrawal, BrdU+ cells are expected to divide into BrdU+ daughter cells, one would expect a flat down-slope. As for many cell types, the fraction of BrdU+ cells decreases during de-labelling, previous mathematical models had to make debatable assumptions to be able to account for the data. We develop a mechanistic model tracking the number of divisions that each cell has undergone in the presence and absence of BrdU, and allow cells to accumulate and dilute their BrdU content. From the same mechanistic model, one can naturally derive expressions for the mean BrdU content (MBC) of all cells, or the MBC of the BrdU+ subset, which is related to the mean fluorescence intensity of BrdU that can be measured in experiments. The model is extended to include subpopulations with different rates of division and death (i.e. kinetic heterogeneity). We fit the extended model to previously published BrdU data from memory T lymphocytes in simian immunodeficiency virus-infected and uninfected macaques, and find that the model describes the data with at least the same quality as previous models. Because the same model predicts a modest decline in the MBC of BrdU+ cells, which is consistent with experimental observations, BrdU dilution seems a natural explanation for the observed down-slopes in self-renewing populations. PMID:23034350

21 CFR 336.50 - Labeling of antiemetic drug products.

Code of Federal Regulations, 2011 CFR

2011-04-01

... labeled for use in adults and for those products that can be and are labeled for use in children under 12... enlargement of the prostate gland.” (ii) For those products that can be and are labeled only for children under 12 years of age. “Do not give this product to children who have a breathing problem such as...

Ideal regularization for learning kernels from labels.

PubMed

Pan, Binbin; Lai, Jianhuang; Shen, Lixin

2014-08-01

In this paper, we propose a new form of regularization that is able to utilize the label information of a data set for learning kernels. The proposed regularization, referred to as ideal regularization, is a linear function of the kernel matrix to be learned. The ideal regularization allows us to develop efficient algorithms to exploit labels. Three applications of the ideal regularization are considered. Firstly, we use the ideal regularization to incorporate the labels into a standard kernel, making the resulting kernel more appropriate for learning tasks. Next, we employ the ideal regularization to learn a data-dependent kernel matrix from an initial kernel matrix (which contains prior similarity information, geometric structures, and labels of the data). Finally, we incorporate the ideal regularization to some state-of-the-art kernel learning problems. With this regularization, these learning problems can be formulated as simpler ones which permit more efficient solvers. Empirical results show that the ideal regularization exploits the labels effectively and efficiently. Copyright © 2014 Elsevier Ltd. All rights reserved.

Towards Automated Structure-Based NMR Resonance Assignment

NASA Astrophysics Data System (ADS)

Jang, Richard; Gao, Xin; Li, Ming

We propose a general framework for solving the structure-based NMR backbone resonance assignment problem. The core is a novel 0-1 integer programming model that can start from a complete or partial assignment, generate multiple assignments, and model not only the assignment of spins to residues, but also pairwise dependencies consisting of pairs of spins to pairs of residues. It is still a challenge for automated resonance assignment systems to perform the assignment directly from spectra without any manual intervention. To test the feasibility of this for structure-based assignment, we integrated our system with our automated peak picking and sequence-based resonance assignment system to obtain an assignment for the protein TM1112 with 91% recall and 99% precision without manual intervention. Since using a known structure has the potential to allow one to use only N-labeled NMR data and avoid the added expense of using C-labeled data, we work towards the goal of automated structure-based assignment using only such labeled data. Our system reduced the assignment error of Xiong-Pandurangan-Bailey-Kellogg's contact replacement (CR) method, which to our knowledge is the most error-tolerant method for this problem, by 5 folds on average. By using an iterative algorithm, our system has the added capability of using the NOESY data to correct assignment errors due to errors in predicting the amino acid and secondary structure type of each spin system. On a publicly available data set for Ubiquitin, where the type prediction accuracy is 83%, we achieved 91% assignment accuracy, compared to the 59% accuracy that was obtained without correcting for typing errors.

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.

Evaluation of the procedure for separating barley from other spring small grains. [North Dakota, South Dakota, Minnesota and Montana

NASA Technical Reports Server (NTRS)

Magness, E. R. (Principal Investigator)

1980-01-01

The success of the Transition Year procedure to separate and label barley and the other small grains was assessed. It was decided that developers of the procedure would carry out the exercise in order to prevent compounding procedural problems with implementation problems. The evaluation proceeded by labeling the sping small grains first. The accuracy of this labeling was, on the average, somewhat better than that in the Transition Year operations. Other departures from the original procedure included a regionalization of the labeling process, the use of trend analysis, and the removal of time constraints from the actual processing. Segment selection, ground truth derivation, and data available for each segment in the analysis are discussed. Labeling accuracy is examined for North Dakota, South Dakota, Minnesota, and Montana as well as for the entire four-state area. Errors are characterized.

Interpretation and use of the 5-level EQ-5D response labels varied with survey language among Asians in Singapore.

PubMed

Luo, Nan; Wang, Ye; How, Choon How; Tay, Ee Guan; Thumboo, Julian; Herdman, Michael

2015-10-01

This study aimed to investigate the comparability of the English, Chinese, and Malay versions of the 5-level EQ-5D (EQ-5D-5L) response labels in Singapore. Visitors to a primary care institution in Singapore (n = 743) were asked to complete two exercises: (1) rating the severity of the EQ-5D-5L response labels presented in English, Chinese, or Malay using a 0-100 numeric rating scale and (2) using the labels to describe various hypothetical health problems. Label ratings and choices between language versions were compared using regression analysis. Perceived severity of the English and Chinese labels was similar. Compared with their English counterparts, the Malay label "slight(ly)" was rated as more severe (adjusted mean difference: 10.5 to 14.5) and "unable"/"extreme(ly)" as less severe (adjusted mean difference: -13.3 to -11.0) (P < 0.001 for all). The Malay labels "no(t)" and "unable"/"extreme(ly)" and the less severe Chinese labels were more frequently used to describe hypothetical health problems than their English counterparts. Interpretation and use of the EQ-5D-5L response labels vary among Singaporeans using different language versions of the instrument. Future studies need to investigate ways to reduce the variations and increase the cross-cultural measurement equivalence of the instrument. Copyright © 2015 Elsevier Inc. All rights reserved.

Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

PubMed Central

Wang, Hongzhi; Yushkevich, Paul A.

2013-01-01

Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far. PMID:24319427

Tools for Protecting the Privacy of Specific Individuals in Video

NASA Astrophysics Data System (ADS)

Chen, Datong; Chang, Yi; Yan, Rong; Yang, Jie

2007-12-01

This paper presents a system for protecting the privacy of specific individuals in video recordings. We address the following two problems: automatic people identification with limited labeled data, and human body obscuring with preserved structure and motion information. In order to address the first problem, we propose a new discriminative learning algorithm to improve people identification accuracy using limited training data labeled from the original video and imperfect pairwise constraints labeled from face obscured video data. We employ a robust face detection and tracking algorithm to obscure human faces in the video. Our experiments in a nursing home environment show that the system can obtain a high accuracy of people identification using limited labeled data and noisy pairwise constraints. The study result indicates that human subjects can perform reasonably well in labeling pairwise constraints with the face masked data. For the second problem, we propose a novel method of body obscuring, which removes the appearance information of the people while preserving rich structure and motion information. The proposed approach provides a way to minimize the risk of exposing the identities of the protected people while maximizing the use of the captured data for activity/behavior analysis.

Qualitative Constraint Reasoning For Image Understanding

NASA Astrophysics Data System (ADS)

Perry, John L.

1987-05-01

Military planners and analysts are exceedingly concerned with increasing the effectiveness of command and control (C2) processes for battlefield management (BM). A variety of technical approaches have been taken in this effort. These approaches are intended to support and assist commanders in situation assessment, course of action generation and evaluation, and other C2 decision-making tasks. A specific task within this technology support includes the ability to effectively gather information concerning opposing forces and plan/replan tactical maneuvers. Much of the information that is gathered is image-derived, along with collateral data supporting this visual imagery. In this paper, we intend to describe a process called qualitative constraint reasoning (QCR) which is being developed as a mechanism for reasoning in the mid to high level vision domain. The essential element of QCR is the abstraction process. One of the factors that is unique to QCR is the level at which the abstraction process occurs relative to the problem domain. The computational mechanisms used in QCR belong to a general class of problem called the consistent labeling problem. The success of QCR is its ability to abstract out from a visual domain a structure appropriate for applying the labeling procedure. An example will be given that will exemplify the abstraction process for a battlefield management application. Exploratory activities are underway for investigating the suitability of QCR approach for the battlefield scenario. Further research is required to investigate the utility of QCR in a more complex battlefield environment.

Heuristics in Problem Solving: The Role of Direction in Controlling Search Space

ERIC Educational Resources Information Center

Chu, Yun; Li, Zheng; Su, Yong; Pizlo, Zygmunt

2010-01-01

Isomorphs of a puzzle called m+m resulted in faster solution times and an easily reproduced solution path in a labeled version of the problem compared to a more difficult binary version. We conjecture that performance is related to a type of heuristic called direction that not only constrains search space in the labeled version, but also…

Reactions to FDA-Proposed Graphic Warning Labels Affixed to U.S. Smokers' Cigarette Packs.

PubMed

McQueen, Amy; Kreuter, Matthew W; Boyum, Sonia; Thompson, Vetta S; Caburnay, Charlene A; Waters, Erika A; Kaphingst, Kimberly A; Rath, Suchitra; Fu, Qiang

2015-07-01

Graphic warning labels have been shown to be more effective than text-only labels in increasing attention and perceived health risks, but most U.S. studies have involved single exposures in laboratory or Internet settings. We recruited a convenience sample (N = 202) of U.S. adult smokers from population subgroups with higher rates of smoking and smoking-related deaths who had participated in a larger survey about graphic warning labels. Participants were randomized to get 1 of 9 graphic + text labels or a text-only label. Research staff affixed a warning label sticker to participants' cigarette pack(s) at enrollment. Color graphic labels covered slightly more than the lower half of packs. Black and white labels of current U.S. text-only warnings covered the existing side warning to prompt attention to the label (i.e., attention control). Participants received extra stickers of the same label for subsequent packs, and completed 3 telephone interviews in 1 week. Participants reported low avoidance (<34%) and consistent use of the stickers (91%). Smokers consistently paid more attention to graphic than text-only labels. Only 5 of the 9 graphic warning labels were significantly associated with greater thoughts of health risks. Thinking about quitting and stopping smoking did not differ by label. Qualitative data illustrated differences in the "stickiness," self-referencing, and counterarguments of graphic warning labels. U.S. smokers' reactions to graphic warning labels on their own packs were similar to other, more controlled studies. Qualitative findings underscore the need for warning labels that encourage self-referential processing without increasing defensive reactions. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Reactions to FDA-Proposed Graphic Warning Labels Affixed to U.S. Smokers’ Cigarette Packs

PubMed Central

Kreuter, Matthew W.; Boyum, Sonia; Thompson, Vetta S.; Caburnay, Charlene A.; Waters, Erika A.; Kaphingst, Kimberly A.; Rath, Suchitra; Fu, Qiang

2015-01-01

Introduction: Graphic warning labels have been shown to be more effective than text-only labels in increasing attention and perceived health risks, but most U.S. studies have involved single exposures in laboratory or Internet settings. Methods: We recruited a convenience sample (N = 202) of U.S. adult smokers from population subgroups with higher rates of smoking and smoking-related deaths who had participated in a larger survey about graphic warning labels. Participants were randomized to get 1 of 9 graphic + text labels or a text-only label. Research staff affixed a warning label sticker to participants’ cigarette pack(s) at enrollment. Color graphic labels covered slightly more than the lower half of packs. Black and white labels of current U.S. text-only warnings covered the existing side warning to prompt attention to the label (i.e., attention control). Participants received extra stickers of the same label for subsequent packs, and completed 3 telephone interviews in 1 week. Results: Participants reported low avoidance (<34%) and consistent use of the stickers (91%). Smokers consistently paid more attention to graphic than text-only labels. Only 5 of the 9 graphic warning labels were significantly associated with greater thoughts of health risks. Thinking about quitting and stopping smoking did not differ by label. Qualitative data illustrated differences in the “stickiness,” self-referencing, and counterarguments of graphic warning labels. Conclusions: U.S. smokers’ reactions to graphic warning labels on their own packs were similar to other, more controlled studies. Qualitative findings underscore the need for warning labels that encourage self-referential processing without increasing defensive reactions. PMID:25589676

16 CFR 309.20 - Labeling requirements for new covered vehicles.

Code of Federal Regulations, 2010 CFR

2010-01-01

.... (b) Layout. Figures 4, 5, and 5.1 are prototype labels that demonstrate the proper layout. All positioning, spacing, type size, and line widths shall be similar to and consistent with the prototype labels... and 71/2 inches (19.05 cm) long. Figure 4 of appendix A represents the prototype for the labels for...

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

Orthology and paralogy constraints: satisfiability and consistency.

PubMed

Lafond, Manuel; El-Mabrouk, Nadia

2014-01-01

A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family  G. But is a given set  C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for  G? While previous studies have focused on full sets of constraints, here we consider the general case where  C does not necessarily involve a constraint for each pair of genes. The problem is subdivided in two parts: (1) Is  C satisfiable, i.e. can we find an event-labeled gene tree G inducing  C? (2) Is there such a G which is consistent, i.e., such that all displayed triplet phylogenies are included in a species tree? Previous results on the Graph sandwich problem can be used to answer to (1), and we provide polynomial-time algorithms for satisfiability and consistency with a given species tree. We also describe a new polynomial-time algorithm for the case of consistency with an unknown species tree and full knowledge of pairwise orthology/paralogy relationships, as well as a branch-and-bound algorithm in the case when unknown relations are present. We show that our algorithms can be used in combination with ProteinOrtho, a sequence similarity-based orthology detection tool, to extract a set of robust orthology/paralogy relationships.

Orthology and paralogy constraints: satisfiability and consistency

PubMed Central

2014-01-01

Background A variety of methods based on sequence similarity, reconciliation, synteny or functional characteristics, can be used to infer orthology and paralogy relations between genes of a given gene family  G. But is a given set  C of orthology/paralogy constraints possible, i.e., can they simultaneously co-exist in an evolutionary history for  G? While previous studies have focused on full sets of constraints, here we consider the general case where  C does not necessarily involve a constraint for each pair of genes. The problem is subdivided in two parts: (1) Is  C satisfiable, i.e. can we find an event-labeled gene tree G inducing  C? (2) Is there such a G which is consistent, i.e., such that all displayed triplet phylogenies are included in a species tree? Results Previous results on the Graph sandwich problem can be used to answer to (1), and we provide polynomial-time algorithms for satisfiability and consistency with a given species tree. We also describe a new polynomial-time algorithm for the case of consistency with an unknown species tree and full knowledge of pairwise orthology/paralogy relationships, as well as a branch-and-bound algorithm in the case when unknown relations are present. We show that our algorithms can be used in combination with ProteinOrtho, a sequence similarity-based orthology detection tool, to extract a set of robust orthology/paralogy relationships. PMID:25572629

Label-enhanced surface plasmon resonance applied to label-free interaction analysis of small molecules and fragments.

PubMed

Eng, Lars; Nygren-Babol, Linnéa; Hanning, Anders

2016-10-01

Surface plasmon resonance (SPR) is a well-established method for studying interactions between small molecules and biomolecules. In particular, SPR is being increasingly applied within fragment-based drug discovery; however, within this application area, the limited sensitivity of SPR may constitute a problem. This problem can be circumvented by the use of label-enhanced SPR that shows a 100-fold higher sensitivity as compared with conventional SPR. Truly label-free interaction data for small molecules can be obtained by applying label-enhanced SPR in a surface competition assay format. The enhanced sensitivity is accompanied by an increased specificity and inertness toward disturbances (e.g., bulk refractive index disturbances). Label-enhanced SPR can be used for fragment screening in a competitive assay format; the competitive format has the added advantage of confirming the specificity of the molecular interaction. In addition, label-enhanced SPR extends the accessible kinetic regime of SPR to the analysis of very fast fragment binding kinetics. In this article, we demonstrate the working principles and benchmark the performance of label-enhanced SPR in a model system-the interaction between carbonic anhydrase II and a number of small-molecule sulfonamide-based inhibitors. Copyright © 2016 Elsevier Inc. All rights reserved.

A general soft label based linear discriminant analysis for semi-supervised dimensionality reduction.

PubMed

Zhao, Mingbo; Zhang, Zhao; Chow, Tommy W S; Li, Bing

2014-07-01

Dealing with high-dimensional data has always been a major problem in research of pattern recognition and machine learning, and Linear Discriminant Analysis (LDA) is one of the most popular methods for dimension reduction. However, it only uses labeled samples while neglecting unlabeled samples, which are abundant and can be easily obtained in the real world. In this paper, we propose a new dimension reduction method, called "SL-LDA", by using unlabeled samples to enhance the performance of LDA. The new method first propagates label information from the labeled set to the unlabeled set via a label propagation process, where the predicted labels of unlabeled samples, called "soft labels", can be obtained. It then incorporates the soft labels into the construction of scatter matrixes to find a transformed matrix for dimension reduction. In this way, the proposed method can preserve more discriminative information, which is preferable when solving the classification problem. We further propose an efficient approach for solving SL-LDA under a least squares framework, and a flexible method of SL-LDA (FSL-LDA) to better cope with datasets sampled from a nonlinear manifold. Extensive simulations are carried out on several datasets, and the results show the effectiveness of the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Health warning labels for alcoholic beverages in Canada.

PubMed

Smart, R G

1990-01-01

This paper reviews the background and rationale for health warning labels for alcoholic beverages. They have been recently approved for the United States. Mexico and Colombia already have such labels. However, Canadian health officials seem reluctant to require them unless the alcohol industry agrees. Arguments against labels (i.e. that they detract from other efforts, are misguided or ineffective) are not convincing. Evidence from research on health warnings on cigarettes and prescription and non-prescription drugs shows that labels can be effective if well designed. Special problems in having bilingual labels may exist but could be overcome. Canada should have health warning labels on alcoholic beverages as soon as possible.

Building confidence and credibility into CAD with belief decision trees

NASA Astrophysics Data System (ADS)

Affenit, Rachael N.; Barns, Erik R.; Furst, Jacob D.; Rasin, Alexander; Raicu, Daniela S.

2017-03-01

Creating classifiers for computer-aided diagnosis in the absence of ground truth is a challenging problem. Using experts' opinions as reference truth is difficult because the variability in the experts' interpretations introduces uncertainty in the labeled diagnostic data. This uncertainty translates into noise, which can significantly affect the performance of any classifier on test data. To address this problem, we propose a new label set weighting approach to combine the experts' interpretations and their variability, as well as a selective iterative classification (SIC) approach that is based on conformal prediction. Using the NIH/NCI Lung Image Database Consortium (LIDC) dataset in which four radiologists interpreted the lung nodule characteristics, including the degree of malignancy, we illustrate the benefits of the proposed approach. Our results show that the proposed 2-label-weighted approach significantly outperforms the accuracy of the original 5- label and 2-label-unweighted classification approaches by 39.9% and 7.6%, respectively. We also found that the weighted 2-label models produce higher skewness values by 1.05 and 0.61 for non-SIC and SIC respectively on root mean square error (RMSE) distributions. When each approach was combined with selective iterative classification, this further improved the accuracy of classification for the 2-weighted-label by 7.5% over the original, and improved the skewness of the 5-label and 2-unweighted-label by 0.22 and 0.44 respectively.

Radioimmunotherapy with monoclonal antibodies. A new horizon in nuclear medicine therapy?

PubMed

Sautter-Bihl, M L; Bihl, H

1994-08-01

Radioimmunotherapy (RIT) with labeled tumor-associated monoclonal antibodies (MAbs) is a promising concept in oncology, which essentially consists of biological targeting of ionising radiation to tumors. Some encouraging clinical results have been achieved with RIT. However, there are severe problems associated with both understanding the mechanisms and predicting the effectiveness of RIT. This paper reviews the results of some major clinical trials, especially in malignant lymphomas and in some solid tumors. Furthermore, problems with RIT are described such as the significance of dose inhomogeneity and dose-rate effects, the appropriate dose calculation method, the toxicity of RIT and the development of HAMAs. It is suggested that newer technologies including chimeric antibodies, multiple-step targeting protocols, bone marrow transplantation, parallel application of external radiation, heat or bioreductive drugs will enable RIT to make an essential contribution to strategies for combating cancer.

The Problem of Labels in E-Assessment of Diagrams

ERIC Educational Resources Information Center

Jayal, Ambikesh; Shepperd, Martin

2009-01-01

In this article we explore a problematic aspect of automated assessment of diagrams. Diagrams have partial and sometimes inconsistent semantics. Typically much of the meaning of a diagram resides in the labels; however, the choice of labeling is largely unrestricted. This means a correct solution may utilize differing yet semantically equivalent…

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.

Selective Chemical Labeling of Proteins with Small Fluorescent Molecules Based on Metal-Chelation Methodology

PubMed Central

Soh, Nobuaki

2008-01-01

Site-specific chemical labeling utilizing small fluorescent molecules is a powerful and attractive technique for in vivo and in vitro analysis of cellular proteins, which can circumvent some problems in genetic encoding labeling by large fluorescent proteins. In particular, affinity labeling based on metal-chelation, advantageous due to the high selectivity/simplicity and the small tag-size, is promising, as well as enzymatic covalent labeling, thereby a variety of novel methods have been studied in recent years. This review describes the advances in chemical labeling of proteins, especially highlighting the metal-chelation methodology. PMID:27879749

Learning with imperfectly labeled patterns

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of learning in pattern recognition using imperfectly labeled patterns is considered. The performance of the Bayes and nearest neighbor classifiers with imperfect labels is discussed using a probabilistic model for the mislabeling of the training patterns. Schemes for training the classifier using both parametric and non parametric techniques are presented. Methods for the correction of imperfect labels were developed. To gain an understanding of the learning process, expressions are derived for success probability as a function of training time for a one dimensional increment error correction classifier with imperfect labels. Feature selection with imperfectly labeled patterns is described.

The anatomy of a laser label

USDA-ARS?s Scientific Manuscript database

Laser labeling of fruits and vegetables is an efficient alternative to adhesive tags. The advantages of this system are numerous. In general the label consists of alphanumerical characters formed by laser generated pinhole depressions that penetrate the produce’s surface creating visible markings. H...

Communicating with whom? The effectiveness of appliance energy labels in the U.S. and Thailand

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

Pont, P. du

The proliferation of household appliances is a global energy problem, and this comparative study of appliance energy labeling in the US and Thailand offers opportunities to learn from the implementation of programs in countries with different income levels and cultural and political climates. In the US, the author conducted participant observation in an appliance store and interviewed 16 policymakers, 14 salespeople, and 100 consumers. In Thailand, he interviewed 11 policymakers, 53 salespeople, and 62 consumers, and carried out a national survey of 971 consumers. This study is the first time that energy labels have been examined primarily as a problemmore » of consumer cognition in context--that is, how consumers read, interpret, and think about energy labels in the retail environment. After just three years of implementation, the Thai appliance labeling program is having a significantly greater impact on the consumer appliance market than is the 20-year-old US program. While Thai salespeople report that more than 60% of consumers ask about or look at the label, the corresponding number for the US is just 20%. Energy efficiency was reported among the top-three purchase priorities by 28% of Thai appliance consumers, compared to just 11% of US consumers. In his in-store tests of label cognition, the US EnergyGuide label fared poorly, and the Thai appliance label was more effective at helping consumers to identify efficient models. Yet both labels suffer from the problem of too much detailed product information, which hinders label comprehension.« less

Convex Formulations of Learning from Crowds

NASA Astrophysics Data System (ADS)

Kajino, Hiroshi; Kashima, Hisashi

It has attracted considerable attention to use crowdsourcing services to collect a large amount of labeled data for machine learning, since crowdsourcing services allow one to ask the general public to label data at very low cost through the Internet. The use of crowdsourcing has introduced a new challenge in machine learning, that is, coping with low quality of crowd-generated data. There have been many recent attempts to address the quality problem of multiple labelers, however, there are two serious drawbacks in the existing approaches, that are, (i) non-convexity and (ii) task homogeneity. Most of the existing methods consider true labels as latent variables, which results in non-convex optimization problems. Also, the existing models assume only single homogeneous tasks, while in realistic situations, clients can offer multiple tasks to crowds and crowd workers can work on different tasks in parallel. In this paper, we propose a convex optimization formulation of learning from crowds by introducing personal models of individual crowds without estimating true labels. We further extend the proposed model to multi-task learning based on the resemblance between the proposed formulation and that for an existing multi-task learning model. We also devise efficient iterative methods for solving the convex optimization problems by exploiting conditional independence structures in multiple classifiers.

French Sizing of Medical Devices is not Fit for Purpose

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

Kibriya, Nabil, E-mail: nabskib@yahoo.co.uk; Hall, Rebecca; Powell, Steven

PurposeThe purpose of the study is to quantify the variation in the metric equivalent of French size in a range of medical devices, from various manufacturers, used in interventional radiology.MethodsThe labelling of a range of catheters, introducers, drains, balloons, stents, and endografts was examined. Products were chosen to achieve a broad range of French sizes from several manufacturers. To assess manufacturing accuracy, eight devices were selected for measurement using a laser micrometer. The external diameters of three specimens of each device were measured at centimeter intervals along the length of the device to ensure uniformity.ResultsA total of 200 labels ofmore » interventional radiology equipment were scrutinized. The results demonstrate a wide variation in the metric equivalent of French sizing. Labelled products can vary in diameter across the product range by up to 0.79 mm.The devices selected for measurement with the non-contact laser micrometer demonstrate acceptable manufacturing consistency. The external diameter differed by 0.05 mm on average.ConclusionsOur results demonstrate wide variation in the interpretation of the French scale by different manufacturers of medical devices. This has the potential to lead to problems using coaxial systems especially when the products are from different manufacturers. It is recommended that standard labelling should be employed by all manufacturers conveying specific details of the equipment. Given the wide variation in the interpretation of the French scale, our opinion is that this scale either needs to be abandoned or be strictly defined and followed.« less

Choice of rating scale labels: implication for minimizing patient satisfaction response ceiling effect in telemedicine surveys.

PubMed

Masino, Caterina; Lam, Tony C M

2014-12-01

Lack of response variability is problematic in surveys because of its detrimental effects on sensitivity and consequently reliability of the responses. In satisfaction surveys, this problem is caused by the ceiling effect resulting from high satisfaction ratings. A potential solution strategy is to manipulate the labels of the rating scale to create greater discrimination of responses on the high end of the response continuum. This study examined the effects of a positive-centered scale on the distribution and reliability of telemedicine satisfaction responses in a highly positive respondent population. In total, 216 telemedicine participants were randomly assigned to one of three experimental conditions as defined by the form of Likert scale: (1) 5-point Balanced Equal-Interval, (2) 5-point Positive-Packed, and (3) 5-point Positive-Centered Equal-Interval. Although the study findings were not statistically significant, partially because of sample size, the distribution and internal consistency reliability of responses occurred in the direction hypothesized. Loading the rating scale with more positive labels appears to be a useful strategy for reducing the ceiling effect and increases the discrimination ability of survey responses. The current research provides a survey design strategy to minimize ceiling effects. Although the findings provide some evidence suggesting the benefit of using rating scales loaded with positive labels, more research is needed to confirm this, as well as extend it to examine other types of rating scales and the interaction between rating scale formats and respondent characteristics.

Domain Adaptation for Pedestrian Detection Based on Prediction Consistency

PubMed Central

Huan-ling, Tang; Zhi-yong, An

2014-01-01

Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene. PMID:25013850

Fluorescent labeling of tetracysteine-tagged proteins in intact cells.

PubMed

Hoffmann, Carsten; Gaietta, Guido; Zürn, Alexander; Adams, Stephen R; Terrillon, Sonia; Ellisman, Mark H; Tsien, Roger Y; Lohse, Martin J

2010-09-01

In this paper, we provide a general protocol for labeling proteins with the membrane-permeant fluorogenic biarsenical dye fluorescein arsenical hairpin binder-ethanedithiol (FlAsH-EDT₂). Generation of the tetracysteine-tagged protein construct by itself is not described, as this is a protein-specific process. This method allows site-selective labeling of proteins in living cells and has been applied to a wide variety of proteins and biological problems. We provide here a generally applicable labeling procedure and discuss the problems that can occur as well as general considerations that must be taken into account when designing and implementing the procedure. The method can even be applied to proteins with expression below 1 pmol mg⁻¹ of protein, such as G protein-coupled receptors, and it can be used to study the intracellular localization of proteins as well as functional interactions in fluorescence resonance energy transfer experiments. The labeling procedure using FlAsH-EDT₂ as described takes 2-3 h, depending on the number of samples to be processed.

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.

A comparison of the scaling properties of the English, Spanish, French, and Chinese EQ-5D descriptive systems.

PubMed

Luo, Nan; Li, Minghui; Chevalier, Julie; Lloyd, Andrew; Herdman, Michael

2013-10-01

To compare the scaling properties of the English, Spanish, French, and Chinese versions of the EQ-5D-3L and EQ-5D-5L descriptive systems. Members of the general populations in the UK, Spain, France, and China were interviewed to measure the severity of health problems represented by the response labels used in the EQ-5D descriptive systems using a visual analog scale. Multiple linear regression models were used to compare the perceived label severity across the four language groups. Severity scores for labels from each EQ-5D-5L dimension scale were compared with each other to assess ordinality. EQ-5D-5L and EQ-5D-3L labels used for describing different levels of health problems were rated differently, while those describing the same level of health problems were rated similarly. For example, the deviation of any group mean from the grand severity mean score for the label 'slight(ly)' was no larger than 5 points on a 0-100 scale for all five EQ-5D dimensions (p > 0.05 for all, t tests). Label ratings violating hypothesized ordinality of the EQ-5D-5L scales were observed in only a small proportion of respondents. Our study provided some preliminary evidence supporting the ordinality and equivalence of the EQ-5D-5L and EQ-5D-3L descriptive systems across four major languages.

Sequential strand displacement beacon for detection of DNA coverage on functionalized gold nanoparticles.

PubMed

Paliwoda, Rebecca E; Li, Feng; Reid, Michael S; Lin, Yanwen; Le, X Chris

2014-06-17

Functionalizing nanomaterials for diverse analytical, biomedical, and therapeutic applications requires determination of surface coverage (or density) of DNA on nanomaterials. We describe a sequential strand displacement beacon assay that is able to quantify specific DNA sequences conjugated or coconjugated onto gold nanoparticles (AuNPs). Unlike the conventional fluorescence assay that requires the target DNA to be fluorescently labeled, the sequential strand displacement beacon method is able to quantify multiple unlabeled DNA oligonucleotides using a single (universal) strand displacement beacon. This unique feature is achieved by introducing two short unlabeled DNA probes for each specific DNA sequence and by performing sequential DNA strand displacement reactions. Varying the relative amounts of the specific DNA sequences and spacing DNA sequences during their coconjugation onto AuNPs results in different densities of the specific DNA on AuNP, ranging from 90 to 230 DNA molecules per AuNP. Results obtained from our sequential strand displacement beacon assay are consistent with those obtained from the conventional fluorescence assays. However, labeling of DNA with some fluorescent dyes, e.g., tetramethylrhodamine, alters DNA density on AuNP. The strand displacement strategy overcomes this problem by obviating direct labeling of the target DNA. This method has broad potential to facilitate more efficient design and characterization of novel multifunctional materials for diverse applications.

A Pragmatic View of Disturbed Self-Reflection in Personality Disorders: Implications for Psychotherapy.

PubMed

Dimaggio, Giancarlo; Lysaker, Paul H

2018-06-01

Patients with personality disorders suffer from impairment in self-reflective capacities. This is not a matter of making incorrect judgments about self-experience but reflects problems with (a) labeling internal experience consistent with the type and level of bodily arousal, (b) seeing how thoughts and feelings are connected to one another within the flow of daily life, and (c) realizing that one's own ideas about interpersonal relationships are subjective and fallible and not direct perceptions of external reality. The authors offer a discussion and definition of each of these three impairments and then offer suggestions for how to address these impairments in psychotherapy.

Probabilistic cluster labeling of imagery data

NASA Technical Reports Server (NTRS)

Chittineni, C. B. (Principal Investigator)

1980-01-01

The problem of obtaining the probabilities of class labels for the clusters using spectral and spatial information from a given set of labeled patterns and their neighbors is considered. A relationship is developed between class and clusters conditional densities in terms of probabilities of class labels for the clusters. Expressions are presented for updating the a posteriori probabilities of the classes of a pixel using information from its local neighborhood. Fixed-point iteration schemes are developed for obtaining the optimal probabilities of class labels for the clusters. These schemes utilize spatial information and also the probabilities of label imperfections. Experimental results from the processing of remotely sensed multispectral scanner imagery data are presented.

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.

Multi-iPPseEvo: A Multi-label Classifier for Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into Chou's General PseAAC via Grey System Theory.

PubMed

Qiu, Wang-Ren; Zheng, Quan-Shu; Sun, Bi-Qian; Xiao, Xuan

2017-03-01

Predicting phosphorylation protein is a challenging problem, particularly when query proteins have multi-label features meaning that they may be phosphorylated at two or more different type amino acids. In fact, human protein usually be phosphorylated at serine, threonine and tyrosine. By introducing the "multi-label learning" approach, a novel predictor has been developed that can be used to deal with the systems containing both single- and multi-label phosphorylation protein. Here we proposed a predictor called Multi-iPPseEvo by (1) incorporating the protein sequence evolutionary information into the general pseudo amino acid composition (PseAAC) via the grey system theory, (2) balancing out the skewed training datasets by the asymmetric bootstrap approach, and (3) constructing an ensemble predictor by fusing an array of individual random forest classifiers thru a voting system. Rigorous cross-validations via a set of multi-label metrics indicate that the multi-label phosphorylation predictor is very promising and encouraging. The current approach represents a new strategy to deal with the multi-label biological problems, and the software is freely available for academic use at http://www.jci-bioinfo.cn/Multi-iPPseEvo. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

40 CFR 1042.135 - Labeling.

Code of Federal Regulations, 2011 CFR

2011-07-01

... label. (e) For engines requiring ULSD, create a separate label with the statement: “ULTRA LOW SULFUR... power (in kW), and power density (in kW/L) as needed to determine the emission standards for the engine family. You may specify displacement, maximum engine power, or power density as a range consistent with...

40 CFR 85.530 - Vehicle/engine labels and packaging labels.

Code of Federal Regulations, 2013 CFR

2013-07-01

... PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM MOBILE SOURCES Exemption of Clean Alternative Fuel... from the tampering prohibition: (1) You must make a supplemental emission control information label for..., consistent with the requirements of this subpart. You may do this by identifying the OEM test group/engine...

40 CFR 85.530 - Vehicle/engine labels and packaging labels.

Code of Federal Regulations, 2011 CFR

2011-07-01

... PROGRAMS (CONTINUED) CONTROL OF AIR POLLUTION FROM MOBILE SOURCES Exemption of Clean Alternative Fuel... from the tampering prohibition: (1) You must make a supplemental emission control information label for..., consistent with the requirements of this subpart. You may do this by identifying the OEM test group/engine...

Convex formulation of multiple instance learning from positive and unlabeled bags.

PubMed

Bao, Han; Sakai, Tomoya; Sato, Issei; Sugiyama, Masashi

2018-05-24

Multiple instance learning (MIL) is a variation of traditional supervised learning problems where data (referred to as bags) are composed of sub-elements (referred to as instances) and only bag labels are available. MIL has a variety of applications such as content-based image retrieval, text categorization, and medical diagnosis. Most of the previous work for MIL assume that training bags are fully labeled. However, it is often difficult to obtain an enough number of labeled bags in practical situations, while many unlabeled bags are available. A learning framework called PU classification (positive and unlabeled classification) can address this problem. In this paper, we propose a convex PU classification method to solve an MIL problem. We experimentally show that the proposed method achieves better performance with significantly lower computation costs than an existing method for PU-MIL. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analytical performance of reciprocal isotope labeling of proteome digests for quantitative proteomics and its application for comparative studies of aerobic and anaerobic Escherichia coli proteomes.

PubMed

Lo, Andy; Weiner, Joel H; Li, Liang

2013-09-17

Due to limited sample amounts, instrument time considerations, and reagent costs, only a small number of replicate experiments are typically performed for quantitative proteome analyses. Generation of reproducible data that can be readily assessed for consistency within a small number of datasets is critical for accurate quantification. We report our investigation of a strategy using reciprocal isotope labeling of two comparative samples as a tool for determining proteome changes. Reciprocal labeling was evaluated to determine the internal consistency of quantified proteome changes from Escherichia coli grown under aerobic and anaerobic conditions. Qualitatively, the peptide overlap between replicate analyses of the same sample and reverse labeled samples were found to be within 8%. Quantitatively, reciprocal analyses showed only a slight increase in average overall inconsistency when compared with replicate analyses (1.29 vs. 1.24-fold difference). Most importantly, reverse labeling was successfully used to identify spurious values resulting from incorrect peptide identifications and poor peak fitting. After removal of 5% of the peptide data with low reproducibility, a total of 275 differentially expressed proteins (>1.50-fold difference) were consistently identified and were then subjected to bioinformatics analysis. General considerations and guidelines for reciprocal labeling experimental design and biological significance of obtained results are discussed. Copyright © 2013 Elsevier B.V. All rights reserved.

Do we need annotation experts? A case study in celiac disease classification.

PubMed

Kwitt, Roland; Hegenbart, Sebastian; Rasiwasia, Nikhil; Vécsei, Andreas; Uhl, Andreas

2014-01-01

Inference of clinically-relevant findings from the visual appearance of images has become an essential part of processing pipelines for many problems in medical imaging. Typically, a sufficient amount labeled training data is assumed to be available, provided by domain experts. However, acquisition of this data is usually a time-consuming and expensive endeavor. In this work, we ask the question if, for certain problems, expert knowledge is actually required. In fact, we investigate the impact of letting non-expert volunteers annotate a database of endoscopy images which are then used to assess the absence/presence of celiac disease. Contrary to previous approaches, we are not interested in algorithms that can handle the label noise. Instead, we present compelling empirical evidence that label noise can be compensated by a sufficiently large corpus of training data, labeled by the non-experts.

Use of EPR to Solve Biochemical Problems

PubMed Central

Sahu, Indra D.; McCarrick, Robert M.; Lorigan, Gary A.

2013-01-01

EPR spectroscopy is a very powerful biophysical tool that can provide valuable structural and dynamic information on a wide variety of biological systems. The intent of this review is to provide a general overview for biochemists and biological researchers on the most commonly used EPR methods and how these techniques can be used to answer important biological questions. The topics discussed could easily fill one or more textbooks; thus, we present a brief background on several important biological EPR techniques and an overview of several interesting studies that have successfully used EPR to solve pertinent biological problems. The review consists of the following sections: an introduction to EPR techniques, spin labeling methods, and studies of naturally occurring organic radicals and EPR active transition metal systems which are presented as a series of case studies in which EPR spectroscopy has been used to greatly further our understanding of several important biological systems. PMID:23961941

Abandoning a label doesn’t make it disappear: The perseverance of labeling effects

PubMed Central

Foroni, Francesco; Rothbart, Myron

2012-01-01

Labels exert strong influence on perception and judgment. The present experiment examines the possibility that such effects may persist even when labels are abandoned. Participants judged the similarity of pairs of silhouette drawings of female body types, ordered on a continuum from very thin to very heavy, under conditions where category labels were, and were not, superimposed on the ordered stimuli. Consistent with earlier research, labels had strong effects on perceived similarity, with silhouettes sharing the same label judged as more similar than those having different labels. Moreover, when the labels were removed and no longer present, the effect of the labels, although diminished, persisted. It did not make any difference whether the labels were simply abandoned or, in addition, had their validity challenged. The results are important for our understanding of categorization and labeling processes. The potential theoretical and practical implications of these results for social processes are discussed. PMID:23105148

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.

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: an application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39).

PubMed

Borchani, Hanen; Bielza, Concha; Martı Nez-Martı N, Pablo; Larrañaga, Pedro

2012-12-01

Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson's patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson's disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables. Copyright © 2012 Elsevier Inc. All rights reserved.

Inductive generalization with familiar categories: developmental changes in children's reliance on perceptual similarity and kind information

PubMed Central

Godwin, Karrie E.; Fisher, Anna V.

2015-01-01

Inductive generalization is ubiquitous in human cognition; however, the factors underpinning this ability early in development remain contested. The present study was designed to (1) test the predictions of the naïve theory and a similarity-based account and (2) examine the mechanism by which labels promote induction. In Experiment 1, 3- to 5-year-old children made inferences about highly familiar categories. The results were not fully consistent with either theoretical account. In contrast to the predictions of the naïve theory approach, the youngest children in the study did not ignore perceptually compelling lures in favor of category-match items; in contrast to the predictions of the similarity-based account, no group of participants favored perceptually compelling lures in the presence of dissimilar-looking category-match items. In Experiment 2 we investigated the mechanisms by which labels promote induction by examining the influence of different label types, namely category labels (e.g., the target and category-match both labeled as bird) and descriptor labels (e.g., the target and the perceptual lure both labeled as brown) on induction performance. In contrast to the predictions of the naïve theory approach, descriptor labels but not category labels affected induction in 3-year-old children. Consistent with the predictions of the similarity-based account, descriptor labels affected the performance of children in all age groups included in the study. The implications of these findings for the developmental account of induction are discussed. PMID:26217254

Inductive generalization with familiar categories: developmental changes in children's reliance on perceptual similarity and kind information.

PubMed

Godwin, Karrie E; Fisher, Anna V

2015-01-01

Inductive generalization is ubiquitous in human cognition; however, the factors underpinning this ability early in development remain contested. The present study was designed to (1) test the predictions of the naïve theory and a similarity-based account and (2) examine the mechanism by which labels promote induction. In Experiment 1, 3- to 5-year-old children made inferences about highly familiar categories. The results were not fully consistent with either theoretical account. In contrast to the predictions of the naïve theory approach, the youngest children in the study did not ignore perceptually compelling lures in favor of category-match items; in contrast to the predictions of the similarity-based account, no group of participants favored perceptually compelling lures in the presence of dissimilar-looking category-match items. In Experiment 2 we investigated the mechanisms by which labels promote induction by examining the influence of different label types, namely category labels (e.g., the target and category-match both labeled as bird) and descriptor labels (e.g., the target and the perceptual lure both labeled as brown) on induction performance. In contrast to the predictions of the naïve theory approach, descriptor labels but not category labels affected induction in 3-year-old children. Consistent with the predictions of the similarity-based account, descriptor labels affected the performance of children in all age groups included in the study. The implications of these findings for the developmental account of induction are discussed.

Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning

PubMed Central

Goerner-Potvin, Patricia; Morin, Andreanne; Shao, Xiaojian; Pastinen, Tomi

2017-01-01

Motivation: Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily labeled by visual inspection of aligned read counts in a genome browser. We propose a supervised machine learning approach for ChIP-seq data analysis, using labels that encode qualitative judgments about which genomic regions contain or do not contain peaks. The main idea is to manually label a small subset of the genome, and then learn a model that makes consistent peak predictions on the rest of the genome. Results: We created 7 new histone mark datasets with 12 826 visually determined labels, and analyzed 3 existing transcription factor datasets. We observed that default peak detection parameters yield high false positive rates, which can be reduced by learning parameters using a relatively small training set of labeled data from the same experiment type. We also observed that labels from different people are highly consistent. Overall, these data indicate that our supervised labeling method is useful for quantitatively training and testing peak detection algorithms. Availability and Implementation: Labeled histone mark data http://cbio.ensmp.fr/~thocking/chip-seq-chunk-db/, R package to compute the label error of predicted peaks https://github.com/tdhock/PeakError Contacts: toby.hocking@mail.mcgill.ca or guil.bourque@mcgill.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27797775

Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning.

PubMed

Hocking, Toby Dylan; Goerner-Potvin, Patricia; Morin, Andreanne; Shao, Xiaojian; Pastinen, Tomi; Bourque, Guillaume

2017-02-15

Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which algorithm and what parameters are optimal for any given dataset. In contrast, regions with and without obvious peaks can be easily labeled by visual inspection of aligned read counts in a genome browser. We propose a supervised machine learning approach for ChIP-seq data analysis, using labels that encode qualitative judgments about which genomic regions contain or do not contain peaks. The main idea is to manually label a small subset of the genome, and then learn a model that makes consistent peak predictions on the rest of the genome. We created 7 new histone mark datasets with 12 826 visually determined labels, and analyzed 3 existing transcription factor datasets. We observed that default peak detection parameters yield high false positive rates, which can be reduced by learning parameters using a relatively small training set of labeled data from the same experiment type. We also observed that labels from different people are highly consistent. Overall, these data indicate that our supervised labeling method is useful for quantitatively training and testing peak detection algorithms. Labeled histone mark data http://cbio.ensmp.fr/~thocking/chip-seq-chunk-db/ , R package to compute the label error of predicted peaks https://github.com/tdhock/PeakError. toby.hocking@mail.mcgill.ca or guil.bourque@mcgill.ca. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Nutrition labelling: purpose, scientific issues and challenges.

PubMed

Van den Wijngaart, Annoek W E M

2002-01-01

Nutrition labels describe the nutrient content of a food and are intended to guide the consumer in food selection. The nutrition information provided must be selected on the basis of consistency with dietary recommendations. Selection of the specific nutrients or food components to be listed should further take into account label space, the analytical feasibility of measuring the particular nutritional component within the food matrix, and the relative costs of such analyses. Nutrition information provided on labels should be truthful and not mislead consumers. At the same time, labelling regulations should provide incentives to manufacturers to develop products that promote public health and assist consumers in following dietary recommendations. It is likely that in many countries, there would be some segments of the population that would benefit from information about the composition of foods. In these cases, countries should consider the need to provide for appropriate labelling and its presentation relative to existing guidelines and approaches. As nutrition-labelling efforts have evolved, different approaches and legal requirements have been established. These create difficulties in developing and harmonizing nutrition information listings, which have broad international applications. For these reasons, the Codex Guidelines on Nutrition Labeling play an important role to provide guidance to member countries when they want to develop or update their national regulations and to encourage harmonization of national standards with international standards. These Guidelines are based on the principle that no food should be described or presented in a manner that is false, misleading or deceptive. The Guidelines include provisions for voluntary nutrient declaration, calculation and presentation of nutrient information. The Guidelines on Claims establish general principles to be followed and leave the definition of specific claims to national regulations. Definitions are provided for a number of claims (nutrient content, comparative claims, nutrient function claims) as well as general requirements concerning consumer information in relation with claims. Nutrition labelling by itself cannot solve nutrition problems. It should be seen as one of the elements of nutrition policy and should be envisaged in the larger perspective of consumer education, which in its turn is part of an overall development policy. Exchange of information at the regional and subregional level is important, as each country can learn from the experience of others and regional co-ordination and co-operation can be developed.

Tunnel Vision in Environmental Management.

ERIC Educational Resources Information Center

Miller, Alan

1982-01-01

Discusses problem-solving styles in environmental management and the specific deficiencies in these styles that might be grouped under the label "tunnel vision," a form of selective attention contributing to inadequate problem-formulation, partial solutions to complex problems, and generation of additional problems. Includes educational…

Classification without labels: learning from mixed samples in high energy physics

NASA Astrophysics Data System (ADS)

Metodiev, Eric M.; Nachman, Benjamin; Thaler, Jesse

2017-10-01

Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these models are trained on imperfect simulations due to a lack of truth-level information in the data, which risks the model learning artifacts of the simulation. In this paper, we introduce the paradigm of classification without labels (CWoLa) in which a classifier is trained to distinguish statistical mixtures of classes, which are common in collider physics. Crucially, neither individual labels nor class proportions are required, yet we prove that the optimal classifier in the CWoLa paradigm is also the optimal classifier in the traditional fully-supervised case where all label information is available. After demonstrating the power of this method in an analytical toy example, we consider a realistic benchmark for collider physics: distinguishing quark- versus gluon-initiated jets using mixed quark/gluon training samples. More generally, CWoLa can be applied to any classification problem where labels or class proportions are unknown or simulations are unreliable, but statistical mixtures of the classes are available.

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.

Classification without labels: learning from mixed samples in high energy physics

DOE PAGES

Metodiev, Eric M.; Nachman, Benjamin; Thaler, Jesse

2017-10-25

Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these models are trained on imperfect simulations due to a lack of truth-level information in the data, which risks the model learning artifacts of the simulation. In this paper, we introduce the paradigm of classification without labels (CWoLa) in which a classifier is trained to distinguish statistical mixtures of classes, which are common in collider physics. Crucially, neither individual labels nor class proportions are required, yet we prove that the optimal classifier in the CWoLa paradigm is also the optimalmore » classifier in the traditional fully-supervised case where all label information is available. After demonstrating the power of this method in an analytical toy example, we consider a realistic benchmark for collider physics: distinguishing quark- versus gluon-initiated jets using mixed quark/gluon training samples. More generally, CWoLa can be applied to any classification problem where labels or class proportions are unknown or simulations are unreliable, but statistical mixtures of the classes are available.« less

Fluorescent labeling of tetracysteine-tagged proteins in intact cells

PubMed Central

Hoffmann, Carsten; Gaietta, Guido; Zürn, Alexander; Adams, Stephen R; Terrillon, Sonia; Ellisman, Mark H; Tsien, Roger Y; Lohse, Martin J

2011-01-01

In this paper, we provide a general protocol for labeling proteins with the membrane-permeant fluorogenic biarsenical dye fluorescein arsenical hairpin binder–ethanedithiol (FlAsH-EDT2). Generation of the tetracysteine-tagged protein construct by itself is not described, as this is a protein-specific process. This method allows site-selective labeling of proteins in living cells and has been applied to a wide variety of proteins and biological problems. We provide here a generally applicable labeling procedure and discuss the problems that can occur as well as general considerations that must be taken into account when designing and implementing the procedure. The method can even be applied to proteins with expression below 1 pmol mg−1 of protein, such as G protein–coupled receptors, and it can be used to study the intracellular localization of proteins as well as functional interactions in fluorescence resonance energy transfer experiments. The labeling procedure using FlAsH-EDT2 as described takes 2–3 h, depending on the number of samples to be processed. PMID:20885379

Classification without labels: learning from mixed samples in high energy physics

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

Metodiev, Eric M.; Nachman, Benjamin; Thaler, Jesse

Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these models are trained on imperfect simulations due to a lack of truth-level information in the data, which risks the model learning artifacts of the simulation. In this paper, we introduce the paradigm of classification without labels (CWoLa) in which a classifier is trained to distinguish statistical mixtures of classes, which are common in collider physics. Crucially, neither individual labels nor class proportions are required, yet we prove that the optimal classifier in the CWoLa paradigm is also the optimalmore » classifier in the traditional fully-supervised case where all label information is available. After demonstrating the power of this method in an analytical toy example, we consider a realistic benchmark for collider physics: distinguishing quark- versus gluon-initiated jets using mixed quark/gluon training samples. More generally, CWoLa can be applied to any classification problem where labels or class proportions are unknown or simulations are unreliable, but statistical mixtures of the classes are available.« less

A microfluidics-based technique for automated and rapid labeling of cells for flow cytometry

NASA Astrophysics Data System (ADS)

Patibandla, Phani K.; Estrada, Rosendo; Kannan, Manasaa; Sethu, Palaniappan

2014-03-01

Flow cytometry is a powerful technique capable of simultaneous multi-parametric analysis of heterogeneous cell populations for research and clinical applications. In recent years, the flow cytometer has been miniaturized and made portable for application in clinical- and resource-limited settings. The sample preparation procedure, i.e. labeling of cells with antibodies conjugated to fluorescent labels, is a time consuming (˜45 min) and labor-intensive procedure. Microfluidics provides enabling technologies to accomplish rapid and automated sample preparation. Using an integrated microfluidic device consisting of a labeling and washing module, we demonstrate a new protocol that can eliminate sample handling and accomplish sample and reagent metering, high-efficiency mixing, labeling and washing in rapid automated fashion. The labeling module consists of a long microfluidic channel with an integrated chaotic mixer. Samples and reagents are precisely metered into this device to accomplish rapid and high-efficiency mixing. The mixed sample and reagents are collected in a holding syringe and held for up to 8 min following which the mixture is introduced into an inertial washing module to obtain ‘analysis-ready’ samples. The washing module consists of a high aspect ratio channel capable of focusing cells to equilibrium positions close to the channel walls. By introducing the cells and labeling reagents in a narrow stream at the center of the channel flanked on both sides by a wash buffer, the elution of cells into the wash buffer away from the free unbound antibodies is accomplished. After initial calibration experiments to determine appropriate ‘holding time’ to allow antibody binding, both modules were used in conjunction to label MOLT-3 cells (T lymphoblast cell line) with three different antibodies simultaneously. Results confirm no significant difference in mean fluorescence intensity values for all three antibodies labels (p < 0.01) between the conventional procedure (45 min) and our microfluidic approach (12 min).

The relationship among expressions, labels, and descriptions of contempt.

PubMed

Matsumoto, David; Ekman, Paul

2004-10-01

This article reports 4 studies that demonstrate that the contempt expression is reliably associated with situations that elicit contempt and that the inability to label the contempt expression reflects a problem with its label or concept and not with the relationship between its expression and emotion. In Study I, the labeling of contempt in fixed-choice judgment tasks did not occur because of a process of elimination. In Studies 2 and 3, the contempt expression was associated with situations that elicit contempt, but participants did not label the situations in an open-ended response. In Study 3, participants also more reliably labeled the contempt expression with situations rather than with labels and did not generate contempt situations from labels. In Study 4, participants reported using, hearing, and reading about contempt the least among 7 emotions tested. (c) 2004 APA, all rights reserved

Linguistically informed digital fingerprints for text

NASA Astrophysics Data System (ADS)

Uzuner, Özlem

2006-02-01

Digital fingerprinting, watermarking, and tracking technologies have gained importance in the recent years in response to growing problems such as digital copyright infringement. While fingerprints and watermarks can be generated in many different ways, use of natural language processing for these purposes has so far been limited. Measuring similarity of literary works for automatic copyright infringement detection requires identifying and comparing creative expression of content in documents. In this paper, we present a linguistic approach to automatically fingerprinting novels based on their expression of content. We use natural language processing techniques to generate "expression fingerprints". These fingerprints consist of both syntactic and semantic elements of language, i.e., syntactic and semantic elements of expression. Our experiments indicate that syntactic and semantic elements of expression enable accurate identification of novels and their paraphrases, providing a significant improvement over techniques used in text classification literature for automatic copy recognition. We show that these elements of expression can be used to fingerprint, label, or watermark works; they represent features that are essential to the character of works and that remain fairly consistent in the works even when works are paraphrased. These features can be directly extracted from the contents of the works on demand and can be used to recognize works that would not be correctly identified either in the absence of pre-existing labels or by verbatim-copy detectors.

Issues in modern bone histomorphometry☆

PubMed Central

Recker, R.R.; Kimmel, D.B.; Dempster, D.; Weinstein, R.S.; Wronski, T.J.; Burr, D.B.

2012-01-01

This review reports on proceedings of a bone histomorphometry session conducted at the Fortieth International IBMS Sun Valley Skeletal Tissue Biology Workshop held on August 1, 2010. The session was prompted by recent technical problems encountered in conducting histomorphometry on bone biopsies from humans and animals treated with anti-remodeling agents such as bisphosphonates and RANKL antibodies. These agents reduce remodeling substantially, and thus cause problems in calculating bone remodeling dynamics using in vivo fluorochrome labeling. The tissue specimens often contain few or no fluorochrome labels, and thus create statistical and other problems in analyzing variables such as mineral apposition rates, mineralizing surface and bone formation rates. The conference attendees discussed these problems and their resolutions, and the proceedings reported here summarize their discussions and recommendations. PMID:21810491

User Interface Problems of a Nationwide Inpatient Information System: A Heuristic Evaluation.

PubMed

Atashi, Alireza; Khajouei, Reza; Azizi, Amirabbas; Dadashi, Ali

2016-01-01

While studies have shown that usability evaluation could uncover many design problems of health information systems, the usability of health information systems in developing countries using their native language is poorly studied. The objective of this study was to evaluate the usability of a nationwide inpatient information system used in many academic hospitals in Iran. Three trained usability evaluators independently evaluated the system using Nielsen's 10 usability heuristics. The evaluators combined identified problems in a single list and independently rated the severity of the problems. We statistically compared the number and severity of problems identified by HIS experienced and non-experienced evaluators. A total of 158 usability problems were identified. After removing duplications 99 unique problems were left. The highest mismatch with usability principles was related to "Consistency and standards" heuristic (25%) and the lowest related to "Flexibility and efficiency of use" (4%). The average severity of problems ranged from 2.4 (Major problem) to 3.3 (Catastrophe problem). The experienced evaluator with HIS identified significantly more problems and gave higher severities to problems (p<0.02). Heuristic Evaluation identified a high number of usability problems in a widely used inpatient information system in many academic hospitals. These problems, if remain unsolved, may waste users' and patients' time, increase errors and finally threaten patient's safety. Many of them can be fixed with simple redesign solutions such as using clear labels and better layouts. This study suggests conducting further studies to confirm the findings concerning effect of evaluator experience on the results of Heuristic Evaluation.

User Interface Problems of a Nationwide Inpatient Information System: A Heuristic Evaluation

PubMed Central

Atashi, Alireza; Azizi, Amirabbas; Dadashi, Ali

2016-01-01

Summary Introduction While studies have shown that usability evaluation could uncover many design problems of health information systems, the usability of health information systems in developing countries using their native language is poorly studied. The objective of this study was to evaluate the usability of a nationwide inpatient information system used in many academic hospitals in Iran. Material and Methods Three trained usability evaluators independently evaluated the system using Nielsen’s 10 usability heuristics. The evaluators combined identified problems in a single list and independently rated the severity of the problems. We statistically compared the number and severity of problems identified by HIS experienced and non-experienced evaluators. Results A total of 158 usability problems were identified. After removing duplications 99 unique problems were left. The highest mismatch with usability principles was related to “Consistency and standards” heuristic (25%) and the lowest related to “Flexibility and efficiency of use” (4%). The average severity of problems ranged from 2.4 (Major problem) to 3.3 (Catastrophe problem). The experienced evaluator with HIS identified significantly more problems and gave higher severities to problems (p<0.02). Discussion Heuristic Evaluation identified a high number of usability problems in a widely used inpatient information system in many academic hospitals. These problems, if remain unsolved, may waste users’ and patients’ time, increase errors and finally threaten patient’s safety. Many of them can be fixed with simple redesign solutions such as using clear labels and better layouts. This study suggests conducting further studies to confirm the findings concerning effect of evaluator experience on the results of Heuristic Evaluation. PMID:27081409

Consistent assignment of the vibrations of symmetric and asymmetric para-disubstituted benzene molecules

NASA Astrophysics Data System (ADS)

Andrejeva, Anna; Gardner, Adrian M.; Tuttle, William D.; Wright, Timothy G.

2016-03-01

We give a description of the phenyl-ring-localized vibrational modes of the ground states of the para-disubstituted benzene molecules including both symmetric and asymmetric cases. In line with others, we quickly conclude that the use of Wilson mode labels is misleading and ambiguous; we conclude the same regarding the related ones of Varsányi. Instead we label the modes consistently based upon the Mulliken (Herzberg) method for the modes of para-difluorobenzene (pDFB). Since we wish the labelling scheme to cover both symmetrically- and asymmetrically-substituted molecules, we apply the Mulliken labelling under C2v symmetry. By studying the variation of the vibrational wavenumbers with mass of the substituent, we are able to identify the corresponding modes across a wide range of molecules and hence provide consistent assignments. Particularly interesting are pairs of vibrations that evolve from in- and out-of-phase motions in pDFB to more localized modes in asymmetric molecules. We consider the para isomers of the following: the symmetric dihalobenzenes, xylene, hydroquinone, the asymmetric dihalobenzenes, halotoluenes, halophenols and cresol.

Robust multi-atlas label propagation by deep sparse representation

PubMed Central

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2016-01-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer (label-specific dictionaries) consists of groups of representative atlas patches and the subsequent layers (residual dictionaries) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods. PMID:27942077

Robust multi-atlas label propagation by deep sparse representation.

PubMed

Zu, Chen; Wang, Zhengxia; Zhang, Daoqiang; Liang, Peipeng; Shi, Yonghong; Shen, Dinggang; Wu, Guorong

2017-03-01

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer ( label-specific dictionaries ) consists of groups of representative atlas patches and the subsequent layers ( residual dictionaries ) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods.

BLOND, a building-level office environment dataset of typical electrical appliances.

PubMed

Kriechbaumer, Thomas; Jacobsen, Hans-Arno

2018-03-27

Energy metering has gained popularity as conventional meters are replaced by electronic smart meters that promise energy savings and higher comfort levels for occupants. Achieving these goals requires a deeper understanding of consumption patterns to reduce the energy footprint: load profile forecasting, power disaggregation, appliance identification, startup event detection, etc. Publicly available datasets are used to test, verify, and benchmark possible solutions to these problems. For this purpose, we present the BLOND dataset: continuous energy measurements of a typical office environment at high sampling rates with common appliances and load profiles. We provide voltage and current readings for aggregated circuits and matching fully-labeled ground truth data (individual appliance measurements). The dataset contains 53 appliances (16 classes) in a 3-phase power grid. BLOND-50 contains 213 days of measurements sampled at 50kSps (aggregate) and 6.4kSps (individual appliances). BLOND-250 consists of the same setup: 50 days, 250kSps (aggregate), 50kSps (individual appliances). These are the longest continuous measurements at such high sampling rates and fully-labeled ground truth we are aware of.

BLOND, a building-level office environment dataset of typical electrical appliances

NASA Astrophysics Data System (ADS)

Kriechbaumer, Thomas; Jacobsen, Hans-Arno

2018-03-01

Energy metering has gained popularity as conventional meters are replaced by electronic smart meters that promise energy savings and higher comfort levels for occupants. Achieving these goals requires a deeper understanding of consumption patterns to reduce the energy footprint: load profile forecasting, power disaggregation, appliance identification, startup event detection, etc. Publicly available datasets are used to test, verify, and benchmark possible solutions to these problems. For this purpose, we present the BLOND dataset: continuous energy measurements of a typical office environment at high sampling rates with common appliances and load profiles. We provide voltage and current readings for aggregated circuits and matching fully-labeled ground truth data (individual appliance measurements). The dataset contains 53 appliances (16 classes) in a 3-phase power grid. BLOND-50 contains 213 days of measurements sampled at 50kSps (aggregate) and 6.4kSps (individual appliances). BLOND-250 consists of the same setup: 50 days, 250kSps (aggregate), 50kSps (individual appliances). These are the longest continuous measurements at such high sampling rates and fully-labeled ground truth we are aware of.

BLOND, a building-level office environment dataset of typical electrical appliances

PubMed Central

Kriechbaumer, Thomas; Jacobsen, Hans-Arno

2018-01-01

Energy metering has gained popularity as conventional meters are replaced by electronic smart meters that promise energy savings and higher comfort levels for occupants. Achieving these goals requires a deeper understanding of consumption patterns to reduce the energy footprint: load profile forecasting, power disaggregation, appliance identification, startup event detection, etc. Publicly available datasets are used to test, verify, and benchmark possible solutions to these problems. For this purpose, we present the BLOND dataset: continuous energy measurements of a typical office environment at high sampling rates with common appliances and load profiles. We provide voltage and current readings for aggregated circuits and matching fully-labeled ground truth data (individual appliance measurements). The dataset contains 53 appliances (16 classes) in a 3-phase power grid. BLOND-50 contains 213 days of measurements sampled at 50kSps (aggregate) and 6.4kSps (individual appliances). BLOND-250 consists of the same setup: 50 days, 250kSps (aggregate), 50kSps (individual appliances). These are the longest continuous measurements at such high sampling rates and fully-labeled ground truth we are aware of. PMID:29583141

An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases

PubMed Central

Forbes, Jessica L.; Kim, Regina E. Y.; Paulsen, Jane S.; Johnson, Hans J.

2016-01-01

The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%. PMID:27536233

An Open-Source Label Atlas Correction Tool and Preliminary Results on Huntingtons Disease Whole-Brain MRI Atlases.

PubMed

Forbes, Jessica L; Kim, Regina E Y; Paulsen, Jane S; Johnson, Hans J

2016-01-01

The creation of high-quality medical imaging reference atlas datasets with consistent dense anatomical region labels is a challenging task. Reference atlases have many uses in medical image applications and are essential components of atlas-based segmentation tools commonly used for producing personalized anatomical measurements for individual subjects. The process of manual identification of anatomical regions by experts is regarded as a so-called gold standard; however, it is usually impractical because of the labor-intensive costs. Further, as the number of regions of interest increases, these manually created atlases often contain many small inconsistently labeled or disconnected regions that need to be identified and corrected. This project proposes an efficient process to drastically reduce the time necessary for manual revision in order to improve atlas label quality. We introduce the LabelAtlasEditor tool, a SimpleITK-based open-source label atlas correction tool distributed within the image visualization software 3D Slicer. LabelAtlasEditor incorporates several 3D Slicer widgets into one consistent interface and provides label-specific correction tools, allowing for rapid identification, navigation, and modification of the small, disconnected erroneous labels within an atlas. The technical details for the implementation and performance of LabelAtlasEditor are demonstrated using an application of improving a set of 20 Huntingtons Disease-specific multi-modal brain atlases. Additionally, we present the advantages and limitations of automatic atlas correction. After the correction of atlas inconsistencies and small, disconnected regions, the number of unidentified voxels for each dataset was reduced on average by 68.48%.

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.

LP-LPA: A link influence-based label propagation algorithm for discovering community structures in networks

NASA Astrophysics Data System (ADS)

Berahmand, Kamal; Bouyer, Asgarali

2018-03-01

Community detection is an essential approach for analyzing the structural and functional properties of complex networks. Although many community detection algorithms have been recently presented, most of them are weak and limited in different ways. Label Propagation Algorithm (LPA) is a well-known and efficient community detection technique which is characterized by the merits of nearly-linear running time and easy implementation. However, LPA has some significant problems such as instability, randomness, and monster community detection. In this paper, an algorithm, namely node’s label influence policy for label propagation algorithm (LP-LPA) was proposed for detecting efficient community structures. LP-LPA measures link strength value for edges and nodes’ label influence value for nodes in a new label propagation strategy with preference on link strength and for initial nodes selection, avoid of random behavior in tiebreak states, and efficient updating order and rule update. These procedures can sort out the randomness issue in an original LPA and stabilize the discovered communities in all runs of the same network. Experiments on synthetic networks and a wide range of real-world social networks indicated that the proposed method achieves significant accuracy and high stability. Indeed, it can obviously solve monster community problem with regard to detecting communities in networks.

Manifold Regularized Experimental Design for Active Learning.

PubMed

Zhang, Lining; Shum, Hubert P H; Shao, Ling

2016-12-02

Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one sample after another in a greedy manner. However, this is not very effective because the classification models has to be retrained for each newly labeled sample. Moreover, many popular active learning approaches utilize the most uncertain samples by leveraging the classification hyperplane of the classifier, which is not appropriate since the classification hyperplane is inaccurate when the training data are small-sized. The problem of insufficient training data in real-world systems limits the potential applications of these approaches. This paper presents a novel method of active learning called manifold regularized experimental design (MRED), which can label multiple informative samples at one time for training. In addition, MRED gives an explicit geometric explanation for the selected samples to be labeled by the user. Different from existing active learning methods, our method avoids the intrinsic problems caused by insufficiently labeled samples in real-world applications. Various experiments on synthetic datasets, the Yale face database and the Corel image database have been carried out to show how MRED outperforms existing methods.

IgG red blood cell autoantibodies in autoimmune hemolytic anemia bind to epitopes on red blood cell membrane band 3 glycoprotein

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

Victoria, E.J.; Pierce, S.W.; Branks, M.J.

1990-01-01

Red blood cell (RBC) autoantibodies from patients with IgG warm-type autoimmune hemolytic anemia were labeled with iodine 125 and their RBC binding behavior characterized. Epitope-bearing RBC membrane polypeptides were identified after autoantibody immunoprecipitation of labeled membranes and immunoblotting. Immunoaffinity isolation of labeled membrane proteins with 12 different IgG hemolytic autoantibodies with protein A-agarose revealed a major polypeptide at Mr 95 to 110 kd, which coelectrophoresed on sodium dodecylsulfate-polyacrylamide gel electrophoresis with a membrane component isolated with sheep IgG anti-band 3. Immunoprecipitation studies with chymotrypsinized RBCs resulted in the recovery of two labeled membrane polypeptides with molecular weights characteristically resulting frommore » the chymotryptic fragmentation of band 3. Immunoblotting with sheep IgG anti-band 3 of the immunoprecipitated polypeptides confirmed that hemolytic autoantibody binding led to recovery of band 3 or its fragments. Two 125I-labeled IgG hemolytic autoantibodies showed binding behavior consistent with epitope localization on band 3. The labeled RBC autoantibodies bound immunospecifically to all types of human RBC tested, including those of rare Rh type (Rh-null, D--) at a site density of approximately 10(6) per RBC. The 125I-IgG in two labeled autoantibodies was 84% and 92% adsorbable by human and higher nonhuman primate RBCs. Antigen-negative animal RBC bound less than 10%, consistent with immunospecific RBC binding. IgG-1 was the major subclass in five autoantibodies tested; one of six fixed complement; and autoantibody IgG appeared polyclonal by isoelectric focusing. We conclude that IgG eluted from RBCs of patients with autoimmune hemolytic anemia consists predominantly of a single totally RBC-adsorbable antibody population that binds to antigenic determinants on band 3.« less

Rapid Verification of Candidate Serological Biomarkers Using Gel-based, Label-free Multiple Reaction Monitoring

PubMed Central

Tang, Hsin-Yao; Beer, Lynn A.; Barnhart, Kurt T.; Speicher, David W.

2011-01-01

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves, quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1-D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μl serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers. PMID:21726088

Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring.

PubMed

Tang, Hsin-Yao; Beer, Lynn A; Barnhart, Kurt T; Speicher, David W

2011-09-02

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μL of serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers.

The conclusion of a comparative efficacy study of fluralaner and sarolaner against the tick Amblyomma americanum on dogs is based on results obtained at study times that are outside the fluralaner label recommendations.

PubMed

Armstrong, Rob

2017-03-24

The only fluralaner-related conclusion presented in a study comparing the efficacy of fluralaner and sarolaner for control of the tick Amblyomma americanum on dogs is based on study times that are outside the label administration recommendations. Label recommendations for fluralaner treatment of A. americanum on dogs in the USA require re-administration at 56 days. This 56 day re-administration was not conducted in the study; therefore, all assessed time points following 56 days post-treatment in the study present comparisons that are not consistent with fluralaner administration recommendations. The only comparative time point assessed prior to 56 days showing a difference between treatments was at 42 days post-administration, a time point when methodological problems were identified by the investigators. Therefore, the only comparative study conclusion that a difference was shown between fluralaner and sarolaner beyond 6 weeks (42 days) after treatment is not based on recommended product use. Furthermore, if the study does not show that there is a difference between the treatments at times when the products are used as recommended, then there also can be no comparative discussion of the risk of tick-borne pathogen transmission risk between treatments.

Development of a gambling addictive behavior scale for adolescents in Korea.

PubMed

Park, Hyun Sook; Jung, Sun Young

2012-12-01

This study was conducted to develop a gambling addictive behavior scale for adolescents. The process involved construction of a conceptual framework, initial item search, verification of content validity, selection of secondary items, and extraction of final items. The participants were 299 adolescents from two middle schools and four high schools. Item analysis, factor analysis, criterion validity, internal consistency, and ROC curve were used to analyze the data. For the final scale, 25 items were selected, and categorized into 4 factors which accounted for 54.9% of the total variance. The factors were labeled as loss of control, life dysfunction from gambling addiction, gambling experience, and social dysfunction from problem gambling. The scores for the scale were significantly correlated with addictive personality, irrational gambling belief, and adolescent's gambling addictive behavior. Cronbach's alpha coefficient for the 25 items was .94. Scale scores identified adolescents as being in a problem gambling group, a non-problem gambling group, and a non-gambling group by the ROC curve. The above findings indicate that the gambling addictive behavior scale has good validity and reliability and can be used with adolescents in Korea.

A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.

PubMed

Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2018-06-12

Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.

Faster Bit-Parallel Algorithms for Unordered Pseudo-tree Matching and Tree Homeomorphism

NASA Astrophysics Data System (ADS)

Kaneta, Yusaku; Arimura, Hiroki

In this paper, we consider the unordered pseudo-tree matching problem, which is a problem of, given two unordered labeled trees P and T, finding all occurrences of P in T via such many-one embeddings that preserve node labels and parent-child relationship. This problem is closely related to tree pattern matching problem for XPath queries with child axis only. If m > w , we present an efficient algorithm that solves the problem in O(nm log(w)/w) time using O(hm/w + mlog(w)/w) space and O(m log(w)) preprocessing on a unit-cost arithmetic RAM model with addition, where m is the number of nodes in P, n is the number of nodes in T, h is the height of T, and w is the word length. We also discuss a modification of our algorithm for the unordered tree homeomorphism problem, which corresponds to a tree pattern matching problem for XPath queries with descendant axis only.

Assessing the Social Skills and Problem Behaviors of Adolescents With Severe Disabilities Enrolled in General Education Classes.

PubMed

Lyons, Gregory L; Huber, Heartley B; Carter, Erik W; Chen, Rui; Asmus, Jennifer M

2016-07-01

Although enhancing the social competence of students with severe disabilities has long remained a prominent focus of school-based intervention efforts, relatively little attention has focused on identifying the most critical social and behavioral needs of students during high school. We examined the social skills and problem behaviors of 137 adolescents with severe disabilities from the vantage point of both special educators and parents. We sought to identify areas of potential intervention need, explore factors associated with social skill and problem behavior ratings, and examine the extent to which teachers and parents converged in their assessments of these needs. Our findings indicate teachers and parents of high school students with severe disabilities rated social skills as considerably below average and problem behaviors as above average. In addition, lower social skills ratings were evident for students with greater support needs, lower levels of overall adaptive behavior, and a special education label of autism. We found moderate consistency in the degree to which teachers and parents aligned in their assessments of both social skills and problem behavior. We offer recommendations for assessment and intervention focused on strengthening the social competence of adolescents with severe disabilities within secondary school classrooms, as well as promising avenues for future research.

Adaptive Framework for Classification and Novel Class Detection over Evolving Data Streams with Limited Labeled Data.

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

Haque, Ahsanul; Khan, Latifur; Baron, Michael

2015-09-01

Most approaches to classifying evolving data streams either divide the stream of data into fixed-size chunks or use gradual forgetting to address the problems of infinite length and concept drift. Finding the fixed size of the chunks or choosing a forgetting rate without prior knowledge about time-scale of change is not a trivial task. As a result, these approaches suffer from a trade-off between performance and sensitivity. To address this problem, we present a framework which uses change detection techniques on the classifier performance to determine chunk boundaries dynamically. Though this framework exhibits good performance, it is heavily dependent onmore » the availability of true labels of data instances. However, labeled data instances are scarce in realistic settings and not readily available. Therefore, we present a second framework which is unsupervised in nature, and exploits change detection on classifier confidence values to determine chunk boundaries dynamically. In this way, it avoids the use of labeled data while still addressing the problems of infinite length and concept drift. Moreover, both of our proposed frameworks address the concept evolution problem by detecting outliers having similar values for the attributes. We provide theoretical proof that our change detection method works better than other state-of-the-art approaches in this particular scenario. Results from experiments on various benchmark and synthetic data sets also show the efficiency of our proposed frameworks.« less

Exploring Consumer Literacy

ERIC Educational Resources Information Center

Moore, Virginia; Sumrall, William; Mott, Michael; Mitchell, Elizabeth; Theobald, Becky

2015-01-01

Methods for facilitating students' standards-based consumer literacy are addressed via the use of problem solving with food and product labels. Fifth graders will be able to: (1) provide detailed analysis of food and product labels; (2) understand large themes, including production, distribution, and consumption; and (3) explore consumer…

Difficulties in avoiding exposure to allergens in cosmetics.

PubMed

Noiesen, Eline; Munk, Martin D; Larsen, Kristian; Johansen, Jeanne Duus; Agner, Tove

2007-08-01

The aim of the study is to describe the ability of patients with allergic contact dermatitis to avoid exposure to allergens in cosmetics. The study is a questionnaire survey among 382 patients with contact allergy to preservatives and fragrances, included from 3 dermatological clinics. The questionnaire included questions about the level of difficulty in reading labels of ingredients on cosmetics and about patients' strategies to avoid substances they were allergic to. It also included questions about eczema severity as well as about educational level. 46% of the patients found it difficult or extremely difficult to read the ingredient labelling of cosmetics, and this finding was significantly related to low educational level. Patients allergic to formaldehyde and methyldibromo glutaronitrile experienced the worst difficulties, while patients with fragrance allergy found ingredient label reading easier than patients with preservative allergy. Reading of ingredient labels is a major problem for patients with contact allergy to allergens in consumer products. It is a general problem for all patients and not restricted to a small group with multiple allergies.

Tracer-based estimates of protein flux in cases of incomplete product renewal: evidence and implications of heterogeneity in collagen turnover

PubMed Central

Zhou, Haihong; Wang, Sheng-Ping; Herath, Kithsiri; Kasumov, Takhar; Sadygov, Rovshan G.; Kelley, David E.

2015-01-01

The synthesis of various molecules can be estimated by measuring the incorporation of a labeled precursor into a product of interest. Unfortunately, a central problem in many studies has been an inability to estimate the intracellular dilution of the precursor and therein correctly calculate the synthesis of the product; it is generally assumed that measuring the true product labeling is straightforward. We initiated a study to examine liver collagen synthesis and identified an apparent problem with assumptions regarding measurements of the product labeling. Since it is well known that collagen production is relatively slow, we relied on the use of [2H]H2O labeling (analogous to a primed infusion) and sampled animals over the course of 16 days. Although the water labeling (the precursor) remained stable and we observed the incorporation of labeled amino acids into collagen, the asymptotic protein labeling was considerably lower than what would be expected based on the precursor labeling. Although this observation is not necessarily surprising (i.e., one might expect that a substantial fraction of the collagen pool would appear “inert” or turn over at a very slow rate), its implications are of interest in certain areas. Herein, we discuss a novel situation in which tracers are used to quantify rates of flux under conditions where a product may not undergo complete replacement. We demonstrate how heterogeneity in the product pool can lead one to the wrong conclusions regarding estimates of flux, and we outline an approach that may help to minimize errors surrounding data interpretation. PMID:26015435

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.

Temporal Codes for Memories: Issues and Problems.

DTIC Science & Technology

1977-04-01

for specific dates they were quite unable to reconstruct the dates. It has been reported (Gibson & Levin, 197S) that children afflicted with dyslexia ...used. Two answers predominated. First, a verbal label was used for the first item, and a "last" label was used by some subjects for the last item...this being assigned when the list terminated. Some subjects indicated that more general labels were used for several items, such phrases as the

78 FR 12760 - Guidance for Industry on Labeling for Human Prescription Drug and Biological Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-25

...The Food and Drug Administration (FDA) is announcing the availability of a guidance for industry entitled ``Labeling for Human Prescription Drug and Biological Products--Implementing the PLR Content and Format Requirements.'' This guidance is intended to assist applicants in complying with the content and format requirements of labeling for human prescription drug and biological products. The recommendations in this guidance will help ensure that the labeling is clear; useful; informative; and to the extent possible, consistent in content and format. It will assist applicants in developing labeling for new products, revising existing labeling, and implementing the requirements on content and format of labeling for human prescription drug and biological products (71 FR 3922), which appeared in the Federal Register of January 24, 2006. The rule is commonly referred to as the ``Physician Labeling Rule'' (PLR) because it addresses prescription drug labeling that is used by prescribers and other health care practitioners.

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.

Discriminative graph embedding for label propagation.

PubMed

Nguyen, Canh Hao; Mamitsuka, Hiroshi

2011-09-01

In many applications, the available information is encoded in graph structures. This is a common problem in biological networks, social networks, web communities and document citations. We investigate the problem of classifying nodes' labels on a similarity graph given only a graph structure on the nodes. Conventional machine learning methods usually require data to reside in some Euclidean spaces or to have a kernel representation. Applying these methods to nodes on graphs would require embedding the graphs into these spaces. By embedding and then learning the nodes on graphs, most methods are either flexible with different learning objectives or efficient enough for large scale applications. We propose a method to embed a graph into a feature space for a discriminative purpose. Our idea is to include label information into the embedding process, making the space representation tailored to the task. We design embedding objective functions that the following learning formulations become spectral transforms. We then reformulate these spectral transforms into multiple kernel learning problems. Our method, while being tailored to the discriminative tasks, is efficient and can scale to massive data sets. We show the need of discriminative embedding on some simulations. Applying to biological network problems, our method is shown to outperform baselines.

Modeling activity recognition of multi resident using label combination of multi label classification in smart home

NASA Astrophysics Data System (ADS)

Mohamed, Raihani; Perumal, Thinagaran; Sulaiman, Md Nasir; Mustapha, Norwati; Zainudin, M. N. Shah

2017-10-01

Pertaining to the human centric concern and non-obtrusive way, the ambient sensor type technology has been selected, accepted and embedded in the environment in resilient style. Human activities, everyday are gradually becoming complex and thus complicate the inferences of activities when it involving the multi resident in the same smart environment. Current works solutions focus on separate model between the resident, activities and interactions. Some study use data association and extra auxiliary of graphical nodes to model human tracking information in an environment and some produce separate framework to incorporate the auxiliary for interaction feature model. Thus, recognizing the activities and which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. This paper will cater the above issue by considering the simplification and efficient method using the multi label classification framework. This effort eliminates time consuming and simplifies a lot of pre-processing tasks comparing with previous approach. Applications to the multi resident multi label learning in smart home problems shows the LC (Label Combination) using Decision Tree (DT) as base classifier can tackle the above problems.

Learning to merge: a new tool for interactive mapping

NASA Astrophysics Data System (ADS)

Porter, Reid B.; Lundquist, Sheng; Ruggiero, Christy

2013-05-01

The task of turning raw imagery into semantically meaningful maps and overlays is a key area of remote sensing activity. Image analysts, in applications ranging from environmental monitoring to intelligence, use imagery to generate and update maps of terrain, vegetation, road networks, buildings and other relevant features. Often these tasks can be cast as a pixel labeling problem, and several interactive pixel labeling tools have been developed. These tools exploit training data, which is generated by analysts using simple and intuitive paint-program annotation tools, in order to tailor the labeling algorithm for the particular dataset and task. In other cases, the task is best cast as a pixel segmentation problem. Interactive pixel segmentation tools have also been developed, but these tools typically do not learn from training data like the pixel labeling tools do. In this paper we investigate tools for interactive pixel segmentation that also learn from user input. The input has the form of segment merging (or grouping). Merging examples are 1) easily obtained from analysts using vector annotation tools, and 2) more challenging to exploit than traditional labels. We outline the key issues in developing these interactive merging tools, and describe their application to remote sensing.

Synthesis of carbon-11, fluorine-18, and nitrogen-13 labeled radiotracers for biomedical applications. Nuclear Science Series: Nuclear Medicine

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

Fowler, J.S.; Wolf, A.P.

1982-09-01

Carbon 11, Fluorine 18, and Nitrogen 13-labeled radiotracers are reviewed from the standpoint of synthetic organic chemistry while keeping in perspective the necessity of integrating the organic chemistry with the design and ultimate application of the radiotracer. The reactions used, the principles used to adapt these reactions to labeling with short-lived radionuclides, and the concepts of chemical reactivity form the framework upon which synthetic strategies for short-lived radiotracers are developed. Potentially new routes are suggested which may be applied to problems in labeling organic molecules. (ACR)

The Labeling Strategy: Moving beyond Order in Counting Problems

ERIC Educational Resources Information Center

CadwalladerOlsker, Todd

2013-01-01

Permutations and combinations are used to solve certain kinds of counting problems, but many students have trouble distinguishing which of these concepts applies to a given problem. An "order heuristic" is usually used to distinguish the two, but this heuristic can cause confusion when problems do not explicitly mention order. This…

Diagnostic labels of NANDA-I in a southern region of Spain

PubMed Central

González-Rodríguez, Rafael; Martelo-Baro, María de los Ángeles; Bas-Sarmiento, Pilar

2017-01-01

ABSTRACT Objective: to determine the incidence of NANDA-I diagnostic labels (North American Nursing Diagnosis Association-International) and to establish the distribution of cases of assistance and the associated labels, according to sociodemographic variables (age and sex). Method: descriptive, cross-sectional epidemiological study of labels of NANDA-I, under ecological design. The distribution of labels was analyzed according to sex and age; the corresponding frequencies were calculated and for each label the incidence were calculated rates with aggregate data from the attended cases. Results: the total number of cases of care under study was 9,928 (41.65% men and 58.35% women). The identified labels were 16,456 (7,084 men and 9,372 women); average of 1.7 labels per case of care; Out of 216 labels proposed by NANDA-I, in its 2012-14 classification, 152 were used, representing 70.4%. The labels with the highest incidence rates per thousand inhabitants were: Anxiety, Willingness to Improve Knowledge and Risk of Infection. Conclusions: the study allowed detecting, through NANDA-I, the answers to the health problems of greater incidence in the users attended. PMID:28614433

Parallel consistent labeling algorithms

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

Samal, A.; Henderson, T.

Mackworth and Freuder have analyzed the time complexity of several constraint satisfaction algorithms. Mohr and Henderson have given new algorithms, AC-4 and PC-3, for arc and path consistency, respectively, and have shown that the arc consistency algorithm is optimal in time complexity and of the same order space complexity as the earlier algorithms. In this paper, they give parallel algorithms for solving node and arc consistency. They show that any parallel algorithm for enforcing arc consistency in the worst case must have O(na) sequential steps, where n is number of nodes, and a is the number of labels per node.more » They give several parallel algorithms to do arc consistency. It is also shown that they all have optimal time complexity. The results of running the parallel algorithms on a BBN Butterfly multiprocessor are also presented.« less

76 FR 31513 - Labeling Requirements for Alternative Fuels and Alternative Fueled Vehicles

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-01

... systematic review of all FTC rules and guides, the Commission requests public comment on the overall costs... Act, such labels should provide ``appropriate information with respect to costs and benefits [of... problems associated with developing and publishing useful and timely cost and benefit information, taking...

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

ERIC Educational Resources Information Center

Setalo, Gyorgy, Jr.

2013-01-01

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

Encouraging Maternal Sacrifice: How Regulations Governing the Consumption of Pharmaceuticals During Pregnancy Prioritize Fetal Safety over Maternal Health and Autonomy.

PubMed

Donley, Greer

Pregnant women are routinely faced with the stressful decision of whether to consume needed medications during their pregnancies. Because the risks associated with pharmaceutical drug consumption during pregnancy are largely unknown, pregnant women both inadvertently consume dangerous medications and avoid needed drugs. Both outcomes are harmful to pregnant women and their fetuses. This unparalleled lack of drug safety information is a result of ill-conceived, paternalistic regulations in two areas of the law: regulations governing ethical research in human subjects and regulations that dictate the required labels on drugs. The former categorizes pregnant women as "vulnerable" and thus precludes them from most medical research. The result is that ninety-one percent of drugs lack any reliable safety information for pregnant consumers. The latter currently requires all drug labels to encourage drug avoidance during pregnancy, despite ample evidence that avoiding needed medications can harm pregnant women. On June 30, 2015, new pregnancy labeling regulations took effect. Though these regulations make important improvements, they continue to treat pregnant women unlike any population, including other unique subpopulations, such as children. As a result, the new regulations do not fix the problem of over-warning pregnant women about the risks of drug consumption. This article questions the legitimacy of both regulations and suggests three reforms for how to improve access to vital safety information: (1) amend the regulations governing ethical research in human subjects to reclassify pregnant women as non-vulnerable adults; (2) create incentives to generate safety data in pregnant women by granting a period of market exclusivity for drug companies that invest in this research; and (3) make the FDA pregnancy labeling regulations consistent with the routine FDA practice of requiring the display of balanced, human data on risk.

Label-free image-based detection of drug resistance with optofluidic time-stretch microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kobayashi, Hirofumi; Lei, Cheng; Mao, Ailin; Jiang, Yiyue; Guo, Baoshan; Ozeki, Yasuyuki; Goda, Keisuke

2017-02-01

Acquired drug resistance is a fundamental predicament in cancer therapy. Early detection of drug-resistant cancer cells during or after treatment is expected to benefit patients from unnecessary drug administration and thus play a significant role in the development of a therapeutic strategy. However, the development of an effective method of detecting drug-resistant cancer cells is still in its infancy due to their complex mechanism in drug resistance. To address this problem, we propose and experimentally demonstrate label-free image-based drug resistance detection with optofluidic time-stretch microscopy using leukemia cells (K562 and K562/ADM). By adding adriamycin (ADM) to both K562 and K562/ADM (ADM-resistant K562 cells) cells, both types of cells express unique morphological changes, which are subsequently captured by an optofluidic time-stretch microscope. These unique morphological changes are extracted as image features and are subjected to supervised machine learning for cell classification. We hereby have successfully differentiated K562 and K562/ADM solely with label-free images, which suggests that our technique is capable of detecting drug-resistant cancer cells. Our optofluidic time-stretch microscope consists of a time-stretch microscope with a high spatial resolution of 780 nm at a 1D frame rate of 75 MHz and a microfluidic device that focuses and orders cells. We compare various machine learning algorithms as well as various concentrations of ADM for cell classification. Owing to its unprecedented versatility of using label-free image and its independency from specific molecules, our technique holds great promise for detecting drug resistance of cancer cells for which its underlying mechanism is still unknown or chemical probes are still unavailable.

Development of C60-based labeling reagents for the determination of low-molecular-weight compounds by matrix assisted laser desorption ionization mass (I): Determination of amino acids in microliter biofluids.

PubMed

Wu, Pin; Xiao, Hua-Ming; Ding, Jun; Deng, Qian-Yun; Zheng, Fang; Feng, Yu-Qi

2017-04-01

Quantification of low molecular weight compounds (<800 Da) using matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI MS) is challenging due to the matrix signal interference at low m/z region and poor reproducibility of MS responses. In this study, a C60 labeling-MALDI MS strategy was proposed for the fast, sensitive and reliable determination of amino acids (AAs) in biofluids. An N-hydroxysuccinimide functionalized C60 was synthesized as the labeling reagent and added as an 880 Da tag to AAs; a carboxyl acid containing C60 was employed as the internal standards to normalize MS variations. This solved the inherent problems of MALDI MS for small molecule analysis. The entire analytical procedure-which consisted of simple protein precipitation and 10 min of derivatization in a microwave prior to the MALDI MS analysis-could be accomplished within 20 min with high throughput and great sample matrix tolerance. AA quantification showed good linearity from 0.7 to 70.0 μM with correlation coefficients (R) larger than 0.9954. The limits of detection were 70.0-300.0 fmol. Good reproducibility and reliability of the method were demonstrated by intra-day and inter-day precision with relative standard deviations less than 13.8%, and the recovery in biofluid ranged from 80.4% to 106.8%. This approach could be used in 1 μL of urine, serum, plasma, whole blood, and cerebrospinal fluid. Most importantly, the C60 labeling strategy is a universal approach for MALDI MS analysis of various LMW compounds because functionalized C60 is now available on demand. Copyright © 2017 Elsevier B.V. All rights reserved.

PRN 97-8: Time Extension of PR Notice 96-7 - Termiticide Labeling

EPA Pesticide Factsheets

EPA intends to grant a 90-day extension to permit the distribution or sale of products not bearing labeling consistent with PR Notice 96-7. View the reasons for this extension and what products are affected.

Palladium-109 labeled anti-melanoma monoclonal antibodies

DOEpatents

Srivastava, S.C.; Fawwaz, R.A.; Ferrone, S.

1984-04-30

The invention consists of new monoclonal antibodies labelled with Palladium 109, a beta-emitting radionuclide, the method of preparing this material, and its use in the radiotherapy of melanoma. The antibodies are chelate-conjugated and demonstrate a high uptake in melanomas. (ACR)

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

PubMed

Christiansen, Eric M; Yang, Samuel J; Ando, D Michael; Javaherian, Ashkan; Skibinski, Gaia; Lipnick, Scott; Mount, Elliot; O'Neil, Alison; Shah, Kevan; Lee, Alicia K; Goyal, Piyush; Fedus, William; Poplin, Ryan; Esteva, Andre; Berndl, Marc; Rubin, Lee L; Nelson, Philip; Finkbeiner, Steven

2018-04-19

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire. Copyright © 2018 Elsevier Inc. All rights reserved.

The science on front-of-package food labels.

PubMed

Hawley, Kristy L; Roberto, Christina A; Bragg, Marie A; Liu, Peggy J; Schwartz, Marlene B; Brownell, Kelly D

2013-03-01

The U.S. Food and Drug Administration and Institute of Medicine are currently investigating front-of-package (FOP) food labelling systems to provide science-based guidance to the food industry. The present paper reviews the literature on FOP labelling and supermarket shelf-labelling systems published or under review by February 2011 to inform current investigations and identify areas of future research. A structured search was undertaken of research studies on consumer use, understanding of, preference for, perception of and behaviours relating to FOP/shelf labelling published between January 2004 and February 2011. Twenty-eight studies from a structured search met inclusion criteria. Reviewed studies examined consumer preferences, understanding and use of different labelling systems as well as label impact on purchasing patterns and industry product reformulation. The findings indicate that the Multiple Traffic Light system has most consistently helped consumers identify healthier products; however, additional research on different labelling systems' abilities to influence consumer behaviour is needed.

End labeling procedures: an overview.

PubMed

Hilario, Elena

2004-09-01

There are two ways to label a DNA molecular; by the ends or all along the molecule. End labeling can be performed at the 3'- or 5'-end. Labeling at the 3' end is performed by filling 3'-end recessed ends with a mixture or labeled and unlabeled dNTPs using Klenow or T4 DNA polymerases. Both reactions are template dependent. Terminal deoxynucleotide transferase incorporates dNTPs at the 3' end of any kind of DNA molecule or RNA. Labels incorporated at the 3'-end of the DNA molecule prevent any further extension or ligation to any other molecule, but this can be overcome by labeling the 5'-end of the desired DNA molecule. 5'-end labeling is performed by enzymatic methods (T4 polynucleotide kinase exchange and forward reactions), by chemical modification of sensitized oligonucleotides with phosphoroamidite, or by combined methods. Probe cleanup is recommended when high background problems occur, but caution should be taken not to damage the attached probe with harsh chemicals or by light exposure.

Essays on environmental policies, corruption, and energy

NASA Astrophysics Data System (ADS)

Baksi, Soham

This thesis consists of four essays. The first essay looks at pollution taxation under capital mobility, and analyzes the role of pre-commitment by countries to their pollution tax rate. A polluting firm sells its product in two countries, and can locate and produce in a single country or in both countries. Due to the discrete-choice nature of the firm's location problem, the countries' welfare functions are discontinuous in their pollution tax rate. We show that when the countries cannot pre-commit to their pollution tax, the firm can still engender tax competition between them by strategically locating in both the countries. Moreover, pre-commitment pollution taxation may not be welfare improving for the countries, although it always makes the firm better off. The second essay studies the effect of liberalization on corruption. Corruptible inspectors enforce an environmental regulation on firms, and are monitored by an honest regulator. Liberalization not only increases the variety of goods and the marginal utility of accepting a bribe, but also puts pressure on the regulator to curb corruption. The interaction of these two effects can cause corruption to initially increase with liberalization, and then decrease beyond a threshold. Moreover, equilibrium corruption is lower when the regulator is able to pre-commit to her monitoring frequency. The third essay analyzes optimal labeling (information revelation) procedures for hidden attributes of credence goods. Consumers are heterogeneous in their preference for the hidden attribute, and producers can either self-label their products, or have them certified by a third party. The government can impose self or third-party labeling requirements on either the "green" or the "brown" producers. When corrupt producers can affix spurious labels, the government needs to monitor them. A mandatory self-labeling policy is shown to generally dominate mandatory third-party labeling. The fourth essay develops formulas for computing the economy-wide energy intensity decline rate by aggregating sectoral energy efficiency improvements, and sectoral shifts in economic activities. The formulas are used to (i) construct plausible scenarios for the global rate of energy intensity decline, and (ii) show the restraining role of the "electricity generation" sector on the energy intensity decline rate.

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.

Allergen labelling in meat, dairy and cereal products from the Serbian market

NASA Astrophysics Data System (ADS)

Spirić, D.; Nikolić, D.; Ćirić, J.; Janković, S.; Stefanović, S.; Janković, V.; Teodorović, V.

2017-09-01

Allergens in food are a great health risk, because of the ratio of severity of problems compared to small amounts of ingested allergen. Since 2014, Serbian producers and importers of food have been obliged to declare allergens from the list of Codex Alimentarius on the product packaging. Surveillance of different meat, diary, and cereal product took place in 2016, with aim of checking if the Serbian regulatory requirements for labelling of allergens in food are being fulfilled. Out of 68 different meat products, 20 were not labelled for allergens. Thirty-six labels of various dairy products were examined revealing that allergen information was included on 27 of them. Only one of eight examined cereal products did not have allergen labelling.

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.

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.

Discriminating nutritional quality of foods using the 5-Color nutrition label in the French food market: consistency with nutritional recommendations.

PubMed

Julia, Chantal; Ducrot, Pauline; Péneau, Sandrine; Deschamps, Valérie; Méjean, Caroline; Fézeu, Léopold; Touvier, Mathilde; Hercberg, Serge; Kesse-Guyot, Emmanuelle

2015-09-28

Our objectives were to assess the performance of the 5-Colour nutrition label (5-CNL) front-of-pack nutrition label based on the Food Standards Agency nutrient profiling system to discriminate nutritional quality of foods currently on the market in France and its consistency with French nutritional recommendations. Nutritional composition of 7777 foods available on the French market collected from the web-based collaborative project Open Food Facts were retrieved. Distribution of products across the 5-CNL categories according to food groups, as arranged in supermarket shelves was assessed. Distribution of similar products from different brands in the 5-CNL categories was also assessed. Discriminating performance was considered as the number of color categories present in each food group. In the case of discrepancies between the category allocation and French nutritional recommendations, adaptations of the original score were proposed. Overall, the distribution of foodstuffs in the 5-CNL categories was consistent with French recommendations: 95.4% of 'Fruits and vegetables', 72.5% of 'Cereals and potatoes' were classified as 'Green' or 'Yellow' whereas 86.0% of 'Sugary snacks' were classified as 'Pink' or 'Red'. Adaptations to the original FSA score computation model were necessary for beverages, added fats and cheese in order to be consistent with French official nutritional recommendations. The 5-CNL label displays a high performance in discriminating nutritional quality of foods across food groups, within a food group and for similar products from different brands. Adaptations from the original model were necessary to maintain consistency with French recommendations and high performance of the system.

Hierarchical semi-numeric method for pairwise fuzzy group decision making.

PubMed

Marimin, M; Umano, M; Hatono, I; Tamura, H

2002-01-01

Gradual improvements to a single-level semi-numeric method, i.e., linguistic labels preference representation by fuzzy sets computation for pairwise fuzzy group decision making are summarized. The method is extended to solve multiple criteria hierarchical structure pairwise fuzzy group decision-making problems. The problems are hierarchically structured into focus, criteria, and alternatives. Decision makers express their evaluations of criteria and alternatives based on each criterion by using linguistic labels. The labels are converted into and processed in triangular fuzzy numbers (TFNs). Evaluations of criteria yield relative criteria weights. Evaluations of the alternatives, based on each criterion, yield a degree of preference for each alternative or a degree of satisfaction for each preference value. By using a neat ordered weighted average (OWA) or a fuzzy weighted average operator, solutions obtained based on each criterion are aggregated into final solutions. The hierarchical semi-numeric method is suitable for solving a larger and more complex pairwise fuzzy group decision-making problem. The proposed method has been verified and applied to solve some real cases and is compared to Saaty's (1996) analytic hierarchy process (AHP) method.

Superpixel-based graph cuts for accurate stereo matching

NASA Astrophysics Data System (ADS)

Feng, Liting; Qin, Kaihuai

2017-06-01

Estimating the surface normal vector and disparity of a pixel simultaneously, also known as three-dimensional label method, has been widely used in recent continuous stereo matching problem to achieve sub-pixel accuracy. However, due to the infinite label space, it’s extremely hard to assign each pixel an appropriate label. In this paper, we present an accurate and efficient algorithm, integrating patchmatch with graph cuts, to approach this critical computational problem. Besides, to get robust and precise matching cost, we use a convolutional neural network to learn a similarity measure on small image patches. Compared with other MRF related methods, our method has several advantages: its sub-modular property ensures a sub-problem optimality which is easy to perform in parallel; graph cuts can simultaneously update multiple pixels, avoiding local minima caused by sequential optimizers like belief propagation; it uses segmentation results for better local expansion move; local propagation and randomization can easily generate the initial solution without using external methods. Middlebury experiments show that our method can get higher accuracy than other MRF-based algorithms.

21 CFR 73.2180 - Guaiazulene.

Code of Federal Regulations, 2013 CFR

2013-04-01

... ADDITIVES EXEMPT FROM CERTIFICATION Cosmetics § 73.2180 Guaiazulene. (a) Identity. (1) The color additive... cosmetic use may contain the following diluent: Polyethylene glycol-40 castor oil (PEG-40 castor oil... applied cosmetics in amounts consistent with good manufacturing practice. (d) Labeling. The label of the...

21 CFR 73.2180 - Guaiazulene.

Code of Federal Regulations, 2012 CFR

2012-04-01

... ADDITIVES EXEMPT FROM CERTIFICATION Cosmetics § 73.2180 Guaiazulene. (a) Identity. (1) The color additive... cosmetic use may contain the following diluent: Polyethylene glycol-40 castor oil (PEG-40 castor oil... applied cosmetics in amounts consistent with good manufacturing practice. (d) Labeling. The label of the...

21 CFR 73.2180 - Guaiazulene.

Code of Federal Regulations, 2014 CFR

2014-04-01

... ADDITIVES EXEMPT FROM CERTIFICATION Cosmetics § 73.2180 Guaiazulene. (a) Identity. (1) The color additive... cosmetic use may contain the following diluent: Polyethylene glycol-40 castor oil (PEG-40 castor oil... applied cosmetics in amounts consistent with good manufacturing practice. (d) Labeling. The label of the...

21 CFR 73.2180 - Guaiazulene.

Code of Federal Regulations, 2010 CFR

2010-04-01

... ADDITIVES EXEMPT FROM CERTIFICATION Cosmetics § 73.2180 Guaiazulene. (a) Identity. (1) The color additive... cosmetic use may contain the following diluent: Polyethylene glycol-40 castor oil (PEG-40 castor oil... applied cosmetics in amounts consistent with good manufacturing practice. (d) Labeling. The label of the...

Lentivirus-mediated bifunctional cell labeling for in vivo melanoma study

PubMed Central

Day, Chi-Ping; Carter, John; Bonomi, Carrie; Esposito, Dominic; Crise, Bruce; Ortiz-Conde, Betty; Hollingshead, Melinda; Merlino, Glenn

2009-01-01

SUMMARY Lentiviral vectors (LVs) are capable of labeling a broad spectrum of cell types, achieving stable expression of transgenes. However, for in vivo studies, the duration of marker gene expression has been highly variable. We have developed a series of LVs harboring different promoters for expressing reporter gene in mouse cells. Long-term culture and colony formation of several LV-labeled mouse melanoma cells showed that promoters derived from mammalian house-keeping genes, especially those encoding RNA polymerase II (Pol2) and ferritin (FerH), provided the highest consistency for reporter expression. For in vivo studies, primary B16BL6 mouse melanoma were infected with LVs whose luciferase-GFP fusion gene (Luc/GFP) was driven by either Pol2 or FerH promoters. When transplanted into syngeneic C57BL/6 mice, Luc/GFP-labeled B16BL6 mouse melanoma cells can be monitored by bioluminescence imaging in vivo, and GFP-positive cells can be isolated from the tumors by FACS. Pol2-Luc/GFP labeling, while lower in activity, was more sustainable than FerH-Luc/GFP labeling in B16BL6 over consecutive passages into mice. We conclude that Pol-2-Luc/GFP labeling allows long-term in vivo monitoring and tumor cell isolation in immunocompetent mouse melanoma models. SIGNIFICANCE In this study we have developed and identified lentiviral vectors that allow labeled mouse melanoma cells to maintain long-term and consistent expression of a bifunctional luciferase-GFP marker gene, even in syngeneic mice with an intact immune function. This cell-labeling system can be used to build immunocompetent mouse melanoma models that permit both tumor monitoring and FACS-based tumor cell isolation from tissues, greatly facilitating the in vivo study of melanoma. PMID:19175523

Counting malaria parasites with a two-stage EM based algorithm using crowsourced data.

PubMed

Cabrera-Bean, Margarita; Pages-Zamora, Alba; Diaz-Vilor, Carles; Postigo-Camps, Maria; Cuadrado-Sanchez, Daniel; Luengo-Oroz, Miguel Angel

2017-07-01

Malaria eradication of the worldwide is currently one of the main WHO's global goals. In this work, we focus on the use of human-machine interaction strategies for low-cost fast reliable malaria diagnostic based on a crowdsourced approach. The addressed technical problem consists in detecting spots in images even under very harsh conditions when positive objects are very similar to some artifacts. The clicks or tags delivered by several annotators labeling an image are modeled as a robust finite mixture, and techniques based on the Expectation-Maximization (EM) algorithm are proposed for accurately counting malaria parasites on thick blood smears obtained by microscopic Giemsa-stained techniques. This approach outperforms other traditional methods as it is shown through experimentation with real data.

Considering context: reliable entity networks through contextual relationship extraction

NASA Astrophysics Data System (ADS)

David, Peter; Hawes, Timothy; Hansen, Nichole; Nolan, James J.

2016-05-01

Existing information extraction techniques can only partially address the problem of exploiting unreadable-large amounts text. When discussion of events and relationships is limited to simple, past-tense, factual descriptions of events, current NLP-based systems can identify events and relationships and extract a limited amount of additional information. But the simple subset of available information that existing tools can extract from text is only useful to a small set of users and problems. Automated systems need to find and separate information based on what is threatened or planned to occur, has occurred in the past, or could potentially occur. We address the problem of advanced event and relationship extraction with our event and relationship attribute recognition system, which labels generic, planned, recurring, and potential events. The approach is based on a combination of new machine learning methods, novel linguistic features, and crowd-sourced labeling. The attribute labeler closes the gap between structured event and relationship models and the complicated and nuanced language that people use to describe them. Our operational-quality event and relationship attribute labeler enables Warfighters and analysts to more thoroughly exploit information in unstructured text. This is made possible through 1) More precise event and relationship interpretation, 2) More detailed information about extracted events and relationships, and 3) More reliable and informative entity networks that acknowledge the different attributes of entity-entity relationships.

Expectancies for Sexually Abused Children: Evidence of Perceiver Bias

ERIC Educational Resources Information Center

Saathoff-Wells, Tara; Culp, Rex E.; Yancey, Candace T.

2005-01-01

We investigated perceiver bias in relation to children labeled as sexually abused. Building on recent research indicating that adults perceive children with such a label as having more behavioral problems and lower achievement, we replicated and expanded upon an earlier study. We tested undergraduate students (N = 699), who judged a six-year old…

The Difficult Patron in the Academic Library: Problem Issues or Problem Patrons?

ERIC Educational Resources Information Center

Simmonds Patience L.; Ingold, Jane L.

2002-01-01

Identifies difficult patron issues in academic libraries from the librarians' perspectives and offers solutions to try and prevent them from becoming problems. Topics include labeling academic library users; eliminating sources of conflict between faculty and library staff; and conflicts between students and library staff. (Author/LRW)

Identifying and Overcoming Barriers to Diabetes Management in the Elderly: An Intervention Study

DTIC Science & Technology

2009-06-01

food labels (p=0.05), suggesting possible problems with health literacy . Higher frequency of falls, fear of falls, and difficulty walking were more...problems with health literacy . Higher frequency of falls, fear of falls, and difficulty walking were more common in the group having problems taking

Metabolomics of Early Stage Plant Cell–Microbe Interaction Using Stable Isotope Labeling

PubMed Central

Pang, Qiuying; Zhang, Tong; Wang, Yang; Kong, Wenwen; Guan, Qijie; Yan, Xiufeng; Chen, Sixue

2018-01-01

Metabolomics has been used in unraveling metabolites that play essential roles in plant–microbe (including pathogen) interactions. However, the problem of profiling a plant metabolome with potential contaminating metabolites from the coexisting microbes has been largely ignored. To address this problem, we implemented an effective stable isotope labeling approach, where the metabolome of a plant bacterial pathogen Pseudomonas syringae pv. tomato (Pst) DC3000 was labeled with heavy isotopes. The labeled bacterial cells were incubated with Arabidopsis thaliana epidermal peels (EPs) with guard cells, and excessive bacterial cells were subsequently removed from the plant tissues by washing. The plant metabolites were characterized by liquid chromatography mass spectrometry using multiple reactions monitoring, which can differentiate plant and bacterial metabolites. Targeted metabolomic analysis suggested that Pst DC3000 infection may modulate stomatal movement by reprograming plant signaling and primary metabolic pathways. This proof-of-concept study demonstrates the utility of this strategy in differentiation of the plant and microbe metabolomes, and it has broad applications in studying metabolic interactions between microbes and other organisms. PMID:29922325

GPU-Based Point Cloud Superpositioning for Structural Comparisons of Protein Binding Sites.

PubMed

Leinweber, Matthias; Fober, Thomas; Freisleben, Bernd

2018-01-01

In this paper, we present a novel approach to solve the labeled point cloud superpositioning problem for performing structural comparisons of protein binding sites. The solution is based on a parallel evolution strategy that operates on large populations and runs on GPU hardware. The proposed evolution strategy reduces the likelihood of getting stuck in a local optimum of the multimodal real-valued optimization problem represented by labeled point cloud superpositioning. The performance of the GPU-based parallel evolution strategy is compared to a previously proposed CPU-based sequential approach for labeled point cloud superpositioning, indicating that the GPU-based parallel evolution strategy leads to qualitatively better results and significantly shorter runtimes, with speed improvements of up to a factor of 1,500 for large populations. Binary classification tests based on the ATP, NADH, and FAD protein subsets of CavBase, a database containing putative binding sites, show average classification rate improvements from about 92 percent (CPU) to 96 percent (GPU). Further experiments indicate that the proposed GPU-based labeled point cloud superpositioning approach can be superior to traditional protein comparison approaches based on sequence alignments.

Reading the Small Print – Labelling Recommendations for Orthopaedic Implants

PubMed Central

Haene, Roger A; Sandhu, Ranbir S; Baxandall, Richard

2009-01-01

INTRODUCTION There exist, currently, no clear guidelines regarding standards for surgical implant labelling. Dimensions of the laminar flow canopies in orthopaedic use fixes the distance at which implant labels can be read. Mistakes when reading the label on an implant box can pose health risks for patients, and financial consequences for medical institutions. SUBJECTS AND METHODS Using scientifically validated tools such as the Snellen Chart Formula, a theoretical minimum standard for text on implant labels was reached. This theoretical standard was then tested under real operating conditions. After discovering a minimum practical standard for implant labels, the authors then audited current labels in use on a wide range of orthopaedic implant packages. Furthermore, other non-text-related labelling problems were also noted. RESULTS There is a definite minimum standard which should be observed when implant labels are manufactured. Implants in current use bear labels on the packaging that are of an insufficient standard to ensure patient safety in theatre. CONCLUSIONS The authors have established text parameters that will increase the legibility of implant labels. In the interests of improving risk management in theatre, therefore, the authors propose a standard for orthopaedic implant labelling, and believe this will provide a useful foundation for further discussion between the orthopaedic community and implant manufacturers. PMID:19686615

Surface chemistry and morphology in single particle optical imaging

NASA Astrophysics Data System (ADS)

Ekiz-Kanik, Fulya; Sevenler, Derin Deniz; Ünlü, Neşe Lortlar; Chiari, Marcella; Ünlü, M. Selim

2017-05-01

Biological nanoparticles such as viruses and exosomes are important biomarkers for a range of medical conditions, from infectious diseases to cancer. Biological sensors that detect whole viruses and exosomes with high specificity, yet without additional labeling, are promising because they reduce the complexity of sample preparation and may improve measurement quality by retaining information about nanoscale physical structure of the bio-nanoparticle (BNP). Towards this end, a variety of BNP biosensor technologies have been developed, several of which are capable of enumerating the precise number of detected viruses or exosomes and analyzing physical properties of each individual particle. Optical imaging techniques are promising candidates among broad range of label-free nanoparticle detectors. These imaging BNP sensors detect the binding of single nanoparticles on a flat surface functionalized with a specific capture molecule or an array of multiplexed capture probes. The functionalization step confers all molecular specificity for the sensor's target but can introduce an unforeseen problem; a rough and inhomogeneous surface coating can be a source of noise, as these sensors detect small local changes in optical refractive index. In this paper, we review several optical technologies for label-free BNP detectors with a focus on imaging systems. We compare the surface-imaging methods including dark-field, surface plasmon resonance imaging and interference reflectance imaging. We discuss the importance of ensuring consistently uniform and smooth surface coatings of capture molecules for these types of biosensors and finally summarize several methods that have been developed towards addressing this challenge.

16 CFR 309.21 - Labeling requirements for used covered vehicles.

Code of Federal Regulations, 2012 CFR

2012-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figure 6. (c) Type size and setting... vehicles. 309.21 Section 309.21 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.21 - Labeling requirements for used covered vehicles.

Code of Federal Regulations, 2013 CFR

2013-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figure 6. (c) Type size and setting... vehicles. 309.21 Section 309.21 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.20 - Labeling requirements for new covered vehicles.

Code of Federal Regulations, 2013 CFR

2013-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figures 4, 5, and 5.1. (c) Type... vehicles. 309.20 Section 309.20 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

16 CFR 309.20 - Labeling requirements for new covered vehicles.

Code of Federal Regulations, 2012 CFR

2012-01-01

... numbers, bar codes, and vehicle identification numbers consistent with Figures 4, 5, and 5.1. (c) Type... vehicles. 309.20 Section 309.20 Commercial Practices FEDERAL TRADE COMMISSION REGULATIONS UNDER SPECIFIC ACTS OF CONGRESS LABELING REQUIREMENTS FOR ALTERNATIVE FUELS AND ALTERNATIVE FUELED VEHICLES...

Distribution of distances between DNA barcode labels in nanochannels close to the persistence length

NASA Astrophysics Data System (ADS)

Reinhart, Wesley F.; Reifenberger, Jeff G.; Gupta, Damini; Muralidhar, Abhiram; Sheats, Julian; Cao, Han; Dorfman, Kevin D.

2015-02-01

We obtained experimental extension data for barcoded E. coli genomic DNA molecules confined in nanochannels from 40 nm to 51 nm in width. The resulting data set consists of 1 627 779 measurements of the distance between fluorescent probes on 25 407 individual molecules. The probability density for the extension between labels is negatively skewed, and the magnitude of the skewness is relatively insensitive to the distance between labels. The two Odijk theories for DNA confinement bracket the mean extension and its variance, consistent with the scaling arguments underlying the theories. We also find that a harmonic approximation to the free energy, obtained directly from the probability density for the distance between barcode labels, leads to substantial quantitative error in the variance of the extension data. These results suggest that a theory for DNA confinement in such channels must account for the anharmonic nature of the free energy as a function of chain extension.

A multi-center study benchmarks software tools for label-free proteome quantification

PubMed Central

Gillet, Ludovic C; Bernhardt, Oliver M.; MacLean, Brendan; Röst, Hannes L.; Tate, Stephen A.; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I.; Aebersold, Ruedi; Tenzer, Stefan

2016-01-01

The consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra), a method that uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test datasets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation windows setups. For consistent evaluation we developed LFQbench, an R-package to calculate metrics of precision and accuracy in label-free quantitative MS, and report the identification performance, robustness and specificity of each software tool. Our reference datasets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics. PMID:27701404

A multicenter study benchmarks software tools for label-free proteome quantification.

PubMed

Navarro, Pedro; Kuharev, Jörg; Gillet, Ludovic C; Bernhardt, Oliver M; MacLean, Brendan; Röst, Hannes L; Tate, Stephen A; Tsou, Chih-Chiang; Reiter, Lukas; Distler, Ute; Rosenberger, George; Perez-Riverol, Yasset; Nesvizhskii, Alexey I; Aebersold, Ruedi; Tenzer, Stefan

2016-11-01

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.

Complex networks with large numbers of labelable attractors

NASA Astrophysics Data System (ADS)

Mi, Yuanyuan; Zhang, Lisheng; Huang, Xiaodong; Qian, Yu; Hu, Gang; Liao, Xuhong

2011-09-01

Information storage in many functional subsystems of the brain is regarded by theoretical neuroscientists to be related to attractors of neural networks. The number of attractors is large and each attractor can be temporarily represented or suppressed easily by corresponding external stimulus. In this letter, we discover that complex networks consisting of excitable nodes have similar fascinating properties of coexistence of large numbers of oscillatory attractors, most of which can be labeled with a few nodes. According to a simple labeling rule, different attractors can be identified and the number of labelable attractors can be predicted from the analysis of network topology. With the cues of the labeling association, these attractors can be conveniently retrieved or suppressed on purpose.

iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins.

PubMed

Lin, Wei-Zhong; Fang, Jian-An; Xiao, Xuan; Chou, Kuo-Chen

2013-04-05

Predicting protein subcellular localization is a challenging problem, particularly when query proteins have multi-label features meaning that they may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing methods can only be used to deal with the single-label proteins. Actually, multi-label proteins should not be ignored because they usually bear some special function worthy of in-depth studies. By introducing the "multi-label learning" approach, a new predictor, called iLoc-Animal, has been developed that can be used to deal with the systems containing both single- and multi-label animal (metazoan except human) proteins. Meanwhile, to measure the prediction quality of a multi-label system in a rigorous way, five indices were introduced; they are "Absolute-True", "Absolute-False" (or Hamming-Loss"), "Accuracy", "Precision", and "Recall". As a demonstration, the jackknife cross-validation was performed with iLoc-Animal on a benchmark dataset of animal proteins classified into the following 20 location sites: (1) acrosome, (2) cell membrane, (3) centriole, (4) centrosome, (5) cell cortex, (6) cytoplasm, (7) cytoskeleton, (8) endoplasmic reticulum, (9) endosome, (10) extracellular, (11) Golgi apparatus, (12) lysosome, (13) mitochondrion, (14) melanosome, (15) microsome, (16) nucleus, (17) peroxisome, (18) plasma membrane, (19) spindle, and (20) synapse, where many proteins belong to two or more locations. For such a complicated system, the outcomes achieved by iLoc-Animal for all the aforementioned five indices were quite encouraging, indicating that the predictor may become a useful tool in this area. It has not escaped our notice that the multi-label approach and the rigorous measurement metrics can also be used to investigate many other multi-label problems in molecular biology. As a user-friendly web-server, iLoc-Animal is freely accessible to the public at the web-site .

Direct synthesis of ESBO derivatives-¹⁸O labelled with dioxirane.

PubMed

La Tegola, Stefano; Annese, Cosimo; Suman, Michele; Tommasi, Immacolata; Fusco, Caterina; D'Accolti, Lucia

2013-01-01

This work addresses a new approach developed in our laboratory, consisting in the application of isolated dimethyldioxirane (DDO, 1a) labelled with ¹⁸O for synthesis of epoxidized glyceryl linoleate (Gly-LLL, 2). We expect that this work could contribute in improving analytical methods for the determination of epoxidized soybean oil (ESBO) in complex food matrices by adopting an ¹⁸O-labelled-epoxidized triacylglycerol as an internal standard.

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.

Rooting out institutional corruption to manage inappropriate off-label drug use.

PubMed

Rodwin, Marc A

2013-01-01

Prescribing drugs for uses that the FDA has not approved - off-label drug use - can sometimes be justified but is typically not supported by substantial evidence of effectiveness. At the root of inappropriate off-label drug use lie perverse incentives for pharmaceutical firms and flawed oversight of prescribing physicians. Typical reform proposals such as increased sanctions for manufacturers might reduce the incidence of unjustified off-label use, but they do not remove the source of the problem. Public policy should address the cause and control the practice. To manage inappropriate off-label drug use, off-label prescriptions must be tracked in order to monitor the risks and benefits and the manufacturers' conduct. Even more important, reimbursement rules should be changed so that manufacturers cannot profit from off-label sales. When off-label sales pass a critical threshold, manufacturers should also be required to pay for independent testing of the safety and effectiveness of off-label drug uses and for the FDA to review the evidence. Manufacturers should also finance, under FDA supervision, programs designed to warn physicians and the public about the risks of off-label drug use. © 2013 American Society of Law, Medicine & Ethics, Inc.

Learning to Predict Combinatorial Structures

NASA Astrophysics Data System (ADS)

Vembu, Shankar

2009-12-01

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.

Fluorescent Photo-conversion: A second chance to label unique cells.

PubMed

Mellott, Adam J; Shinogle, Heather E; Moore, David S; Detamore, Michael S

2015-03-01

Not all cells behave uniformly after treatment in tissue engineering studies. In fact, some treated cells display no signs of treatment or show unique characteristics not consistent with other treated cells. What if the "unique" cells could be isolated from a treated population, and further studied? Photo-convertible reporter proteins, such as Dendra2 , allow for the ability to selectively identify unique cells with a secondary label within a primary labeled treated population. In the current study, select cells were identified and labeled through photo-conversion of Dendra2 -transfected human Wharton's Jelly cells (hWJCs) for the first time. Robust photo-conversion of green-to-red fluorescence was achieved consistently in arbitrarily selected cells, allowing for precise cell identification of select hWJCs. The current study demonstrates a method that offers investigators the opportunity to selectively label and identify unique cells within a treated population for further study or isolation from the treatment population. Photo-convertible reporter proteins, such as Dendra2 , offer the ability over non-photo-convertible reporter proteins, such as green fluorescent protein, to analyze unique individual cells within a treated population, which allows investigators to gain more meaningful information on how a treatment affects all cells within a target population.

Analysis of U.S. Food and Drug Administration food allergen recalls after implementation of the food allergen labeling and consumer protection act.

PubMed

Gendel, Steven M; Zhu, Jianmei

2013-11-01

To avoid potentially life-threatening reactions, food allergic consumers rely on information on food labels to help them avoid exposure to a food or ingredient that could trigger a reaction. To help consumers in the United States obtain the information that they need, the Food Allergen Labeling and Consumer Protection Act of 2004 defined a major food allergen as being one of eight foods or food groups and any ingredient that contains protein from one of these foods or food groups. A food that contains an undeclared major food allergen is misbranded under the U.S. Food, Drug, and Cosmetic Act and is subject to recall. Food allergen labeling problems are the most common cause of recalls for U.S. Food and Drug Administration (FDA)-regulated food products. To help understand why food allergen recalls continue to occur at a high rate, information on each food allergen recall that occurred in fiscal years 2007 through 2012 was obtained from the FDA recall database. This information was analyzed to identify the food, allergen, root cause, and mode of discovery for each food allergen recall. Bakery products were the most frequently recalled food type, and milk was the most frequently undeclared major food allergen. Use of the wrong package or label was the most frequent problem leading to food allergen recalls. These data are the first reported that indicate the importance of label and package controls as public health measures.

Naming, labeling, and packaging of pharmaceuticals.

PubMed

Kenagy, J W; Stein, G C

2001-11-01

The problem of medical errors associated with the naming, labeling, and packaging of pharmaceuticals is discussed. Sound-alike and look-alike drug names and packages can lead pharmacists and nurses to unintended interchanges of drugs that can result in patient injury or death. The existing medication-use system is flawed because its safety depends on human perfection. Simplicity, standardization, differentiation, lack of duplication, and unambiguous communication are human factors concepts that are relevant to the medication-use process. These principles have often been ignored in drug naming, labeling, and packaging. Instead, current methods are based on long-standing commercial considerations and bureaucratic procedures. The process for naming a marketable drug is lengthy and complex and involves submission of a new chemical entity and patent application, generic naming, brand naming, FDA review, and final approval. Drug companies seek the fastest possible approval and may believe that the incremental benefit of human factors evaluation is small. "Trade dress" is the concept that underlies labeling and packaging issues for the drug industry. Drug companies are resistant to changing trade dress and brand names. Although a variety of private-sector organizations have called for reforms in drug naming, labeling, and packaging standards have been proposed, the problem remains. Drug names, labels, and packages are not selected and designed in accordance with human factors principles. FDA standards do not require application of these principles, the drug industry has struggled with change, and private-sector initiatives have had only limited success.

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

Electron Detachment Dissociation (EDD) of Fluorescently Labeled Sialylated Oligosaccharides

PubMed Central

Zhou, Wen; Håkansson, Kristina

2012-01-01

We explored the application of electron detachment dissociation (EDD) and infrared multiphoton dissociation (IRMPD) tandem mass spectrometry to fluorescently labeled sialylated oligosaccharides. Standard sialylated oligosaccharides and a sialylated N-linked glycan released from human transferrin were investigated. EDD yielded extensive glycosidic cleavages and cross-ring cleavages in all cases studied, consistently providing complementary structural information compared to IRMPD. Neutral losses and satellite ions such as C – 2H ions were also observed following EDD. In addition, we examined the influence of different fluorescent labels. The acidic label 2-aminobenzoic acid (2-AA) enhanced signal abundance in negative-ion mode. However, few cross-ring fragments were observed for 2-AA labeled oligosaccharides. The neutral label 2-aminobenzamide (2-AB) resulted in more cross-ring cleavages compared to 2-AA labeled species, but not as extensive fragmentation as for native oligosaccharides, likely resulting from altered negative charge locations from introduction of the fluorescent tag. PMID:22120881

An Ensemble Multilabel Classification for Disease Risk Prediction

PubMed Central

Liu, Wei; Zhao, Hongling; Zhang, Chaoyang

2017-01-01

It is important to identify and prevent disease risk as early as possible through regular physical examinations. We formulate the disease risk prediction into a multilabel classification problem. A novel Ensemble Label Power-set Pruned datasets Joint Decomposition (ELPPJD) method is proposed in this work. First, we transform the multilabel classification into a multiclass classification. Then, we propose the pruned datasets and joint decomposition methods to deal with the imbalance learning problem. Two strategies size balanced (SB) and label similarity (LS) are designed to decompose the training dataset. In the experiments, the dataset is from the real physical examination records. We contrast the performance of the ELPPJD method with two different decomposition strategies. Moreover, the comparison between ELPPJD and the classic multilabel classification methods RAkEL and HOMER is carried out. The experimental results show that the ELPPJD method with label similarity strategy has outstanding performance. PMID:29065647

Individual Responsibility for Promoting Global Health: The Case for a New Kind of Socially Conscious Consumption.

PubMed

Hassoun, Nicole

2016-06-01

The problems of global health are truly terrible. Millions suffer and die from diseases like tuberculosis, HIV/AIDS, and malaria. One way of addressing these problems is via a Global Health Impact labeling campaign (http://global-health-impact.org/). If even a small percentage of consumers promote global health by purchasing Global Health Impact products, the incentive to use this label will be substantial. One might wonder, however, whether consumers are morally obligation to purchase any these goods or whether doing so is even morally permissible. This paper suggests that if the proposal is implemented, purchasing Global Health Impact labelled goods is at least morally permissible, if not morally required. Its argument should, moreover, be of much more general interest to those considering different kinds of ethical consumption. © 2016 American Society of Law, Medicine & Ethics.

Multiclassifier fusion in human brain MR segmentation: modelling convergence.

PubMed

Heckemann, Rolf A; Hajnal, Joseph V; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander

2006-01-01

Segmentations of MR images of the human brain can be generated by propagating an existing atlas label volume to the target image. By fusing multiple propagated label volumes, the segmentation can be improved. We developed a model that predicts the improvement of labelling accuracy and precision based on the number of segmentations used as input. Using a cross-validation study on brain image data as well as numerical simulations, we verified the model. Fit parameters of this model are potential indicators of the quality of a given label propagation method or the consistency of the input segmentations used.

Impact of race and diagnostic label on older adults' emotions, illness beliefs, and willingness to help a family member with osteoarthritis.

PubMed

Mingo, Chivon A; McIlvane, Jessica M; Haley, William E; Luong, My-Linh N

2015-04-01

To examine how race and the diagnostic label of Osteoarthritis (OA) affects older adults' emotions, illness beliefs, and willingness to help a family member. African American and White older adults were randomly assigned to read vignettes describing a sister suffering from chronic pain and disability, either with or without the OA label. Race × diagnostic label ANOVAs were conducted. Compared to Whites, African Americans were more optimistic that OA could improve with health care, and showed greater willingness to help their sister. The OA label had little impact on emotions, beliefs, or willingness to help. African Americans rated the sister as having more control of their problem than Whites without the OA label, but providing the diagnosis eliminated this difference. The diagnostic label of OA had little effect on these older adults, but racial differences indicate that cultural values regarding family caregiving are important in arthritis care. © The Author(s) 2013.

Particle Filter with State Permutations for Solving Image Jigsaw Puzzles

PubMed Central

Yang, Xingwei; Adluru, Nagesh; Latecki, Longin Jan

2016-01-01

We deal with an image jigsaw puzzle problem, which is defined as reconstructing an image from a set of square and non-overlapping image patches. It is known that a general instance of this problem is NP-complete, and it is also challenging for humans, since in the considered setting the original image is not given. Recently a graphical model has been proposed to solve this and related problems. The target label probability function is then maximized using loopy belief propagation. We also formulate the problem as maximizing a label probability function and use exactly the same pairwise potentials. Our main contribution is a novel inference approach in the sampling framework of Particle Filter (PF). Usually in the PF framework it is assumed that the observations arrive sequentially, e.g., the observations are naturally ordered by their time stamps in the tracking scenario. Based on this assumption, the posterior density over the corresponding hidden states is estimated. In the jigsaw puzzle problem all observations (puzzle pieces) are given at once without any particular order. Therefore, we relax the assumption of having ordered observations and extend the PF framework to estimate the posterior density by exploring different orders of observations and selecting the most informative permutations of observations. This significantly broadens the scope of applications of the PF inference. Our experimental results demonstrate that the proposed inference framework significantly outperforms the loopy belief propagation in solving the image jigsaw puzzle problem. In particular, the extended PF inference triples the accuracy of the label assignment compared to that using loopy belief propagation. PMID:27795660

Polysemy and the Taxonomic Constraint: Children's Representation of Words That Label Multiple Kinds

ERIC Educational Resources Information Center

Srinivasan, Mahesh; Snedeker, Jesse

2014-01-01

How do children resolve the problem of indeterminacy when learning a new word? By one account, children adopt a "taxonomic assumption" and expect the word to denote only members of a particular taxonomic category. According to one version of this constraint, young children should represent polysemous words that label multiple kinds--for…

Differential Labeling of Mental Illness by Social Status: A New Look at an Old Problem

ERIC Educational Resources Information Center

Thoits, Peggy A.

2005-01-01

Whether the higher rates of mental hospitalization and involuntary treatment for marginal social groups are due to differential labeling or simply to the occurrence of higher rates of disorder in these groups remains unresolved. I reexamine this issue with data from the National Comorbidity Survey (N = 5,877) that allow comparisons between…

Acoustic classification of multiple simultaneous bird species: a multi-instance multi-label approach

Treesearch

F. Briggs; B. Lakshminarayanan; L. Neal; X.Z. Fern; R. Raich; S.F. Hadley; A.S. Hadley; M.G. Betts

2012-01-01

Although field-collected recordings typically contain multiple simultaneously vocalizing birds of different species, acoustic species classification in this setting has received little study so far. This work formulates the problem of classifying the set of species present in an audio recording using the multi-instance multi-label (MIML) framework for machine learning...

The Effects of Labels on Learning Subgoals for Solving Problems.

ERIC Educational Resources Information Center

Catrambone, Richard

This study, involving 65 undergraduates at the Georgia Institute of Technology (Atlanta); explores a scheme for representing problem-solving knowledge and predicting transfer as a function of problem-solving subgoals acquired from examples. A subgoal is an unknown entity (numerical or conceptual) that needs to be found in order to achieve a higher…

Biomedical literature classification using encyclopedic knowledge: a Wikipedia-based bag-of-concepts approach.

PubMed

Mouriño García, Marcos Antonio; Pérez Rodríguez, Roberto; Anido Rifón, Luis E

2015-01-01

Automatic classification of text documents into a set of categories has a lot of applications. Among those applications, the automatic classification of biomedical literature stands out as an important application for automatic document classification strategies. Biomedical staff and researchers have to deal with a lot of literature in their daily activities, so it would be useful a system that allows for accessing to documents of interest in a simple and effective way; thus, it is necessary that these documents are sorted based on some criteria-that is to say, they have to be classified. Documents to classify are usually represented following the bag-of-words (BoW) paradigm. Features are words in the text-thus suffering from synonymy and polysemy-and their weights are just based on their frequency of occurrence. This paper presents an empirical study of the efficiency of a classifier that leverages encyclopedic background knowledge-concretely Wikipedia-in order to create bag-of-concepts (BoC) representations of documents, understanding concept as "unit of meaning", and thus tackling synonymy and polysemy. Besides, the weighting of concepts is based on their semantic relevance in the text. For the evaluation of the proposal, empirical experiments have been conducted with one of the commonly used corpora for evaluating classification and retrieval of biomedical information, OHSUMED, and also with a purpose-built corpus of MEDLINE biomedical abstracts, UVigoMED. Results obtained show that the Wikipedia-based bag-of-concepts representation outperforms the classical bag-of-words representation up to 157% in the single-label classification problem and up to 100% in the multi-label problem for OHSUMED corpus, and up to 122% in the single-label classification problem and up to 155% in the multi-label problem for UVigoMED corpus.

Biomedical literature classification using encyclopedic knowledge: a Wikipedia-based bag-of-concepts approach

PubMed Central

Pérez Rodríguez, Roberto; Anido Rifón, Luis E.

2015-01-01

Automatic classification of text documents into a set of categories has a lot of applications. Among those applications, the automatic classification of biomedical literature stands out as an important application for automatic document classification strategies. Biomedical staff and researchers have to deal with a lot of literature in their daily activities, so it would be useful a system that allows for accessing to documents of interest in a simple and effective way; thus, it is necessary that these documents are sorted based on some criteria—that is to say, they have to be classified. Documents to classify are usually represented following the bag-of-words (BoW) paradigm. Features are words in the text—thus suffering from synonymy and polysemy—and their weights are just based on their frequency of occurrence. This paper presents an empirical study of the efficiency of a classifier that leverages encyclopedic background knowledge—concretely Wikipedia—in order to create bag-of-concepts (BoC) representations of documents, understanding concept as “unit of meaning”, and thus tackling synonymy and polysemy. Besides, the weighting of concepts is based on their semantic relevance in the text. For the evaluation of the proposal, empirical experiments have been conducted with one of the commonly used corpora for evaluating classification and retrieval of biomedical information, OHSUMED, and also with a purpose-built corpus of MEDLINE biomedical abstracts, UVigoMED. Results obtained show that the Wikipedia-based bag-of-concepts representation outperforms the classical bag-of-words representation up to 157% in the single-label classification problem and up to 100% in the multi-label problem for OHSUMED corpus, and up to 122% in the single-label classification problem and up to 155% in the multi-label problem for UVigoMED corpus. PMID:26468436

Affect labeling enhances exposure effectiveness for public speaking anxiety.

PubMed

Niles, Andrea N; Craske, Michelle G; Lieberman, Matthew D; Hur, Christopher

2015-05-01

Exposure is an effective treatment for anxiety but many patients do not respond fully. Affect labeling (labeling emotional experience) attenuates emotional responding. The current project examined whether affect labeling enhances exposure effectiveness in participants with public speaking anxiety. Participants were randomized to exposure with or without affect labeling. Physiological arousal and self-reported fear were assessed before and after exposure and compared between groups. Consistent with hypotheses, participants assigned to Affect Labeling, especially those who used more labels during exposure, showed greater reduction in physiological activation than Control participants. No effect was found for self-report measures. Also, greater emotion regulation deficits at baseline predicted more benefit in physiological arousal from exposure combined with affect labeling than exposure alone. The current research provides evidence that behavioral strategies that target prefrontal-amygdala circuitry can improve treatment effectiveness for anxiety and these effects are particularly pronounced for patients with the greatest deficits in emotion regulation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Folk concepts of mental disorders among Chinese-Australian patients and their caregivers.

PubMed

Hsiao, Fei-Hsiu; Klimidis, Steven; Minas, Harry I; Tan, Eng S

2006-07-01

This paper reports a study of (a) popular conceptions of mental illness throughout history, (b) how current social and cultural knowledge about mental illness influences Chinese-Australian patients' and caregivers' understanding of mental illness and the consequences of this for explaining and labelling patients' problems. According to traditional Chinese cultural knowledge about health and illness, Chinese people believe that psychotic illness is the only type of mental illness, and that non-psychotic illness is a physical illness. Regarding patients' problems as not being due to mental illness may result in delaying use of Western mental health services. Data collection took place in 2001. Twenty-eight Chinese-Australian patients with mental illness and their caregivers were interviewed at home, drawing on Kleinman's explanatory model and studies of cultural transmission. Interviews were tape-recorded and transcribed, and analysed for plots and themes. Chinese-Australians combined traditional knowledge with Western medical knowledge to develop their own labels for various kinds of mental disorders, including 'mental illness', 'physical illness', 'normal problems of living' and 'psychological problems'. As they learnt more about Western conceptions of psychology and psychiatry, their understanding of some disorders changed. What was previously ascribed to non-mental disorders was often re-labelled as 'mental illness' or 'psychological problems'. Educational programmes aimed at introducing Chinese immigrants to counselling and other psychiatric services could be made more effective if designers gave greater consideration to Chinese understanding of mental illness.

Using Distance Education to Teach the New Food Label to Extension Educators.

ERIC Educational Resources Information Center

Struempler, Barbara; And Others

1997-01-01

Satellite training about the new national food labeling system was provided to 97 Alabama extension agents and 67 program assistants. The program, which consisted of a 30-minute video and 25-minute question/answer call-in, proved an effective means of distance education. (SK)

Grains are similarly categorized by 8- to 13-year-old children

USDA-ARS?s Scientific Manuscript database

This study assessed how 8- to 13-year-old children categorized and labeled grain foods and how these categories and labels were influenced by child characteristics. The main hypotheses were that children categorized foods in consistent ways and these food categories differed from the professional fo...

PRN 2012-1: Material Safety Data Sheets as Pesticide Labeling

EPA Pesticide Factsheets

This Notice updates and clarifies EPA’s determination in PRN 92-4 that a Material Safety Data Sheet that accompanies a pesticide product is considered part of the pesticide’s labeling but does not need EPA approval if it is consistent with 40CFR Part 156.

Cancer classification through filtering progressive transductive support vector machine based on gene expression data

NASA Astrophysics Data System (ADS)

Lu, Xinguo; Chen, Dan

2017-08-01

Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

Image labeling. The need for a better look.

PubMed

Hunter, T

1994-10-01

The important message in this editorial is for radiologists to critically examine how well images are labeled in their own department. If it is not satisfactory, then institute corrective measures. These can range from sophisticated computer programs for printing flashcards to merely sending the chief technologist all those films one comes across with unreadable labels. The quality of the image labeling should also be a consideration when purchasing CT, MRI, ultrasound, computed radiography and digital angiography equipment. The fact that you consider this important should be communicated to equipment manufacturers in the hope that they will pay more attention to it and offer more flexibility for each department to design its own labels. In any event, I feel consistently bad film labeling results in sloppy radiology with possible patient harm and unpleasant legal consequences for the radiologist.

Development of a DNA microarray for species identification of quarantine aphids.

PubMed

Lee, Won Sun; Choi, Hwalran; Kang, Jinseok; Kim, Ji-Hoon; Lee, Si Hyeock; Lee, Seunghwan; Hwang, Seung Yong

2013-12-01

Aphid pests are being brought into Korea as a result of increased crop trading. Aphids exist on growth areas of plants, and thus plant growth is seriously affected by aphid pests. However, aphids are very small and have several sexual morphs and life stages, so it is difficult to identify species on the basis of morphological features. This problem was approached using DNA microarray technology. DNA targets of the cytochrome c oxidase subunit I gene were generated with a fluorescent dye-labelled primer and were hybridised onto a DNA microarray consisting of specific probes. After analysing the signal intensity of the specific probes, the unique patterns from the DNA microarray, consisting of 47 species-specific probes, were obtained to identify 23 aphid species. To confirm the accuracy of the developed DNA microarray, ten individual blind samples were used in blind trials, and the identifications were completely consistent with the sequencing data of all individual blind samples. A microarray has been developed to distinguish aphid species. DNA microarray technology provides a rapid, easy, cost-effective and accurate method for identifying aphid species for pest control management. © 2013 Society of Chemical Industry.

Weakly supervised image semantic segmentation based on clustering superpixels

NASA Astrophysics Data System (ADS)

Yan, Xiong; Liu, Xiaohua

2018-04-01

In this paper, we propose an image semantic segmentation model which is trained from image-level labeled images. The proposed model starts with superpixel segmenting, and features of the superpixels are extracted by trained CNN. We introduce a superpixel-based graph followed by applying the graph partition method to group correlated superpixels into clusters. For the acquisition of inter-label correlations between the image-level labels in dataset, we not only utilize label co-occurrence statistics but also exploit visual contextual cues simultaneously. At last, we formulate the task of mapping appropriate image-level labels to the detected clusters as a problem of convex minimization. Experimental results on MSRC-21 dataset and LableMe dataset show that the proposed method has a better performance than most of the weakly supervised methods and is even comparable to fully supervised methods.

DOORS to the semantic web and grid with a PORTAL for biomedical computing.

PubMed

Taswell, Carl

2008-03-01

The semantic web remains in the early stages of development. It has not yet achieved the goals envisioned by its founders as a pervasive web of distributed knowledge and intelligence. Success will be attained when a dynamic synergism can be created between people and a sufficient number of infrastructure systems and tools for the semantic web in analogy with those for the original web. The domain name system (DNS), web browsers, and the benefits of publishing web pages motivated many people to register domain names and publish web sites on the original web. An analogous resource label system, semantic search applications, and the benefits of collaborative semantic networks will motivate people to register resource labels and publish resource descriptions on the semantic web. The Domain Ontology Oriented Resource System (DOORS) and Problem Oriented Registry of Tags and Labels (PORTAL) are proposed as infrastructure systems for resource metadata within a paradigm that can serve as a bridge between the original web and the semantic web. The Internet Registry Information Service (IRIS) registers [corrected] domain names while DNS publishes domain addresses with mapping of names to addresses for the original web. Analogously, PORTAL registers resource labels and tags while DOORS publishes resource locations and descriptions with mapping of labels to locations for the semantic web. BioPORT is proposed as a prototype PORTAL registry specific for the problem domain of biomedical computing.

Implementation and Assessment of a Virtual Laboratory of Parallel Robots Developed for Engineering Students

ERIC Educational Resources Information Center

Gil, Arturo; Peidró, Adrián; Reinoso, Óscar; Marín, José María

2017-01-01

This paper presents a tool, LABEL, oriented to the teaching of parallel robotics. The application, organized as a set of tools developed using Easy Java Simulations, enables the study of the kinematics of parallel robotics. A set of classical parallel structures was implemented such that LABEL can solve the inverse and direct kinematic problem of…

Easy as ABCABC: Abstract Language Facilitates Performance on a Concrete Patterning Task

ERIC Educational Resources Information Center

Fyfe, Emily R.; McNeil, Nicole M.; Rittle-Johnson, Bethany

2015-01-01

The labels used to describe patterns and relations can influence children's relational reasoning. In this study, 62 preschoolers (M[subscript age] = 4.4 years) solved and described eight pattern abstraction problems (i.e., recreated the relation in a model pattern using novel materials). Some children were exposed to concrete labels (e.g.,…

Word Frequency, Function Words and the Second Gavagai Problem

ERIC Educational Resources Information Center

Hochmann, Jean-Remy

2013-01-01

The classic gavagai problem exemplifies the difficulty to identify the referent of a novel word uttered in a foreign language. Here, we consider the reverse problem: identifying the referential part of a label. Assuming "gavagai" indicates a rabbit in a foreign language, it may very well mean ""a" rabbit" or ""that" rabbit". How can a learner know…

Synthesis and biological studies of positron-emitting radiopharmaceuticals

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

Dischino, D.D.

The development and clinical evaluation of two-positron emitting radiopharmaceuticals designed to image myelin in humans is reported. Carbon-11-labeled benzyl methyl ether was synthesized by the reaction of carbon-11-labeled methanol and benzyl chloride in dimethyl sulfoxide containing powdered potassium hydroxide in a radiochemical yield of 43% and a synthesis and purification time of 40 minutes. Carbon-11-labeled diphenylmethanol was synthesized by the reaction of carbon-11-labeled carbon dioxide and phenyllithium followed by the reduction of the carbon-11-labeled intermediate to diphenylmethanol via lithium aluminum hydride in a radiochemical yield of 71% and a synthesis and purification time of 38 minutes. Carbon-11-labeled benzyl methyl ethermore » and diphenylmethanol were each evaluated as myelin imaging agents in three patients with multiple sclerosis via positron-emission tomography. In two out of three patients studied with carbon-11-labeled benzyl methyl ether, the distribution of activity in the brain was not consistent with local lipid content. A new synthesis of carbon-11-labeled-DL-phenylalanine labeled in the benzylic position and the synthesis of fluorine-18-labeled 1-(2-nitro-1-imidazolyl)-3-fluoro-2-propanol, a potential in vivo marker of hypoxic tissue, are reported.« less

Spatial reasoning to determine stream network from LANDSAT imagery

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Wang, S.; Elliott, D. B.

1983-01-01

In LANDSAT imagery, spectral and spatial information can be used to detect the drainage network as well as the relative elevation model in mountainous terrain. To do this, mixed information of material reflectance in the original LANDSAT imagery must be separated. From the material reflectance information, big visible rivers can be detected. From the topographic modulation information, ridges and valleys can be detected and assigned relative elevations. A complete elevation model can be generated by interpolating values for nonridge and non-valley pixels. The small streams not detectable from material reflectance information can be located in the valleys with flow direction known from the elevation model. Finally, the flow directions of big visible rivers can be inferred by solving a consistent labeling problem based on a set of spatial reasoning constraints.

Experience with the use of the Codonics Safe Label System(™) to improve labelling compliance of anaesthesia drugs.

PubMed

Ang, S B L; Hing, W C; Tung, S Y; Park, T

2014-07-01

The Codonics Safe Labeling System(™) (http://www.codonics.com/Products/SLS/flash/) is a piece of equipment that is able to barcode scan medications, read aloud the medication and the concentration and print a label of the appropriate concentration in the appropriate colour code. We decided to test this system in our facility to identify risks, benefits and usability. Our project comprised a baseline survey (25 anaesthesia cases during which 212 syringes were prepared from 223 drugs), an observational study (47 cases with 330 syringes prepared) and a user acceptability survey. The baseline compliance with all labelling requirements was 58%. In the observational study the compliance using the Codonics system was 98.6% versus 63.8% with conventional labelling. In the user acceptability survey the majority agreed the Codonics machine was easy to use, more legible and adhered with better security than the conventional preprinted label. However, most were neutral when asked about the likelihood of flexibility and customisation and were dissatisfied with the increased workload. Our findings suggest that the Codonics labelling machine is user-friendly and it improved syringe labelling compliance in our study. However, staff need to be willing to follow proper labelling workflow rather than batch label during preparation. Future syringe labelling equipment developers need to concentrate on user interface issues to reduce human factor and workflow problems. Support logistics are also an important consideration prior to implementation of any new labelling system.

Facilitating Problem Solving in High School Chemistry.

ERIC Educational Resources Information Center

Gabel, Dorothy L.; Sherwood, Robert D.

1983-01-01

Investigated superiority of instructional strategies (factor-label method, proportionality, use of analogies, use of diagrams) in teaching problem-solving related to mole concept, gas laws, stoichiometry, and molarity. Also investigated effectiveness of strategies for students (N=609) with different verbal-visual preferences, proportional…

Image velocimetry for clouds with relaxation labeling based on deformation consistency

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

21 CFR 74.2317 - D&C Red No. 17.

Code of Federal Regulations, 2010 CFR

2010-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2317 D&C Red No. 17. (a) Identity and specifications. The color additive D&C Red No. 17 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2331 - D&C Red No. 31.

Code of Federal Regulations, 2010 CFR

2010-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2331 D&C Red No. 31. (a) Identity and specifications. The color additive D&C Red No. 31 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2334 - D&C Red No. 34.

Code of Federal Regulations, 2010 CFR

2010-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2334 D&C Red No. 34. (a) Identity and specifications. The color additive D&C Red No. 34 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2104 - D&C Blue No. 4.

Code of Federal Regulations, 2010 CFR

2010-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2104 D&C Blue No. 4. (a) Identity and specifications. The color additive D&C Blue No. 4 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2304 - FD&C Red No. 4.

Code of Federal Regulations, 2010 CFR

2010-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2304 FD&C Red No. 4. (a) Identity and specifications. The color additive FD&C Red No. 4 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.1340 - FD&C Red No. 40.

Code of Federal Regulations, 2010 CFR

2010-04-01

... amounts consistent with current good manufacturing practice. (c) Labeling. The label of the color additive... ADDITIVES SUBJECT TO CERTIFICATION Drugs § 74.1340 FD&C Red No. 40. (a) Identity and specifications. (1) The color additive FD&C Red No. 40 shall conform in identity and specifications to the requirements of § 74...

16 CFR 1211.15 - Field-installed labels.

Code of Federal Regulations, 2012 CFR

2012-01-01

..., and (3) A message panel, with adjacent panels delineated from each other by a horizontal black line. The entire label shall be surrounded by a black border and shall measure at least 5 inches (127 mm... consisting of an orange exclamation mark on a black solid equilateral triangle background with the point of...

16 CFR § 1211.15 - Field-installed labels.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., and (3) A message panel, with adjacent panels delineated from each other by a horizontal black line. The entire label shall be surrounded by a black border and shall measure at least 5 inches (127 mm... consisting of an orange exclamation mark on a black solid equilateral triangle background with the point of...

16 CFR 1211.15 - Field-installed labels.

Code of Federal Regulations, 2014 CFR

2014-01-01

..., and (3) A message panel, with adjacent panels delineated from each other by a horizontal black line. The entire label shall be surrounded by a black border and shall measure at least 5 inches (127 mm... consisting of an orange exclamation mark on a black solid equilateral triangle background with the point of...

16 CFR 1211.15 - Field-installed labels.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., and (3) A message panel, with adjacent panels delineated from each other by a horizontal black line. The entire label shall be surrounded by a black border and shall measure at least 5 inches (127 mm... consisting of an orange exclamation mark on a black solid equilateral triangle background with the point of...

75 FR 57794 - Notice of Public Information Collection(s) Being Submitted for Review and Approval to the Office...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-22

..., antennas placed on subscriber premises, and the state of the market. The demarcation point burden consists... must ensure that subscriber antennas are labeled to give notice of potential radio frequency safety hazards of these antennas. Labeling information (third party disclosure requirement) should include...

21 CFR 74.2304 - FD&C Red No. 4.

Code of Federal Regulations, 2013 CFR

2013-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2304 FD&C Red No. 4. (a) Identity and specifications. The color additive FD&C Red No. 4 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2317 - D&C Red No. 17.

Code of Federal Regulations, 2014 CFR

2014-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2317 D&C Red No. 17. (a) Identity and specifications. The color additive D&C Red No. 17 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2334 - D&C Red No. 34.

Code of Federal Regulations, 2012 CFR

2012-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2334 D&C Red No. 34. (a) Identity and specifications. The color additive D&C Red No. 34 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2317 - D&C Red No. 17.

Code of Federal Regulations, 2012 CFR

2012-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2317 D&C Red No. 17. (a) Identity and specifications. The color additive D&C Red No. 17 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.1340 - FD&C Red No. 40.

Code of Federal Regulations, 2012 CFR

2012-04-01

... amounts consistent with current good manufacturing practice. (c) Labeling. The label of the color additive... ADDITIVES SUBJECT TO CERTIFICATION Drugs § 74.1340 FD&C Red No. 40. (a) Identity and specifications. (1) The color additive FD&C Red No. 40 shall conform in identity and specifications to the requirements of § 74...

21 CFR 74.2334 - D&C Red No. 34.

Code of Federal Regulations, 2013 CFR

2013-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2334 D&C Red No. 34. (a) Identity and specifications. The color additive D&C Red No. 34 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2304 - FD&C Red No. 4.

Code of Federal Regulations, 2014 CFR

2014-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2304 FD&C Red No. 4. (a) Identity and specifications. The color additive FD&C Red No. 4 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2331 - D&C Red No. 31.

Code of Federal Regulations, 2012 CFR

2012-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2331 D&C Red No. 31. (a) Identity and specifications. The color additive D&C Red No. 31 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2331 - D&C Red No. 31.

Code of Federal Regulations, 2013 CFR

2013-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2331 D&C Red No. 31. (a) Identity and specifications. The color additive D&C Red No. 31 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2331 - D&C Red No. 31.

Code of Federal Regulations, 2014 CFR

2014-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2331 D&C Red No. 31. (a) Identity and specifications. The color additive D&C Red No. 31 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2317 - D&C Red No. 17.

Code of Federal Regulations, 2013 CFR

2013-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2317 D&C Red No. 17. (a) Identity and specifications. The color additive D&C Red No. 17 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2334 - D&C Red No. 34.

Code of Federal Regulations, 2014 CFR

2014-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2334 D&C Red No. 34. (a) Identity and specifications. The color additive D&C Red No. 34 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.2304 - FD&C Red No. 4.

Code of Federal Regulations, 2012 CFR

2012-04-01

... ADDITIVES SUBJECT TO CERTIFICATION Cosmetics § 74.2304 FD&C Red No. 4. (a) Identity and specifications. The color additive FD&C Red No. 4 shall conform in identity and specifications to the requirements of § 74... externally applied cosmetics in amounts consistent with good manufacturing practice. (c) Labeling. The label...

21 CFR 74.1340 - FD&C Red No. 40.

Code of Federal Regulations, 2014 CFR

2014-04-01

... amounts consistent with current good manufacturing practice. (c) Labeling. The label of the color additive... ADDITIVES SUBJECT TO CERTIFICATION Drugs § 74.1340 FD&C Red No. 40. (a) Identity and specifications. (1) The color additive FD&C Red No. 40 shall conform in identity and specifications to the requirements of § 74...

21 CFR 74.1340 - FD&C Red No. 40.

Code of Federal Regulations, 2013 CFR

2013-04-01

... amounts consistent with current good manufacturing practice. (c) Labeling. The label of the color additive... ADDITIVES SUBJECT TO CERTIFICATION Drugs § 74.1340 FD&C Red No. 40. (a) Identity and specifications. (1) The color additive FD&C Red No. 40 shall conform in identity and specifications to the requirements of § 74...

Further studies on the effect of chloroquine on the uptake, metabolism and intracellular translocation of [35S]cystine in cystinotic fibroblasts.

PubMed

Danpure, C J; Jennings, P R; Fyfe, D A

1986-03-14

The present study uses the lysosomotropic drug chloroquine to investigate the mechanisms by which exogenous [35S]cystine is able to label the intracellular (intralysosomal) cystine pool(s) in cystinotic fibroblasts. When cystinotic fibroblasts were labelled for short periods of time (8 h or less), chloroquine (20 microM) inhibited the labelling of the intracellular cystine pool(s). However, when the cells were labelled for longer periods of time (24 h or more) chloroquine stimulated the labelling of the intracellular cystine pool(s). The short-term effect was selectively abolished when the cells were washed free of chloroquine, while the long-term effect was selectively abolished when the medium was depleted of cystine. Two routes of translocation of exogenous cystine to the lysosomes could be defined. One route was fast, had a low capacity, was inhibited by chloroquine and increased with increasing medium pH, while the other route was slow, had a high capacity, was stimulated by chloroquine and was more active at low pH. The former pathway probably consisted of plasma membrane transport of cystine into the cytosol followed by direct or indirect transport into the lysosomes. The latter route possibly consisted of pinocytosis with fusion of the cystine-containing pinosomes with lysosomes.

Fluorescent Photo-conversion: A second chance to label unique cells

PubMed Central

Mellott, Adam J.; Shinogle, Heather E.; Moore, David S.; Detamore, Michael S.

2014-01-01

Not all cells behave uniformly after treatment in tissue engineering studies. In fact, some treated cells display no signs of treatment or show unique characteristics not consistent with other treated cells. What if the “unique” cells could be isolated from a treated population, and further studied? Photo-convertible reporter proteins, such as Dendra2, allow for the ability to selectively identify unique cells with a secondary label within a primary labeled treated population. In the current study, select cells were identified and labeled through photo-conversion of Dendra2-transfected human Wharton's Jelly cells (hWJCs) for the first time. Robust photo-conversion of green-to-red fluorescence was achieved consistently in arbitrarily selected cells, allowing for precise cell identification of select hWJCs. The current study demonstrates a method that offers investigators the opportunity to selectively label and identify unique cells within a treated population for further study or isolation from the treatment population. Photo-convertible reporter proteins, such as Dendra2, offer the ability over non-photo-convertible reporter proteins, such as green fluorescent protein, to analyze unique individual cells within a treated population, which allows investigators to gain more meaningful information on how a treatment affects all cells within a target population. PMID:25914756

Australian sea-floor survey data, with images and expert annotations.

PubMed

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Marzinelli, Ezequiel M; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B

2015-01-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.

Australian sea-floor survey data, with images and expert annotations

PubMed Central

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B.

2015-01-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research. PMID:26528396

Australian sea-floor survey data, with images and expert annotations

NASA Astrophysics Data System (ADS)

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B.

2015-10-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.

New dye-labeled terminators for improved DNA sequencing patterns.

PubMed Central

Rosenblum, B B; Lee, L G; Spurgeon, S L; Khan, S H; Menchen, S M; Heiner, C R; Chen, S M

1997-01-01

We have used two new dye sets for automated dye-labeled terminator DNA sequencing. One set consists of four, 4,7-dichlororhodamine dyes (d-rhodamines). The second set consists of energy-transfer dyes that use the 5-carboxy-d-rhodamine dyes as acceptor dyes and the 5- or 6-carboxy isomers of 4'-aminomethylfluorescein as the donor dye. Both dye sets utilize a new linker between the dye and the nucleotide, and both provide more even peak heights in terminator sequencing than the dye-terminators consisting of unsubstituted rhodamine dyes. The unsubstituted rhodamine terminators produced electropherograms in which weak G peaks are observed after A peaks and occasionally C peaks. The number of weak G peaks has been reduced or eliminated with the new dye terminators. The general improvement in peak evenness improves accuracy for the automated base-calling software. The improved signal-to-noise ratio of the energy-transfer dye-labeled terminators combined with more even peak heights results in successful sequencing of high molecular weight DNA templates such as bacterial artificial chromosome DNA. PMID:9358158

Food Matrix Effects on Bioaccessibility of β-Carotene Can be Measured in an in Vitro Gastrointestinal Model

PubMed Central

2015-01-01

Since the food matrix determines β-carotene availability for intestinal absorption, food matrix effects on the bioaccessibility of β-carotene from two diets were investigated in vitro and compared with in vivo data. The “mixed diet” consisted of β-carotene-rich vegetables, and the “oil diet” contained β-carotene-low vegetables with supplemental β-carotene. The application of extrinsically labeled β-carotene was also investigated. The bioaccessibility of β-carotene was 28 μg/100 μg β-carotene from the mixed diet and 53 μg/100 μg β-carotene from the oil diet. This ratio of 1.9:1 was consistent with in vivo data, where the apparent absorption was 1.9-fold higher in the oil diet than in the mixed diet. The labeled β-carotene was not equally distributed over time. In conclusion, the food matrix effects on bioaccessibility of β-carotene could be measured using an in vitro model and were consistent with in vivo data. The application of extrinsically labeled β-carotene was not confirmed. PMID:24397305

Formal language constrained path problems

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

Barrett, C.; Jacob, R.; Marathe, M.

1997-07-08

In many path finding problems arising in practice, certain patterns of edge/vertex labels in the labeled graph being traversed are allowed/preferred, while others are disallowed. Motivated by such applications as intermodal transportation planning, the authors investigate the complexity of finding feasible paths in a labeled network, where the mode choice for each traveler is specified by a formal language. The main contributions of this paper include the following: (1) the authors show that the problem of finding a shortest path between a source and destination for a traveler whose mode choice is specified as a context free language is solvablemore » efficiently in polynomial time, when the mode choice is specified as a regular language they provide algorithms with improved space and time bounds; (2) in contrast, they show that the problem of finding simple paths between a source and a given destination is NP-hard, even when restricted to very simple regular expressions and/or very simple graphs; (3) for the class of treewidth bounded graphs, they show that (i) the problem of finding a regular language constrained simple path between source and a destination is solvable in polynomial time and (ii) the extension to finding context free language constrained simple paths is NP-complete. Several extensions of these results are presented in the context of finding shortest paths with additional constraints. These results significantly extend the results in [MW95]. As a corollary of the results, they obtain a polynomial time algorithm for the BEST k-SIMILAR PATH problem studied in [SJB97]. The previous best algorithm was given by [SJB97] and takes exponential time in the worst case.« less

Pattern Recognition Of Blood Vessel Networks In Ocular Fundus Images

NASA Astrophysics Data System (ADS)

Akita, K.; Kuga, H.

1982-11-01

We propose a computer method of recognizing blood vessel networks in color ocular fundus images which are used in the mass diagnosis of adult diseases such as hypertension and diabetes. A line detection algorithm is applied to extract the blood vessels, and the skeleton patterns of them are made to analyze and describe their structures. The recognition of line segments of arteries and/or veins in the vessel networks consists of three stages. First, a few segments which satisfy a certain constraint are picked up and discriminated as arteries or veins. This is the initial labeling. Then the remaining unknown ones are labeled by utilizing the physical level knowledge. We propose two schemes for this stage : a deterministic labeling and a probabilistic relaxation labeling. Finally the label of each line segment is checked so as to minimize the total number of labeling contradictions. Some experimental results are also presented.

Electron detachment dissociation of fluorescently labeled sialylated oligosaccharides.

PubMed

Zhou, Wen; Håkansson, Kristina

2011-12-01

We explored the application of electron detachment dissociation (EDD) and infrared multiphoton dissociation (IRMPD) tandem mass spectrometry to fluorescently labeled sialylated oligosaccharides. Standard sialylated oligosaccharides and a sialylated N-linked glycan released from human transferrin were investigated. EDD yielded extensive glycosidic cleavages and cross-ring cleavages in all cases studied, consistently providing complementary structural information compared with infrared multiphoton dissociation. Neutral losses and satellite ions such as C-2H ions were also observed following EDD. In addition, we examined the influence of different fluorescent labels. The acidic label 2-aminobenzoic acid (2-AA) enhanced signal abundance in negative-ion mode. However, few cross-ring fragments were observed for 2-AA-labeled oligosaccharides. The neutral label 2-aminobenzamide (2-AB) resulted in more cross-ring cleavages compared with 2-AA-labeled species, but not as extensive fragmentation as for native oligosaccharides, likely resulting from altered negative charge locations from introduction of the fluorescent tag. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Copper absorption from foods labelled intrinsically and extrinsically with Cu-65 stable isotope.

PubMed

Harvey, L J; Dainty, J R; Beattie, J H; Majsak-Newman, G; Wharf, S G; Reid, M D; Fairweather-Tait, S J

2005-03-01

To determine copper absorption from copper containing foods labelled either intrinsically or extrinsically with a highly enriched Cu-65 stable isotope label. A longitudinal cross-over study. The study was conducted at the Institute of Food Research, Human Nutrition Unit, Norwich, UK. Subjects were recruited locally via advertisements placed around the Norwich Research Park. A total of 10 volunteers (nine female, one male) took part in the study, but not all volunteers completed each of the test meals. A highly enriched Cu-65 stable isotope label was administered to volunteers in the form of a reference dose or in breakfast test meals consisting of red wine, soya beans, mushrooms or sunflower seeds. Faecal monitoring and mass spectrometry techniques were used to estimate the relative quantities of copper absorbed from the different test meals. True copper absorption from the reference dose (54%) was similar to extrinsically labelled red wine (49%) and intrinsically labelled sunflower seeds (52%), but significantly higher than extrinsically labelled mushrooms (35%), intrinsically (29%) and extrinsically (15%) labelled soya beans and extrinsically labelled sunflower seed (32%) test meals. The use of Cu-65 extrinsic labels in copper absorption studies requires validation according to the food being examined; intrinsic and extrinsic labelling produced significantly different results for sunflower seeds.

Structure of the knowledge base for an expert labeling system

NASA Technical Reports Server (NTRS)

Rajaram, N. S.

1981-01-01

One of the principal objectives of the NASA AgRISTARS program is the inventory of global crop resources using remotely sensed data gathered by Land Satellites (LANDSAT). A central problem in any such crop inventory procedure is the interpretation of LANDSAT images and identification of parts of each image which are covered by a particular crop of interest. This task of labeling is largely a manual one done by trained human analysts and consequently presents obstacles to the development of totally automated crop inventory systems. However, development in knowledge engineering as well as widespread availability of inexpensive hardware and software for artificial intelligence work offers possibilities for developing expert systems for labeling of crops. Such a knowledge based approach to labeling is presented.

In Vivo Defection of Thrombi with Indium-111-Labeled Platelets

NASA Astrophysics Data System (ADS)

Price, David C.; Lipton, Martin J.; Lusby, Robert J.; Engelstad, Barry L.; Stoney, Ronald J.; Prager, Robert J.; Hartmeyer, James A.; Holly, Anne S.

1982-06-01

The use of Indium-111-oxine labeled autologous platelets has been explored in a dog-catheter model, as well as in a variety of clinical disorders in man. Newly forming experimental thrombi in dogs label well during the first 45-90 minutes, then lose both label and thrombus mass in a manner consistent with fibrinolysis. Thrombus weight is linearly related to In-111 activity, so that in vivo scintigraphy will be a practical method to evaluate various thrombotic stimuli and anti-thrombotic interventions experimentally. Preformed thrombus, however, labels poorly and cannot be detected by imaging in this dog model. Initial clinical experience with a variety of arterial, venous and cardiac thrombotic states is reviewed, indicating some of the strengths and same of the potential weaknesses of this new scintigraphic technique.

Magnetic Resonance Imaging of Chondrocytes Labeled with Superparamagnetic Iron Oxide Nanoparticles in Tissue-Engineered Cartilage

PubMed Central

Ramaswamy, Sharan; Greco, Jane B.; Uluer, Mehmet C.; Zhang, Zijun; Zhang, Zhuoli; Fishbein, Kenneth W.

2009-01-01

The distribution of cells within tissue-engineered constructs is difficult to study through nondestructive means, such as would be required after implantation. However, cell labeling with iron-containing particles may prove to be a useful approach to this problem, because regions containing such labeled cells have been shown to be readily detectable using magnetic resonance imaging (MRI). In this study, we used the Food and Drug Administration–approved superparamagnetic iron oxide (SPIO) contrast agent Feridex in combination with transfection agents to label chondrocytes and visualize them with MRI in two different tissue-engineered cartilage constructs. Correspondence between labeled cell spatial location as determined using MRI and histology was established. The SPIO-labeling process was found not to affect the phenotype or viability of the chondrocytes or the production of major cartilage matrix constituents. We believe that this method of visualizing and tracking chondrocytes may be useful in the further development of tissue engineered cartilage therapeutics. PMID:19788362

Probing Protein Structure by Amino Acid-Specific Covalent Labeling and Mass Spectrometry

PubMed Central

Mendoza, Vanessa Leah; Vachet, Richard W.

2009-01-01

For many years, amino acid-specific covalent labeling has been a valuable tool to study protein structure and protein interactions, especially for systems that are difficult to study by other means. These covalent labeling methods typically map protein structure and interactions by measuring the differential reactivity of amino acid side chains. The reactivity of amino acids in proteins generally depends on the accessibility of the side chain to the reagent, the inherent reactivity of the label and the reactivity of the amino acid side chain. Peptide mass mapping with ESI- or MALDI-MS and peptide sequencing with tandem MS are typically employed to identify modification sites to provide site-specific structural information. In this review, we describe the reagents that are most commonly used in these residue-specific modification reactions, details about the proper use of these covalent labeling reagents, and information about the specific biochemical problems that have been addressed with covalent labeling strategies. PMID:19016300

Combining multi-atlas segmentation with brain surface estimation

NASA Astrophysics Data System (ADS)

Huo, Yuankai; Carass, Aaron; Resnick, Susan M.; Pham, Dzung L.; Prince, Jerry L.; Landman, Bennett A.

2016-03-01

Whole brain segmentation (with comprehensive cortical and subcortical labels) and cortical surface reconstruction are two essential techniques for investigating the human brain. The two tasks are typically conducted independently, however, which leads to spatial inconsistencies and hinders further integrated cortical analyses. To obtain self-consistent whole brain segmentations and surfaces, FreeSurfer segregates the subcortical and cortical segmentations before and after the cortical surface reconstruction. However, this "segmentation to surface to parcellation" strategy has shown limitation in various situations. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. To our knowledge, this is the first work that achieves the reliability of state-of-the-art multi-atlas segmentation and labeling methods together with accurate and consistent cortical surface reconstruction. Compared with previous methods, MaCRUISE has three features: (1) MaCRUISE obtains 132 cortical/subcortical labels simultaneously from a single multi-atlas segmentation before reconstructing volume consistent surfaces; (2) Fuzzy tissue memberships are combined with multi-atlas segmentations to address partial volume effects; (3) MaCRUISE reconstructs topologically consistent cortical surfaces by using the sulci locations from multi-atlas segmentation. Two data sets, one consisting of five subjects with expertly traced landmarks and the other consisting of 100 volumes from elderly subjects are used for validation. Compared with CRUISE, MaCRUISE achieves self-consistent whole brain segmentation and cortical reconstruction without compromising on surface accuracy. MaCRUISE is comparably accurate to FreeSurfer while achieving greater robustness across an elderly population.

Combining Multi-atlas Segmentation with Brain Surface Estimation.

PubMed

Huo, Yuankai; Carass, Aaron; Resnick, Susan M; Pham, Dzung L; Prince, Jerry L; Landman, Bennett A

2016-02-27

Whole brain segmentation (with comprehensive cortical and subcortical labels) and cortical surface reconstruction are two essential techniques for investigating the human brain. The two tasks are typically conducted independently, however, which leads to spatial inconsistencies and hinders further integrated cortical analyses. To obtain self-consistent whole brain segmentations and surfaces, FreeSurfer segregates the subcortical and cortical segmentations before and after the cortical surface reconstruction. However, this "segmentation to surface to parcellation" strategy has shown limitations in various situations. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. To our knowledge, this is the first work that achieves the reliability of state-of-the-art multi-atlas segmentation and labeling methods together with accurate and consistent cortical surface reconstruction. Compared with previous methods, MaCRUISE has three features: (1) MaCRUISE obtains 132 cortical/subcortical labels simultaneously from a single multi-atlas segmentation before reconstructing volume consistent surfaces; (2) Fuzzy tissue memberships are combined with multi-atlas segmentations to address partial volume effects; (3) MaCRUISE reconstructs topologically consistent cortical surfaces by using the sulci locations from multi-atlas segmentation. Two data sets, one consisting of five subjects with expertly traced landmarks and the other consisting of 100 volumes from elderly subjects are used for validation. Compared with CRUISE, MaCRUISE achieves self-consistent whole brain segmentation and cortical reconstruction without compromising on surface accuracy. MaCRUISE is comparably accurate to FreeSurfer while achieving greater robustness across an elderly population.

Calorie Labeling, Fast Food Purchasing and Restaurant Visits

PubMed Central

Elbel, Brian; Mijanovich, Tod; Dixon, Beth; Abrams, Courtney; Weitzman, Beth; Kersh, Rogan; Auchincloss, Amy H.; Ogedegbe, Gbenga

2013-01-01

Objective Obesity is a pressing public health problem without proven population-wide solutions. Researchers sought to determine whether a city-mandated policy requiring calorie labeling at fast food restaurants was associated with consumer awareness of labels, calories purchased and fast food restaurant visits. Design and Methods Difference-in-differences design, with data collected from consumers outside fast food restaurants and via a random digit dial telephone survey, before (December 2009) and after (June 2010) labeling in Philadelphia (which implemented mandatory labeling) and Baltimore (matched comparison city). Measures included: self-reported use of calorie information, calories purchased determined via fast food receipts, and self-reported weekly fast-food visits. Results The consumer sample was predominantly Black (71%), and high school educated (62%). Post-labeling, 38% of Philadelphia consumers noticed the calorie labels for a 33 percentage point (p<.001) increase relative to Baltimore. Calories purchased and number of fast food visits did not change in either city over time. Conclusions While some consumer reports noticing and using calorie information, no population level changes were noted in calories purchased or fast food visits. Other controlled studies are needed to examine the longer term impact of labeling as it becomes national law. PMID:24136905

Alternative Programs for At-Risk Students: Wolves in Sheep's Clothing?

ERIC Educational Resources Information Center

Sagor, Richard

1997-01-01

Provides a critique of alternative education and details the disadvantages of segregated schooling. Discusses the problems associated with labeling children as "problem students" and outlines ways in which equitable alternative programs can be devised. Gives a case study as an example. (RJM)

Markers

ERIC Educational Resources Information Center

Healthy Schools Network, Inc., 2011

2011-01-01

Dry erase whiteboards come with toxic dry erase markers and toxic cleaning products. Dry erase markers labeled "nontoxic" are not free of toxic chemicals and can cause health problems. Children are especially vulnerable to environmental health hazards; moreover, schools commonly have problems with indoor air pollution, as they are more densely…

Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

PubMed

Xu, Zhoubing; Burke, Ryan P; Lee, Christopher P; Baucom, Rebeccah B; Poulose, Benjamin K; Abramson, Richard G; Landman, Bennett A

2015-08-01

Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially robust solution by leveraging label atlases via image registration and statistical fusion. We posit that the efficiency of atlas selection requires further exploration in the context of substantial registration errors. The selective and iterative method for performance level estimation (SIMPLE) method is a MAS technique integrating atlas selection and label fusion that has proven effective for prostate radiotherapy planning. Herein, we revisit atlas selection and fusion techniques for segmenting 12 abdominal structures using clinically acquired CT. Using a re-derived SIMPLE algorithm, we show that performance on multi-organ classification can be improved by accounting for exogenous information through Bayesian priors (so called context learning). These innovations are integrated with the joint label fusion (JLF) approach to reduce the impact of correlated errors among selected atlases for each organ, and a graph cut technique is used to regularize the combined segmentation. In a study of 100 subjects, the proposed method outperformed other comparable MAS approaches, including majority vote, SIMPLE, JLF, and the Wolz locally weighted vote technique. The proposed technique provides consistent improvement over state-of-the-art approaches (median improvement of 7.0% and 16.2% in DSC over JLF and Wolz, respectively) and moves toward efficient segmentation of large-scale clinically acquired CT data for biomarker screening, surgical navigation, and data mining. Copyright © 2015 Elsevier B.V. All rights reserved.

Chinese regulation of off-label use of drugs.

PubMed

Ma, Feng; Lou, Nan

2013-01-01

China has significant gaps and weaknesses in its regulatory oversight of the off-label use of drugs. As in the United States, the off-label prescribing of drugs is not prohibited in China if there is a sound scientific basis. Physicians are allowed to prescribe off-label drugs based on their medical judgment if they follow certain requirements. There is some constraint on the right to prescribe by the imposition of malpractice liability if patients are harmed from improper off-label prescribing. However, damages awarded to successful plaintiffs are usually insignificant compared to malpractice damage awards in the U.S. Advertisement of off-label use is prohibited in China. All drug advertisements in China are subject to pre-approval, and must be based on information included in the approved package insert. However, the term "advertisement" is poorly defined. As a result, non-advertisement promotion of drugs for on-label or off-label use exist in a unregulated gray area. To better address the problem of inappropriate off-label promotion and use, China should (i) regulate both drug advertisements and non-advertisement promotion under a standard requiring off-label use to have a sound scientific basis, (ii) introduce harsher regulatory penalties, and (iii) increase compensation available for victims of medical malpractice. Such reform would not only discourage improper off-label use by introducing penalties (or increasing existing penalties) for improper promotion, but would also provide reasonable compensation for victims harmed by off-label use.

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.

Management Observation Facility Fume Hoods

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

Sundsmo, V. A.

I reviewed all the hoods used for AS&I work in buildings 253, 254, and 255. All have had the minimum annual surveys conducted and some have had semi-annual reviews. The operating parameter labels are posted consistent to the right or above right (with the only exception the perchloric acid hood in 1734- on the left) which facilitates users knowing where to check for information. All hoods with sash doors (except the SE one in 1734 have a note on the Operating Parameters label to "keep sash doors closed". Again, this was checking consistency. No surveys were missed.

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.

Learning classification with auxiliary probabilistic information

PubMed Central

Nguyen, Quang; Valizadegan, Hamed; Hauskrecht, Milos

2012-01-01

Finding ways of incorporating auxiliary information or auxiliary data into the learning process has been the topic of active data mining and machine learning research in recent years. In this work we study and develop a new framework for classification learning problem in which, in addition to class labels, the learner is provided with an auxiliary (probabilistic) information that reflects how strong the expert feels about the class label. This approach can be extremely useful for many practical classification tasks that rely on subjective label assessment and where the cost of acquiring additional auxiliary information is negligible when compared to the cost of the example analysis and labelling. We develop classification algorithms capable of using the auxiliary information to make the learning process more efficient in terms of the sample complexity. We demonstrate the benefit of the approach on a number of synthetic and real world data sets by comparing it to the learning with class labels only. PMID:25309141

Extracting latent brain states--Towards true labels in cognitive neuroscience experiments.

PubMed

Porbadnigk, Anne K; Görnitz, Nico; Sannelli, Claudia; Binder, Alexander; Braun, Mikio; Kloft, Marius; Müller, Klaus-Robert

2015-10-15

Neuroscientific data is typically analyzed based on the behavioral response of the participant. However, the errors made may or may not be in line with the neural processing. In particular in experiments with time pressure or studies where the threshold of perception is measured, the error distribution deviates from uniformity due to the structure in the underlying experimental set-up. When we base our analysis on the behavioral labels as usually done, then we ignore this problem of systematic and structured (non-uniform) label noise and are likely to arrive at wrong conclusions in our data analysis. This paper contributes a remedy to this important scenario: we present a novel approach for a) measuring label noise and b) removing structured label noise. We demonstrate its usefulness for EEG data analysis using a standard d2 test for visual attention (N=20 participants). Copyright © 2015 Elsevier Inc. All rights reserved.

The Influence of Sugar-Sweetened Beverage Health Warning Labels on Parents' Choices.

PubMed

Roberto, Christina A; Wong, Diandra; Musicus, Aviva; Hammond, David

2016-02-01

US states have introduced bills requiring sugar-sweetened beverages (SSBs) to display health warning labels. This study examined how such labels may influence parents and which labels are most impactful. In this study, 2381 demographically and educationally diverse parents participated in an online survey. Parents were randomly assigned to 1 of 6 conditions: (1) no warning label (control); (2) calorie label; or (3-6) 1 of 4 text versions of a warning label (eg, Safety Warning: Drinking beverages with added sugar[s] contributes to obesity, diabetes, and tooth decay). Parents chose a beverage for their child in a vending machine choice task, rated perceptions of different beverages, and indicated interest in receiving beverage coupons. Regression analyses controlling for frequency of beverage purchases were used to compare the no warning label group, calorie label group, and all warning label groups combined. Significantly fewer parents chose an SSB for their child in the warning label condition (40%) versus the no label (60%) and calorie label conditions (53%). Parents in the warning label condition also chose significantly fewer SSB coupons, believed that SSBs were less healthy for their child, and were less likely to intend to purchase SSBs. All P values <.05 after correcting for multiple comparisons. There were no consistent differences among different versions of the warning labels. Health warning labels on SSBs improved parents' understanding of health harms associated with overconsumption of such beverages and may reduce parents' purchase of SSBs for their children. Copyright © 2016 by the American Academy of Pediatrics.

Porosity estimation by semi-supervised learning with sparsely available labeled samples

NASA Astrophysics Data System (ADS)

Lima, Luiz Alberto; Görnitz, Nico; Varella, Luiz Eduardo; Vellasco, Marley; Müller, Klaus-Robert; Nakajima, Shinichi

2017-09-01

This paper addresses the porosity estimation problem from seismic impedance volumes and porosity samples located in a small group of exploratory wells. Regression methods, trained on the impedance as inputs and the porosity as output labels, generally suffer from extremely expensive (and hence sparsely available) porosity samples. To optimally make use of the valuable porosity data, a semi-supervised machine learning method was proposed, Transductive Conditional Random Field Regression (TCRFR), showing good performance (Görnitz et al., 2017). TCRFR, however, still requires more labeled data than those usually available, which creates a gap when applying the method to the porosity estimation problem in realistic situations. In this paper, we aim to fill this gap by introducing two graph-based preprocessing techniques, which adapt the original TCRFR for extremely weakly supervised scenarios. Our new method outperforms the previous automatic estimation methods on synthetic data and provides a comparable result to the manual labored, time-consuming geostatistics approach on real data, proving its potential as a practical industrial tool.

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

Visweswara Sathanur, Arun; Choudhury, Sutanay; Joslyn, Cliff A.

Property graphs can be used to represent heterogeneous networks with attributed vertices and edges. Given one property graph, simulating another graph with same or greater size with identical statistical properties with respect to the attributes and connectivity is critical for privacy preservation and benchmarking purposes. In this work we tackle the problem of capturing the statistical dependence of the edge connectivity on the vertex labels and using the same distribution to regenerate property graphs of the same or expanded size in a scalable manner. However, accurate simulation becomes a challenge when the attributes do not completely explain the network structure.more » We propose the Property Graph Model (PGM) approach that uses an attribute (or label) augmentation strategy to mitigate the problem and preserve the graph connectivity as measured via degree distribution, vertex label distributions and edge connectivity. Our proposed algorithm is scalable with a linear complexity in the number of edges in the target graph. We illustrate the efficacy of the PGM approach in regenerating and expanding the datasets by leveraging two distinct illustrations.« less

Photosynthetic carbon metabolism in seagrasses C-labeling evidence for the c(3) pathway.

PubMed

Andrews, T J; Abel, K M

1979-04-01

The delta(13)C values of several seagrasses were considerably less negative than those of terrestrial C(3) plants and tended toward those of terrestrial C(4) plants. However, for Thalassia hemprichii (Ehrenb.) Aschers and Halophila spinulosa (R. Br.) Aschers, phosphoglycerate and other C(3) cycle intermediates predominated among the early labeled products of photosynthesis in (14)C-labeled seawater (more than 90% at the earliest times) and the labeling pattern at longer times was brought about by the operation of the C(3) pathway. Malate and aspartate together accounted for only a minor fraction of the total fixed label at all times and the kinetic data of this labeling were not at all consistent with these compounds being early intermediates in seagrass photosynthesis. Pulse-chase (14)C-labeling studies further substantiated these conclusions. Significant labeling of photorespiratory intermediates was observed in all experiments. The kinetics of total fixation of label during some steady-state and pulse-chase experiments suggested that there may be an intermediate pool of inorganic carbon of variable size closely associated with the leaves, either externally or internally. Such a pool may be one cause for the C(4)-like carbon isotope ratios of seagrasses.

MS lesion segmentation using a multi-channel patch-based approach with spatial consistency

NASA Astrophysics Data System (ADS)

Mechrez, Roey; Goldberger, Jacob; Greenspan, Hayit

2015-03-01

This paper presents an automatic method for segmentation of Multiple Sclerosis (MS) in Magnetic Resonance Images (MRI) of the brain. The approach is based on similarities between multi-channel patches (T1, T2 and FLAIR). An MS lesion patch database is built using training images for which the label maps are known. For each patch in the testing image, k similar patches are retrieved from the database. The matching labels for these k patches are then combined to produce an initial segmentation map for the test case. Finally a novel iterative patch-based label refinement process based on the initial segmentation map is performed to ensure spatial consistency of the detected lesions. A leave-one-out evaluation is done for each testing image in the MS lesion segmentation challenge of MICCAI 2008. Results are shown to compete with the state-of-the-art methods on the MICCAI 2008 challenge.

Structured light: theory and practice and practice and practice...

NASA Astrophysics Data System (ADS)

Keizer, Richard L.; Jun, Heesung; Dunn, Stanley M.

1991-04-01

We have developed a structured light system for noncontact 3-D measurement of human body surface areas and volumes. We illustrate the image processing steps and algorithms used to recover range data from a single camera image, reconstruct a complete surface from one or more sets of range data, and measure areas and volumes. The development of a working system required the solution to a number of practical problems in image processing and grid labeling (the stereo correspondence problem for structured light). In many instances we found that the standard cookbook techniques for image processing failed. This was due in part to the domain (human body), the restrictive assumptions of the models underlying the cookbook techniques, and the inability to consistently predict the outcome of the image processing operations. In this paper, we will discuss some of our successes and failures in two key steps in acquiring range data using structured light: First, the problem of detecting intersections in the structured light grid, and secondly, the problem of establishing correspondence between projected and detected intersections. We will outline the problems and solutions we have arrived at after several years of trial and error. We can now measure range data with an r.m.s. relative error of 0.3% and measure areas on the human body surface within 3% and volumes within 10%. We have found that the solution to building a working vision system requires the right combination of theory and experimental verification.

A life detection problem in a High Arctic microbial community

NASA Astrophysics Data System (ADS)

Rogers, J. D.; Perreault, N. N.; Niederberger, T. D.; Lichten, C.; Whyte, L. G.; Nadeau, J. L.

2010-03-01

Fluorescent labeling of bacterial cell walls, DNA, and metabolic processes demonstrates high (potentially single molecule) sensitivity, is non-invasive, and in some cases can differentiate strains and species. Robust microscopes such as the custom instruments presented here can provide good image quality in the field and are potentially suitable for flight. However, ambiguous or false-positive results with bacterial stains can occur and can create difficulties in interpretation even on Earth. We present a "real" life detection problem in a sample of biofilms taken from the Canadian High Arctic. The samples consisted of numerous small sulfur-oxidizing bacteria and larger structures resembling fungi or diatoms. The identity of these latter structures remained ambiguous until electron microscopy and X-ray spectroscopy were performed, indicating that they were unusual sulfur minerals probably precipitated by the bacterial communities. While such mineral structures may possibly serve as biosignatures after the cells have disappeared, it is important that they not be mistaken for cells themselves. It is also possible that unusual mineral structures will be performed under extraterrestrial conditions, so great care is needed to differentiate cell structures from minerals.

Human neutrophil kinetics: modeling of stable isotope labeling data supports short blood neutrophil half-lives.

PubMed

Lahoz-Beneytez, Julio; Elemans, Marjet; Zhang, Yan; Ahmed, Raya; Salam, Arafa; Block, Michael; Niederalt, Christoph; Asquith, Becca; Macallan, Derek

2016-06-30

Human neutrophils have traditionally been thought to have a short half-life in blood; estimates vary from 4 to 18 hours. This dogma was recently challenged by stable isotope labeling studies with heavy water, which yielded estimates in excess of 3 days. To investigate this disparity, we generated new stable isotope labeling data in healthy adult subjects using both heavy water (n = 4) and deuterium-labeled glucose (n = 9), a compound with more rapid labeling kinetics. To interpret results, we developed a novel mechanistic model and applied it to previously published (n = 5) and newly generated data. We initially constrained the ratio of the blood neutrophil pool to the marrow precursor pool (ratio = 0.26; from published values). Analysis of heavy water data sets yielded turnover rates consistent with a short blood half-life, but parameters, particularly marrow transit time, were poorly defined. Analysis of glucose-labeling data yielded more precise estimates of half-life (0.79 ± 0.25 days; 19 hours) and marrow transit time (5.80 ± 0.42 days). Substitution of this marrow transit time in the heavy water analysis gave a better-defined blood half-life of 0.77 ± 0.14 days (18.5 hours), close to glucose-derived values. Allowing the ratio of blood neutrophils to mitotic neutrophil precursors (R) to vary yielded a best-fit value of 0.19. Reanalysis of the previously published model and data also revealed the origin of their long estimates for neutrophil half-life: an implicit assumption that R is very large, which is physiologically untenable. We conclude that stable isotope labeling in healthy humans is consistent with a blood neutrophil half-life of less than 1 day. © 2016 by The American Society of Hematology.

2.5-Year-Olds Use Cross-Situational Consistency to Learn Verbs under Referential Uncertainty

ERIC Educational Resources Information Center

Scott, Rose M.; Fisher, Cynthia

2012-01-01

Recent evidence shows that children can use cross-situational statistics to learn new object labels under referential ambiguity (e.g., Smith & Yu, 2008). Such evidence has been interpreted as support for proposals that statistical information about word-referent co-occurrence plays a powerful role in word learning. But object labels represent only…

Rapid Fast-Mapping Abilities in 2-Year-Olds

ERIC Educational Resources Information Center

Spiegel, Chad; Halberda, Justin

2011-01-01

Learning a new word consists of two primary tasks that have often been conflated into a single process: "referent selection", in which a child must determine the correct referent of a novel label, and "referent retention", which is the ability to store this newly formed label-object mapping in memory for later use. In addition, children must be…

21 CFR 101.108 - Temporary exemptions for purposes of conducting authorized food labeling experiments.

Code of Federal Regulations, 2014 CFR

2014-04-01

... nutrition and other related food labeling information that is consistent with the current quantitative... effectiveness of the experiment; (7) The method for conveying to consumers the required nutrition and other... Management and Budget and assigned number 0910-0151. [48 FR 15240, Apr. 8, 1983, as amended at 59 FR 14364...

An Expert System Advisor for Medical Evaluation Boards

DTIC Science & Technology

1991-12-01

Condition OR REFERRAL=MedicalBoard_Slip !Condition AND PROBLEM=Spine_Scapulae.. Sacroiliac !Condition THEN ACTION=Refer-toMEB !Rule conclusion BECAUSE "In...Rule conclusion BECAUSE "In Accordance With The VA Schedule For Rating Disabilities" RULE N3 !Mandatory rule label IF Problem= Sacroiliac Joint

Generalised Assignment Matrix Methodology in Linear Programming

ERIC Educational Resources Information Center

Jerome, Lawrence

2012-01-01

Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…

Special Needs Education: A Case of Name Calling?

ERIC Educational Resources Information Center

American Vocational Journal, 1975

1975-01-01

Negative labelling harms by lumping together students with diverse learning problems; instead of diagnosing and treating their problems scientifically, students are stereotyped and relegated to watered down curricula and poor instruction, says one speaker. Other reports on vocational education's response to students special needs are briefly…

The development of measures of organizational citizenship behaviour and changes in job behaviours related to quality management in health care.

PubMed

Irvine, D

1995-08-01

A study was conducted at two tertiary care hospitals in Canada for the purpose of developing instruments to measure organizational citizenship behaviours (OCB) and changes in job behaviours that occur as a result of participation on hospital quality improvement (CQI) teams. Semi structured interviews were conducted among 52 hospital employees in order to elicit critical incidents of OCB and changes in job behaviours related to CQI. The results of the staff interviews were used to develop a measure of OCB in the hospital setting, and a measure of changes in job behaviours related to CQI. 39 employees, who were drawn from the major departments within the two hospitals on the basis of their membership on CQI teams, participated in a test of the psychometric properties of the two research instruments. Exploratory factor analysis, employing an orthogonal rotation, yielded two factors that accounted for 30% of the variation among the OCB items. The Cronbach alpha for items loading highly on the first factor was .88. The factor was labelled 'OCB directed towards individuals within the organization'. This factor was dominated by items reflecting the kinds of extra-role job behaviours employees engage in to assist patients, family members, visitors, and other employees within the organization. The Cronbach alpha for items loading highly on the second factor was 0.71. The second factor was labelled 'organizationally directed OCB', and consisted of behaviours that reflected an impersonal form of OCB in the hospital setting. Factor analysis, employing an orthogonal rotation, yielded four factors that accounted for 48% of the variation among the items measuring changes in job behaviours related to CQI. The four factors were labelled 'problem-solving', Cronbach alpha 0.82; 'customer awareness', Cronbach alpha 0.79; 'use of CQI knowledge', Cronbach alpha 0.77; and 'organizational interests', Cronbach alpha 0.79. The two OCB factors were moderately correlated, there were no significant correlations among any of the factors measuring changes in job behaviours related to CQI, and the problem-solving job behaviours factor was moderately correlated with the two OCB factors. Directions for future research are discussed.

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.

Studies on propagation of microbes in the airborne state

NASA Technical Reports Server (NTRS)

Dimmick, R. L.; Wolochow, H.; Straat, P.; Chatigny, M. A.

1974-01-01

An investigation was conducted to demonstrate whether airborne microbes could propagate. The procedure consisted of: (1) looking for dilution of a labelled base in DNA; (2) looking for labelling of DNA by mixing aerosols of the label and the cells; (3) examining changes in cell size; (4) testing the possibility of spore germination; and (5) seeking evidence of an increase in cell number. Results indicate that growth and propagation can occur under special conditions, principally at temperatures of approximately 30 C (87 F) and water activity equivalents of 0.95 to 0.98.

Nicotinamide Cofactors Suppress Active-Site Labeling of Aldehyde Dehydrogenases.

PubMed

Stiti, Naim; Chandrasekar, Balakumaran; Strubl, Laura; Mohammed, Shabaz; Bartels, Dorothea; van der Hoorn, Renier A L

2016-06-17

Active site labeling by (re)activity-based probes is a powerful chemical proteomic tool to globally map active sites in native proteomes without using substrates. Active site labeling is usually taken as a readout for the active state of the enzyme because labeling reflects the availability and reactivity of active sites, which are hallmarks for enzyme activities. Here, we show that this relationship holds tightly, but we also reveal an important exception to this rule. Labeling of Arabidopsis ALDH3H1 with a chloroacetamide probe occurs at the catalytic Cys, and labeling is suppressed upon nitrosylation and oxidation, and upon treatment with other Cys modifiers. These experiments display a consistent and strong correlation between active site labeling and enzymatic activity. Surprisingly, however, labeling is suppressed by the cofactor NAD(+), and this property is shared with other members of the ALDH superfamily and also detected for unrelated GAPDH enzymes with an unrelated hydantoin-based probe in crude extracts of plant cell cultures. Suppression requires cofactor binding to its binding pocket. Labeling is also suppressed by ALDH modulators that bind at the substrate entrance tunnel, confirming that labeling occurs through the substrate-binding cavity. Our data indicate that cofactor binding adjusts the catalytic Cys into a conformation that reduces the reactivity toward chloroacetamide probes.

Extrinsic labeling method may not accurately measure Fe absorption from cooked pinto beans (Phaseolus vulgaris): comparison of extrinsic and intrinsic labeling of beans.

PubMed

Jin, Fuxia; Cheng, Zhiqiang; Rutzke, Michael A; Welch, Ross M; Glahn, Raymond P

2008-08-27

Isotopic labeling of food has been widely used for the measurement of Fe absorption in determining requirements and evaluating the factors involved in Fe bioavailability. An extrinsic labeling technique will not accurately predict the total Fe absorption from foods unless complete isotopic exchange takes place between an extrinsically added isotope label and the intrinsic Fe of the food. We examined isotopic exchange in the case of both white beans and colored beans (Phaseolus vulgaris) with an in vitro digestion model. There are significant differences in (58)Fe/(56)Fe ratios between the sample digest supernatant and the pellet of extrinsically labeled pinto bean. The white bean digest shows significantly better equilibration of the extrinsic (58)Fe with the intrinsic (56)Fe. In contrast to the extrinsically labeled samples, both white and red beans labeled intrinsically with (58)Fe demonstrated consistent ratios of (58)Fe/(56)Fe in the bean meal, digest, supernatant, and pellet. It is possible that the polyphenolics in the bean seed coat may bind Fe and thus interfere with extrinsic labeling of the bean meals. These observations raise questions on the accuracy of studies that used extrinsic tags to measure Fe absorption from beans. Intrinsic labeling appears necessary to accurately measure Fe bioavailability from beans.

Classifying with confidence from incomplete information.

DOE PAGES

Parrish, Nathan; Anderson, Hyrum S.; Gupta, Maya R.; ...

2013-12-01

For this paper, we consider the problem of classifying a test sample given incomplete information. This problem arises naturally when data about a test sample is collected over time, or when costs must be incurred to compute the classification features. For example, in a distributed sensor network only a fraction of the sensors may have reported measurements at a certain time, and additional time, power, and bandwidth is needed to collect the complete data to classify. A practical goal is to assign a class label as soon as enough data is available to make a good decision. We formalize thismore » goal through the notion of reliability—the probability that a label assigned given incomplete data would be the same as the label assigned given the complete data, and we propose a method to classify incomplete data only if some reliability threshold is met. Our approach models the complete data as a random variable whose distribution is dependent on the current incomplete data and the (complete) training data. The method differs from standard imputation strategies in that our focus is on determining the reliability of the classification decision, rather than just the class label. We show that the method provides useful reliability estimates of the correctness of the imputed class labels on a set of experiments on time-series data sets, where the goal is to classify the time-series as early as possible while still guaranteeing that the reliability threshold is met.« less

From Web Directories to Ontologies: Natural Language Processing Challenges

NASA Astrophysics Data System (ADS)

Zaihrayeu, Ilya; Sun, Lei; Giunchiglia, Fausto; Pan, Wei; Ju, Qi; Chi, Mingmin; Huang, Xuanjing

Hierarchical classifications are used pervasively by humans as a means to organize their data and knowledge about the world. One of their main advantages is that natural language labels, used to describe their contents, are easily understood by human users. However, at the same time, this is also one of their main disadvantages as these same labels are ambiguous and very hard to be reasoned about by software agents. This fact creates an insuperable hindrance for classifications to being embedded in the Semantic Web infrastructure. This paper presents an approach to converting classifications into lightweight ontologies, and it makes the following contributions: (i) it identifies the main NLP problems related to the conversion process and shows how they are different from the classical problems of NLP; (ii) it proposes heuristic solutions to these problems, which are especially effective in this domain; and (iii) it evaluates the proposed solutions by testing them on DMoz data.

Quenched substrates for live-cell labeling of SNAP-tagged fusion proteins with improved fluorescent background.

PubMed

Stöhr, Katharina; Siegberg, Daniel; Ehrhard, Tanja; Lymperopoulos, Konstantinos; Öz, Simin; Schulmeister, Sonja; Pfeifer, Andrea C; Bachmann, Julie; Klingmüller, Ursula; Sourjik, Victor; Herten, Dirk-Peter

2010-10-01

Recent developments in fluorescence microscopy raise the demands for bright and photostable fluorescent tags for specific and background free labeling in living cells. Aside from fluorescent proteins and other tagging methods, labeling of SNAP-tagged proteins has become available thereby increasing the pool of potentially applicable fluorescent dyes for specific labeling of proteins. Here, we report on novel conjugates of benzylguanine (BG) which are quenched in their fluorescence and become highly fluorescent upon labeling of the SNAP-tag, the commercial variant of the human O(6)-alkylguanosyltransferase (hAGT). We identified four conjugates showing a strong increase, i.e., >10-fold, in fluorescence intensity upon labeling of SNAP-tag in vitro. Moreover, we screened a subset of nine BG-dye conjugates in living Escherichia coli and found them all suited for labeling of the SNAP-tag. Here, quenched BG-dye conjugates yield a higher specificity due to reduced contribution from excess conjugate to the fluorescence signal. We further extended the application of these conjugates by labeling a SNAP-tag fusion of the Tar chemoreceptor in live E. coli cells and the eukaryotic transcription factor STAT5b in NIH 3T3 mouse fibroblast cells. Aside from the labeling efficiency and specificity in living cells, we discuss possible mechanisms that might be responsible for the changes in fluorescence emission upon labeling of the SNAP-tag, as well as problems we encountered with nonspecific labeling with certain conjugates in eukaryotic cells.

Improved semi-supervised online boosting for object tracking

NASA Astrophysics Data System (ADS)

Li, Yicui; Qi, Lin; Tan, Shukun

2016-10-01

The advantage of an online semi-supervised boosting method which takes object tracking problem as a classification problem, is training a binary classifier from labeled and unlabeled examples. Appropriate object features are selected based on real time changes in the object. However, the online semi-supervised boosting method faces one key problem: The traditional self-training using the classification results to update the classifier itself, often leads to drifting or tracking failure, due to the accumulated error during each update of the tracker. To overcome the disadvantages of semi-supervised online boosting based on object tracking methods, the contribution of this paper is an improved online semi-supervised boosting method, in which the learning process is guided by positive (P) and negative (N) constraints, termed P-N constraints, which restrict the labeling of the unlabeled samples. First, we train the classification by an online semi-supervised boosting. Then, this classification is used to process the next frame. Finally, the classification is analyzed by the P-N constraints, which are used to verify if the labels of unlabeled data assigned by the classifier are in line with the assumptions made about positive and negative samples. The proposed algorithm can effectively improve the discriminative ability of the classifier and significantly alleviate the drifting problem in tracking applications. In the experiments, we demonstrate real-time tracking of our tracker on several challenging test sequences where our tracker outperforms other related on-line tracking methods and achieves promising tracking performance.

Deep Spatial-Temporal Joint Feature Representation for Video Object Detection.

PubMed

Zhao, Baojun; Zhao, Boya; Tang, Linbo; Han, Yuqi; Wang, Wenzheng

2018-03-04

With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection frameworks are mostly established on still images and only use the spatial information, which means that the feature consistency cannot be ensured because the training procedure loses temporal information. To address these problems, we propose a single, fully-convolutional neural network-based object detection framework that involves temporal information by using Siamese networks. In the training procedure, first, the prediction network combines the multiscale feature map to handle objects of various sizes. Second, we introduce a correlation loss by using the Siamese network, which provides neighboring frame features. This correlation loss represents object co-occurrences across time to aid the consistent feature generation. Since the correlation loss should use the information of the track ID and detection label, our video object detection network has been evaluated on the large-scale ImageNet VID dataset where it achieves a 69.5% mean average precision (mAP).

Facilitating Problem Solving in High School Chemistry.

ERIC Educational Resources Information Center

Gabel, Dorothy L.

The major purpose of this study was to determine whether certain types of instructional strategies (factor-label method, use of analogies, use of diagrams, and proportionality) were superior to others in teaching problem solving in four topics (mole concept, gas laws, stoichiometry, and molarity). Also of major interest was whether particular…

A proposal for new keypad design of electronic locks.

PubMed

Trayner, C

1993-10-01

Electronic locks, for which a password is entered on a computer-style keyboard, are described. Certain security problems associated with them are analysed. It is proposed that different labelling of the keyboard keys can reduce this problem. Theoretical figures are provided to support this claim and to aid design.

Talking Back at School: Using the Literacy Classroom as a Site for Resistance to the School-to-Prison Pipeline and Recognition of Students Labeled "At-Risk"

ERIC Educational Resources Information Center

Martin, Jennifer L.; Beese, Jane A.

2017-01-01

Teaching writing to students of high need in an urban school is simultaneously pedagogical, curricular, and political. Students labeled "at-risk" for school failure often have lowered expectations placed upon them from without that impact how they feel within. Compounding this problem of perception is the real issue of heightened…

Positron emitting nuclides and their synthetic incorporation in radiopharmaceuticals. [Labeled with /sup 11/C, /sup 13/N, and /sup 18/F

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

Fowler, J.S.

/sup 11/C, /sup 13/N, and /sup 15/O has potential applicability to the study of metabolism in humans. Problems in the synthesis of radiopharmaceuticals labeled with /sup 11/C, /sup 13/N, and /sup 18/F are described: quality control, radiation exposure, carboxylic acids, glucose, amines, amino acids, nitrosources, fluoroethanol. 54 references. (DLC)

Reducing Labeling Effort for Structured Prediction Tasks

DTIC Science & Technology

2005-01-01

correctly annotated for the instance to be of use to the learner. Traditional active learning addresses this problem by optimizing the order in which the...than for others. We propose a new active learning paradigm which reduces not only how many instances the annotator must label, but also how difficult...We validate this active learning framework in an interactive information extraction system, reducing the total number of annotation actions by 22%.

Active Learning Strategies for Phenotypic Profiling of High-Content Screens.

PubMed

Smith, Kevin; Horvath, Peter

2014-06-01

High-content screening is a powerful method to discover new drugs and carry out basic biological research. Increasingly, high-content screens have come to rely on supervised machine learning (SML) to perform automatic phenotypic classification as an essential step of the analysis. However, this comes at a cost, namely, the labeled examples required to train the predictive model. Classification performance increases with the number of labeled examples, and because labeling examples demands time from an expert, the training process represents a significant time investment. Active learning strategies attempt to overcome this bottleneck by presenting the most relevant examples to the annotator, thereby achieving high accuracy while minimizing the cost of obtaining labeled data. In this article, we investigate the impact of active learning on single-cell-based phenotype recognition, using data from three large-scale RNA interference high-content screens representing diverse phenotypic profiling problems. We consider several combinations of active learning strategies and popular SML methods. Our results show that active learning significantly reduces the time cost and can be used to reveal the same phenotypic targets identified using SML. We also identify combinations of active learning strategies and SML methods which perform better than others on the phenotypic profiling problems we studied. © 2014 Society for Laboratory Automation and Screening.

Semi-supervised learning for ordinal Kernel Discriminant Analysis.

PubMed

Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

2016-12-01

Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

Normalization of relative and incomplete temporal expressions in clinical narratives.

PubMed

Sun, Weiyi; Rumshisky, Anna; Uzuner, Ozlem

2015-09-01

To improve the normalization of relative and incomplete temporal expressions (RI-TIMEXes) in clinical narratives. We analyzed the RI-TIMEXes in temporally annotated corpora and propose two hypotheses regarding the normalization of RI-TIMEXes in the clinical narrative domain: the anchor point hypothesis and the anchor relation hypothesis. We annotated the RI-TIMEXes in three corpora to study the characteristics of RI-TMEXes in different domains. This informed the design of our RI-TIMEX normalization system for the clinical domain, which consists of an anchor point classifier, an anchor relation classifier, and a rule-based RI-TIMEX text span parser. We experimented with different feature sets and performed an error analysis for each system component. The annotation confirmed the hypotheses that we can simplify the RI-TIMEXes normalization task using two multi-label classifiers. Our system achieves anchor point classification, anchor relation classification, and rule-based parsing accuracy of 74.68%, 87.71%, and 57.2% (82.09% under relaxed matching criteria), respectively, on the held-out test set of the 2012 i2b2 temporal relation challenge. Experiments with feature sets reveal some interesting findings, such as: the verbal tense feature does not inform the anchor relation classification in clinical narratives as much as the tokens near the RI-TIMEX. Error analysis showed that underrepresented anchor point and anchor relation classes are difficult to detect. We formulate the RI-TIMEX normalization problem as a pair of multi-label classification problems. Considering only RI-TIMEX extraction and normalization, the system achieves statistically significant improvement over the RI-TIMEX results of the best systems in the 2012 i2b2 challenge. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Measuring the labeling efficiency of pseudocontinuous arterial spin labeling.

PubMed

Chen, Zhensen; Zhang, Xingxing; Yuan, Chun; Zhao, Xihai; van Osch, Matthias J P

2017-05-01

Optimization and validation of a sequence for measuring the labeling efficiency of pseudocontinuous arterial spin labeling (pCASL) perfusion MRI. The proposed sequence consists of a labeling module and a single slice Look-Locker echo planar imaging readout. A model-based algorithm was used to calculate labeling efficiency from the signal acquired from the main brain-feeding arteries. Stability of the labeling efficiency measurement was evaluated with regard to the use of cardiac triggering, flow compensation and vein signal suppression. Accuracy of the measurement was assessed by comparing the measured labeling efficiency to mean brain pCASL signal intensity over a wide range of flip angles as applied in the pCASL labeling. Simulations show that the proposed algorithm can effectively calculate labeling efficiency when correcting for T1 relaxation of the blood spins. Use of cardiac triggering and vein signal suppression improved stability of the labeling efficiency measurement, while flow compensation resulted in little improvement. The measured labeling efficiency was found to be linearly (R = 0.973; P < 0.001) related to brain pCASL signal intensity over a wide range of pCASL flip angles. The optimized labeling efficiency sequence provides robust artery-specific labeling efficiency measurement within a short acquisition time (∼30 s), thereby enabling improved accuracy of pCASL CBF quantification. Magn Reson Med 77:1841-1852, 2017. © 2016 International Society for Magnetic Resonance in Medicine Magn Reson Med 77:1841-1852, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Choline acetyltransferase expression during a putative developmental waiting period.

PubMed

Simmons, D D; Bertolotto, C; Kim, J; Raji-Kubba, J; Mansdorf, N

1998-07-27

The relationship between the cholinergic expression, morphological development, and target cell innervation of olivocochlear (OC) efferent neurons was investigated in the postnatal hamster. Similar to what was found in previous studies, tracer injections into the contralateral cochlea labeled cells bodies retrogradely in periolivary regions and labeled cell bodies only rarely in the lateral superior olive (LSO). Few morphological differences were found among cell bodies labeled between postnatal day 1 (P1) and P30. Tracer injections into the crossed OC bundles within the brainstem anterogradely labeled terminals below the inner hair cells of the cochlea prior to P5 and labeled terminals below outer hair cells after P5, consistent with a period of transient innervation, as hypothesized previously. Within the superior olive, choline acetyltransferase (ChAT) was expressed differentially. In periolivary regions, ChAT was expressed as early as P0. ChAT-immunoreactive cell bodies in periolivary regions were similar morphologically to retrogradely labeled OC neurons. In contrast, within the LSO, ChAT was not expressed until after P2. Consistent with a medical OC projection to the cochlea at early postnatal ages, ChAT immunoreactivity was detected below inner hair cells as early as P2 but was not detected below outer hair cells until after P6. Our results suggest that medial OC neurons not only provide transient connections to inner hair cells but also may express ChAT when they are below inner hair cells. Furthermore, these results raise the possibility that OC neurons may be capable of acetylcholine synthesis and release prior to or simultaneous with their innervation of the cochlea.

Developing ratings for food products: lessons learned from media rating systems.

PubMed

Kunkel, Dale; McKinley, Christopher

2007-01-01

Children regularly consume low-nutrient, high-calorie food that is not consistent with a healthful diet, contributing to an increasing epidemic of overweight and obesity. Among the multiple causes of this problem is the food industry's emphasis on marketing calorie-dense food products to children. The Institute of Medicine (IOM) has recommended that industry adopt a uniform system of simplified food ratings to convey the nutritional qualities of food in a manner that is understandable and appealing to children and youth. This report analyzes the need for such a system in a food marketing environment that increasingly identifies healthful products for the consumer in inconsistent fashion. It considers evidence regarding current usage of food labeling and draws parallels with media rating systems in discussing the prospects for a uniform food rating system that would accomplish the IOM's objective.

"Can I Believe My Eyes?" Three- to Six-Year-Olds' Willingness to Accept Contradictory Trait Labels

ERIC Educational Resources Information Center

Lapan, Candace; Boseovski, Janet J.; Blincoe, Sarai

2016-01-01

Children base trait inferences about people on direct observations of behavior. In some situations, these inferences might conflict with information supplied by others. This study examined 3- to 6-year-olds' willingness to change their own trait attributions about an actor after receiving a consistent or inconsistent trait label from an authority…

Measuring and modeling C flux rates through the central metabolic pathways in microbial communities using position-specific 13C-labeled tracers

NASA Astrophysics Data System (ADS)

Dijkstra, P.; van Groenigen, K.; Hagerty, S.; Salpas, E.; Fairbanks, D. E.; Hungate, B. A.; KOCH, G. W.; Schwartz, E.

2012-12-01

The production of energy and metabolic precursors occurs in well-known processes such as glycolysis and Krebs cycle. We use position-specific 13C-labeled metabolic tracers, combined with models of microbial metabolic organization, to analyze the response of microbial community energy production, biosynthesis, and C use efficiency (CUE) in soils, decomposing litter, and aquatic communities. The method consists of adding position-specific 13C -labeled metabolic tracers to parallel soil incubations, in this case 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose. The measurement of CO2 released from the labeled tracers is used to calculate the C flux rates through the various metabolic pathways. A simplified metabolic model consisting of 23 reactions is solved using results of the metabolic tracer experiments and assumptions of microbial precursor demand. This new method enables direct estimation of fundamental aspects of microbial energy production, CUE, and soil organic matter formation in relatively undisturbed microbial communities. We will present results showing the range of metabolic patterns observed in these communities and discuss results from testing metabolic models.

Calorie labeling, fast food purchasing and restaurant visits.

PubMed

Elbel, Brian; Mijanovich, Tod; Dixon, L Beth; Abrams, Courtney; Weitzman, Beth; Kersh, Rogan; Auchincloss, Amy H; Ogedegbe, Gbenga

2013-11-01

Obesity is a pressing public health problem without proven population-wide solutions. Researchers sought to determine whether a city-mandated policy requiring calorie labeling at fast food restaurants was associated with consumer awareness of labels, calories purchased and fast food restaurant visits. Difference-in-differences design, with data collected from consumers outside fast food restaurants and via a random digit dial telephone survey, before (December 2009) and after (June 2010) labeling in Philadelphia (which implemented mandatory labeling) and Baltimore (matched comparison city). Measures included: self-reported use of calorie information, calories purchased determined via fast food receipts, and self-reported weekly fast-food visits. The consumer sample was predominantly Black (71%), and high school educated (62%). Postlabeling, 38% of Philadelphia consumers noticed the calorie labels for a 33% point (P < 0.001) increase relative to Baltimore. Calories purchased and number of fast food visits did not change in either city over time. While some consumers report noticing and using calorie information, no population level changes were noted in calories purchased or fast food visits. Other controlled studies are needed to examine the longer term impact of labeling as it becomes national law. Copyright © 2013 The Obesity Society.

Genetically Modified Food Labeling in China: In Pursuit of a Rational Path.

PubMed

Zhu, Xiao; Roberts, Michael T; Wu, Kaijie

2016-08-01

Facing a tension between the increasing use of genetically engineered or modified food and consumer concerns over the risks associated with GMOs, China has established a GM food labeling regime through regulations-known as Agro-GMO regulations-to protect consumers' right to know. However, the design and enforcement of this GM food labeling regime is problematic. As a result, the labeling regime is ineffective and inconsistent, leaving consumers' rights unprotected. As the recently amended Food Safety Law in China requires GM food labeling for the first time, this article argues that China should replace the current Agro-GMO food labeling scheme with a special regulatory scheme. A comparative analysis of the GM food labeling systems in the European Union and United States, coupled with a rigorous examination of the problems and barriers of GM food labeling in China, sets a solid foundation by which to propose changes to incorporate into a special regulatory scheme. To this end, this article engages in such an analysis and recommends practical steps to guide the enactment of a special regulatory scheme. The recommendations comport with China's unique legal and political culture, but also could be used by other national regulatory regimes who permit use of GM food while also being committed to improving consumers' right to know.

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.

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.

Testing of Candidate Icons to Identify Acetaminophen-Containing Medicines

PubMed Central

Shiffman, Saul; Cotton, Helene; Jessurun, Christina; Sembower, Mark A.; Pype, Steve; Phillips, Jerry

2016-01-01

Adding icons on labels of acetaminophen-containing medicines could help users identify the active ingredient and avoid concomitant use of multiple medicines containing acetaminophen. We evaluated five icons for communication effectiveness. Adults (n = 300) were randomized to view a prescription container label or over-the-counter labels with either one or two icons. Participants saw two icon candidates, and reported their interpretation; experts judged whether these reflected critical confusions that might cause harm. Participants rated how effectively each icon communicated key messages. Icons based on abbreviations of “acetaminophen” (“Ac”, “Ace”, “Acm”) were rated less confusing and more effective in communicating the active ingredient than icons based on “APAP” or an abstract symbol. Icons did not result in critical confusion when seen on a readable medicine label. Icon implementation on prescription labels was more effective at communicating the warning against concomitant use than implementation on over-the-counter (OTC) labels. Adding an icon to a second location on OTC labels did not consistently enhance this communication, but reduced rated effectiveness of acetaminophen ingredient communication among participants with limited health literacy. The abbreviation-based icons seem most suitable for labeling acetaminophen-containing medications to enable users to identify acetaminophen-containing products. PMID:28970383

Performance evaluations of hybrid modulation with different optical labels over PDQ in high bit-rate OLS network systems.

PubMed

Xu, M; Li, Y; Kang, T Z; Zhang, T S; Ji, J H; Yang, S W

2016-11-14

Two orthogonal modulation optical label switching(OLS) schemes, which are based on payload of polarization multiplexing-differential quadrature phase shift keying(POLMUX-DQPSK or PDQ) modulated with identifications of duobinary (DB) label and pulse position modulation(PPM) label, are researched in high bit-rate OLS network. The BER performance of hybrid modulation with payload and label signals are discussed and evaluated in theory and simulation. The theoretical BER expressions of PDQ, PDQ-DB and PDQ-PPM are given with analysis method of hybrid modulation encoding in different the bit-rate ratios of payload and label. Theoretical derivation results are shown that the payload of hybrid modulation has a certain gain of receiver sensitivity than payload without label. The sizes of payload BER gain obtained from hybrid modulation are related to the different types of label. The simulation results are consistent with that of theoretical conclusions. The extinction ratio (ER) conflicting between hybrid encoding of intensity and phase types can be compromised and optimized in OLS system of hybrid modulation. The BER analysis method of hybrid modulation encoding in OLS system can be applied to other n-ary hybrid modulation or combination modulation systems.

Microbial detection in microfluidic devices through dual staining of quantum dots-labeled immunoassay and RNA hybridization.

PubMed

Zhang, Qing; Zhu, Liang; Feng, Hanhua; Ang, Simon; Chau, Fook Siong; Liu, Wen-Tso

2006-01-18

This paper reported the development of a microfludic device for the rapid detection of viable and nonviable microbial cells through dual labeling by fluorescent in situ hybridization (FISH) and quantum dots (QDs)-labeled immunofluorescent assay (IFA). The coin sized device consists of a microchannel and filtering pillars (gap=1-2 microm) and was demonstrated to effectively trap and concentrate microbial cells (i.e. Giardia lamblia). After sample injection, FISH probe solution and QDs-labeled antibody solution were sequentially pumped into the device to accelerate the fluorescent labeling reactions at optimized flow rates (i.e. 1 and 20 microL/min, respectively). After 2 min washing for each assay, the whole process could be finished within 30 min, with minimum consumption of labeling reagents and superior fluorescent signal intensity. The choice of QDs 525 for IFA resulted in bright and stable fluorescent signal, with minimum interference with the Cy3 signal from FISH detection.

Physical activity levels from a meta-analysis of doubly labeled water studies for validating energy intake as measured by dietary assessment.

PubMed

Black, A E

1996-06-01

Studies using doubly labeled water have identified underreporting of food intake as a problem of dietary surveys. However, reported energy intakes may be evaluated by comparison with energy requirements expressed as multiples of the basal metabolic rate, and a formula for calculating the value below which reported intake cannot be either a valid measure of habitual intake or a true low intake obtained by chance is presented. The energy requirements of different age-sex groups needed for the comparison with energy intakes have been obtained from a meta-analysis of doubly labeled water data.

Synthesis of 14C-labeled perfluorooctanoic and perfluorodecanoic acids; Purification of perfluorodecanoic acid

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

Reich, I.L.; Reich, H.J.; Menahan, L.A.

1987-01-01

Perfluorooctanoic and -decanoic acids are representative of a series of perfluorinated acids that have been used for a variety of industrial purposes primarily due to their surfactant properties. The toxicity of these compounds is being investigated in a number of laboratories. 14C-labeled materials would be useful in these studies but are not commercially available. Johncock prepared unlabeled PFOA in low yield by carbonation of the unstable perfluoroheptyllithium at -90 degrees Centigrade. We anticipated several problems in applying this procedure to the synthesis of the 14C-labeled material. Johncock's procedure was run on a fairly large scale (10 mmol) with excess CO2.

Distribution of /sup 32/P in laboratory colonies of Solenopsis invicta (Hymenoptera: Formicidae) after feeding on labeled Heliothis zeal (Lepidoptera: Noctuidae) eggs: an explanation of discrepancies encountered in field predation experiments

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

Nuessly, G.S.; Sterling, W.L.

1986-12-01

Factors responsible for low recovery rates of radioactive Solenopsis invicta Buren following placement of /sup 32/P-labeled Heliothis zea (Boddie) eggs on cotton in field predation tests were investigated using laboratory colonies of the ants. S. invicta workers became radioactive while handling labeled eggs by rupturing the egg chorion or by picking up labeled substances present on the surface of eggs. Foragers that removed the eggs from the plants picked up significantly more of the label than did workers that were sampled from the colonies between 12 and 72 h after egg introduction. Percentage of workers that became labeled over timemore » was much lower with the solid live food than in other studies that used powdered food sources. Problems in finding labeled ants in the field may have been associated with low mean levels of /sup 32/P per ant, together with difficulty in locating and isolating labeled ants from the population. Results indicate that egg predation rates estimated from counts per minute per predator have high variability, and suggest fairly large errors in estimates of eggs consumed per ant. Use of recovery rates of labeled predators to improve estimation of predation rates is discussed.« less

Immunogold detection of glycoprotein antigens in sea urchin embryos.

PubMed

Benson, N C; Benson, S C; Wilt, F

1989-01-01

Four developmental stages of sea urchin embryos were labeled with colloidal gold in an attempt to elucidate the intracellular trafficking patterns within the cells that produce the glycoprotein matrix of the embryonic spicule. The primary mesenchyme cells (PMCs) form a syncytium and secrete an organic matrix on which calcium carbonate is laid down to form an endoskeletal spicule. The organic matrix has been isolated and characterized as glycoprotein consisting of four major bands. Polyclonal antibodies to these glycoproteins were used to label embryos from the mesenchyme blastula, early gastrula, late gastrula, and plutei stages of development. The label is concentrated in the Golgi complex and associated vesicles, in secretory vesicles, and in the organic matrix. The density of the labeling increases as development proceeds.

Label Identification from Statistical Tabulation (LIST) temporal extendability study. [North Dakota, South Dakota, and Minnesota

NASA Technical Reports Server (NTRS)

Dennis, T. B. (Principal Investigator)

1980-01-01

The author has identified the following significant results. The most apparent contributors to the problem of poor temporal extension of LIST are the drastic changes in the brightness keys and an inadequate set of AI responses in Phase 3. The brightness trajectories change drastically from Phase 3 to the transition year (TY). Removing brightness channels from the discriminant does not completely correct the lack of extendability. Removing brightness increases the accuracy of the extension from Phase 3 to TY from 57.7 percent to 64.18 percent. The removal of the Al keys increases accuracy to 65.76 percent. Although the latter increase appears insignificant when compared to the first, the removal of only the Al keys increased accuracy to 63.58 percent. Proper weighting of the responses explains 73.8 percent of the ground truth labels but only 56.7 percent of the Al labels. By contrast, the TY responses which were weighted to explain the TY ground truth labels fared equally well, explaining 73.6 percent of those labels and 87.1 percent of the Al labels.

A Cytidine Phosphoramidite with Protected Nitroxide Spin Label: Synthesis of a Full-Length TAR RNA and Investigation by In-Line Probing and EPR Spectroscopy.

PubMed

Weinrich, Timo; Jaumann, Eva A; Scheffer, Ute; Prisner, Thomas F; Göbel, Michael W

2018-04-20

EPR studies on RNA are complicated by three major obstacles related to the chemical nature of nitroxide spin labels: Decomposition while oligonucleotides are chemically synthesized, further decay during enzymatic strand ligation, and undetected changes in conformational equilibria due to the steric demand of the label. Herein possible solutions for all three problems are presented: A 2-nitrobenzyloxymethyl protective group for nitroxides that is stable under all conditions of chemical RNA synthesis and can be removed photochemically. By careful selection of ligation sites and splint oligonucleotides, high yields were achieved in the assembly of a full-length HIV-1 TAR RNA labeled with two protected nitroxide groups. PELDOR measurements on spin-labeled TAR in the absence and presence of arginine amide indicated arrest of interhelical motions on ligand binding. Finally, even minor changes in conformation due to the presence of spin labels are detected with high sensitivity by in-line probing. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Label Information Guided Graph Construction for Semi-Supervised Learning.

PubMed

Zhuang, Liansheng; Zhou, Zihan; Gao, Shenghua; Yin, Jingwen; Lin, Zhouchen; Ma, Yi

2017-09-01

In the literature, most existing graph-based semi-supervised learning methods only use the label information of observed samples in the label propagation stage, while ignoring such valuable information when learning the graph. In this paper, we argue that it is beneficial to consider the label information in the graph learning stage. Specifically, by enforcing the weight of edges between labeled samples of different classes to be zero, we explicitly incorporate the label information into the state-of-the-art graph learning methods, such as the low-rank representation (LRR), and propose a novel semi-supervised graph learning method called semi-supervised low-rank representation. This results in a convex optimization problem with linear constraints, which can be solved by the linearized alternating direction method. Though we take LRR as an example, our proposed method is in fact very general and can be applied to any self-representation graph learning methods. Experiment results on both synthetic and real data sets demonstrate that the proposed graph learning method can better capture the global geometric structure of the data, and therefore is more effective for semi-supervised learning tasks.

Examining Interpretations of Graphic Cigarette Warning Labels Among U.S. Youth and Adults.

PubMed

McQueen, Amy; Waters, Erika A; Kaphingst, Kimberly A; Caburnay, Charlene A; Sanders Thompson, Vetta L; Boyum, Sonia; Kreuter, Matthew W

2016-08-01

Few studies have examined how diverse populations interpret warning labels. This study examined interpretations of 9 graphic cigarette warning labels (image plus text) proposed by the U.S. Food and Drug Administration among a convenience sample of youth (ages 13-17) and adults (18+) across the United States. Participants (N = 1,571) completed a cross-sectional survey. Participants were asked to select 1 of 3 plausible interpretations (1 preferred vs. 2 alternative) created by the research team about the particular consequence of smoking addressed in each warning label. Participants also rated each label for novelty, counterarguing, perceived effectiveness, and harm. Smokers reported their thoughts of quitting, self-efficacy, and motivation to quit. Although at least 70% of the sample chose the preferred interpretation for 7 of 9 labels, only 13% of participants chose all 9 preferred interpretations. The odds of selecting the preferred interpretation were lower among African Americans, among those with less education, and for labels perceived as being more novel. Smokers reported greater counterarguing and less perceived effectiveness and harms than nonsmokers, but results were not consistent across all labels and interpretations. The alternative interpretations of cigarette warning labels were associated with lower perceived effectiveness and lower perceived harms of smoking, both of which are important for motivating quit attempts.

Facilitating problem solving in high school chemistry

NASA Astrophysics Data System (ADS)

Gabel, Dorothy L.; Sherwood, Robert D.

The major purpose for conducting this study was to determine whether certain instructional strategies were superior to others in teaching high school chemistry students problem solving. The effectiveness of four instructional strategies for teaching problem solving to students of various proportional reasoning ability, verbal and visual preference, and mathematics anxiety were compared in this aptitude by treatment interaction study. The strategies used were the factor-label method, analogies, diagrams, and proportionality. Six hundred and nine high school students in eight schools were randomly assigned to one of four teaching strategies within each classroom. Students used programmed booklets to study the mole concept, the gas laws, stoichiometry, and molarity. Problem-solving ability was measured by a series of immediate posttests, delayed posttests and the ACS-NSTA Examination in High School Chemistry. Results showed that mathematics anxiety is negatively correlated with science achievement and that problem solving is dependent on students' proportional reasoning ability. The factor-label method was found to be the most desirable method and proportionality the least desirable method for teaching the mole concept. However, the proportionality method was best for teaching the gas laws. Several second-order interactions were found to be significant when mathematics anxiety was one of the aptitudes involved.

Persistent problems with the Munchausen syndrome by proxy label.

PubMed

Pankratz, Loren

2006-01-01

After nearly 30 years of clinical and legal experience, the definition of Munchausen syndrome by proxy remains controversial. As a result, mothers who present the problems of their children in ways perceived as unusual or problematic have become entangled in legal battles that should have been resolved clinically. Re-labeling the disorder as Pediatric Condition Falsification misdirects the focus onto mistakes and misunderstandings while avoiding the more crucial issue of intentions. Experts have enflamed the fears of harm by confusing warning signs with diagnostic signs and by citing retrospective studies instead of the more optimistic outcome studies. Accused mothers need the support of multidisciplinary teams but are often forced into contentious struggles with legal professionals and child protection services.

The Cannon: A data-driven approach to Stellar Label Determination

NASA Astrophysics Data System (ADS)

Ness, M.; Hogg, David W.; Rix, H.-W.; Ho, Anna. Y. Q.; Zasowski, G.

2015-07-01

New spectroscopic surveys offer the promise of stellar parameters and abundances (“stellar labels”) for hundreds of thousands of stars; this poses a formidable spectral modeling challenge. In many cases, there is a subset of reference objects for which the stellar labels are known with high(er) fidelity. We take advantage of this with The Cannon, a new data-driven approach for determining stellar labels from spectroscopic data. The Cannon learns from the “known” labels of reference stars how the continuum-normalized spectra depend on these labels by fitting a flexible model at each wavelength; then, The Cannon uses this model to derive labels for the remaining survey stars. We illustrate The Cannon by training the model on only 542 stars in 19 clusters as reference objects, with {T}{eff}, {log} g, and [{Fe}/{{H}}] as the labels, and then applying it to the spectra of 55,000 stars from APOGEE DR10. The Cannon is very accurate. Its stellar labels compare well to the stars for which APOGEE pipeline (ASPCAP) labels are provided in DR10, with rms differences that are basically identical to the stated ASPCAP uncertainties. Beyond the reference labels, The Cannon makes no use of stellar models nor any line-list, but needs a set of reference objects that span label-space. The Cannon performs well at lower signal-to-noise, as it delivers comparably good labels even at one-ninth the APOGEE observing time. We discuss the limitations of The Cannon and its future potential, particularly, to bring different spectroscopic surveys onto a consistent scale of stellar labels.

HCG-. beta. -subunit radioimmunoassay: potential error in HCG measurement related to choice of labeled antigen. [/sup 125/I

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

Tyrey, L.; Hammond, C.B.

1976-05-15

Antiserum generated against the hormone-specific ..beta..-subunit of hCG was used with different labeled antigens to measure circulating hCG in patients having trophoblastic disease. When /sup 125/I-hCG..beta.. served as the labeled antigen, a small number of patient sera failed to show parallelism with the second IS-hCG reference and erroneous estimates of hormone concentrations were obtained. Replacement of the /sup 125/I-hCG..beta.. with labeled hCG corrected the nonparallelism exhibited by these samples. Inhibition curves obtained with purified hCG and hCG..beta.. suggested that both the nonparallelism and its correction with the change in labeled antigen would be consistent with the possibility that this assaymore » aberration may result from the presence of free hCG..beta.. in these sera. (auth)« less

The effectiveness of nutrition education and labeling in Dutch supermarkets.

PubMed

Steenhuis, Ingrid; van Assema, Patricia; van Breukelen, Gerard; Glanz, Karen

2004-01-01

Nutrition education and labeling may help consumers to eat less fat. The purpose of this study is to assess the effect of nutrition education with and without shelf labeling on reduced fat intake in Dutch supermarkets. The design consisted of a randomized, pretest-posttest, experimental control group design. In total, 2203 clients of 13 supermarkets were included in the sample. Total fat intake of clients and behavioral determinants of eating less fat were measured by a questionnaire. A mixed-effect regression model was used for the analysis. No significant effects were found for the educational intervention, alone or with the labeling, on total fat intake and the psychosocial determinants of eating less fat. Nutrition education and labeling of low-fat food products in supermarkets did not prove to be effective strategies. The fact that the supermarket is a highly competitive environment may have accounted for this lack of effect.

Classification & Labelling Inventory: role of ECHA and notification requirements.

PubMed

Schöning, Gabriele

2011-01-01

The CLP Regulation introduces the criteria of the UN Globally Harmonised System of Classification and Labelling (UN GHS) in the EU. The European Chemicals Agency (ECHA) manages the CLP related tasks - such as harmonised classification and labelling, handling requests for alternative names and maintaining the Classification & Labelling Inventory (C&L) - to ensure consistent implementation in the EU. The obligations for industry depend on their role in the supply chain. Manufacturers and importers have to notify to ECHA the identity and classification and labelling of substances within one month of placing them on the market either on their own or in a mixture, and regardless of the quantitity. As of 3 January 2011 ECHA has received some 3.1 million notifications of over 107 000 substances. This information is stored in the C&L Inventory and accessible to Member State Competent Authorities. The non-confidential information will be made publicly available on ECHA's website in 2011.

Cellular internalization of LiNbO3 nanocrystals for second harmonic imaging and the effects on stem cell differentiation

NASA Astrophysics Data System (ADS)

Li, Jianhua; Qiu, Jichuan; Guo, Weibo; Wang, Shu; Ma, Baojin; Mou, Xiaoning; Tanes, Michael; Jiang, Huaidong; Liu, Hong

2016-03-01

Second harmonic generation (SHG) nanocrystals have recently been reported to label cancer cells and other functional cell lines due to their unique double-frequency property. In this paper, we report for the first time the use of lithium niobate (LiNbO3, LN) nanocrystals as SHG labels for imaging stem cells. Rat mesenchymal stem cells (rMSCs) were labeled with LN nanocrystals in order to study the cellular internalization of the nanocrystals and the influence on stem cell differentiation. The results showed that LN nanocrystals were endocytosed by the rMSCs and the distribution of the internalized nanoparticles demonstrated a high consistency with the orientation of the actin filaments. Besides, LN-labeled rMSCs showed a concentration-dependent viability. Most importantly, rMSCs labeled with 50 μg per mL of LN nanocrystals retained their ability to differentiate into both osteogenic and adipogenic lineages. The results prove that LN nanocrystals can be used as a cytocompatible, near-infrared (NIR) light driven cell label for long-term imaging, without hindering stem cell differentiation. This work will promote the use of LN nanocrystals to broader applications like deep-tissue tracking, remote drug delivery and stem cell therapy.Second harmonic generation (SHG) nanocrystals have recently been reported to label cancer cells and other functional cell lines due to their unique double-frequency property. In this paper, we report for the first time the use of lithium niobate (LiNbO3, LN) nanocrystals as SHG labels for imaging stem cells. Rat mesenchymal stem cells (rMSCs) were labeled with LN nanocrystals in order to study the cellular internalization of the nanocrystals and the influence on stem cell differentiation. The results showed that LN nanocrystals were endocytosed by the rMSCs and the distribution of the internalized nanoparticles demonstrated a high consistency with the orientation of the actin filaments. Besides, LN-labeled rMSCs showed a concentration-dependent viability. Most importantly, rMSCs labeled with 50 μg per mL of LN nanocrystals retained their ability to differentiate into both osteogenic and adipogenic lineages. The results prove that LN nanocrystals can be used as a cytocompatible, near-infrared (NIR) light driven cell label for long-term imaging, without hindering stem cell differentiation. This work will promote the use of LN nanocrystals to broader applications like deep-tissue tracking, remote drug delivery and stem cell therapy. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00785f

Scintigraphic detection of occult hemorrhage using RBCs labeled in vitro with technetium Tc 99m sodium pertechnetate

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

Bunker, S.R.; Kolina, J.S.; Kaplan, K.A.

1983-05-01

Scintigraphy with RBCs labeled with technetium Tc 99m sodium pertechnetate effectively located the source of hemorrhage in a patient receiving long-term anticoagulant therapy. (The patient was initially seen with a large hematoma on the flank.) More important, the procedure was used to monitor activity in this otherwise-occult bleeding site. Scintigraphic studies may be useful in the management of these difficult clinical problems.

The Fetal Alcohol Syndrome Public Awareness Campaign, 1979: Progress Report Concerning the Advance Notice of Proposed Rulemaking on Warning Labels on Containers of Alcoholic Beverages and Addendum.

ERIC Educational Resources Information Center

Department of the Treasury, Washington, DC.

This report provides expert opinion on the problems of fetal alcohol syndrome (FAS) and ways to inform the public of teratogenic risk of alcohol consumption during pregnancy. In the absence of firm evidence that moderate drinking of alcoholic beverages leads to FAS and uncertainty concerning the effectiveness of labeling of alcoholic beverages, a…

Semantic labeling of digital photos by classification

NASA Astrophysics Data System (ADS)

Ciocca, Gianluigi; Cusano, Claudio; Schettini, Raimondo; Brambilla, Carla

2003-01-01

The paper addresses the problem of annotating photographs with broad semantic labels. To cope with the great variety of photos available on the WEB we have designed a hierarchical classification strategy which first classifies images as pornographic or not-pornographic. Not-pornographic images are then classified as indoor, outdoor, or close-up. On a database of over 9000 images, mostly downloaded from the web, our method achieves an average accuracy of close to 90%.

Injections of Algesic Solutions into Muscle Activate the Lateral Reticular Formation: A Nociceptive Relay of the Spinoreticulothalamic Tract

PubMed Central

Panneton, W. Michael; Gan, Qi; Ariel, Michael

2015-01-01

Although musculoskeletal pain disorders are common clinically, the central processing of muscle pain is little understood. The present study reports on central neurons activated by injections of algesic solutions into the gastrocnemius muscle of the rat, and their subsequent localization by c-Fos immunohistochemistry in the spinal cord and brainstem. An injection (300μl) of an algesic solution (6% hypertonic saline, pH 4.0 acetate buffer, or 0.05% capsaicin) was made into the gastrocnemius muscle and the distribution of immunolabeled neurons compared to that obtained after control injections of phosphate buffered saline [pH 7.0]. Most labeled neurons in the spinal cord were found in laminae IV-V, VI, VII and X, comparing favorably with other studies, with fewer labeled neurons in laminae I and II. This finding is consistent with the diffuse pain perception due to noxious stimuli to muscles mediated by sensory fibers to deep spinal neurons as compared to more restricted pain localization during noxious stimuli to skin mediated by sensory fibers to superficial laminae. Numerous neurons were immunolabeled in the brainstem, predominantly in the lateral reticular formation (LRF). Labeled neurons were found bilaterally in the caudalmost ventrolateral medulla, where neurons responsive to noxious stimulation of cutaneous and visceral structures lie. Immunolabeled neurons in the LRF continued rostrally and dorsally along the intermediate reticular nucleus in the medulla, including the subnucleus reticularis dorsalis caudally and the parvicellular reticular nucleus more rostrally, and through the pons medial and lateral to the motor trigeminal nucleus, including the subcoerulear network. Immunolabeled neurons, many of them catecholaminergic, were found bilaterally in the nucleus tractus solitarii, the gracile nucleus, the A1 area, the CVLM and RVLM, the superior salivatory nucleus, the nucleus locus coeruleus, the A5 area, and the nucleus raphe magnus in the pons. The external lateral and superior lateral subnuclei of the parabrachial nuclear complex were consistently labeled in experimental data, but they also were labeled in many control cases. The internal lateral subnucleus of the parabrachial complex was labeled moderately. Few immunolabeled neurons were found in the medial reticular formation, however, but the rostroventromedial medulla was labeled consistently. These data are discussed in terms of an interoceptive, multisynaptic spinoreticulothalamic path, with its large receptive fields and role in the motivational-affective components of pain perceptions. PMID:26154308

Injections of Algesic Solutions into Muscle Activate the Lateral Reticular Formation: A Nociceptive Relay of the Spinoreticulothalamic Tract.

PubMed

Panneton, W Michael; Gan, Qi; Ariel, Michael

2015-01-01

Although musculoskeletal pain disorders are common clinically, the central processing of muscle pain is little understood. The present study reports on central neurons activated by injections of algesic solutions into the gastrocnemius muscle of the rat, and their subsequent localization by c-Fos immunohistochemistry in the spinal cord and brainstem. An injection (300 μl) of an algesic solution (6% hypertonic saline, pH 4.0 acetate buffer, or 0.05% capsaicin) was made into the gastrocnemius muscle and the distribution of immunolabeled neurons compared to that obtained after control injections of phosphate buffered saline [pH 7.0]. Most labeled neurons in the spinal cord were found in laminae IV-V, VI, VII and X, comparing favorably with other studies, with fewer labeled neurons in laminae I and II. This finding is consistent with the diffuse pain perception due to noxious stimuli to muscles mediated by sensory fibers to deep spinal neurons as compared to more restricted pain localization during noxious stimuli to skin mediated by sensory fibers to superficial laminae. Numerous neurons were immunolabeled in the brainstem, predominantly in the lateral reticular formation (LRF). Labeled neurons were found bilaterally in the caudalmost ventrolateral medulla, where neurons responsive to noxious stimulation of cutaneous and visceral structures lie. Immunolabeled neurons in the LRF continued rostrally and dorsally along the intermediate reticular nucleus in the medulla, including the subnucleus reticularis dorsalis caudally and the parvicellular reticular nucleus more rostrally, and through the pons medial and lateral to the motor trigeminal nucleus, including the subcoerulear network. Immunolabeled neurons, many of them catecholaminergic, were found bilaterally in the nucleus tractus solitarii, the gracile nucleus, the A1 area, the CVLM and RVLM, the superior salivatory nucleus, the nucleus locus coeruleus, the A5 area, and the nucleus raphe magnus in the pons. The external lateral and superior lateral subnuclei of the parabrachial nuclear complex were consistently labeled in experimental data, but they also were labeled in many control cases. The internal lateral subnucleus of the parabrachial complex was labeled moderately. Few immunolabeled neurons were found in the medial reticular formation, however, but the rostroventromedial medulla was labeled consistently. These data are discussed in terms of an interoceptive, multisynaptic spinoreticulothalamic path, with its large receptive fields and role in the motivational-affective components of pain perceptions.

76 FR 63303 - Guidance for Industry on Warnings and Precautions, Contraindications, and Boxed Warning Sections...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-12

...The Food and Drug Administration (FDA) is announcing the availability of a guidance for industry entitled ``Warnings and Precautions, Contraindications, and Boxed Warning Sections of Labeling for Human Prescription Drug and Biological Products--Content and Format.'' This guidance is intended to assist applicants and reviewers in drafting the ``Warnings and Precautions, Contraindications, and Boxed Warning'' sections of labeling for human prescription drug and biological products. The recommendations in this guidance will help ensure that the labeling is clear, useful, informative, and to the extent possible, consistent in content and format.

Synthesis of labeled compounds using recovered tritium from expired beta light sources

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

Matei, L.; Postolache, C.; Bubueanu, G.

2008-07-15

In this paper, the technological procedures for extracting tritium from beta light source are highlighted. The recovered tritium was used in the synthesis of organically labeled compounds and in the preparation of tritiated water (HTO) with high specific activity. Technological procedures for treatment of beta light sources consist of: envelope breaking into evacuated enclosure, the radioactive gaseous mixture pumping and its storage on metallic sodium. The mixtures of T{sub 2} and {sup 3}He were used in the synthesis of tritium labeled steroid hormones, nucleosides analogues and for the preparation of HTO with high radioactivity concentrations. (authors)

Against the Rules: Procedural Problems in Institutional Self-Evaluation.

ERIC Educational Resources Information Center

Simons, Helen

This paper addresses the problem of how to introduce new forms of evaluation into school organization without a damaging loss of trust. The evaluators here are teachers engaged in curriculum policy evaluation within the schools in which they work. One way of conceptualizing and rooting contemporary activity under the label of school…

Psychological Problems in Mental Deficiency.

ERIC Educational Resources Information Center

Sarason, Seymour B.; Doris, John

A statement of goals and the rationale for organization precede a historical discussion of mental deficiency and society. The problem of labels like IQ and brain injured and the consequences of the diagnostic process are illustrated by case histories; case studies are also used to examine the criteria used to decide who is retarded and to discuss…

Bending Back on High School Programs for Youth with Learning Disabilities

ERIC Educational Resources Information Center

Edgar, Eugene

2005-01-01

In this opinion piece, the author views several major problems facing those who care about students labeled has having learning disabilities (LD). He believes that while there are technical problems that educators should be able to fix (definition of LD, best instructional practices for students so identified, powerful secondary programs that…

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.

Quantifying and predicting depression literacy of undergraduates: a cross sectional study in Sri Lanka.

PubMed

Amarasuriya, Santushi D; Jorm, Anthony F; Reavley, Nicola J

2015-10-30

The high rates of depression and low rates of related help-seeking among undergraduates are matters for concern. In response to the need to examine their knowledge about depression and its management, and the dearth of such research from non-western developing countries, this study examined the depression literacy of undergraduates in Sri Lanka. A questionnaire was administered among 4671 undergraduates to examine their depression literacy relating to problem-recognition, measured using a vignette of a depressed undergraduate, and their treatment beliefs measured by assessing their perceptions about the helpfulness of various options of help for the presented problem. Responses for the latter aspect were quantified using a scale comprising the options of help endorsed by Sri Lankan mental health professionals. Regression analysis models were used to identify the correlates of these aspects of depression literacy. Females, medical undergraduates and those in higher years of study (compared to first-years) were more likely to recognise the problem as depression. The undergraduates obtained a mean percentage score of 76% on the constructed Depression Treatment Beliefs Scale. Scores on this scale were higher among females, medical undergraduates, those who got help for the problem after trying to deal with it alone and those who recognised the problem as depression, as well as those who used other mental health-related labels for this purpose. Scores were lower among undergraduates in years 2-4 (compared to first-years), those with family or friends with the problem and those with higher stigma on a Social Distance Scale. However, the effect sizes of these relationships were small. As factors such as gender, discipline, year of study, exposure to depression and stigma are associated with differences in the depression literacy of these undergraduates, concerning their ability to recognise the problem and their related treatment beliefs, these must be considered when designing related educational initiatives. Recognising the problem as depression or the use of other mental health-related labels is associated with better treatment beliefs as per expert consensus, indicating that such labelling could have value for appropriate help-seeking.

The Restaurant Food Hot Potato: Stop Passing it on—A Commentary on Mah and Timming’s, ‘Equity in Public Health Ethics: The Case of Menu Labelling Policy at the Local Level’

PubMed Central

MacKay, Kathryn L.

2015-01-01

In the case discussion, ‘Equity in Public Health Ethics: The Case of Menu Labelling Policy at the Local Level’ (2014), Mah and Timming state that menu labelling would ‘place requirements for information disclosure on private sector food businesses, which, as a policy instrument, is arguably less intrusive than related activities such as requiring changes to the food content’. In this commentary on Mah and Timming’s case study, I focus on discussing how menu-labelling policy permits governments to avoid addressing the heart of the problem, which is high-calorie, high-sodium restaurant food. Menu labelling policy does not address food content in a way that is meaningful for change, instead relying on individuals to change their behaviour given new information. Besides having questionable efficacy, this raises concerns about moralizing food choices. PMID:25815060

[Off-label therapies in oncology].

PubMed

Telekes, András

2009-02-22

The unapproved (off-label) therapies represent a special problem in oncology since they are in the borderline of legal regulation and of free medical practice. Although in Hungary the off-label therapies were regarded as clinical trials without permission until the new regulation came into action at the end of October 2008, certain experts were even so arguing for its use because clinical practice changes more rapidly than the prescription label. Moreover, manufacturers are not obliged to submit Supplemental New Drug Application in spite of the fact that enough evidence is generated to do so. The regulation of off-label therapies should meet the conditions of free medical practice, evidence-based medicine, demand of patients for new chances and expectations of regulatory authorities. In this paper, following the criticism of the Hungarian status and the new regulation, as well as the review of international practice, the author outlines the frame of a potential regulation separately indicating the role of practicing physicians and authorities.

Multiple-Instance Regression with Structured Data

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran; Roper, Alex

2008-01-01

We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.

ACCELERATED FITTING OF STELLAR SPECTRA

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

Ting, Yuan-Sen; Conroy, Charlie; Rix, Hans-Walter

2016-07-20

Stellar spectra are often modeled and fitted by interpolating within a rectilinear grid of synthetic spectra to derive the stars’ labels: stellar parameters and elemental abundances. However, the number of synthetic spectra needed for a rectilinear grid grows exponentially with the label space dimensions, precluding the simultaneous and self-consistent fitting of more than a few elemental abundances. Shortcuts such as fitting subsets of labels separately can introduce unknown systematics and do not produce correct error covariances in the derived labels. In this paper we present a new approach—Convex Hull Adaptive Tessellation (chat)—which includes several new ideas for inexpensively generating amore » sufficient stellar synthetic library, using linear algebra and the concept of an adaptive, data-driven grid. A convex hull approximates the region where the data lie in the label space. A variety of tests with mock data sets demonstrate that chat can reduce the number of required synthetic model calculations by three orders of magnitude in an eight-dimensional label space. The reduction will be even larger for higher dimensional label spaces. In chat the computational effort increases only linearly with the number of labels that are fit simultaneously. Around each of these grid points in the label space an approximate synthetic spectrum can be generated through linear expansion using a set of “gradient spectra” that represent flux derivatives at every wavelength point with respect to all labels. These techniques provide new opportunities to fit the full stellar spectra from large surveys with 15–30 labels simultaneously.« less

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.

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.

Processing Social Information in Messages: Social Group Familiarity, Fiction/Non-fiction Labels, and Subsequent Beliefs.

ERIC Educational Resources Information Center

Slater, Michael D.

A study examined how the relative familiarity of a social group described in a message may affect the impact of ostensibly fiction and nonfiction messages on subsequent beliefs about social groups. The 24 paid subjects each received one of four sets of prose excerpts. Each set consisted of four excerpts that were labelled as fiction or nonfiction…

77 FR 58338 - Trade Regulation Rule on Care Labeling of Textile Wearing Apparel and Certain Piece Goods

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-20

... 423.6(a) and (b). \\2\\ 16 CFR 423.6(c). \\3\\ The Rule provides that the symbol system developed by ASTM..., that it is ``a system of cleaning by means of equipment consisting of a computer-controlled washer and... GINETEX (83), which is responsible for the care labeling system used in European countries. \\17\\ The...

Organic: What's in a name?

PubMed Central

Fisher, B E

1999-01-01

The organic foods industry is booming: by one estimate, the market for organic foods is worth $4 billion annually and is expected to grow at a rate of more than 24% per year. Faced with the threat of pesticide exposures and other food safety problems, many consumers are turning to organic foods in hopes of finding a healthy alternative, but there is currently no consistency in organic food labeling and no guarantee that foods labeled as organic are actually grown and processed in a purely organic fashion. There is also controversy about whether the label "organic" covers such new technologies as irradiation and genetic engineering. As part of the 1990 Farm Bill, the U.S. Department of Agriculture (USDA) is working to develop a proposed rule on organic foods. The rule would regulate the allowable methods, practices, and substances used in producing and handling crops and their processed products. The first draft of the proposed rule, released in December 1997, met with unprecedented opposition, which centered around the fact that the proposal appeared to virtually ignore the recommendations of a standards board formed to assist in the rule's development. Other criticism opposed three practices put forward for comment by the USDA: irradiation, genetic engineering, and the use of sewage sludge in farming. Due to the vehemence of the opposition to its original proposal, the USDA has decided to rewrite the proposed rule. In preparation for that proposal, the USDA Agricultural Marketing Service released three issue papers in October 1998 for public comment. The 10,000-plus comments received in response to those papers will be incorporated into the second draft proposal, due out later this year. PMID:10064558

Ultra-low dose naltrexone attenuates chronic morphine-induced gliosis in rats.

PubMed

Mattioli, Theresa-Alexandra M; Milne, Brian; Cahill, Catherine M

2010-04-16

The development of analgesic tolerance following chronic morphine administration can be a significant clinical problem. Preclinical studies demonstrate that chronic morphine administration induces spinal gliosis and that inhibition of gliosis prevents the development of analgesic tolerance to opioids. Many studies have also demonstrated that ultra-low doses of naltrexone inhibit the development of spinal morphine antinociceptive tolerance and clinical studies demonstrate that it has opioid sparing effects. In this study we demonstrate that ultra-low dose naltrexone attenuates glial activation, which may contribute to its effects on attenuating tolerance. Spinal cord sections from rats administered chronic morphine showed significantly increased immuno-labelling of astrocytes and microglia compared to saline controls, consistent with activation. 3-D images of astrocytes from animals administered chronic morphine had significantly larger volumes compared to saline controls. Co-injection of ultra-low dose naltrexone attenuated this increase in volume, but the mean volume differed from saline-treated and naltrexone-treated controls. Astrocyte and microglial immuno-labelling was attenuated in rats co-administered ultra-low dose naltrexone compared to morphine-treated rats and did not differ from controls. Glial activation, as characterized by immunohistochemical labelling and cell size, was positively correlated with the extent of tolerance developed. Morphine-induced glial activation was not due to cell proliferation as there was no difference observed in the total number of glial cells following chronic morphine treatment compared to controls. Furthermore, using 5-bromo-2-deoxyuridine, no increase in spinal cord cell proliferation was observed following chronic morphine administration. Taken together, we demonstrate a positive correlation between the prevention of analgesic tolerance and the inhibition of spinal gliosis by treatment with ultra-low dose naltrexone. This research provides further validation for using ultra-low dose opioid receptor antagonists in the treatment of various pain syndromes.

Terminological debate over language impairment in children: forward movement and sticking points

PubMed Central

Reilly, Sheena; Bishop, Dorothy V M; Tomblin, Bruce

2014-01-01

Background There is no agreed terminology for describing childhood language problems. In this special issue Reilly et al. and Bishop review the history of the most widely used label, ‘specific language impairment’ (SLI), and discuss the pros and cons of various terms. Commentators from a range of backgrounds, in terms of both discipline and geographical background, were then invited to respond to each lead article. Aims To summarize the main points made by the commentators and identify (1) points of consensus and disagreement, (2) issues for debate including the drivers for change and diagnostic criteria, and (3) the way forward. Conclusions & Implications There was some common ground, namely that the current situation is not tenable because it impedes clinical and research progress and impacts on access to services. There were also wide-ranging disagreements about which term should be adopted. However, before debating the broad diagnostic label it is essential to consider the diagnostic criteria and the systems used to classify childhood language problems. This is critical in order to facilitate communication between and among clinicians and researchers, across sectors (in particular health and education), with the media and policy-makers and with families and individuals who have language problems. We suggest four criteria be taken into account when establishing diagnostic criteria, including: (1) the features of language, (2) the impact on functioning and participation, (3) the presence/absence of other impairments, and (4) the language trajectory or pathway and age of onset. In future, these criteria may expand to include the genetic and neural markers for language problems. Finally, there was overarching agreement about the need for an international and multidisciplinary forum to move this debate forward. The purpose would be to develop consensus regarding the diagnostic criteria and diagnostic label for children with language problems. This process should include canvassing the views of families and people with language problems as well as the views of policy-makers. PMID:25142092

Peptide affinity labels for thrombin and other trypsin-like proteases

DOEpatents

Shaw, Elliott N.; Kettner, Charles A.

1982-03-09

A peptide affinity label of the formula (I): ##STR1## wherein X is a radical capable of acting as a leaving group in a nucleophilic substitution reaction; A is an aromatic amino acid residue; B is H, or a C.sub.1 -C.sub.4 alkyl group, or aryl; Y is selected from the group consisting of hydrogen, aroyl, C.sub.1 -C.sub.6 acyl, and Q--(A)--.sub.n, wherein Q=hydrogen, aroyl, or C.sub.1 -C.sub.6 acyl, n=1-10, A is an amino acid residue selected from the aliphatic, hydroxy-containing, carboxylic acid group, and amide-thereof-containing, aromatic, sulfur-containing and imino-containing amino acids; and wherein J is selected from the group consisting of --CH.sub.2 --, --CH.sub.2 --CH.sub.2 --,--CH.sub.2 --CH.sub.2 --CH.sub.2 --, --CH.dbd.CH-- and --CH(OH)--CH.sub.2. The affinity label is useful for irreversibly inactivating thrombin and trypsin-like enzymes and may be used as a potential anticlotting agent.

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.

Simple and Robust N-Glycan Analysis Based on Improved 2-Aminobenzoic Acid Labeling for Recombinant Therapeutic Glycoproteins.

PubMed

Jeong, Yeong Ran; Kim, Sun Young; Park, Young Sam; Lee, Gyun Min

2018-03-21

N-glycans of therapeutic glycoproteins are critical quality attributes that should be monitored throughout all stages of biopharmaceutical development. To reduce both the time for sample preparation and the variations in analytical results, we have developed an N-glycan analysis method that includes improved 2-aminobenzoic acid (2-AA) labeling to easily remove deglycosylated proteins. Using this analytical method, 15 major 2-AA-labeled N-glycans of Enbrel ® were separated into single peaks in hydrophilic interaction chromatography mode and therefore could be quantitated. 2-AA-labeled N-glycans were also highly compatible with in-line quadrupole time-of-flight mass spectrometry (MS) for structural identification. The structures of 15 major and 18 minor N-glycans were identified from their mass values determined by quadrupole time-of-flight MS. Furthermore, the structures of 14 major N-glycans were confirmed by interpreting the MS/MS data of each N-glycan. This analytical method was also successfully applied to neutral N-glycans of Humira ® and highly sialylated N-glycans of NESP ® . Furthermore, the analysis data of Enbrel ® that were accumulated for 2.5 years demonstrated the high-level consistency of this analytical method. Taken together, the results show that a wide repertoire of N-glycans of therapeutic glycoproteins can be analyzed with high efficiency and consistency using the improved 2-AA labeling-based N-glycan analysis method. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation.

PubMed

Xu, Yong; Fang, Xiaozhao; Wu, Jian; Li, Xuelong; Zhang, David

2016-02-01

In this paper, we address the problem of unsupervised domain transfer learning in which no labels are available in the target domain. We use a transformation matrix to transfer both the source and target data to a common subspace, where each target sample can be represented by a combination of source samples such that the samples from different domains can be well interlaced. In this way, the discrepancy of the source and target domains is reduced. By imposing joint low-rank and sparse constraints on the reconstruction coefficient matrix, the global and local structures of data can be preserved. To enlarge the margins between different classes as much as possible and provide more freedom to diminish the discrepancy, a flexible linear classifier (projection) is obtained by learning a non-negative label relaxation matrix that allows the strict binary label matrix to relax into a slack variable matrix. Our method can avoid a potentially negative transfer by using a sparse matrix to model the noise and, thus, is more robust to different types of noise. We formulate our problem as a constrained low-rankness and sparsity minimization problem and solve it by the inexact augmented Lagrange multiplier method. Extensive experiments on various visual domain adaptation tasks show the superiority of the proposed method over the state-of-the art methods. The MATLAB code of our method will be publicly available at http://www.yongxu.org/lunwen.html.

Autofocusing in digital holography using deep learning

NASA Astrophysics Data System (ADS)

Ren, Zhenbo; Xu, Zhimin; Lam, Edmund Y.

2018-02-01

In digital holography, it is critical to know the distance in order to reconstruct the multi-sectional object. This autofocusing is traditionally solved by reconstructing a stack of in-focus and out-of-focus images and using some focus metric, such as entropy or variance, to calculate the sharpness of each reconstructed image. Then the distance corresponding to the sharpest image is determined as the focal position. This method is effective but computationally demanding and time-consuming. To get an accurate estimation, one has to reconstruct many images. Sometimes after a coarse search, a refinement is needed. To overcome this problem in autofocusing, we propose to use deep learning, i.e., a convolutional neural network (CNN), to solve this problem. Autofocusing is viewed as a classification problem, in which the true distance is transferred as a label. To estimate the distance is equated to labeling a hologram correctly. To train such an algorithm, totally 1000 holograms are captured under the same environment, i.e., exposure time, incident angle, object, except the distance. There are 5 labels corresponding to 5 distances. These data are randomly split into three datasets to train, validate and test a CNN network. Experimental results show that the trained network is capable of predicting the distance without reconstructing or knowing any physical parameters about the setup. The prediction time using this method is far less than traditional autofocusing methods.

Outcomes of self-labeling sexual harassment.

PubMed

Magley, V J; Hulin, C L; Fitzgerald, L F; DeNardo, M

1999-06-01

Research has consistently documented a discrepancy between experiencing offensive sex-related behaviors and labeling these situations as sexual harassment, leading to several attempts to understand this phenomenon. The authors propose that the issue of why it is that women who report such experiences generally do not indicate that they have been sexually harassed is an important psychological question, and may provide a path through the nested meanings of workplace harassment. The authors argue for the value of moving beyond a descriptive approach to this issue by examining the effects of self-labeling on the psychological, health, and work-related outcomes of unwelcome, sex-related experiences. They present data from female employees working in 3 separate organizations, demonstrating that women exposed to such behaviors report very similar consequences, whether they label their experiences as harassment or not.

Problem-based test: replication of mitochondrial DNA during the cell cycle.

PubMed

Sétáló, György

2013-01-01

Terms to be familiar with before you start to solve the test: cell cycle, generation time, S-phase, cell culture synchronization, isotopic pulse-chase labeling, density labeling, equilibrium density-gradient centrifugation, buoyant density, rate-zonal centrifugation, nucleoside, nucleotide, kinase enzymes, polymerization of nucleic acids, re-replication block, cell fractionation, Svedberg (sedimentation constant = [ S]), nuclear DNA, mitochondrial DNA, heavy and light mitochondrial DNA chains, heteroplasmy, mitochondrial diseases Copyright © 2013 Wiley Periodicals, Inc.

Instant live-cell super-resolution imaging of cellular structures by nanoinjection of fluorescent probes.

PubMed

Hennig, Simon; van de Linde, Sebastian; Lummer, Martina; Simonis, Matthias; Huser, Thomas; Sauer, Markus

2015-02-11

Labeling internal structures within living cells with standard fluorescent probes is a challenging problem. Here, we introduce a novel intracellular staining method that enables us to carefully control the labeling process and provides instant access to the inner structures of living cells. Using a hollow glass capillary with a diameter of <100 nm, we deliver functionalized fluorescent probes directly into the cells by (di)electrophoretic forces. The label density can be adjusted and traced directly during the staining process by fluorescence microscopy. We demonstrate the potential of this technique by delivering and imaging a range of commercially available cell-permeable and nonpermeable fluorescent probes to cells.

HCP: A Flexible CNN Framework for Multi-label Image Classification.

PubMed

Wei, Yunchao; Xia, Wei; Lin, Min; Huang, Junshi; Ni, Bingbing; Dong, Jian; Zhao, Yao; Yan, Shuicheng

2015-10-26

Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still remains an open problem, mainly due to the complex underlying object layouts and insufficient multi-label training images. In this work, we propose a flexible deep CNN infrastructure, called Hypotheses-CNN-Pooling (HCP), where an arbitrary number of object segment hypotheses are taken as the inputs, then a shared CNN is connected with each hypothesis, and finally the CNN output results from different hypotheses are aggregated with max pooling to produce the ultimate multi-label predictions. Some unique characteristics of this flexible deep CNN infrastructure include: 1) no ground-truth bounding box information is required for training; 2) the whole HCP infrastructure is robust to possibly noisy and/or redundant hypotheses; 3) the shared CNN is flexible and can be well pre-trained with a large-scale single-label image dataset, e.g., ImageNet; and 4) it may naturally output multi-label prediction results. Experimental results on Pascal VOC 2007 and VOC 2012 multi-label image datasets well demonstrate the superiority of the proposed HCP infrastructure over other state-of-the-arts. In particular, the mAP reaches 90.5% by HCP only and 93.2% after the fusion with our complementary result in [44] based on hand-crafted features on the VOC 2012 dataset.

Labelling effects and adolescent responses to peers with depression: an experimental investigation.

PubMed

Dolphin, Louise; Hennessy, Eilis

2017-06-24

The impact of illness labels on the stigma experiences of individuals with mental health problems is a matter of ongoing debate. Some argue that labels have a negative influence on judgments and should be avoided in favour of information emphasising the existence of a continuum of mental health/illness. Others believe that behavioral symptoms are more powerful influencers of stigma than labels. The phenomenon has received little attention in adolescent research, despite the critical importance of the peer group at this developmental stage. This study employs a novel experimental design to examine the impact of the depression label and continuum information on adolescents' responses to peers with depression. Participants were 156 adolescents, 76 male, 80 female (M = 16.25 years; SD = .361), assigned to one of three conditions (Control, Label, Continuum). Participants respond to four audio-visual vignette characters (two clinically depressed) on three occasions. Outcome measures included judgment of the mental health of the vignette characters and emotional responses to them. Neither the provision of a depression label or continuum information influenced perceptions of the mental health of the characters in the audio-visual vignettes or participants' emotional responses to them. The findings have implications for the design of interventions to combat depression stigma with adolescents. Interventions should not necessarily target perceptions of psychiatric labels, but rather perceptions of symptomatic behaviour.

Fusing Continuous-Valued Medical Labels Using a Bayesian Model.

PubMed

Zhu, Tingting; Dunkley, Nic; Behar, Joachim; Clifton, David A; Clifford, Gari D

2015-12-01

With the rapid increase in volume of time series medical data available through wearable devices, there is a need to employ automated algorithms to label data. Examples of labels include interventions, changes in activity (e.g. sleep) and changes in physiology (e.g. arrhythmias). However, automated algorithms tend to be unreliable resulting in lower quality care. Expert annotations are scarce, expensive, and prone to significant inter- and intra-observer variance. To address these problems, a Bayesian Continuous-valued Label Aggregator (BCLA) is proposed to provide a reliable estimation of label aggregation while accurately infer the precision and bias of each algorithm. The BCLA was applied to QT interval (pro-arrhythmic indicator) estimation from the electrocardiogram using labels from the 2006 PhysioNet/Computing in Cardiology Challenge database. It was compared to the mean, median, and a previously proposed Expectation Maximization (EM) label aggregation approaches. While accurately predicting each labelling algorithm's bias and precision, the root-mean-square error of the BCLA was 11.78 ± 0.63 ms, significantly outperforming the best Challenge entry (15.37 ± 2.13 ms) as well as the EM, mean, and median voting strategies (14.76 ± 0.52, 17.61 ± 0.55, and 14.43 ± 0.57 ms respectively with p < 0.0001). The BCLA could therefore provide accurate estimation for medical continuous-valued label tasks in an unsupervised manner even when the ground truth is not available.

Consistent assignment of the vibrations of symmetric and asymmetric ortho-disubstituted benzenes

NASA Astrophysics Data System (ADS)

Tuttle, William D.; Gardner, Adrian M.; Andrejeva, Anna; Kemp, David J.; Wakefield, Jonathan C. A.; Wright, Timothy G.

2018-02-01

The form of molecular vibrations, and changes in these, give valuable insights into geometric and electronic structure upon electronic excitation or ionization, and within families of molecules. Here, we give a description of the phenyl-ring-localized vibrational modes of the ground (S0) electronic states of a wide range of ortho-disubstituted benzene molecules including both symmetrically- and asymmetrically-substituted cases. We conclude that the use of the commonly-used Wilson or Varsányi mode labels, which are based on the vibrational motions of benzene itself, is misleading and ambiguous. In addition, we also find the use of the Mi labels for monosubstituted benzenes [A.M. Gardner, T.G. Wright. J. Chem. Phys. 135 (2011) 114305], or the recently-suggested labels for para-disubstituted benzenes [A. Andrejeva, A.M. Gardner, W.D. Tuttle, T.G. Wright, J. Molec. Spectrosc. 321, 28 (2016)] are not appropriate. Instead, we label the modes consistently based upon the Mulliken (Herzberg) method for the modes of ortho-difluorobenzene (pDFB) under Cs symmetry, since we wish the labelling scheme to cover both symmetrically- and asymmetrically-substituted molecules. By studying the vibrational wavenumbers from the same force field while varying the mass of the substituent, we are able to identify the corresponding modes across a wide range of molecules and hence provide consistent assignments. We assign the vibrations of the following sets of molecules: the symmetric o-dihalobenzenes, o-xylene and catechol (o-dihydroxybenzene); and the asymmetric o-dihalobenzenes, o-halotoluenes, o-halophenols and o-cresol. In the symmetrically-substituted species, we find a pair of in-phase and out-of-phase carbon-substituent stretches, and this motion persists in asymmetrically-substituted molecules for heavier substituents. When at least one of the substituents is light, then we find that these evolve into localized carbon-substituent stretches.

Detection of {open_quotes}cryptic{close_quotes}karyotypic rearrangements in closely related primate species by fluorescence in situ hybridization (FISH) using human subtelomeric DNA probes

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

Youngblom, J.J.; Trask, B.J.; Friedman, C.

Specific human subtelomeric DNA probes were used to reveal cryptic chromosomal rearrangements that cannot be detected by conventional high resolution cytogenetic techniques, or by chromosomal in situ suppression hybridization using whole chromosome paint analysis. Two cosmids containing different subtelomeric DNA sequences were derived from human chromosome 19 and designated as 7501 and 16432. Cosmid 7501 was hybridized to chromosomes from humans, chimpanzee, gorilla and orangutan. In humans, 7501 consistently labeled chromosomes 3q, 15q, and 19p. Additional chromosomes were labeled in different individuals, indicating a polymorphic distribution of this sequence in the human genome. In contrast, 7501 consistently and strongly labeledmore » only the q arm terminus of chromosome 3 in both chimp and gorilla. The identification of the chromosome was made by two-color FISH analysis using human chromosome 4-specific paint and homologous to human chromosome 4. None of the human subjects showed labeling of chromosome 4 with 7501. This finding suggests that in the course of human evolution, subsequent to the divergence of humans and African apes, a cryptic translocation occurred between the ancestral human chromosome 4 and one or more of the other human chromosomes that now contain this DNA segment. In orangutan, 7501 labeled a single acrocentric chromosome pair, a distinctly different chromosome than that labeled in chimp and gorilla. Comparison of chromosome sites labeled with cosmid 16432 showed the distribution of signals on chromosome 1q arm is the same for humans and chimp, but different in the gorilla. Humans and chimps show distinct labeling on sites 1q terminus and 1q41-42. In gorilla, there is instead a large cluster of intense signal near the terminus of 1q that clearly does not extend all the way to the terminus. A paracentric inversion or an unequal cross-over event may account for the observed difference between these species.« less

Interfacial polymerization for colorimetric labeling of protein expression in cells.

PubMed

Lilly, Jacob L; Sheldon, Phillip R; Hoversten, Liv J; Romero, Gabriela; Balasubramaniam, Vivek; Berron, Brad J

2014-01-01

Determining the location of rare proteins in cells typically requires the use of on-sample amplification. Antibody based recognition and enzymatic amplification is used to produce large amounts of visible label at the site of protein expression, but these techniques suffer from the presence of nonspecific reactivity in the biological sample and from poor spatial control over the label. Polymerization based amplification is a recently developed alternative means of creating an on-sample amplification for fluorescence applications, while not suffering from endogenous labels or loss of signal localization. This manuscript builds upon polymerization based amplification by developing a stable, archivable, and colorimetric mode of amplification termed Polymer Dye Labeling. The basic concept involves an interfacial polymer grown at the site of protein expression and subsequent staining of this polymer with an appropriate dye. The dyes Evans Blue and eosin were initially investigated for colorimetric response in a microarray setting, where both specifically stained polymer films on glass. The process was translated to the staining of protein expression in human dermal fibroblast cells, and Polymer Dye Labeling was specific to regions consistent with desired protein expression. The labeling is stable for over 200 days in ambient conditions and is also compatible with modern mounting medium.

Label Distribution in Tissues of Wheat Seedlings Cultivated with Tritium-Labeled Leonardite Humic Acid

PubMed Central

Kulikova, Natalia A.; Abroskin, Dmitry P.; Badun, Gennady A.; Chernysheva, Maria G.; Korobkov, Viktor I.; Beer, Anton S.; Tsvetkova, Eugenia A.; Senik, Svetlana V.; Klein, Olga I.; Perminova, Irina V.

2016-01-01

Humic substances (HS) play important roles in the biotic-abiotic interactions of the root plant and soil contributing to plant adaptation to external environments. However, their mode of action on plants remains largely unknown. In this study the HS distribution in tissues of wheat seedlings was examined using tritium-labeled humic acid (HA) derived from leonardite (a variety of lignites) and microautoradiography (MAR). Preferential accumulation of labeled products from tritiated HA was found in the roots as compared to the shoots, and endodermis was shown to be the major control point for radial transport of label into vascular system of plant. Tritium was also found in the stele and xylem tissues indicating that labeled products from tritiated HA could be transported to shoot tissues via the transpiration stream. Treatment with HA lead to an increase in the content of polar lipids of photosynthetic membranes. The observed accumulation of labeled HA products in root endodermis and positive impact on lipid synthesis are consistent with prior reported observations on physiological effects of HS on plants such as enhanced growth and development of lateral roots and improvement/repairs of the photosynthetic status of plants under stress conditions. PMID:27350412

Density and distribution of hippocampal neurotransmitter receptors in autism: an autoradiographic study.

PubMed

Blatt, G J; Fitzgerald, C M; Guptill, J T; Booker, A B; Kemper, T L; Bauman, M L

2001-12-01

Neuropathological studies in autistic brains have shown small neuronal size and increased cell packing density in a variety of limbic system structures including the hippocampus, a change consistent with curtailment of normal development. Based on these observations in the hippocampus, a series of quantitative receptor autoradiographic studies were undertaken to determine the density and distribution of eight types of neurotransmitter receptors from four neurotransmitter systems (GABAergic, serotoninergic [5-HT], cholinergic, and glutamatergic). Data from these single concentration ligand binding studies indicate that the GABAergic receptor system (3[H]-flunitrazepam labeled benzodiazepine binding sites and 3[H]-muscimol labeled GABA(A) receptors) is significantly reduced in high binding regions, marking for the first time an abnormality in the GABA system in autism. In contrast, the density and distribution of the other six receptors studied (3[H]-80H-DPAT labeled 5-HT1A receptors, 3[H]-ketanserin labeled 5-HT2 receptors, 3[H]-pirenzepine labled M1 receptors, 3[H]-hemicholinium labeled high affinity choline uptake sites, 3[H]-MK801 labeled NMDA receptors, and 3[H]-kainate labeled kainate receptors) in the hippocampus did not demonstrate any statistically significant differences in binding.

Label Distribution in Tissues of Wheat Seedlings Cultivated with Tritium-Labeled Leonardite Humic Acid

NASA Astrophysics Data System (ADS)

Kulikova, Natalia A.; Abroskin, Dmitry P.; Badun, Gennady A.; Chernysheva, Maria G.; Korobkov, Viktor I.; Beer, Anton S.; Tsvetkova, Eugenia A.; Senik, Svetlana V.; Klein, Olga I.; Perminova, Irina V.

2016-06-01

Humic substances (HS) play important roles in the biotic-abiotic interactions of the root plant and soil contributing to plant adaptation to external environments. However, their mode of action on plants remains largely unknown. In this study the HS distribution in tissues of wheat seedlings was examined using tritium-labeled humic acid (HA) derived from leonardite (a variety of lignites) and microautoradiography (MAR). Preferential accumulation of labeled products from tritiated HA was found in the roots as compared to the shoots, and endodermis was shown to be the major control point for radial transport of label into vascular system of plant. Tritium was also found in the stele and xylem tissues indicating that labeled products from tritiated HA could be transported to shoot tissues via the transpiration stream. Treatment with HA lead to an increase in the content of polar lipids of photosynthetic membranes. The observed accumulation of labeled HA products in root endodermis and positive impact on lipid synthesis are consistent with prior reported observations on physiological effects of HS on plants such as enhanced growth and development of lateral roots and improvement/repairs of the photosynthetic status of plants under stress conditions.

Patient, consumer, client, or customer: what do people want to be called?

PubMed

Deber, Raisa B; Kraetschmer, Nancy; Urowitz, Sara; Sharpe, Natasha

2005-12-01

To clarify preferred labels for people receiving health care. The proper label to describe people receiving care has evoked considerable debate among providers and bio-ethicists, but there is little evidence as to the preferences of the people involved. We analysed dictionary definitions as to the derivation and connotations of such potential labels as: patient, client, customer, consumer, partner and survivor. We then surveyed outpatients from four clinical populations in Ontario, Canada about their feelings about these labels. People from breast cancer (n = 202), prostate disease (n = 202) and fracture (n = 202) clinics in an urban Canadian teaching hospital (Sharpe study), and people with HIV/AIDS at 10 specialty care clinics and three primary care practices affiliated with the HIV Ontario Observational Database (n = 431). VARIABLES AND OUTCOME MEASURES: The survey instruments included questions about opinion of label, role in treatment decision-making (the Problem Solving Decision Making scale), trust, use of information and health status. Our respondents moderately liked the label 'patient'. The other alternatives evoked moderate to strong dislike. Many alternatives to 'patient' incorporate assumptions (e.g. a market relationship) which care recipients may also find objectionable. People who are receiving care find the label 'patient' much less objectionable than the alternatives that have been suggested.

Bidirectional reaction steps in metabolic networks: I. Modeling and simulation of carbon isotope labeling experiments.

PubMed

Wiechert, W; de Graaf, A A

1997-07-05

The extension of metabolite balancing with carbon labeling experiments, as described by Marx et al. (Biotechnol. Bioeng. 49: 11-29), results in a much more detailed stationary metabolic flux analysis. As opposed to basic metabolite flux balancing alone, this method enables both flux directions of bidirectional reaction steps to be quantitated. However, the mathematical treatment of carbon labeling systems is much more complicated, because it requires the solution of numerous balance equations that are bilinear with respect to fluxes and fractional labeling. In this study, a universal modeling framework is presented for describing the metabolite and carbon atom flux in a metabolic network. Bidirectional reaction steps are extensively treated and their impact on the system's labeling state is investigated. Various kinds of modeling assumptions, as usually made for metabolic fluxes, are expressed by linear constraint equations. A numerical algorithm for the solution of the resulting linear constrained set of nonlinear equations is developed. The numerical stability problems caused by large bidirectional fluxes are solved by a specially developed transformation method. Finally, the simulation of carbon labeling experiments is facilitated by a flexible software tool for network synthesis. An illustrative simulation study on flux identifiability from available flux and labeling measurements in the cyclic pentose phosphate pathway of a recombinant strain of Zymomonas mobilis concludes this contribution.

The visibility of controls and labels on electronic devices and their suitability for people with impaired vision.

PubMed

Tan, Hsuan; Boon, Mei Ying; Dain, Stephen J

2014-01-01

People with low vision complain of difficulty operating controls on electronic appliances and equipment which suggests that the readability of controls and their labels is below their ability. To investigate whether electronic appliances available today are designed with controls of sufficient size (at least 6/18 Snellen VA) and contrast (at least 30%) to facilitate identification and use by people with low vision. Controls and labels of electronic appliances for sale in retail stores in Singapore (January, February 2012) and a sample of domestic appliances in Sydney, Australia (October, November of 2011) were evaluated in terms of high- and low- importance in function, size and contrast (luminance and colour difference). Labels and controls of 96 electronic appliances were evaluated. All controls were of sufficient size but 22% (26/117) of high- and 27% (12/44) of low-importance controls measured had insufficient luminance contrast. 79% (152/192) of high- and 46% (24/52) of low-importance labels were of insufficient size. 17% (26/160) of the high- and 0.03% (1/33) of low-importance labels had insufficient luminance contrast. Most controls and labels of recently available electronic appliances can cause problems for operability in people with low vision.

21 CFR 336.50 - Labeling of antiemetic drug products.

Code of Federal Regulations, 2010 CFR

2010-04-01

... years of age. “Do not take this product, unless directed by a doctor, if you have a breathing problem... Section 336.50 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES... under 12 years of age. “Do not give this product to children who have a breathing problem such as...

A Biochemical Approach to the Problem of Dyslexia.

ERIC Educational Resources Information Center

Baker, Sidney McDonald

1985-01-01

The paper presents the case of a sixth-grade boy, labeled dyslexic, who responded positively to a biochemical approach. Remedy of iron, zinc, and Vitamin B-6 deficiencies as well as an imbalance of fatty acids resulted in improvements in hair and skin and also in reading. A biochemical approach to behavior problems is proposed. (Author/CL)

The Role of Input Frequency and Semantic Transparency in the Acquisition of Verb Meaning: Evidence from Placement Verbs in Tamil and Dutch

ERIC Educational Resources Information Center

Narasimhan, Bhuvana; Gullberg, Marianne

2011-01-01

We investigate how Tamil- and Dutch-speaking adults and four- to five-year-old children use caused posture verbs ("lay/stand a bottle on a table") to label placement events in which objects are oriented vertically or horizontally. Tamil caused posture verbs consist of morphemes that individually label the causal and result subevents ("nikka…

Effect of Micronutrients on Behavior and Mood in Adults with ADHD: Evidence from an 8-Week Open Label Trial with Natural Extension

ERIC Educational Resources Information Center

Rucklidge, Julia; Taylor, Mairin; Whitehead, Kathryn

2011-01-01

Objective: To investigate the effect of a 36-ingredient micronutrient formula consisting mainly of minerals and vitamins in the treatment of adults with both ADHD and severe mood dysregulation (SMD). Method: 14 medication-free adults (9 men, 5 women; 18-55 years) with ADHD and SMD completed an 8-week open-label trial. Results: A minority reported…

Empirical Evaluation of Different Feature Representations for Social Circles Detection

DTIC Science & Technology

2015-06-16

study and compare the performance on the available labelled Facebook data from the Kaggle competition on learning social circles in networks . We...Kaggle competition on learning social circles in networks [5]. The data consist of hand- labelled friendship egonets from Facebook and a set of 57...16. SECURITY CLASSIFICATION OF: Social circles detection is a special case of community detection in social network that is currently attracting a

The role of health-related, motivational and sociodemographic aspects in predicting food label use: a comprehensive study.

PubMed

Hess, Rebecca; Visschers, Vivianne H M; Siegrist, Michael

2012-03-01

Previous studies focused on a limited number of determinants of food label use. We therefore tested a comprehensive model of food label use consisting of sociodemographic, health-related and motivating variables. These three predictor groups were chosen based on the previous literature and completed with new predictors not yet examined in a comprehensive study of frequency of label use. We sent questionnaires to a random sample of households in the German-speaking part of Switzerland. The respondents filled in the questionnaire at home and returned it by mail. We analysed the data of 1162 filled-in questionnaires (response rate = 38 %). Of the respondents, 637 were women (55 %), and their mean age was 53·54 (sd 15·68) years. Health-related variables were the most important group of predictors of label use, followed by motivating factors and sociodemographic variables. Placing importance on health, healthy eating and nutritional value of food, perceived vulnerability for diet-related diseases, nutrition knowledge, numeracy and gender were positively associated with frequency of food label use whereas shopping habits and seeing eating as something positive were negative predictors of frequency of label use. People's health consciousness should be raised in order to increase the frequency of food label use. Furthermore, it should be stressed that reading labels and keeping a healthy diet do not contradict 'good eating', and that both of these aspects can be combined with the help of food labels.

The impact of front-of-pack nutrition labels on consumer product evaluation and choice: an experimental study.

PubMed

Hamlin, Robert P; McNeill, Lisa S; Moore, Vanessa

2015-08-01

The present research was an experimental test that aimed to quantify the impact of two dominant front-of-pack (FOP) nutritional label formats on consumer evaluations of food products that carried them. The two FOP label types tested were the traffic light label and the Percentage Daily Intake. A 4×5 partially replicated Latin square design was used that allowed the impact of the FOP labels to be isolated from the effects of the product and the consumers who were performing the evaluations. The experiment was conducted on campus at the University of Otago, New Zealand. The participants were 250 university students selected at random who met qualifying criteria of independent living and regular purchase of the products used in the research. They were not aware of the purpose of the research. The presence of FOP labels led to significant and positive changes in consumer purchase intentions towards the products that carried them. These changes were not affected by the nature of FOP labels used, their size or the product nutritional status (good/bad) that they were reporting. The result is consistent with the participants paying attention to the FOP label and then using it as an adimensional cue indicating product desirability. As such, it represents a complete functional failure of both of these FOP label types in this specific instance. This result supports calls for further research on the performance of these FOP labels before any move to compulsory deployment is made.

Study and development of label-free optical biosensors for biomedical applications

NASA Astrophysics Data System (ADS)

Choi, Charles J.

For the majority of assays currently performed, fluorescent or colorimetric chemical labels are commonly attached to the molecules under study so that they may be readily visualized. The methods of using labels to track biomolecular binding events are very sensitive and effective, and are employed as standardized assay protocol across research labs worldwide. However, using labels induces experimental uncertainties due to the effect of the label on molecular conformation, active binding sites, or inability to find an appropriate label that functions equivalently for all molecules in an experiment. Therefore, the ability to perform highly sensitive biochemical detection without the use of fluorescent labels would further simplify assay protocols and would provide quantitative kinetic data, while removing experimental artifacts from fluorescent quenching, shelf-life, and background fluorescence phenomena. In view of the advantages mentioned above, the study and development of optical label-free sensor technologies have been undertaken here. In general, label-free photonic crystal (PC) biosensors and metal nanodome array surface-enhanced Raman scattering (SERS) substrates, both of which are fabricated by nanoreplica molding process, have been used as the method to attack the problem. Chapter 1 shows the work on PC label-free biosensor incorporated microfluidic network for bioassay performance enhancement and kinetic reaction rate constant determination. Chapter 2 describes the work on theoretical and experimental comparison of label-free biosensing in microplate, microfluidic, and spot-based affinity capture assays. Chapter 3 shows the work on integration of PC biosensor with actuate-to-open valve microfluidic chip for pL-volume combinatorial mixing and screening application. In Chapter 4, the development and characterization of SERS nanodome array is shown. Lastly, Chapter 5 describes SERS nanodome sensor incorporated tubing for point-of-care monitoring of intravenous drugs and metabolites.

Category-contingent face adaptation for novel colour categories: Contingent effects are seen only after social or meaningful labelling.

PubMed

Little, Anthony C; DeBruine, Lisa M; Jones, Benedict C

2011-01-01

A face appears normal when it approximates the average of a population. Consequently, exposure to faces biases perceptions of subsequently viewed faces such that faces similar to those recently seen are perceived as more normal. Simultaneously inducing such aftereffects in opposite directions for two groups of faces indicates somewhat discrete representations for those groups. Here we examine how labelling influences the perception of category in faces differing in colour. We show category-contingent aftereffects following exposure to faces differing in eye spacing (wide versus narrow) for blue versus red faces when such groups are consistently labelled with socially meaningful labels (Extravert versus Introvert; Soldier versus Builder). Category-contingent aftereffects were not seen using identical methodology when labels were not meaningful or were absent. These data suggest that human representations of faces can be rapidly tuned to code for meaningful social categories and that such tuning requires both a label and an associated visual difference. Results highlight the flexibility of the cognitive visual system to discriminate categories even in adulthood. Copyright © 2010 Elsevier B.V. All rights reserved.

Pilot Evaluation of an In-Store Nutrition Label Education Program.

PubMed

Dukeshire, Steven; Nicks, Emily; Ferguson, Jennifer

2014-12-01

To describe and provide recommendations for the implementation of an evaluation for an already existing, in-store Nutrition Label Education Program (NLEP). We describe the development and implementation of an evaluation consisting of a pre- and postsurvey and one month follow-up. The evaluation was designed to assess satisfaction with the NLEP as well as changes in participant nutrition label knowledge, confidence in using nutrition labels, and actual changes in nutrition label use. Nineteen participants took part in the pilot evaluation. The evaluation was successful in demonstrating high levels of satisfaction with the NLEP as well as positive changes in participant confidence and some increased knowledge in using nutrition labels. However, only 3 people participated in the follow-up, limiting the ability to assess behaviour change. Ideally, NLEPs should include ongoing evaluation that extends beyond just assessing participant satisfaction. Recommendations are provided for conducting such evaluations, including the importance of incorporating the evaluation into the program itself, using existing questionnaires when possible, and employing pre- and postsurveys as well as follow-up interviews to assess change.

Joint learning of labels and distance metric.

PubMed

Liu, Bo; Wang, Meng; Hong, Richang; Zha, Zhengjun; Hua, Xian-Sheng

2010-06-01

Machine learning algorithms frequently suffer from the insufficiency of training data and the usage of inappropriate distance metric. In this paper, we propose a joint learning of labels and distance metric (JLLDM) approach, which is able to simultaneously address the two difficulties. In comparison with the existing semi-supervised learning and distance metric learning methods that focus only on label prediction or distance metric construction, the JLLDM algorithm optimizes the labels of unlabeled samples and a Mahalanobis distance metric in a unified scheme. The advantage of JLLDM is multifold: 1) the problem of training data insufficiency can be tackled; 2) a good distance metric can be constructed with only very few training samples; and 3) no radius parameter is needed since the algorithm automatically determines the scale of the metric. Extensive experiments are conducted to compare the JLLDM approach with different semi-supervised learning and distance metric learning methods, and empirical results demonstrate its effectiveness.

The forced-choice paradigm and the perception of facial expressions of emotion.

PubMed

Frank, M G; Stennett, J

2001-01-01

The view that certain facial expressions of emotion are universally agreed on has been challenged by studies showing that the forced-choice paradigm may have artificially forced agreement. This article addressed this methodological criticism by offering participants the opportunity to select a none of these terms are correct option from a list of emotion labels in a modified forced-choice paradigm. The results show that agreement on the emotion label for particular facial expressions is still greater than chance, that artifactual agreement on incorrect emotion labels is obviated, that participants select the none option when asked to judge a novel expression, and that adding 4 more emotion labels does not change the pattern of agreement reported in universality studies. Although the original forced-choice format may have been prone to artifactual agreement, the modified forced-choice format appears to remedy that problem.

Bidirectional Active Learning: A Two-Way Exploration Into Unlabeled and Labeled Data Set.

PubMed

Zhang, Xiao-Yu; Wang, Shupeng; Yun, Xiaochun

2015-12-01

In practical machine learning applications, human instruction is indispensable for model construction. To utilize the precious labeling effort effectively, active learning queries the user with selective sampling in an interactive way. Traditional active learning techniques merely focus on the unlabeled data set under a unidirectional exploration framework and suffer from model deterioration in the presence of noise. To address this problem, this paper proposes a novel bidirectional active learning algorithm that explores into both unlabeled and labeled data sets simultaneously in a two-way process. For the acquisition of new knowledge, forward learning queries the most informative instances from unlabeled data set. For the introspection of learned knowledge, backward learning detects the most suspiciously unreliable instances within the labeled data set. Under the two-way exploration framework, the generalization ability of the learning model can be greatly improved, which is demonstrated by the encouraging experimental results.

Alcohol counter-advertising and the media. A review of recent research.

PubMed

Agostinelli, Gina; Grube, Joel W

2002-01-01

Counter-advertising commonly is used to balance the effects that alcohol advertising may have on alcohol consumption and alcohol-related problems. Such measures can take the form of print or broadcast advertisements (e.g., public service announcements [PSAs]) as well as product warning labels. The effectiveness of both types of counter-advertising is reviewed using the Elaboration Likelihood Model as a theoretical framework. For print and broadcast counter-advertisements, such factors as their emotional appeal and the credibility of the source, as well as audience factors, can influence their effectiveness. Further, brewer-sponsored counter-advertisements are evaluated and received differently than are the more conventional PSA counter-advertisements. For warning labels, both the content and design of the label influence their effectiveness, as do audience factors. The effectiveness of those labels is evaluated in terms of the extent to which they impact cognitive and affective processes as well as drinking behavior.

Sliding movement of single actin filaments on one-headed myosin filaments

NASA Astrophysics Data System (ADS)

Harada, Yoshie; Noguchi, Akira; Kishino, Akiyoshi; Yanagida, Toshio

1987-04-01

The myosin molecule consists of two heads, each of which contains an enzymatic active site and an actin-binding site. The fundamental problem of whether the two heads function independently or cooperatively during muscle contraction has been studied by methods using an actomyosin thread1, superprecipitation2-4 and chemical modification of muscle fibres5. No clear conclusion has yet been reached. We have approached this question using an assay system in which sliding movements of fluorescently labelled single actin filaments along myosin filaments can be observed directly6,7. Here, we report direct measurement of the sliding of single actin filaments along one-headed myosin filaments in which the density of heads was varied over a wide range. Our results show that cooperative interaction between the two heads of myosin is not essential for inducing the sliding movement of actin filaments.

Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments.

PubMed

Han, Wenjing; Coutinho, Eduardo; Ruan, Huabin; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

2016-01-01

Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances.

Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments

PubMed Central

Han, Wenjing; Coutinho, Eduardo; Li, Haifeng; Schuller, Björn; Yu, Xiaojie; Zhu, Xuan

2016-01-01

Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances. PMID:27627768

Ingredient Consistency of Commercially Available Polyphenol and Tocopherol Nutraceuticals

PubMed Central

Remsberg, Connie M.; Good, Renee L.; Davies, Neal M.

2010-01-01

Label claims of vitamin E succinate and polyphenolic nutraceuticals are assessed. A validated HPLC method was utilized to assess vitamin E succinate products. Three novel LC/MS methods were used to assess the polyphenols, pterostilbene, phloretin, and myricetin, in dietary supplements. The amount of vitamin E succinate varied from 0-130% of the stated label content with two products containing vitamin E acetate rather than vitamin E succinate. Expected polyphenols were found in 7 of the 8 supplement products. None of the polyphenol supplements contained content within 100-120% of label claims. The present study indicates a lack of uniformity in nutraceutical products. PMID:27721342

Sensitivity Analysis of Flux Determination in Heart by H2 18O -provided Labeling Using a Dynamic Isotopologue Model of Energy Transfer Pathways

PubMed Central

Schryer, David W.; Peterson, Pearu; Illaste, Ardo; Vendelin, Marko

2012-01-01

To characterize intracellular energy transfer in the heart, two organ-level methods have frequently been employed: inversion and saturation transfer, and dynamic labeling. Creatine kinase (CK) fluxes obtained by following oxygen labeling have been considerably smaller than the fluxes determined by saturation transfer. It has been proposed that dynamic labeling determines net flux through CK shuttle, whereas saturation transfer measures total unidirectional flux. However, to our knowledge, no sensitivity analysis of flux determination by oxygen labeling has been performed, limiting our ability to compare flux distributions predicted by different methods. Here we analyze oxygen labeling in a physiological heart phosphotransfer network with active CK and adenylate kinase (AdK) shuttles and establish which fluxes determine the labeling state. A mathematical model consisting of a system of ordinary differential equations was composed describing enrichment in each phosphoryl group and inorganic phosphate. By varying flux distributions in the model and calculating the labeling, we analyzed labeling sensitivity to different fluxes in the heart. We observed that the labeling state is predominantly sensitive to total unidirectional CK and AdK fluxes and not to net fluxes. We conclude that measuring dynamic incorporation of into the high-energy phosphotransfer network in heart does not permit unambiguous determination of energetic fluxes with a higher magnitude than the ATP synthase rate when the bidirectionality of fluxes is taken into account. Our analysis suggests that the flux distributions obtained using dynamic labeling, after removing the net flux assumption, are comparable with those from inversion and saturation transfer. PMID:23236266

A multiple distributed representation method based on neural network for biomedical event extraction.

PubMed

Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

2017-12-20

Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

Soft and hard classification by reproducing kernel Hilbert space methods.

PubMed

Wahba, Grace

2002-12-24

Reproducing kernel Hilbert space (RKHS) methods provide a unified context for solving a wide variety of statistical modelling and function estimation problems. We consider two such problems: We are given a training set [yi, ti, i = 1, em leader, n], where yi is the response for the ith subject, and ti is a vector of attributes for this subject. The value of y(i) is a label that indicates which category it came from. For the first problem, we wish to build a model from the training set that assigns to each t in an attribute domain of interest an estimate of the probability pj(t) that a (future) subject with attribute vector t is in category j. The second problem is in some sense less ambitious; it is to build a model that assigns to each t a label, which classifies a future subject with that t into one of the categories or possibly "none of the above." The approach to the first of these two problems discussed here is a special case of what is known as penalized likelihood estimation. The approach to the second problem is known as the support vector machine. We also note some alternate but closely related approaches to the second problem. These approaches are all obtained as solutions to optimization problems in RKHS. Many other problems, in particular the solution of ill-posed inverse problems, can be obtained as solutions to optimization problems in RKHS and are mentioned in passing. We caution the reader that although a large literature exists in all of these topics, in this inaugural article we are selectively highlighting work of the author, former students, and other collaborators.

A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs.

PubMed

Forkan, Abdur Rahim Mohammad; Khalil, Ibrahim

2017-02-01

In home-based context-aware monitoring patient's real-time data of multiple vital signs (e.g. heart rate, blood pressure) are continuously generated from wearable sensors. The changes in such vital parameters are highly correlated. They are also patient-centric and can be either recurrent or can fluctuate. The objective of this study is to develop an intelligent method for personalized monitoring and clinical decision support through early estimation of patient-specific vital sign values, and prediction of anomalies using the interrelation among multiple vital signs. In this paper, multi-label classification algorithms are applied in classifier design to forecast these values and related abnormalities. We proposed a completely new approach of patient-specific vital sign prediction system using their correlations. The developed technique can guide healthcare professionals to make accurate clinical decisions. Moreover, our model can support many patients with various clinical conditions concurrently by utilizing the power of cloud computing technology. The developed method also reduces the rate of false predictions in remote monitoring centres. In the experimental settings, the statistical features and correlations of six vital signs are formulated as multi-label classification problem. Eight multi-label classification algorithms along with three fundamental machine learning algorithms are used and tested on a public dataset of 85 patients. Different multi-label classification evaluation measures such as Hamming score, F1-micro average, and accuracy are used for interpreting the prediction performance of patient-specific situation classifications. We achieved 90-95% Hamming score values across 24 classifier combinations for 85 different patients used in our experiment. The results are compared with single-label classifiers and without considering the correlations among the vitals. The comparisons show that multi-label method is the best technique for this problem domain. The evaluation results reveal that multi-label classification techniques using the correlations among multiple vitals are effective ways for early estimation of future values of those vitals. In context-aware remote monitoring this process can greatly help the doctors in quick diagnostic decision making. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Infants' understanding of false labeling events: the referential roles of words and the speakers who use them.

PubMed

Koenig, Melissa A; Echols, Catharine H

2003-04-01

The four studies reported here examine whether 16-month-old infants' responses to true and false utterances interact with their knowledge of human agents. In Study 1, infants heard repeated instances either of true or false labeling of common objects; labels came from an active human speaker seated next to the infant. In Study 2, infants experienced the same stimuli and procedure; however, we replaced the human speaker of Study 1 with an audio speaker in the same location. In Study 3, labels came from a hidden audio speaker. In Study 4, a human speaker labeled the objects while facing away from them. In Study 1, infants looked significantly longer to the human agent when she falsely labeled than when she truthfully labeled the objects. Infants did not show a similar pattern of attention for the audio speaker of Study 2, the silent human of Study 3 or the facing-backward speaker of Study 4. In fact, infants who experienced truthful labeling looked significantly longer to the facing-backward labeler of Study 4 than to true labelers of the other three contexts. Additionally, infants were more likely to correct false labels when produced by the human labeler of Study 1 than in any of the other contexts. These findings suggest, first, that infants are developing a critical conception of other human speakers as truthful communicators, and second, that infants understand that human speakers may provide uniquely useful information when a word fails to match its referent. These findings are consistent with the view that infants can recognize differences in knowledge and that such differences can be based on differences in the availability of perceptual experience.

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

Sensing and enumerating rare circulating cells with diffuse light

NASA Astrophysics Data System (ADS)

Zettergren, Eric; Vickers, Dwayne; Niedre, Mark

2011-02-01

Detection and quantification of circulating cells in live animals is a challenging and important problem in many areas of biomedical research. Current methods involve extraction of blood samples and counting of cells ex-vivo. Since only small blood volumes are analyzed at specific time points, monitoring of changes in cell populations over time is difficult and rare cells often escape detection. The goal of this research is to develop a method for enumerating very rare circulating cells in the bloodstream non-invasively. This would have many applications in biomedical research, including monitoring of cancer metastasis and tracking of hematopoietic stem cells. In this work we describe the optical configuration of our instrument which allows fluorescence detection of single cells in diffusive media at the mesoscopic scale. Our instrument design consists of two continuous wave laser diode sources and an 8-channel fiber coupled multi-anode photon counting PMT. Fluorescence detector fibers were arranged circularly around the target in a miniaturized ring configuration. Cell-simulating fluorescent microspheres and fluorescently-labeled cells were passed through a limb mimicking phantom with similar optical properties and background fluorescence as a limb of a mouse. Our data shows that we are able to successfully detect and count these with high quantitative accuracy. Future work includes characterization of our instrument using fluorescently labeled cells in-vivo. If successful, this technique would allow several orders of magnitude in vivo detection sensitivity improvement versus current approaches.

Rapid and field-deployable biological and chemical Raman-based identification

NASA Astrophysics Data System (ADS)

Botonjic-Sehic, Edita; Paxon, Tracy L.; Boudries, Hacene

2011-06-01

Pathogen detection using Raman spectroscopy is achieved through the use of a sandwich immunoassay. Antibody-modified magnetic beads are used to capture and concentrate target analytes in solution and surface-enhanced Raman spectroscopy (SERS) tags are conjugated with antibodies and act as labels to enable specific detection of biological pathogens. The rapid detection of biological pathogens is critical to first responders, thus assays to detect E.Coli and Anthrax have been developed and will be reported. The problems associated with pathogen detection resulting from the spectral complexity and variability of microorganisms are overcome through the use of SERS tags, which provide an intense, easily recognizable, and spectrally consistent Raman signal. The developed E. coli assay has been tested with 5 strains of E. coli and shows a low limit of detection, on the order of 10 and 100 c.f.u. per assay. Additionally, the SERS assay utilizes magnetic beads to collect the labeled pathogens into the focal point of the detection laser beam, making the assay robust to commonly encountered white powder interferants such as flour, baking powder, and corn starch. The reagents were also found to be stable at room temperature over extended periods of time with testing conducted over a one year period. Finally, through a specialized software algorithm, the assays are interfaced to the Raman instrument, StreetLab Mobile, for rapid-field-deployable biological identification.

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

NASA Astrophysics Data System (ADS)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

[Perspective applications of multi-species probiotics in the prevention of antibiotic-associated diarrhea].

PubMed

Uspenskiĭ, Iu P; Zakharenko, S M; Fominykh, Iu A

2013-01-01

The problem of antibiotic-associated conditions is one of the most actual problems of clinical practice. The antibiotic-associated diarrhea is a multidisciplinary problem. Investigations of the small intestine microecological status and assessment of microflora at the patients receiving antibiotics testifies to dysbiosis existence. In article results of open-label investigation of a multispecies probiotic RioFlora Balance using for antibiotic-associated diarrhea prophylaxis in patients used antibacterial therapy are presented.

Changing patterns of peanut agglutinin labelling in the dorsal cochlear nucleus correspond to axonal ingrowth.

PubMed Central

Riggs, G H; Schweitzer, L

1994-01-01

Various studies have suggested that glycoconjugates may influence connectivity and lamination in the developing central nervous system and may function as barriers to neuritic extension. It has been proposed that the peanut agglutinin lectin labels a glycoconjugate subserving a barrier function. We chose to investigate the distribution of this peanut-agglutinin-labelled glycoconjugate in the dorsal cochlear nucleus of the developing hamster since the development of the dorsal cochlear nucleus is well characterised and its axons obey laminar boundaries. The distribution of peanut agglutinin label throughout the cochlear nucleus delineated zones that cochlear axons fail to invade. In the dorsal cochlear nucleus, laminar differences were reduced on postnatal d 13 and virtually disappearing by postnatal d 23. Label in the molecular layer dissipated as axons and dendrites grew into this layer. These patterns of peanut agglutinin binding correspond to axonal ingrowth and are consistent with a barrier function for glycoconjugates in the molecular layer. Images Fig. 1 Fig. 2 Fig. 4 PMID:7961144

A novel colloidal gold labeled antigen for the detection of Deoxynivalenol using an immunochromatographic assay method

NASA Astrophysics Data System (ADS)

Jin, Yu; Liu, Renrong; Zhu, Lixin; Chen, Zhenzhen

2017-11-01

In this paper, an immunochromatographic assay card was developed for the detection of DON in feed and cereals using a novel colloidal gold labeling method. For the colloidal gold immunochromatographic rapid detection (GICD) card, a monoclonal antibody DON-mAb and a goat anti-chicken IgY were drawn on NC membrane as the test line (T line) and the control line (C line) respectively. A gold labeled DON-CBSA conjugate and a gold labeled chicken IgY were sprayed onto the conjugate pad. The GICD card has cut-off levels of 50ng/mL for DON, which is invulnerable to matrix interference, and applicable to a wide range of samples. The GICD detecting results of feed and grain samples were compared with the results of ELISA testing, which showed good consistency.

Label inspection of approximate cylinder based on adverse cylinder panorama

NASA Astrophysics Data System (ADS)

Lin, Jianping; Liao, Qingmin; He, Bei; Shi, Chenbo

2013-12-01

This paper presents a machine vision system for automated label inspection, with the goal to reduce labor cost and ensure consistent product quality. Firstly, the images captured from each single-camera are distorted, since the inspection object is approximate cylindrical. Therefore, this paper proposes an algorithm based on adverse cylinder projection, where label images are rectified by distortion compensation. Secondly, to overcome the limited field of viewing for each single-camera, our method novelly combines images of all single-cameras and build a panorama for label inspection. Thirdly, considering the shake of production lines and error of electronic signal, we design the real-time image registration to calculate offsets between the template and inspected images. Experimental results demonstrate that our system is accurate, real-time and can be applied for numerous real- time inspections of approximate cylinders.

The effects of echolalia on acquisition and generalization of receptive labeling in autistic children.

PubMed Central

Charlop, M H

1983-01-01

This investigation, consisting of two experiments, was designed to assess the effects of autistic immediate echolalia on acquisition and generalization of receptive labeling tasks. Experiment 1 addressed whether autistic children could use their echolalia to facilitate acquisition. The results indicated that incorporating echolalia (echo of the requested object's label) into the task before manual response (handing the requested object to the experimenter) facilitated receptive labeling. Experiment 2 was designed to determine the effects of incorporating echolalia into task response on acquisition and subsequent generalization. These results indicated that echolalia facilitated generalization for echolalic autistic children but not for functionally mute autistic children. The results of the experiments are discussed in terms of stimulus control. Additionally, it is proposed that perhaps in certain cases, echolalia should not be eliminated, but used to advantage in receptive responding. PMID:6833164

The effects of echolalia on acquisition and generalization of receptive labeling in autistic children.

PubMed

Charlop, M H

1983-01-01

This investigation, consisting of two experiments, was designed to assess the effects of autistic immediate echolalia on acquisition and generalization of receptive labeling tasks. Experiment 1 addressed whether autistic children could use their echolalia to facilitate acquisition. The results indicated that incorporating echolalia (echo of the requested object's label) into the task before manual response (handing the requested object to the experimenter) facilitated receptive labeling. Experiment 2 was designed to determine the effects of incorporating echolalia into task response on acquisition and subsequent generalization. These results indicated that echolalia facilitated generalization for echolalic autistic children but not for functionally mute autistic children. The results of the experiments are discussed in terms of stimulus control. Additionally, it is proposed that perhaps in certain cases, echolalia should not be eliminated, but used to advantage in receptive responding.

Using Supervised Learning Techniques for Diagnosis of Dynamic Systems

DTIC Science & Technology

2002-05-04

M. Gasca 2 , Juan A. Ortega2 Abstract. This paper describes an approach based on supervised diagnose systems faults are needed to maintain the systems...labelled, data will be used for this purpose [5] [6]. treated to add additional information about the running of system. In [7] the fundaments of the based ...8] proposes classification tool to the set of labelled and treated data. This a consistency- based approach with qualitative models. way, any

Teachers as Expert Learners and Fellow Travelers: A Review of Professional Development Practices for Problem-Based Learning

ERIC Educational Resources Information Center

Walton, Janet

2014-01-01

The label of "teacher" is something of a misnomer for the problem-based learning (PBL) practitioner. Rather than acting as a source of content knowledge, PBL educators are lead learners who demonstrate learning to students through their own authentic inquiry (Hmelo-Silver, 2004). PBL educators and students travel a road together that…

Reading and the Emotionally Handicapped Child. Highlights of a Special Study Institute (Poughkeepsie, New York, October 5-7, 1970).

ERIC Educational Resources Information Center

Duchess County Board of Cooperative Educational Services, NY.

The conference proceedings include seven papers dealing with reading problems of emotionally disturbed children. Emotional resistance to reading is discussed by Jules Abrams, a psychiatrist. The purposes of testing and the problem of labeling are touched upon by Clifford Kolson. Some practical suggestions of classroom techniques for combining a…

Food quality and safety: traceability and labeling.

PubMed

Lupien, John R

2005-01-01

This article discusses food systems in general, their development over the past 120 years, and realities and problems faced by a world population of over 6 billion people. Various food and feed problems are mentioned, and the concept of "traceability" is discussed in the context of the broader and more useful approach of using "good practices" at all levels of the food chain.

The School Library: A Space for Critical Thinking about Data and Mathematical Questions

ERIC Educational Resources Information Center

Kimmel, Sue C.

2012-01-01

Which potato chip is healthiest: (1) regular; (2) baked; or (3) sour cream and onion? This problem requires critical and numerical skills in order to read and compare nutrition labels. The question has applications in mathematics and science classrooms but also in teachers' lounges and school cafeterias. It is a problem that addresses the five…

21 CFR 336.50 - Labeling of antiemetic drug products.

Code of Federal Regulations, 2014 CFR

2014-04-01

... years of age. “Do not take this product, unless directed by a doctor, if you have a breathing problem... under 12 years of age. “Do not give this product to children who have a breathing problem such as... diphenhydramine, including one used on skin”. 1 See § 201.66(b)(4) of this chapter for definition of bullet symbol...

21 CFR 336.50 - Labeling of antiemetic drug products.

Code of Federal Regulations, 2012 CFR

2012-04-01

... years of age. “Do not take this product, unless directed by a doctor, if you have a breathing problem... under 12 years of age. “Do not give this product to children who have a breathing problem such as... diphenhydramine, including one used on skin”. 1 See § 201.66(b)(4) of this chapter for definition of bullet symbol...

21 CFR 336.50 - Labeling of antiemetic drug products.

Code of Federal Regulations, 2013 CFR

2013-04-01

... years of age. “Do not take this product, unless directed by a doctor, if you have a breathing problem... under 12 years of age. “Do not give this product to children who have a breathing problem such as... diphenhydramine, including one used on skin”. 1 See § 201.66(b)(4) of this chapter for definition of bullet symbol...

The influence of calorie labeling on food orders and consumption: A review of the literature1

PubMed Central

Kiszko, Kamila M.; Martinez, Olivia D.; Abrams, Courtney; Elbel, Brian

2014-01-01

Obesity is a challenging public health problem that affects millions of Americans. Increasingly policy makers are seeking environmental and policy-based solutions to combat and prevent its serious health effects. Calorie labeling mandates, including the provision in the 2010 Patient Protection and Affordable Care Act that is set to begin in 2014, have been one of the most popular and most studied approaches. This review examines 31 studies published from January 1, 2007 through July 19, 2013. It builds on Harnack and French's 2008 review and assesses the evidence on the effectiveness of calorie labeling at the point of purchase. We find that, while there are some positive results reported from studies examining the effects of calorie labeling, overall the best designed studies (real world studies, with a comparison group) show that calorie labels do not have the desired effect in reducing total calories ordered at the population level. Moving forward, researchers should consider novel, more effective ways of presenting nutrition information, while keeping a focus on particular subgroups that may be differentially affected by nutrition policies. PMID:24760208

Artistic image analysis using graph-based learning approaches.

PubMed

Carneiro, Gustavo

2013-08-01

We introduce a new methodology for the problem of artistic image analysis, which among other tasks, involves the automatic identification of visual classes present in an art work. In this paper, we advocate the idea that artistic image analysis must explore a graph that captures the network of artistic influences by computing the similarities in terms of appearance and manual annotation. One of the novelties of our methodology is the proposed formulation that is a principled way of combining these two similarities in a single graph. Using this graph, we show that an efficient random walk algorithm based on an inverted label propagation formulation produces more accurate annotation and retrieval results compared with the following baseline algorithms: bag of visual words, label propagation, matrix completion, and structural learning. We also show that the proposed approach leads to a more efficient inference and training procedures. This experiment is run on a database containing 988 artistic images (with 49 visual classification problems divided into a multiclass problem with 27 classes and 48 binary problems), where we show the inference and training running times, and quantitative comparisons with respect to several retrieval and annotation performance measures.

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks

PubMed Central

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S.

2017-01-01

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a=(u,v) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages. PMID:28771201

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

PubMed

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

2017-08-03

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

Modernization of the Driver Behaviour Questionnaire.

PubMed

Cordazzo, Sheila T D; Scialfa, Charles T; Ross, Rachel Jones

2016-02-01

The current study builds on previous versions of the Driver Behaviour Questionnaire (DBQ) by incorporating a larger sample of driving behaviors targeting inattention, distraction, aggressive driving, and health related to aging. The goals of this study were to determine if the resulting factor structure was consistent with a more contemporary view of unsafe driving behaviors, and to determine whether scores on the factors could predict self-reported collisions and police citations. The instrument was given to a sample of 3295 drivers ranging in age from 19 to 80+ years old. It was divided in two sections, the first to provide demographic information and driving history data and the second containing 105 driver behavior questions. An exploratory factor analysis resulted in a 65-item scale organized in four factors. The factors were labeled tentatively as Inattention Errors, Age-Related Problems, Distraction and Hurry, and Aggressive Violations. Regression analyses showed that the factors were predictors of self-reported, at-fault collisions and police citations. The factor scores found in this research are consistent with a useful theoretical framework for understanding unsafe driver actions, and demonstrate some potential to identify several individual difference variables that predict self-reported collisions and citations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Enhancing Endosomal Escape of Transduced Proteins by Photochemical Internalisation

PubMed Central

Mellert, Kevin; Lamla, Markus; Scheffzek, Klaus; Wittig, Rainer; Kaufmann, Dieter

2012-01-01

Induced internalisation of functional proteins into cultured cells has become an important aspect in a rising number of in vitro and in vivo assays. The endo-lysosomal entrapment of the transduced proteins remains the major problem in all transduction protocols. In this study we compared the efficiency, cytotoxicity and protein targeting of different commercially available transduction reagents by transducing a well-studied fluorescently labelled protein (Atto488-bovine serum albumin) into cultured human sarcoma cells. The amount of internalised protein and toxicity differed between the different reagents, but the percentage of transduced cells was consistently high. Furthermore, in all protocols the signals of the transduced Atto488-BSA were predominantly punctual consistent with an endosomal localisation. To overcome the endosomal entrapment, the transduction protocols were combined with a photochemical internalisation (PCI) treatment. Using this combination revealed that an endosomal disruption is highly effective in cell penetrating peptide (CPP) mediated transduction, whereas lipid-mediated transductions lead to a lower signal spreading throughout the cytosol. No change in the signal distribution could be achieved in treatments using non-lipid polymers as a transduction reagent. Therefore, the combination of protein transduction protocols based on CPPs with the endosomolytic treatment PCI can facilitate protein transduction experiments in vitro. PMID:23285056

Enhancing endosomal escape of transduced proteins by photochemical internalisation.

PubMed

Mellert, Kevin; Lamla, Markus; Scheffzek, Klaus; Wittig, Rainer; Kaufmann, Dieter

2012-01-01

Induced internalisation of functional proteins into cultured cells has become an important aspect in a rising number of in vitro and in vivo assays. The endo-lysosomal entrapment of the transduced proteins remains the major problem in all transduction protocols. In this study we compared the efficiency, cytotoxicity and protein targeting of different commercially available transduction reagents by transducing a well-studied fluorescently labelled protein (Atto488-bovine serum albumin) into cultured human sarcoma cells. The amount of internalised protein and toxicity differed between the different reagents, but the percentage of transduced cells was consistently high. Furthermore, in all protocols the signals of the transduced Atto488-BSA were predominantly punctual consistent with an endosomal localisation. To overcome the endosomal entrapment, the transduction protocols were combined with a photochemical internalisation (PCI) treatment. Using this combination revealed that an endosomal disruption is highly effective in cell penetrating peptide (CPP) mediated transduction, whereas lipid-mediated transductions lead to a lower signal spreading throughout the cytosol. No change in the signal distribution could be achieved in treatments using non-lipid polymers as a transduction reagent. Therefore, the combination of protein transduction protocols based on CPPs with the endosomolytic treatment PCI can facilitate protein transduction experiments in vitro.

Conditional Anomaly Detection with Soft Harmonic Functions

PubMed Central

Valko, Michal; Kveton, Branislav; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2012-01-01

In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response or a class label. We develop a new non-parametric approach for conditional anomaly detection based on the soft harmonic solution, with which we estimate the confidence of the label to detect anomalous mislabeling. We further regularize the solution to avoid the detection of isolated examples and examples on the boundary of the distribution support. We demonstrate the efficacy of the proposed method on several synthetic and UCI ML datasets in detecting unusual labels when compared to several baseline approaches. We also evaluate the performance of our method on a real-world electronic health record dataset where we seek to identify unusual patient-management decisions. PMID:25309142

Conditional Anomaly Detection with Soft Harmonic Functions.

PubMed

Valko, Michal; Kveton, Branislav; Valizadegan, Hamed; Cooper, Gregory F; Hauskrecht, Milos

2011-01-01

In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response or a class label. We develop a new non-parametric approach for conditional anomaly detection based on the soft harmonic solution, with which we estimate the confidence of the label to detect anomalous mislabeling. We further regularize the solution to avoid the detection of isolated examples and examples on the boundary of the distribution support. We demonstrate the efficacy of the proposed method on several synthetic and UCI ML datasets in detecting unusual labels when compared to several baseline approaches. We also evaluate the performance of our method on a real-world electronic health record dataset where we seek to identify unusual patient-management decisions.

Collaborative labeling of malignant glioma with WebMILL: a first look

NASA Astrophysics Data System (ADS)

Singh, Eesha; Asman, Andrew J.; Xu, Zhoubing; Chambless, Lola; Thompson, Reid; Landman, Bennett A.

2012-02-01

Malignant gliomas are the most common form of primary neoplasm in the central nervous system, and one of the most rapidly fatal of all human malignancies. They are treated by maximal surgical resection followed by radiation and chemotherapy. Herein, we seek to improve the methods available to quantify the extent of tumors using newly presented, collaborative labeling techniques on magnetic resonance imaging. Traditionally, labeling medical images has entailed that expert raters operate on one image at a time, which is resource intensive and not practical for very large datasets. Using many, minimally trained raters to label images has the possibility of minimizing laboratory requirements and allowing high degrees of parallelism. A successful effort also has the possibility of reducing overall cost. This potentially transformative technology presents a new set of problems, because one must pose the labeling challenge in a manner accessible to people with little or no background in labeling medical images and raters cannot be expected to read detailed instructions. Hence, a different training method has to be employed. The training must appeal to all types of learners and have the same concepts presented in multiple ways to ensure that all the subjects understand the basics of labeling. Our overall objective is to demonstrate the feasibility of studying malignant glioma morphometry through statistical analysis of the collaborative efforts of many, minimally-trained raters. This study presents preliminary results on optimization of the WebMILL framework for neoplasm labeling and investigates the initial contributions of 78 raters labeling 98 whole-brain datasets.

21 CFR 73.2400 - Pyrophyllite.

Code of Federal Regulations, 2012 CFR

2012-04-01

... ADDITIVES EXEMPT FROM CERTIFICATION Cosmetics § 73.2400 Pyrophyllite. (a) Identity and specifications. The... applied cosmetics, in amounts consistent with good manufacturing practice. (c) Labeling requirements. The...

21 CFR 73.2400 - Pyrophyllite.

Code of Federal Regulations, 2014 CFR

2014-04-01

... ADDITIVES EXEMPT FROM CERTIFICATION Cosmetics § 73.2400 Pyrophyllite. (a) Identity and specifications. The... applied cosmetics, in amounts consistent with good manufacturing practice. (c) Labeling requirements. The...

21 CFR 73.2400 - Pyrophyllite.

Code of Federal Regulations, 2013 CFR

2013-04-01

... ADDITIVES EXEMPT FROM CERTIFICATION Cosmetics § 73.2400 Pyrophyllite. (a) Identity and specifications. The... applied cosmetics, in amounts consistent with good manufacturing practice. (c) Labeling requirements. The...

Multi-label literature classification based on the Gene Ontology graph.

PubMed

Jin, Bo; Muller, Brian; Zhai, Chengxiang; Lu, Xinghua

2008-12-08

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

Consumer perceptions of front-of-package labelling systems and healthiness of foods.

PubMed

Savoie, Nathalie; Barlow Gale, Karine; Harvey, Karen L; Binnie, Mary Ann; Pasut, Laura

2013-09-19

The purpose of this study was to assess the impact of four different front-of-package (FOP) labelling systems on consumer perception and purchasing intent of food, and whether these systems help consumers select a balanced pattern of eating. The four FOP labelling systems studied included two nutrient-specific systems ‒ the Traffic Light (TL) and the Guideline Daily Amount (GDA) ‒ and two summary indicator systems ‒ NuVal(®) and My-5(®). Phase 1 was a small study with 36 participants to determine consumer understanding of the four FOP labelling systems and to inform the development of the questions for Phase 2, which consisted of a survey of 2,200 adults obtained through an online panel. Although the TL and GDA were rated similar to the Nutrition Facts table in terms of attributes, these FOP systems were considered more visually appealing. Consumers indicated that the numeric summary indicator systems did not provide sufficient information. Approximately half of the respondents indicated that the FOP systems would help them make healthier choices. However, due to the limitations of each, consumers often misinterpreted a food's healthiness compared to their baseline perceptions. Similarly, consumers' intent to purchase based on the FOP system did not show a consistent pattern. Although well received by consumers, FOP labelling systems can lead to confusion depending on perceived understanding of the system used. The nutrient-specific systems tend to be preferred by most consumers; however, the overall impact on selecting healthier eating patterns has yet to be demonstrated.

Detecting experimental techniques and selecting relevant documents for protein-protein interactions from biomedical literature

PubMed Central

2011-01-01

Background 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. Results 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. Conclusions 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. PMID:22151769

Food and the consumer: could labelling be the answer?

PubMed

Kerr, Maeve A; McCann, Mary T; Livingstone, M Barbara E

2015-05-01

Extensive research into the impact of nutrition labelling across Europe has shown that many consumers can effectively use a nutrition label to rank a food for healthiness. The present paper considers observational and laboratory evidence which has examined the impact of nutrition labelling (on food packaging and at point of purchase) on dietary behaviour. In addition, the potential counterproductive effects of foods bearing 'healthy' nutrition labels are examined. The observational evidence provides a useful insight into the key characteristics of nutrition label use. Those most likely to engage with nutrition labels are more likely to have a diet related disease and/or be on a weight loss diet and have a good overall diet quality. Experimental evidence, while limited, suggests that serving size information may be overlooked by consumers. In fact, there may be a tendency among consumers to overeat foods that are perceived to be healthier. The findings from the present paper suggest that if nutrition labelling is to be considered a strategy to facilitate consumers in managing their energy intake, it must coincide with salient, consistent and simple serving size information on the front of food packages and at the point of purchase. There is a clear need for more experimental research using robust methodologies, to examine the impact of nutrition information on dietary intake. In the meantime, there should be greater attention given to portion size within national dietary guidance.

Webly-Supervised Fine-Grained Visual Categorization via Deep Domain Adaptation.

PubMed

Xu, Zhe; Huang, Shaoli; Zhang, Ya; Tao, Dacheng

2018-05-01

Learning visual representations from web data has recently attracted attention for object recognition. Previous studies have mainly focused on overcoming label noise and data bias and have shown promising results by learning directly from web data. However, we argue that it might be better to transfer knowledge from existing human labeling resources to improve performance at nearly no additional cost. In this paper, we propose a new semi-supervised method for learning via web data. Our method has the unique design of exploiting strong supervision, i.e., in addition to standard image-level labels, our method also utilizes detailed annotations including object bounding boxes and part landmarks. By transferring as much knowledge as possible from existing strongly supervised datasets to weakly supervised web images, our method can benefit from sophisticated object recognition algorithms and overcome several typical problems found in webly-supervised learning. We consider the problem of fine-grained visual categorization, in which existing training resources are scarce, as our main research objective. Comprehensive experimentation and extensive analysis demonstrate encouraging performance of the proposed approach, which, at the same time, delivers a new pipeline for fine-grained visual categorization that is likely to be highly effective for real-world applications.

Shape complexes: the intersection of label orderings and star convexity constraints in continuous max-flow medical image segmentation

PubMed Central

Baxter, John S. H.; Inoue, Jiro; Drangova, Maria; Peters, Terry M.

2016-01-01

Abstract. Optimization-based segmentation approaches deriving from discrete graph-cuts and continuous max-flow have become increasingly nuanced, allowing for topological and geometric constraints on the resulting segmentation while retaining global optimality. However, these two considerations, topological and geometric, have yet to be combined in a unified manner. The concept of “shape complexes,” which combine geodesic star convexity with extendable continuous max-flow solvers, is presented. These shape complexes allow more complicated shapes to be created through the use of multiple labels and super-labels, with geodesic star convexity governed by a topological ordering. These problems can be optimized using extendable continuous max-flow solvers. Previous approaches required computationally expensive coordinate system warping, which are ill-defined and ambiguous in the general case. These shape complexes are demonstrated in a set of synthetic images as well as vessel segmentation in ultrasound, valve segmentation in ultrasound, and atrial wall segmentation from contrast-enhanced CT. Shape complexes represent an extendable tool alongside other continuous max-flow methods that may be suitable for a wide range of medical image segmentation problems. PMID:28018937

Non-rigid image registration using graph-cuts.

PubMed

Tang, Tommy W H; Chung, Albert C S

2007-01-01

Non-rigid image registration is an ill-posed yet challenging problem due to its supernormal high degree of freedoms and inherent requirement of smoothness. Graph-cuts method is a powerful combinatorial optimization tool which has been successfully applied into image segmentation and stereo matching. Under some specific constraints, graph-cuts method yields either a global minimum or a local minimum in a strong sense. Thus, it is interesting to see the effects of using graph-cuts in non-rigid image registration. In this paper, we formulate non-rigid image registration as a discrete labeling problem. Each pixel in the source image is assigned a displacement label (which is a vector) indicating which position in the floating image it is spatially corresponding to. A smoothness constraint based on first derivative is used to penalize sharp changes in displacement labels across pixels. The whole system can be optimized by using the graph-cuts method via alpha-expansions. We compare 2D and 3D registration results of our method with two state-of-the-art approaches. It is found that our method is more robust to different challenging non-rigid registration cases with higher registration accuracy.

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.

Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies.

PubMed

Koch, Lisa M; Rajchl, Martin; Bai, Wenjia; Baumgartner, Christian F; Tong, Tong; Passerat-Palmbach, Jonathan; Aljabar, Paul; Rueckert, Daniel

2017-08-22

Multi-atlas segmentation is a widely used tool in medical image analysis, providing robust and accurate results by learning from annotated atlas datasets. However, the availability of fully annotated atlas images for training is limited due to the time required for the labelling task. Segmentation methods requiring only a proportion of each atlas image to be labelled could therefore reduce the workload on expert raters tasked with annotating atlas images. To address this issue, we first re-examine the labelling problem common in many existing approaches and formulate its solution in terms of a Markov Random Field energy minimisation problem on a graph connecting atlases and the target image. This provides a unifying framework for multi-atlas segmentation. We then show how modifications in the graph configuration of the proposed framework enable the use of partially annotated atlas images and investigate different partial annotation strategies. The proposed method was evaluated on two Magnetic Resonance Imaging (MRI) datasets for hippocampal and cardiac segmentation. Experiments were performed aimed at (1) recreating existing segmentation techniques with the proposed framework and (2) demonstrating the potential of employing sparsely annotated atlas data for multi-atlas segmentation.

Cooperative inference: Features, objects, and collections.

PubMed

Searcy, Sophia Ray; Shafto, Patrick

2016-10-01

Cooperation plays a central role in theories of development, learning, cultural evolution, and education. We argue that existing models of learning from cooperative informants have fundamental limitations that prevent them from explaining how cooperation benefits learning. First, existing models are shown to be computationally intractable, suggesting that they cannot apply to realistic learning problems. Second, existing models assume a priori agreement about which concepts are favored in learning, which leads to a conundrum: Learning fails without precise agreement on bias yet there is no single rational choice. We introduce cooperative inference, a novel framework for cooperation in concept learning, which resolves these limitations. Cooperative inference generalizes the notion of cooperation used in previous models from omission of labeled objects to the omission values of features, labels for objects, and labels for collections of objects. The result is an approach that is computationally tractable, does not require a priori agreement about biases, applies to both Boolean and first-order concepts, and begins to approximate the richness of real-world concept learning problems. We conclude by discussing relations to and implications for existing theories of cognition, cognitive development, and cultural evolution. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Sprinkler Body Fact Sheet

EPA Pesticide Factsheets

Landscape irrigation sprinklers are often installed at sites where the system pressure is higher than what is recommended for the sprinkler body, thus resulting in system inefficiencies. WaterSense labeled sprinkler bodies can address this problem.

ALE: automated label extraction from GEO metadata.

PubMed

Giles, Cory B; Brown, Chase A; Ripperger, Michael; Dennis, Zane; Roopnarinesingh, Xiavan; Porter, Hunter; Perz, Aleksandra; Wren, Jonathan D

2017-12-28

NCBI's Gene Expression Omnibus (GEO) is a rich community resource containing millions of gene expression experiments from human, mouse, rat, and other model organisms. However, information about each experiment (metadata) is in the format of an open-ended, non-standardized textual description provided by the depositor. Thus, classification of experiments for meta-analysis by factors such as gender, age of the sample donor, and tissue of origin is not feasible without assigning labels to the experiments. Automated approaches are preferable for this, primarily because of the size and volume of the data to be processed, but also because it ensures standardization and consistency. While some of these labels can be extracted directly from the textual metadata, many of the data available do not contain explicit text informing the researcher about the age and gender of the subjects with the study. To bridge this gap, machine-learning methods can be trained to use the gene expression patterns associated with the text-derived labels to refine label-prediction confidence. Our analysis shows only 26% of metadata text contains information about gender and 21% about age. In order to ameliorate the lack of available labels for these data sets, we first extract labels from the textual metadata for each GEO RNA dataset and evaluate the performance against a gold standard of manually curated labels. We then use machine-learning methods to predict labels, based upon gene expression of the samples and compare this to the text-based method. Here we present an automated method to extract labels for age, gender, and tissue from textual metadata and GEO data using both a heuristic approach as well as machine learning. We show the two methods together improve accuracy of label assignment to GEO samples.

Nutrition labelling is a trade policy issue: lessons from an analysis of specific trade concerns at the World Trade Organization.

PubMed

Thow, Anne Marie; Jones, Alexandra; Hawkes, Corinna; Ali, Iqra; Labonté, Ronald

2017-01-12

Interpretive nutrition labels provide simplified nutrient-specific text and/or symbols on the front of pre-packaged foods, to encourage and enable consumers to make healthier choices. This type of labelling has been proposed as part of a comprehensive policy response to the global epidemic of non-communicable diseases. However, regulation of nutrition labelling falls under the remit of not just the health sector but also trade. Specific Trade Concerns have been raised at the World Trade Organization's Technical Barriers to Trade Committee regarding interpretive nutrition labelling initiatives in Thailand, Chile, Indonesia, Peru and Ecuador. This paper presents an analysis of the discussions of these concerns. Although nutrition labelling was identified as a legitimate policy objective, queries were raised regarding the justification of the specific labelling measures proposed, and the scientific evidence for effectiveness of such measures. Concerns were also raised regarding the consistency of the measures with international standards. Drawing on policy learning theory, we identified four lessons for public health policy makers, including: strategic framing of nutrition labelling policy objectives; pro-active policy engagement between trade and health to identify potential trade issues; identifying ways to minimize potential 'practical' trade concerns; and engagement with the Codex Alimentarius Commission to develop international guidance on interpretative labelling. This analysis indicates that while there is potential for trade sector concerns to stifle innovation in nutrition labelling policy, care in how interpretive nutrition labelling measures are crafted in light of trade commitments can minimize such a risk and help ensure that trade policy is coherent with nutrition action. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Interfacial Polymerization for Colorimetric Labeling of Protein Expression in Cells

PubMed Central

Lilly, Jacob L.; Sheldon, Phillip R.; Hoversten, Liv J.; Romero, Gabriela; Balasubramaniam, Vivek; Berron, Brad J.

2014-01-01

Determining the location of rare proteins in cells typically requires the use of on-sample amplification. Antibody based recognition and enzymatic amplification is used to produce large amounts of visible label at the site of protein expression, but these techniques suffer from the presence of nonspecific reactivity in the biological sample and from poor spatial control over the label. Polymerization based amplification is a recently developed alternative means of creating an on-sample amplification for fluorescence applications, while not suffering from endogenous labels or loss of signal localization. This manuscript builds upon polymerization based amplification by developing a stable, archivable, and colorimetric mode of amplification termed Polymer Dye Labeling. The basic concept involves an interfacial polymer grown at the site of protein expression and subsequent staining of this polymer with an appropriate dye. The dyes Evans Blue and eosin were initially investigated for colorimetric response in a microarray setting, where both specifically stained polymer films on glass. The process was translated to the staining of protein expression in human dermal fibroblast cells, and Polymer Dye Labeling was specific to regions consistent with desired protein expression. The labeling is stable for over 200 days in ambient conditions and is also compatible with modern mounting medium. PMID:25536421

75 FR 58077 - Revisions and Additions to Motor Vehicle Fuel Economy Label

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-23

...The Environmental Protection Agency (EPA) and the National Highway Traffic Safety Administration (NHTSA) are conducting a joint rulemaking to redesign and add information to the current fuel economy label that is posted on the window sticker of all new cars and light- duty trucks sold in the U.S. The redesigned label will provide new information to American consumers about the fuel economy and consumption, fuel costs, and environmental impacts associated with purchasing new vehicles beginning with model year 2012 cars and trucks. This action will also develop new labels for certain advanced technology vehicles, which are poised to enter the U.S. market, in particular plug-in hybrid electric vehicles and electric vehicles. NHTSA and EPA are proposing these changes because the Energy Independence and Security Act (EISA) of 2007 imposes several new labeling requirements, because the agencies believe that the current labels can be improved to help consumers make more informed vehicle purchase decisions, and because the time is right to develop new labels for advanced technology vehicles that are being commercialized. This proposal is also consistent with the recent joint rulemaking by EPA and NHTSA that established harmonized federal greenhouse gas (GHG) emissions and corporate average fuel economy (CAFE) standards for new cars, sport utility vehicles, minivans, and pickup trucks for model years 2012-2016.

Communicating doses of pediatric liquid medicines to parents/caregivers: a comparison of written dosing directions on prescriptions with labels applied by dispensed pharmacy.

PubMed

Shah, Rita; Blustein, Leona; Kuffner, Ed; Davis, Lisa

2014-03-01

To identify and compare volumetric measures used by healthcare providers in communicating dosing instructions for pediatric liquid prescriptions to parents/caregivers. Dosing instructions were retrospectively reviewed for the 10 most frequently prescribed liquid medications dispensed from 4 community pharmacies for patients aged ≤ 12 years during a 3-month period. Volumetric measures on original prescriptions (ie, milliliters, teaspoons) were compared with those utilized by the pharmacist on the pharmacy label dispensed to the parent/caregiver. Of 649 prescriptions and corresponding pharmacy labels evaluated, 68% of prescriptions and 62% of pharmacy labels communicated dosing in milliliters, 24% of prescriptions and 29% of pharmacy labels communicated dosing in teaspoonfuls, 7% of prescriptions and 0% of pharmacy labels communicated dosing in other measures (ie, milligrams, cubic centimeters, "dose"), and 25% of dispensed pharmacy labels did not reflect units as written in the prescription. Volumetric measures utilized by healthcare professionals in dosing instructions for prescription pediatric oral liquid medications are not consistent. Healthcare professionals and parents/caregivers should be educated on safe dosing practices for liquid pediatric medications. Generalizability to the larger pediatric population may vary depending on pharmacy chain, location, and medications evaluated. Copyright © 2014 Mosby, Inc. All rights reserved.

Use of the Go-for-Green nutrition labeling system in military dining facilities is associated with lower fat intake.

PubMed

Arsenault, Joanne E; Singleton, Michelle C; Funderburk, LesLee K

2014-07-01

Point-of-purchase nutrition labeling is a potential tool to help consumers choose healthier foods. The objectives of our study were to survey soldiers on their use of the Go-for-Green nutrition labeling system in dining facilities and compare characteristics of users and nonusers. The study population consisted of 299 US Army active duty soldiers at two US Army installations. The frequency of use of food labels and characteristics were calculated and differences in characteristics of label users and nonusers were compared using χ(2) and regression analyses. Forty-seven percent of soldiers reported using nutrition labels to make food choices always or sometimes. Users were more likely to be following a special diet (P=0.04) and to take a multivitamin or protein supplement (P<0.001) than nonusers. Users consumed a mean of 32% of energy from fat vs 36% for nonusers (P<0.0001) after adjusting for reported use of special diets. Use of the Go-for-Green nutrition labeling system is encouraging and should be further investigated to determine whether the program is actually influencing dietary choices in broader military settings. Copyright © 2014 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Does the Australasian "Health Star Rating" Front of Pack Nutritional Label System Work?

PubMed

Hamlin, Robert; McNeill, Lisa

2016-06-01

This article describes an experiment to measure the impact of the Australasian "Health Star Rating" front of pack nutritional label system on consumer choice behaviour. This system presents a one-half to five star rating of nutritional quality via the front facings of food product packages. While this system has been recently rolled out across Australasia, no test of its impact on food choice has been conducted. A sample of 1200 consumers was recruited on exit from supermarkets in New Zealand. A 2 × 2 factorial design was used with two levels of cold cereal product nutritional status (high, five star/low, two star) and two levels of the Health Star Rating label (present/absent). The dependent variable was revealed choice behaviour. The results indicated that the presence of the label had a significant depressive effect on consumer preference, but that this impact was not moderated in any way by the nutritional status expressed by the label. The result represents a significant functional failure of the Health Star Rating label in this research environment. The nature of the failure is consistent with the consumers processing the label in much the same way as the nominal brand cues that dominate the retail food packaging.

[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.

Calorie labeling in a rural middle school influences food selection: findings from community-based participatory research.

PubMed

Hunsberger, Monica; McGinnis, Paul; Smith, Jamie; Beamer, Beth Ann; O'Malley, Jean

2015-01-01

Calorie labeling at the point-of-purchase in chain restaurants has been shown to reduce energy intake. To investigate the impact of point-of-purchase calorie information at one rural middle school. With a community-based participatory research framework a mixed method approach was used to evaluate the impact of point-of-purchase calorie information. Students in grades 6-8, dining at the school cafeteria January and February 2010, participated for 17 school days each month; in January a menu was offered in the usual manner without calorie labels; the same menu was prepared in February with the addition of calorie labels at point-of-purchase. Gross calories served per student were measured each day allowing for matched comparison by menu. In March/April of 2010, 32 students who ate in the cafeteria 3 or more times per week were interviewed regarding their views on menu labeling. Calorie consumption decreased by an average of 47 calories/day; fat intake reduced by 2.1 grams/day. Five main themes were consistent throughout the interviews. Point-of-purchase calorie labels can play a role in reducing the number of calories consumed by middle school age children at the lunch. The majority of students interviewed found the calorie labels helped them choose healthier food.

Does the Australasian “Health Star Rating” Front of Pack Nutritional Label System Work?

PubMed Central

Hamlin, Robert; McNeill, Lisa

2016-01-01

This article describes an experiment to measure the impact of the Australasian “Health Star Rating” front of pack nutritional label system on consumer choice behaviour. This system presents a one-half to five star rating of nutritional quality via the front facings of food product packages. While this system has been recently rolled out across Australasia, no test of its impact on food choice has been conducted. A sample of 1200 consumers was recruited on exit from supermarkets in New Zealand. A 2 × 2 factorial design was used with two levels of cold cereal product nutritional status (high, five star/low, two star) and two levels of the Health Star Rating label (present/absent). The dependent variable was revealed choice behaviour. The results indicated that the presence of the label had a significant depressive effect on consumer preference, but that this impact was not moderated in any way by the nutritional status expressed by the label. The result represents a significant functional failure of the Health Star Rating label in this research environment. The nature of the failure is consistent with the consumers processing the label in much the same way as the nominal brand cues that dominate the retail food packaging. PMID:27258305

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.

Proximity-Induced Covalent Labeling of Proteins with a Reactive Fluorophore-Binding Peptide Tag.

PubMed

Sunbul, Murat; Nacheva, Lora; Jäschke, Andres

2015-08-19

Labeling of proteins with fluorescent dyes in live cells enables the investigation of their roles in biological systems by fluorescence microscopy. Because the labeling procedure should not disturb the native function of the protein of interest, it is of high importance to find the optimum labeling method for the problem to be studied. Here, we developed a rapid one-step method to covalently and site-specifically label proteins with a TexasRed fluorophore in vitro and in live bacteria. To this end, a genetically encodable TexasRed fluorophore-binding peptide (TR512) was converted into a reactive tag (ReacTR) by adjoining a cysteine residue which rapidly reacts with N-α-chloroacetamide-conjugated TexasRed fluorophore owing to the proximity effect; ReacTR tag first binds to the TexasRed fluorophore and this interaction brings the nucleophilic cysteine and the electrophilic N-α-chloroacetamide groups in close proximity. Our method has several advantages over existing methods: (i) it utilizes a peptide tag much smaller than fluorescent proteins, the SNAP, CLIP, or HaLo tags; (ii) it allows for labeling of proteins with a small, photostable, red-emitting TexasRed fluorophore; (iii) the probe used is very easy to synthesize; (iv) no enzyme is required to transfer the fluorophore to the peptide tag; and (v) labeling yields a stable covalent product in a very fast reaction.

Patient, consumer, client, or customer: what do people want to be called?

PubMed Central

Deber, Raisa B.; Kraetschmer, Nancy; Urowitz, Sara; Sharpe, Natasha

2005-01-01

Abstract Objective  To clarify preferred labels for people receiving health care. Background  The proper label to describe people receiving care has evoked considerable debate among providers and bio‐ethicists, but there is little evidence as to the preferences of the people involved. Design  We analysed dictionary definitions as to the derivation and connotations of such potential labels as: patient, client, customer, consumer, partner and survivor. We then surveyed outpatients from four clinical populations in Ontario, Canada about their feelings about these labels. Setting and participants  People from breast cancer (n = 202), prostate disease (n = 202) and fracture (n = 202) clinics in an urban Canadian teaching hospital (Sharpe study), and people with HIV/AIDS at 10 specialty care clinics and three primary care practices affiliated with the HIV Ontario Observational Database (n = 431). Variables and outcome measures  The survey instruments included questions about opinion of label, role in treatment decision‐making (the Problem Solving Decision Making scale), trust, use of information and health status. Results  Our respondents moderately liked the label ‘patient’. The other alternatives evoked moderate to strong dislike. Conclusions  Many alternatives to ‘patient’ incorporate assumptions (e.g. a market relationship) which care recipients may also find objectionable. People who are receiving care find the label ‘patient’ much less objectionable than the alternatives that have been suggested. PMID:16266422

An examination of perceptions of individuals with an intellectual disability, with and without co-morbid schizophrenia: effects of labels on stigma.

PubMed

Rasdale, A R; Warman, D M; Phalen, P L

2018-06-01

Research demonstrates negative perceptions of individuals with intellectual disabilities (ID) and individuals with schizophrenia, but no study has examined ID with a co-morbid psychiatric disorder. The present study examined the social distance desired from and perceptions of dangerousness of ID, schizophrenia and co-morbid schizophrenia and ID and examined the impact of providing a label for the behaviours presented in a vignette. A total of 160 participants, all university students, were randomly assigned to one of six vignettes detailing a person with schizophrenia, ID, or a person with both presenting problems. Half of the participants were randomly assigned to read vignettes that had a label provided for the behaviours of the target. Participants desired more social distance from the unlabelled than labelled targets. Presence of schizophrenia resulted in increased social distance, but co-morbid ID and schizophrenia elicited less desire for social distance than schizophrenia alone. Schizophrenia resulted in more perceived danger, but labelled co-morbid schizophrenia and ID resulted in little perceived danger. Labels resulted in positive outcomes, particularly, when ID was co-morbid with schizophrenia. Schizophrenia stigma appears to be impacted by an ID label, indicating educating the public about the spectrum of co-morbidity may be useful. © 2018 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Peptide affinity labels for thrombin and other trypsin-like proteases

DOEpatents

Shaw, E.N.; Kettner, C.A.

1982-03-09

A peptide affinity label is disclosed of the formula (I): as given in the patent wherein X is a radical capable of acting as a leaving group in a nucleophilic substitution reaction; A is an aromatic amino acid residue; B is H, or a C[sub 1]--C[sub 4] alkyl group, or aryl; Y is selected from the group consisting of hydrogen, aroyl, C[sub 1]--C[sub 6] acyl, and Q--(A)--[sub n], wherein Q = hydrogen, aroyl, or C[sub 1]--C[sub 6] acyl, n = 1--10, A is an amino acid residue selected from the aliphatic, hydroxy-containing, carboxylic acid group, and amide-thereofcontaining, aromatic, sulfur-containing and imino-containing amino acids; and wherein J is selected from the group consisting of --CH[sub 2]--, --CH[sub 2]--CH[sub 2]--, --CH[sub 2]--CH[sub 2]--CH[sub 2]--, --CH[double bond]CH-- and --CH(OH)--CH[sub 2]. The affinity label is useful for irreversibly inactivating thrombin and trypsin-like enzymes and may be used as a potential anticlotting agent. 2 figs.

Psychometrics of the Laffrey Health Conception Scale for adolescents.

PubMed

Yarcheski, Adela; Mahon, Noreen E; Yarcheski, Thomas J

2005-01-01

The purposes of this methodological study were to factor analyze the Laffrey Health Conception Scale (LHCS) and to assess construct validity of the instrument with early adolescents. The final sample consisted of 230 early adolescents, aged 12 to 14, who responded to instrument packets in classrooms in an urban middle school. Data obtained on the LHCS were subjected to principal components factor analysis with oblique rotation. A two-factor solution was accepted, which is consistent with early adolescents' conceptions of health. Factor I was labeled Wellness and Factor II was labeled Clinical Health. A higher order factor analysis yielded one factor with 26 items, labeled the LHCS for Early Adolescents. The 26-item LHCS had a coefficient alpha of .95. Construct validity was assessed by testing three theoretical propositions, which significantly linked health conception to social support, self-esteem, and positive health practices. The findings indicate that the LHCS is a reliable and valid measure of health conceptions in early adolescents. Results also offer flexibility to researchers interested in testing theory involving the constructs of the definition of health, wellness, and clinical health in early adolescents.

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.

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.

Self-medication.

PubMed

Lottier, W I

1978-10-01

Self-medication and drug interaction have been a problem in recent years. Pharmacists in ethical pharmacies and neighborhood establishments can best monitor these problems through use of patient profile records and consultations. The pharmacist should advise the public on over-the-counter (OTC) purchases. Auxiliary labels are recommended for use on containers to prevent drug interactions. Members of the black community have some specific problems with respect to self medications. These are addressed in this article. Self-medication, under supervision, is proper and can be controlled.

Synthesis Of Labeled Metabolites

DOEpatents

Martinez, Rodolfo A.; Silks, III, Louis A.; Unkefer, Clifford J.; Atcher, Robert

2004-03-23

The present invention is directed to labeled compounds, for example, isotopically enriched mustard gas metabolites including: [1,1',2,2'-.sup.13 C.sub.4 ]ethane, 1,1'-sulfonylbis[2-(methylthio); [1,1',2,2'-.sup.13 C.sub.4 ]ethane, 1-[[2-(methylsulfinyl)ethyl]sulfonyl]-2-(methylthio); [1,1',2,2'-.sup.13 C.sub.4 ]ethane, 1,1'-sulfonylbis[2-(methylsulfinyl)]; and, 2,2'-sulfinylbis([1,2-.sup.13 C.sub.2 ]ethanol of the general formula ##STR1## where Q.sup.1 is selected from the group consisting of sulfide (--S--), sulfone (--S(O)--), sulfoxide (--S(O.sub.2)--) and oxide (--O--), at least one C* is .sup.13 C, X is selected from the group consisting of hydrogen and deuterium, and Z is selected from the group consisting of hydroxide (--OH), and --Q.sup.2 --R where Q.sup.2 is selected from the group consisting of sulfide (--S--), sulfone(--S(O)--), sulfoxide (--S(O.sub.2)--) and oxide (--O--), and R is selected from the group consisting of hydrogen, a C.sub.1 to C.sub.4 lower alkyl, and amino acid moieties, with the proviso that when Z is a hydroxide and Q.sup.1 is a sulfide, then at least one X is deuterium.

76 FR 54932 - Revisions and Additions to Motor Vehicle Fuel Economy Label; Correction

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-06

...The Environmental Protection Agency and the Department of Transportation published a final rule regarding labeling of cars and trucks with fuel economy and environmental information in the Federal Register on July 6, 2011 (76 FR 39478). An error in the amendatory instruction for Sec. 86.1867-12 inadvertently calls for the removal of paragraph (a)(3)(iv)(A) of that section. This rule revises the amendatory language for consistency with the regulatory text.

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

Measurement of skeletal muscle perfusion dynamics with pseudo-continuous arterial spin labeling (pCASL): Assessment of relative labeling efficiency at rest and during hyperemia, and comparison to pulsed arterial spin labeling (PASL).

PubMed

Englund, Erin K; Rodgers, Zachary B; Langham, Michael C; Mohler, Emile R; Floyd, Thomas F; Wehrli, Felix W

2016-10-01

To compare calf skeletal muscle perfusion measured with pulsed arterial spin labeling (PASL) and pseudo-continuous arterial spin labeling (pCASL) methods, and to assess the variability of pCASL labeling efficiency in the popliteal artery throughout an ischemia-reperfusion paradigm. At 3T, relative pCASL labeling efficiency was experimentally assessed in five subjects by measuring the signal intensity of blood in the popliteal artery just distal to the labeling plane immediately following pCASL labeling or control preparation pulses, or without any preparation pulses throughout separate ischemia-reperfusion paradigms. The relative label and control efficiencies were determined during baseline, hyperemia, and recovery. In a separate cohort of 10 subjects, pCASL and PASL sequences were used to measure reactive hyperemia perfusion dynamics. Calculated pCASL labeling and control efficiencies did not differ significantly between baseline and hyperemia or between hyperemia and recovery periods. Relative to the average baseline, pCASL label efficiency was 2 ± 9% lower during hyperemia. Perfusion dynamics measured with pCASL and PASL did not differ significantly (P > 0.05). Average leg muscle peak perfusion was 47 ± 20 mL/min/100g or 50 ± 12 mL/min/100g, and time to peak perfusion was 25 ± 3 seconds and 25 ± 7 seconds from pCASL and PASL data, respectively. Differences of further metrics parameterizing the perfusion time course were not significant between pCASL and PASL measurements (P > 0.05). No change in pCASL labeling efficiency was detected despite the almost 10-fold increase in average blood flow velocity in the popliteal artery. pCASL and PASL provide precise and consistent measurement of skeletal muscle reactive hyperemia perfusion dynamics. J. MAGN. RESON. IMAGING 2016;44:929-939. © 2016 International Society for Magnetic Resonance in Medicine.

Structural analysis of N-glycans by the glycan-labeling method using 3-aminoquinoline-based liquid matrix in negative-ion MALDI-MS.

PubMed

Nishikaze, Takashi; Kaneshiro, Kaoru; Kawabata, Shin-ichirou; Tanaka, Koichi

2012-11-06

Negative-ion fragmentation of underivatized N-glycans has been proven to be more informative than positive-ion fragmentation. Fluorescent labeling via reductive amination is often employed for glycan analysis, but little is known about the influence of the labeling group on negative-ion fragmentation. We previously demonstrated that the on-target glycan-labeling method using 3-aminoquinoline/α-cyano-4-hydroxycinnamic acid (3AQ/CHCA) liquid matrix enables highly sensitive, rapid, and quantitative N-glycan profiling analysis. The current study investigates the suitability of 3AQ-labeled N-glycans for structural analysis based on negative-ion collision-induced dissociation (CID) spectra. 3AQ-labeled N-glycans exhibited simple and informative CID spectra similar to those of underivatized N-glycans, with product ions due to cross-ring cleavages of the chitobiose core and ions specific to two antennae (D and E ions). The interpretation of diagnostic fragment ions suggested for underivatized N-glycans could be directly applied to the 3AQ-labeled N-glycans. However, fluorescently labeled N-glycans by conventional reductive amination, such as 2-aminobenzamide (2AB)- and 2-pyrydilamine (2PA)-labeled N-glycans, exhibited complicated CID spectra consisting of numerous signals formed by dehydration and multiple cleavages. The complicated spectra of 2AB- and 2PA-labeled N-glycans was found to be due to their open reducing-terminal N-acetylglucosamine (GlcNAc) ring, rather than structural differences in the labeling group in the N-glycan derivative. Finally, as an example, the on-target 3AQ labeling method followed by negative-ion CID was applied to structurally analyze neutral N-glycans released from human epidermal growth factor receptor type 2 (HER2) protein. The glycan-labeling method using 3AQ-based liquid matrix should facilitate highly sensitive quantitative and qualitative analyses of glycans.

Permeabilization of the plasma membrane of L1210 mouse leukemia cells using lithotripter shock waves.

PubMed

Gambihler, S; Delius, M; Ellwart, J W

1994-09-01

Permeabilization of L1210 cells by lithotripter shock waves in vitro was monitored by evaluating the accumulation of fluorescein-labeled dextrans with a relative molecular mass ranging from 3,900-2,000,000. Incubation with labeled dextran alone caused a dose- and time-dependent increase in cellular fluorescence as determined by flow cytometry, with a vesicular distribution pattern in the cells consistent with endocytotic uptake. Shock wave exposure prior to incubation with labeled dextran revealed similar fluorescence intensities compared to incubation with labeled dextran alone. When cells were exposed to shock waves in the presence of labeled dextran, mean cellular fluorescence was further increased, indicating additional internalization of the probe. Confocal laser scanning microscopy confirmed intracellular fluorescence of labeled dextran with a diffuse distribution pattern. Fluorescence-activated cell sorting with subsequent determination of proliferation revealed that permeabilized cells were viable and able to proliferate. Permeabilization of the membrane of L1210 cells by shock waves in vitro allowed loading of dextrans with a relative molecular mass up to 2,000,000. Permeabilization of tumor cells by shock waves provides a useful tool for introducing molecules into cells which might be of interest for drug targeting in tumor therapy in vivo.

Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

PubMed Central

Bakas, Spyridon; Akbari, Hamed; Sotiras, Aristeidis; Bilello, Michel; Rozycki, Martin; Kirby, Justin S.; Freymann, John B.; Farahani, Keyvan; Davatzikos, Christos

2017-01-01

Gliomas belong to a group of central nervous system tumors, and consist of various sub-regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for both clinical and computational studies, including radiomic and radiogenomic analyses. Towards this end, we release segmentation labels and radiomic features for all pre-operative multimodal magnetic resonance imaging (MRI) (n=243) of the multi-institutional glioma collections of The Cancer Genome Atlas (TCGA), publicly available in The Cancer Imaging Archive (TCIA). Pre-operative scans were identified in both glioblastoma (TCGA-GBM, n=135) and low-grade-glioma (TCGA-LGG, n=108) collections via radiological assessment. The glioma sub-region labels were produced by an automated state-of-the-art method and manually revised by an expert board-certified neuroradiologist. An extensive panel of radiomic features was extracted based on the manually-revised labels. This set of labels and features should enable i) direct utilization of the TCGA/TCIA glioma collections towards repeatable, reproducible and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments, as well as ii) performance evaluation of computer-aided segmentation methods, and comparison to our state-of-the-art method. PMID:28872634

The Age-related Positivity Effect and Tobacco Warning Labels

PubMed Central

Roberts, Megan E.; Peters, Ellen; Ferketich, Amy K.; Klein, Elizabeth G.

2016-01-01

Objectives This study tested whether age is a factor in viewing time for tobacco warning labels. The approach drew from previous work demonstrating an age-related positivity effect, whereby older adults show preferences toward positive and away from negative stimuli. Methods Participants were 295 daily smokers from Appalachian Ohio (age range: 21–68). All participants took part in an eye-tracking paradigm that captured the attention paid to elements of health warning labels in the context of magazine advertisements. Participants also reported on their past cessation attempts and their beliefs about the dangers of smoking. Results Consistent with theory on age-related positivity, older age predicted weaker beliefs about smoking risks, but only among those with no past-year quit attempts. In support of our primary hypothesis, older age was also related to a lower percentage of time spent viewing tobacco warning labels, both overall (text + image) and for the graphic image alone. These associations remained after controlling for cigarettes smoked per day. Conclusions Overall, findings suggest that age is an important consideration for the design of future graphic warning labels and other tobacco risk communications. For older adults, warning labels may need to be tailored to overcome the age-related positivity effect. PMID:27617273

The mechanism of vascular leakage induced by leukotriene E4. Endothelial contraction.

PubMed Central

Joris, I.; Majno, G.; Corey, E. J.; Lewis, R. A.

1987-01-01

This study identifies the microvascular target of leukotriene E4 (LTE4) by vascular labeling with carbon black and establishes the mechanism of its action at the cellular level by electron microscopy. LTE4 and its tripeptide precursor, leukotriene C4 (LTC4) were injected subcutaneously in guinea pigs. With LTE4, venular labeling was intense at 1000 and 100 ng and slight at 10 ng, with extinction at 1 ng. LTC4 induced a ring of labeled venules around a blank central area, suggestive of vasospasm. The nonpeptidyl leukotriene LTB4 induced no labeling. Histamine (1000 ng) induced an area of vascular labeling about equal to that by 1000 ng LTE4, but the labeling of individual venules was more intense. By electron microscopy, LTE4 was found to induce gaps in the endothelium of the venules; the endothelial cells adjacent to the gaps bulged into the lumen and showed wrinkled nuclei, consistent with cellular contraction. This ultrastructural evidence suggests that LTE4 increases vascular permeability by contraction of endothelial cells selectively, in the postcapillary venules, as was previously demonstrated for other inflammatory mediators, including histamine, serotonin, and bradykinin. Images Figure 2 Figure 3 Figure 4 PMID:3028143

Publication bias in situ.

PubMed

Phillips, Carl V

2004-08-05

Publication bias, as typically defined, refers to the decreased likelihood of studies' results being published when they are near the null, not statistically significant, or otherwise "less interesting." But choices about how to analyze the data and which results to report create a publication bias within the published results, a bias I label "publication bias in situ" (PBIS). PBIS may create much greater bias in the literature than traditionally defined publication bias (the failure to publish any result from a study). The causes of PBIS are well known, consisting of various decisions about reporting that are influenced by the data. But its impact is not generally appreciated, and very little attention is devoted to it. What attention there is consists largely of rules for statistical analysis that are impractical and do not actually reduce the bias in reported estimates. PBIS cannot be reduced by statistical tools because it is not fundamentally a problem of statistics, but rather of non-statistical choices and plain language interpretations. PBIS should be recognized as a phenomenon worthy of study - it is extremely common and probably has a huge impact on results reported in the literature - and there should be greater systematic efforts to identify and reduce it. The paper presents examples, including results of a recent HIV vaccine trial, that show how easily PBIS can have a large impact on reported results, as well as how there can be no simple answer to it. PBIS is a major problem, worthy of substantially more attention than it receives. There are ways to reduce the bias, but they are very seldom employed because they are largely unrecognized.

Evaluation of desialylation during 2-amino benzamide labeling of asparagine-linked oligosaccharides.

PubMed

Aich, Udayananth; Hurum, Deanna C; Basumallick, Lipika; Rao, Srinivasa; Pohl, Chris; Rohrer, Jeffrey S; Kandzia, Sebastian

2014-08-01

Labeling of released asparagine-linked (N-linked) oligosaccharides from glycoproteins is commonly performed to aid in the separation and detection of the oligosaccharide. Of the many available oligosaccharide labels, 2-amino benzamide (2-AB) is a popular choice for providing a fluorescent product. The derivatization conditions can potentially lead to oligosaccharide desialylation. This work evaluated the extent of sialic acid loss during 2-AB labeling of N-linked oligosaccharides released from bovine fetuin, polyclonal human serum immunoglobulin G (IgG), and human α1-acid glycoprotein (AGP) as well as of sialylated oligosaccharide reference standards and found that for more highly sialylated oligosaccharides the loss is greater than the <2% value commonly cited. Manufacturers of glycoprotein biotherapeutics need to produce products with a consistent state of sialylation and, therefore, require an accurate assessment of glycoprotein sialylation. Copyright © 2014 Elsevier Inc. All rights reserved.

A label-free fluorescent aptamer sensor based on regulation of malachite green fluorescence

PubMed Central

Xu, Weichen; Lu, Yi

2009-01-01

We report a label-free fluorescent aptamer sensor for adenosine based on the regulation of malachite green (MG) fluorescence, with comparable sensitivity and selectivity to other labeled adenosine aptamer-based sensors. The sensor consists of free MG, an aptamer strand containing an adenosine aptamer next to an MG aptamer, and a bridging strand that partially hybridizes to the aptamer strand. Such a hybridization prevents MG from binding to MG aptamer, resulting in low fluorescence of MG in the absence of adenosine. Addition of adenosine causes the adenosine aptamer to bind adenosine, weakening the hybridization of the aptamer strand with the bridging strand, making it possible for MG to bind to the aptamer strand and exhibits high fluorescence intensity. Since this design is based purely on nucleic acid hybridization, it can be generally applied to other aptamers for the label-free detection of a broad range of analytes. PMID:20017558

Putative melatonin receptors in a human biological clock

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

Reppert, S.M.; Weaver, D.R.; Rivkees, S.A.

In vitro autoradiography with /sup 125/I-labeled melatonin was used to examine melatonin binding sites in human hypothalamus. Specific /sup 125/I-labeled melatonin binding was localized to the suprachiasmatic nuclei, the site of a putative biological clock, and was not apparent in other hypothalamic regions. Specific /sup 125/I-labeled melatonin binding was consistently found in the suprachiasmatic nuclei of hypothalami from adults and fetuses. Densitometric analysis of competition experiments with varying concentrations of melatonin showed monophasic competition curves, with comparable half-maximal inhibition values for the suprachiasmatic nuclei of adults (150 picomolar) and fetuses (110 picomolar). Micromolar concentrations of the melatonin agonist 6-chloromelatonin completelymore » inhibited specific /sup 125/I-labeled melatonin binding, whereas the same concentrations of serotonin and norepinephrine caused only a partial reduction in specific binding. The results suggest that putative melatonin receptors are located in a human biological clock.« less