Machine learning approach to automatic exudate detection in retinal images from diabetic patients

NASA Astrophysics Data System (ADS)

Sopharak, Akara; Dailey, Matthew N.; Uyyanonvara, Bunyarit; Barman, Sarah; Williamson, Tom; Thet Nwe, Khine; Aye Moe, Yin

2010-01-01

Exudates are among the preliminary signs of diabetic retinopathy, a major cause of vision loss in diabetic patients. Early detection of exudates could improve patients' chances to avoid blindness. In this paper, we present a series of experiments on feature selection and exudates classification using naive Bayes and support vector machine (SVM) classifiers. We first fit the naive Bayes model to a training set consisting of 15 features extracted from each of 115,867 positive examples of exudate pixels and an equal number of negative examples. We then perform feature selection on the naive Bayes model, repeatedly removing features from the classifier, one by one, until classification performance stops improving. To find the best SVM, we begin with the best feature set from the naive Bayes classifier, and repeatedly add the previously-removed features to the classifier. For each combination of features, we perform a grid search to determine the best combination of hyperparameters ν (tolerance for training errors) and γ (radial basis function width). We compare the best naive Bayes and SVM classifiers to a baseline nearest neighbour (NN) classifier using the best feature sets from both classifiers. We find that the naive Bayes and SVM classifiers perform better than the NN classifier. The overall best sensitivity, specificity, precision, and accuracy are 92.28%, 98.52%, 53.05%, and 98.41%, respectively.

An Analysis of Document Category Prediction Responses to Classifier Model Parameter Treatment Permutations within the Software Design Patterns Subject Domain

ERIC Educational Resources Information Center

Pankau, Brian L.

2009-01-01

This empirical study evaluates the document category prediction effectiveness of Naive Bayes (NB) and K-Nearest Neighbor (KNN) classifier treatments built from different feature selection and machine learning settings and trained and tested against textual corpora of 2300 Gang-Of-Four (GOF) design pattern documents. Analysis of the experiment's…

Recognition of pornographic web pages by classifying texts and images.

PubMed

Hu, Weiming; Wu, Ou; Chen, Zhouyao; Fu, Zhouyu; Maybank, Steve

2007-06-01

With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can be easily accessed. It is important to recognize such unsuitable, offensive, or pornographic Web pages. In this paper, a novel framework for recognizing pornographic Web pages is described. A C4.5 decision tree is used to divide Web pages, according to content representations, into continuous text pages, discrete text pages, and image pages. These three categories of Web pages are handled, respectively, by a continuous text classifier, a discrete text classifier, and an algorithm that fuses the results from the image classifier and the discrete text classifier. In the continuous text classifier, statistical and semantic features are used to recognize pornographic texts. In the discrete text classifier, the naive Bayes rule is used to calculate the probability that a discrete text is pornographic. In the image classifier, the object's contour-based features are extracted to recognize pornographic images. In the text and image fusion algorithm, the Bayes theory is used to combine the recognition results from images and texts. Experimental results demonstrate that the continuous text classifier outperforms the traditional keyword-statistics-based classifier, the contour-based image classifier outperforms the traditional skin-region-based image classifier, the results obtained by our fusion algorithm outperform those by either of the individual classifiers, and our framework can be adapted to different categories of Web pages.

The diagnose of oil palm disease using Naive Bayes Method based on Expert System Technology

NASA Astrophysics Data System (ADS)

Nababan, Marlince; Laia, Yonata; Sitanggang, Delima; Sihombing, Oloan; Indra, Evta; Siregar, Saut; Purba, Windania; Mancur, Roy

2018-04-01

Expert system is dealt with system that used computer-based human intelligence to overcome particular problem which is commonly conducted by an expert. Frequent problem faced by the farmers of oil palm is the difficulty in defining the type of plant disease. As a result, the delay treatment of plant disease brings out the declining of farm products. An application system is needed to deal with the obstacles and diagnosing the type of oil palm plant disease. The researcher designed an intelligence-based application with input-output plan which is able to diagnose the type of oil palm plant disease by applying naive bayes method. Based on the research result by conducting bayes method with recognized symptom, diagnose of oil palm plant disease could be accomplished. The data of symptoms found are leaves turned yellow 0.4, dead leaves 0.4, black and brown color among the veins of leaves 0.5, young and old fruit with whole space 0.4, and decay of bunches is 0.3. The roots are tender in the amount of 0.5, and damage on sheath is 0.3. Through the chosen symptoms as mentioned above, the value of bayes is 80% with the type of disease is rotten bunch.

Optimization of Candidate Selection Using Naive Bayes: Case Study in Company X

NASA Astrophysics Data System (ADS)

Kadar, JA; Agustono, D.; Napitupulu, D.

2018-01-01

This research was conducted as a decision-making system, and an alternative solution to complete the candidate assessment for a particular position. The human resources (HR) section on company X is responsible and initiative in selecting candidates in accordance with the assessment of their superiors. Selection by using the method of filling out the manager’s assessment questionnaire on the candidate’s subordinate. Three (3) managers have been determined to assess the 11 candidates for subordinates. By using questionnaire of quality classification of human resources and formula naive bayes it will get result which finally grouped using criteria scale as final grouping. The HR department has also determined that what is received is that which meets criteria 5. The result is three (3) candidates who can be proposed as candidates for certain positions in company X, and have met all required calculations. Furthermore the candidate will be given to management as an alternative input data in the selection of candidates.

Uses and misuses of Bayes' rule and Bayesian classifiers in cybersecurity

NASA Astrophysics Data System (ADS)

Bard, Gregory V.

2017-12-01

This paper will discuss the applications of Bayes' Rule and Bayesian Classifiers in Cybersecurity. While the most elementary form of Bayes' rule occurs in undergraduate coursework, there are more complicated forms as well. As an extended example, Bayesian spam filtering is explored, and is in many ways the most triumphant accomplishment of Bayesian reasoning in computer science, as nearly everyone with an email address has a spam folder. Bayesian Classifiers have also been responsible significant cybersecurity research results; yet, because they are not part of the standard curriculum, few in the mathematics or information-technology communities have seen the exact definitions, requirements, and proofs that comprise the subject. Moreover, numerous errors have been made by researchers (described in this paper), due to some mathematical misunderstandings dealing with conditional independence, or other badly chosen assumptions. Finally, to provide instructors and researchers with real-world examples, 25 published cybersecurity papers that use Bayesian reasoning are given, with 2-4 sentence summaries of the focus and contributions of each paper.

Detection of dechallenge in spontaneous reporting systems: a comparison of Bayes methods.

PubMed

Banu, A Bazila; Alias Balamurugan, S Appavu; Thirumalaikolundusubramanian, Ponniah

2014-01-01

Dechallenge is a response observed for the reduction or disappearance of adverse drug reactions (ADR) on withdrawal of a drug from a patient. Currently available algorithms to detect dechallenge have limitations. Hence, there is a need to compare available new methods. To detect dechallenge in Spontaneous Reporting Systems, data-mining algorithms like Naive Bayes and Improved Naive Bayes were applied for comparing the performance of the algorithms in terms of accuracy and error. Analyzing the factors of dechallenge like outcome and disease category will help medical practitioners and pharmaceutical industries to determine the reasons for dechallenge in order to take essential steps toward drug safety. Adverse drug reactions of the year 2011 and 2012 were downloaded from the United States Food and Drug Administration's database. The outcome of classification algorithms showed that Improved Naive Bayes algorithm outperformed Naive Bayes with accuracy of 90.11% and error of 9.8% in detecting the dechallenge. Detecting dechallenge for unknown samples are essential for proper prescription. To overcome the issues exposed by Naive Bayes algorithm, Improved Naive Bayes algorithm can be used to detect dechallenge in terms of higher accuracy and minimal error.

Naive Bayes Bearing Fault Diagnosis Based on Enhanced Independence of Data

PubMed Central

Zhang, Nannan; Wu, Lifeng; Yang, Jing; Guan, Yong

2018-01-01

The bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Data-based bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not completely independent, which reduces the performance of NB algorithms. In order to solve this problem, we propose a NB bearing fault diagnosis method based on enhanced independence of data. The method deals with data vector from two aspects: the attribute feature and the sample dimension. After processing, the classification limitation of NB is reduced by the independence hypothesis. First, we extract the statistical characteristics of the original signal of the bearings effectively. Then, the Decision Tree algorithm is used to select the important features of the time domain signal, and the low correlation features is selected. Next, the Selective Support Vector Machine (SSVM) is used to prune the dimension data and remove redundant vectors. Finally, we use NB to diagnose the fault with the low correlation data. The experimental results show that the independent enhancement of data is effective for bearing fault diagnosis. PMID:29401730

Naive scoring of human sleep based on a hidden Markov model of the electroencephalogram.

PubMed

Yaghouby, Farid; Modur, Pradeep; Sunderam, Sridhar

2014-01-01

Clinical sleep scoring involves tedious visual review of overnight polysomnograms by a human expert. Many attempts have been made to automate the process by training computer algorithms such as support vector machines and hidden Markov models (HMMs) to replicate human scoring. Such supervised classifiers are typically trained on scored data and then validated on scored out-of-sample data. Here we describe a methodology based on HMMs for scoring an overnight sleep recording without the benefit of a trained initial model. The number of states in the data is not known a priori and is optimized using a Bayes information criterion. When tested on a 22-subject database, this unsupervised classifier agreed well with human scores (mean of Cohen's kappa > 0.7). The HMM also outperformed other unsupervised classifiers (Gaussian mixture models, k-means, and linkage trees), that are capable of naive classification but do not model dynamics, by a significant margin (p < 0.05).

Risk Classification with an Adaptive Naive Bayes Kernel Machine Model.

PubMed

Minnier, Jessica; Yuan, Ming; Liu, Jun S; Cai, Tianxi

2015-04-22

Genetic studies of complex traits have uncovered only a small number of risk markers explaining a small fraction of heritability and adding little improvement to disease risk prediction. Standard single marker methods may lack power in selecting informative markers or estimating effects. Most existing methods also typically do not account for non-linearity. Identifying markers with weak signals and estimating their joint effects among many non-informative markers remains challenging. One potential approach is to group markers based on biological knowledge such as gene structure. If markers in a group tend to have similar effects, proper usage of the group structure could improve power and efficiency in estimation. We propose a two-stage method relating markers to disease risk by taking advantage of known gene-set structures. Imposing a naive bayes kernel machine (KM) model, we estimate gene-set specific risk models that relate each gene-set to the outcome in stage I. The KM framework efficiently models potentially non-linear effects of predictors without requiring explicit specification of functional forms. In stage II, we aggregate information across gene-sets via a regularization procedure. Estimation and computational efficiency is further improved with kernel principle component analysis. Asymptotic results for model estimation and gene set selection are derived and numerical studies suggest that the proposed procedure could outperform existing procedures for constructing genetic risk models.

Bayes classifiers for imbalanced traffic accidents datasets.

PubMed

Mujalli, Randa Oqab; López, Griselda; Garach, Laura

2016-03-01

Traffic accidents data sets are usually imbalanced, where the number of instances classified under the killed or severe injuries class (minority) is much lower than those classified under the slight injuries class (majority). This, however, supposes a challenging problem for classification algorithms and may cause obtaining a model that well cover the slight injuries instances whereas the killed or severe injuries instances are misclassified frequently. Based on traffic accidents data collected on urban and suburban roads in Jordan for three years (2009-2011); three different data balancing techniques were used: under-sampling which removes some instances of the majority class, oversampling which creates new instances of the minority class and a mix technique that combines both. In addition, different Bayes classifiers were compared for the different imbalanced and balanced data sets: Averaged One-Dependence Estimators, Weightily Average One-Dependence Estimators, and Bayesian networks in order to identify factors that affect the severity of an accident. The results indicated that using the balanced data sets, especially those created using oversampling techniques, with Bayesian networks improved classifying a traffic accident according to its severity and reduced the misclassification of killed and severe injuries instances. On the other hand, the following variables were found to contribute to the occurrence of a killed causality or a severe injury in a traffic accident: number of vehicles involved, accident pattern, number of directions, accident type, lighting, surface condition, and speed limit. This work, to the knowledge of the authors, is the first that aims at analyzing historical data records for traffic accidents occurring in Jordan and the first to apply balancing techniques to analyze injury severity of traffic accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Classification of Indonesian quote on Twitter using Naïve Bayes

NASA Astrophysics Data System (ADS)

Rachmadany, A.; Pranoto, Y. M.; Gunawan; Multazam, M. T.; Nandiyanto, A. B. D.; Abdullah, A. G.; Widiaty, I.

2018-01-01

Quote is sentences made in the hope that someone can become strong personalities, individuals who always improve themselves to move forward and achieve success. Social media is a place for people to express his heart to the world that sometimes the expression of the heart is quotes. Here, the purpose of this study was to classify Indonesian quote on Twitter using Naïve Bayes. This experiment uses text classification from Twitter data written by Twitter users which are quote then classification again grouped into 6 categories (Love, Life, Motivation, Education, Religion, Others). The language used is Indonesian. The method used is Naive Bayes. The results of this experiment are a web application collection of Indonesian quote that have been classified. This classification gives the user ease in finding quote based on class or keyword. For example, when a user wants to find a 'motivation' quote, this classification would be very useful.

Naïve Bayes classification in R.

PubMed

Zhang, Zhongheng

2016-06-01

Naïve Bayes classification is a kind of simple probabilistic classification methods based on Bayes' theorem with the assumption of independence between features. The model is trained on training dataset to make predictions by predict() function. This article introduces two functions naiveBayes() and train() for the performance of Naïve Bayes classification.

Data mining for dengue hemorrhagic fever (DHF) prediction with naive Bayes method

NASA Astrophysics Data System (ADS)

Arafiyah, Ria; Hermin, Fariani

2018-01-01

Handling of infectious diseases is determined by the accuracy and speed of diagnosis. Government through the Regulation of the Minister of Health of the Republic of Indonesia No. 82 of 2014 on the Control of Communicable Diseases establishes Dengue Hemorrhagic Fever (DHF) has made DHF prevention a national priority. Various attempts were made to overcome this misdiagnosis. The treatment and diagnosis of DHF using ANFIS has result an application program that can decide whether a patient has dengue fever or not [1]. An expert system of dengue prevention by using ANFIS has predict the weather and the number of sufferers [2]. The large number of data on DHF often cannot affect a person in making decisions. The use of data mining method, able to build data base support in decision makers diagnose DHF disease [3]. This study predicts DHF with the method of Naive Bayes. Parameter of The input variable is the patient’s medical data (temperature, spotting, bleeding, and tornuine test) and the output variable suffers from DBD or not while the system output is diagnosis of the patient suffering from DHF or not. Result of model test by using tools of Orange 3.4.5 obtained level of precision model is 77,3%.

Classifying smoking urges via machine learning.

PubMed

Dumortier, Antoine; Beckjord, Ellen; Shiffman, Saul; Sejdić, Ervin

2016-12-01

Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. To test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications. In conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms' performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions. Copyright © 2016 Elsevier Ireland Ltd. All rights

Classifying smoking urges via machine learning

PubMed Central

Dumortier, Antoine; Beckjord, Ellen; Shiffman, Saul; Sejdić, Ervin

2016-01-01

Background and objective Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this paper, we examine different machine learning approaches to use situational features associated with having or not having urges to smoke during a quit attempt in order to accurately classify high-urge states. Methods To test our machine learning approaches, specifically, Bayes, discriminant analysis and decision tree learning methods, we used a dataset collected from over 300 participants who had initiated a quit attempt. The three classification approaches are evaluated observing sensitivity, specificity, accuracy and precision. Results The outcome of the analysis showed that algorithms based on feature selection make it possible to obtain high classification rates with only a few features selected from the entire dataset. The classification tree method outperformed the naive Bayes and discriminant analysis methods, with an accuracy of the classifications up to 86%. These numbers suggest that machine learning may be a suitable approach to deal with smoking cessation matters, and to predict smoking urges, outlining a potential use for mobile health applications. Conclusions In conclusion, machine learning classifiers can help identify smoking situations, and the search for the best features and classifier parameters significantly improves the algorithms’ performance. In addition, this study also supports the usefulness of new technologies in improving the effect of smoking cessation interventions, the management of time and patients by therapists, and thus the optimization of available health care resources. Future studies should focus on providing more adaptive and personalized support to people who really need it, in a minimum amount of time by developing novel expert systems capable of delivering real-time interventions

Development of novel prediction model for drug-induced mitochondrial toxicity by using naïve Bayes classifier method.

PubMed

Zhang, Hui; Yu, Peng; Ren, Ji-Xia; Li, Xi-Bo; Wang, He-Li; Ding, Lan; Kong, Wei-Bao

2017-12-01

Mitochondrial dysfunction has been considered as an important contributing factor in the etiology of drug-induced organ toxicity, and even plays an important role in the pathogenesis of some diseases. The objective of this investigation was to develop a novel prediction model of drug-induced mitochondrial toxicity by using a naïve Bayes classifier. For comparison, the recursive partitioning classifier prediction model was also constructed. Among these methods, the prediction performance of naïve Bayes classifier established here showed best, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set were 95 ± 0.6% and 81 ± 1.1%, respectively. In addition, four important molecular descriptors and some representative substructures of toxicants produced by ECFP_6 fingerprints were identified. We hope the established naïve Bayes prediction model can be employed for the mitochondrial toxicity assessment, and these obtained important information of mitochondrial toxicants can provide guidance for medicinal chemists working in drug discovery and lead optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Overlapped Partitioning for Ensemble Classifiers of P300-Based Brain-Computer Interfaces

PubMed Central

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance. PMID:24695550

Overlapped partitioning for ensemble classifiers of P300-based brain-computer interfaces.

PubMed

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance.

Comparisons and Selections of Features and Classifiers for Short Text Classification

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.

PubMed

Wolfson, Julian; Bandyopadhyay, Sunayan; Elidrisi, Mohamed; Vazquez-Benitez, Gabriela; Vock, David M; Musgrove, Donald; Adomavicius, Gediminas; Johnson, Paul E; O'Connor, Patrick J

2015-09-20

Predicting an individual's risk of experiencing a future clinical outcome is a statistical task with important consequences for both practicing clinicians and public health experts. Modern observational databases such as electronic health records provide an alternative to the longitudinal cohort studies traditionally used to construct risk models, bringing with them both opportunities and challenges. Large sample sizes and detailed covariate histories enable the use of sophisticated machine learning techniques to uncover complex associations and interactions, but observational databases are often 'messy', with high levels of missing data and incomplete patient follow-up. In this paper, we propose an adaptation of the well-known Naive Bayes machine learning approach to time-to-event outcomes subject to censoring. We compare the predictive performance of our method with the Cox proportional hazards model which is commonly used for risk prediction in healthcare populations, and illustrate its application to prediction of cardiovascular risk using an electronic health record dataset from a large Midwest integrated healthcare system. Copyright © 2015 John Wiley & Sons, Ltd.

Learning accurate and concise naïve Bayes classifiers from attribute value taxonomies and data

PubMed Central

Kang, D.-K.; Silvescu, A.; Honavar, V.

2009-01-01

In many application domains, there is a need for learning algorithms that can effectively exploit attribute value taxonomies (AVT)—hierarchical groupings of attribute values—to learn compact, comprehensible and accurate classifiers from data—including data that are partially specified. This paper describes AVT-NBL, a natural generalization of the naïve Bayes learner (NBL), for learning classifiers from AVT and data. Our experimental results show that AVT-NBL is able to generate classifiers that are substantially more compact and more accurate than those produced by NBL on a broad range of data sets with different percentages of partially specified values. We also show that AVT-NBL is more efficient in its use of training data: AVT-NBL produces classifiers that outperform those produced by NBL using substantially fewer training examples. PMID:20351793

Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

NASA Astrophysics Data System (ADS)

Wang, Leilei; Cheng, Jinyong

2018-03-01

Protein secondary structure prediction is belong to bioinformatics,and it's important in research area. In this paper, we propose a new prediction way of protein using bayes classifier and autoEncoder network. Our experiments show some algorithms including the construction of the model, the classification of parameters and so on. The data set is a typical CB513 data set for protein. In terms of accuracy, the method is the cross validation based on the 3-fold. Then we can get the Q3 accuracy. Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.

Brain-computer interface using wavelet transformation and naïve bayes classifier.

PubMed

Bassani, Thiago; Nievola, Julio Cesar

2010-01-01

The main purpose of this work is to establish an exploratory approach using electroencephalographic (EEG) signal, analyzing the patterns in the time-frequency plane. This work also aims to optimize the EEG signal analysis through the improvement of classifiers and, eventually, of the BCI performance. In this paper a novel exploratory approach for data mining of EEG signal based on continuous wavelet transformation (CWT) and wavelet coherence (WC) statistical analysis is introduced and applied. The CWT allows the representation of time-frequency patterns of the signal's information content by WC qualiatative analysis. Results suggest that the proposed methodology is capable of identifying regions in time-frequency spectrum during the specified task of BCI. Furthermore, an example of a region is identified, and the patterns are classified using a Naïve Bayes Classifier (NBC). This innovative characteristic of the process justifies the feasibility of the proposed approach to other data mining applications. It can open new physiologic researches in this field and on non stationary time series analysis.

The Persistence of "Solid" and "Liquid" Naive Conceptions: A Reaction Time Study

ERIC Educational Resources Information Center

Babai, Reuven; Amsterdamer, Anat

2008-01-01

The study explores whether the naive concepts of "solid" and "liquid" persist in adolescence. Accuracy of responses and reaction times where measured while 41 ninth graders classified different solids (rigid, non-rigid and powders) and different liquids (runny, dense) into solid or liquid. The results show that these naive conceptions affect…

Diagnosis of combined faults in Rotary Machinery by Non-Naive Bayesian approach

NASA Astrophysics Data System (ADS)

Asr, Mahsa Yazdanian; Ettefagh, Mir Mohammad; Hassannejad, Reza; Razavi, Seyed Naser

2017-02-01

When combined faults happen in different parts of the rotating machines, their features are profoundly dependent. Experts are completely familiar with individuals faults characteristics and enough data are available from single faults but the problem arises, when the faults combined and the separation of characteristics becomes complex. Therefore, the experts cannot declare exact information about the symptoms of combined fault and its quality. In this paper to overcome this drawback, a novel method is proposed. The core idea of the method is about declaring combined fault without using combined fault features as training data set and just individual fault features are applied in training step. For this purpose, after data acquisition and resampling the obtained vibration signals, Empirical Mode Decomposition (EMD) is utilized to decompose multi component signals to Intrinsic Mode Functions (IMFs). With the use of correlation coefficient, proper IMFs for feature extraction are selected. In feature extraction step, Shannon energy entropy of IMFs was extracted as well as statistical features. It is obvious that most of extracted features are strongly dependent. To consider this matter, Non-Naive Bayesian Classifier (NNBC) is appointed, which release the fundamental assumption of Naive Bayesian, i.e., the independence among features. To demonstrate the superiority of NNBC, other counterpart methods, include Normal Naive Bayesian classifier, Kernel Naive Bayesian classifier and Back Propagation Neural Networks were applied and the classification results are compared. An experimental vibration signals, collected from automobile gearbox, were used to verify the effectiveness of the proposed method. During the classification process, only the features, related individually to healthy state, bearing failure and gear failures, were assigned for training the classifier. But, combined fault features (combined gear and bearing failures) were examined as test data. The achieved

Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier.

PubMed

Kambhampati, Satya Samyukta; Singh, Vishal; Manikandan, M Sabarimalai; Ramkumar, Barathram

2015-08-01

In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%.

Creating Diverse Ensemble Classifiers to Reduce Supervision

DTIC Science & Technology

2005-12-01

artificial examples. Quite often training with noise improves network generalization (Bishop, 1995; Raviv & Intrator, 1996). Adding noise to training...full training set, as seen by comparing to the to- tal dataset sizes. Hence, improving on the data utilization of DECORATE is a fairly difficult task...prohibitively expensive, except (perhaps) with an incremen- tal learner such as Naive Bayes. Our AFA framework is significantly more efficient because

Use of machine-learning classifiers to predict requests for preoperative acute pain service consultation.

PubMed

Tighe, Patrick J; Lucas, Stephen D; Edwards, David A; Boezaart, André P; Aytug, Haldun; Bihorac, Azra

2012-10-01

  The purpose of this project was to determine whether machine-learning classifiers could predict which patients would require a preoperative acute pain service (APS) consultation.   Retrospective cohort.   University teaching hospital.   The records of 9,860 surgical patients posted between January 1 and June 30, 2010 were reviewed.   Request for APS consultation. A cohort of machine-learning classifiers was compared according to its ability or inability to classify surgical cases as requiring a request for a preoperative APS consultation. Classifiers were then optimized utilizing ensemble techniques. Computational efficiency was measured with the central processing unit processing times required for model training. Classifiers were tested using the full feature set, as well as the reduced feature set that was optimized using a merit-based dimensional reduction strategy.   Machine-learning classifiers correctly predicted preoperative requests for APS consultations in 92.3% (95% confidence intervals [CI], 91.8-92.8) of all surgical cases. Bayesian methods yielded the highest area under the receiver operating curve (0.87, 95% CI 0.84-0.89) and lowest training times (0.0018 seconds, 95% CI, 0.0017-0.0019 for the NaiveBayesUpdateable algorithm). An ensemble of high-performing machine-learning classifiers did not yield a higher area under the receiver operating curve than its component classifiers. Dimensional reduction decreased the computational requirements for multiple classifiers, but did not adversely affect classification performance.   Using historical data, machine-learning classifiers can predict which surgical cases should prompt a preoperative request for an APS consultation. Dimensional reduction improved computational efficiency and preserved predictive performance. Wiley Periodicals, Inc.

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sentimental analysis of Amazon reviews using naïve bayes on laptop products with MongoDB and R

NASA Astrophysics Data System (ADS)

Kamal Hassan, Mohan; Prasanth Shakthi, Sana; Sasikala, R.

2017-11-01

Start In Today’s era the e-commerce is developing rapidly these years, buying products on-line has become more and more fashionable owing to its variety of options, low cost value (high discounts) and quick supply systems, so abundant folks intend to do online shopping. In the meantime the standard and delivery of merchandise is uneven, fake branded products are delivered. We use product users review comments about product and review about retailers from Amazon as data set and classify review text by subjectivity/objectivity and negative/positive attitude of buyer. Such reviews are helpful to some extent, promising both the shoppers and products makers. This paper presents an empirical study of efficacy of classifying product review by tagging the keyword. In the present study, we tend to analyse the fundamentals of determining, positive and negative approach towards the product. Thus we hereby propose completely different approaches by removing the unstructured data and then classifying comments employing Naive Bayes algorithm.

A Pairwise Naïve Bayes Approach to Bayesian Classification.

PubMed

Asafu-Adjei, Josephine K; Betensky, Rebecca A

2015-10-01

Despite the relatively high accuracy of the naïve Bayes (NB) classifier, there may be several instances where it is not optimal, i.e. does not have the same classification performance as the Bayes classifier utilizing the joint distribution of the examined attributes. However, the Bayes classifier can be computationally intractable due to its required knowledge of the joint distribution. Therefore, we introduce a "pairwise naïve" Bayes (PNB) classifier that incorporates all pairwise relationships among the examined attributes, but does not require specification of the joint distribution. In this paper, we first describe the necessary and sufficient conditions under which the PNB classifier is optimal. We then discuss sufficient conditions for which the PNB classifier, and not NB, is optimal for normal attributes. Through simulation and actual studies, we evaluate the performance of our proposed classifier relative to the Bayes and NB classifiers, along with the HNB, AODE, LBR and TAN classifiers, using normal density and empirical estimation methods. Our applications show that the PNB classifier using normal density estimation yields the highest accuracy for data sets containing continuous attributes. We conclude that it offers a useful compromise between the Bayes and NB classifiers.

Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

PubMed

Awaysheh, Abdullah; Wilcke, Jeffrey; Elvinger, François; Rees, Loren; Fan, Weiguo; Zimmerman, Kurt L

2016-11-01

Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. We tested the use of supervised machine-learning algorithms to differentiate between the 2 diseases using data generated from noninvasive diagnostic tests. Three prediction models were developed using 3 machine-learning algorithms: naive Bayes, decision trees, and artificial neural networks. The models were trained and tested on data from complete blood count (CBC) and serum chemistry (SC) results for the following 3 groups of client-owned cats: normal, inflammatory bowel disease (IBD), or alimentary lymphoma (ALA). Naive Bayes and artificial neural networks achieved higher classification accuracy (sensitivities of 70.8% and 69.2%, respectively) than the decision tree algorithm (63%, p < 0.0001). The areas under the receiver-operating characteristic curve for classifying cases into the 3 categories was 83% by naive Bayes, 79% by decision tree, and 82% by artificial neural networks. Prediction models using machine learning provided a method for distinguishing between ALA-IBD, ALA-normal, and IBD-normal. The naive Bayes and artificial neural networks classifiers used 10 and 4 of the CBC and SC variables, respectively, to outperform the C4.5 decision tree, which used 5 CBC and SC variables in classifying cats into the 3 classes. These models can provide another noninvasive diagnostic tool to assist clinicians with differentiating between IBD and ALA, and between diseased and nondiseased cats. © 2016 The Author(s).

Bayes-LQAS: classifying the prevalence of global acute malnutrition

PubMed Central

2010-01-01

Lot Quality Assurance Sampling (LQAS) applications in health have generally relied on frequentist interpretations for statistical validity. Yet health professionals often seek statements about the probability distribution of unknown parameters to answer questions of interest. The frequentist paradigm does not pretend to yield such information, although a Bayesian formulation might. This is the source of an error made in a recent paper published in this journal. Many applications lend themselves to a Bayesian treatment, and would benefit from such considerations in their design. We discuss Bayes-LQAS (B-LQAS), which allows for incorporation of prior information into the LQAS classification procedure, and thus shows how to correct the aforementioned error. Further, we pay special attention to the formulation of Bayes Operating Characteristic Curves and the use of prior information to improve survey designs. As a motivating example, we discuss the classification of Global Acute Malnutrition prevalence and draw parallels between the Bayes and classical classifications schemes. We also illustrate the impact of informative and non-informative priors on the survey design. Results indicate that using a Bayesian approach allows the incorporation of expert information and/or historical data and is thus potentially a valuable tool for making accurate and precise classifications. PMID:20534159

Bayes-LQAS: classifying the prevalence of global acute malnutrition.

PubMed

Olives, Casey; Pagano, Marcello

2010-06-09

Lot Quality Assurance Sampling (LQAS) applications in health have generally relied on frequentist interpretations for statistical validity. Yet health professionals often seek statements about the probability distribution of unknown parameters to answer questions of interest. The frequentist paradigm does not pretend to yield such information, although a Bayesian formulation might. This is the source of an error made in a recent paper published in this journal. Many applications lend themselves to a Bayesian treatment, and would benefit from such considerations in their design. We discuss Bayes-LQAS (B-LQAS), which allows for incorporation of prior information into the LQAS classification procedure, and thus shows how to correct the aforementioned error. Further, we pay special attention to the formulation of Bayes Operating Characteristic Curves and the use of prior information to improve survey designs. As a motivating example, we discuss the classification of Global Acute Malnutrition prevalence and draw parallels between the Bayes and classical classifications schemes. We also illustrate the impact of informative and non-informative priors on the survey design. Results indicate that using a Bayesian approach allows the incorporation of expert information and/or historical data and is thus potentially a valuable tool for making accurate and precise classifications.

Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm.

PubMed

Chapman, Brian E; Lee, Sean; Kang, Hyunseok Peter; Chapman, Wendy W

2011-10-01

In this paper we describe an application called peFinder for document-level classification of CT pulmonary angiography reports. peFinder is based on a generalized version of the ConText algorithm, a simple text processing algorithm for identifying features in clinical report documents. peFinder was used to answer questions about the disease state (pulmonary emboli present or absent), the certainty state of the diagnosis (uncertainty present or absent), the temporal state of an identified pulmonary embolus (acute or chronic), and the technical quality state of the exam (diagnostic or not diagnostic). Gold standard answers for each question were determined from the consensus classifications of three human annotators. peFinder results were compared to naive Bayes' classifiers using unigrams and bigrams. The sensitivities (and positive predictive values) for peFinder were 0.98(0.83), 0.86(0.96), 0.94(0.93), and 0.60(0.90) for disease state, quality state, certainty state, and temporal state respectively, compared to 0.68(0.77), 0.67(0.87), 0.62(0.82), and 0.04(0.25) for the naive Bayes' classifier using unigrams, and 0.75(0.79), 0.52(0.69), 0.59(0.84), and 0.04(0.25) for the naive Bayes' classifier using bigrams. Copyright © 2011 Elsevier Inc. All rights reserved.

Predicting Classifier Performance with Limited Training Data: Applications to Computer-Aided Diagnosis in Breast and Prostate Cancer

PubMed Central

Basavanhally, Ajay; Viswanath, Satish; Madabhushi, Anant

2015-01-01

Clinical trials increasingly employ medical imaging data in conjunction with supervised classifiers, where the latter require large amounts of training data to accurately model the system. Yet, a classifier selected at the start of the trial based on smaller and more accessible datasets may yield inaccurate and unstable classification performance. In this paper, we aim to address two common concerns in classifier selection for clinical trials: (1) predicting expected classifier performance for large datasets based on error rates calculated from smaller datasets and (2) the selection of appropriate classifiers based on expected performance for larger datasets. We present a framework for comparative evaluation of classifiers using only limited amounts of training data by using random repeated sampling (RRS) in conjunction with a cross-validation sampling strategy. Extrapolated error rates are subsequently validated via comparison with leave-one-out cross-validation performed on a larger dataset. The ability to predict error rates as dataset size increases is demonstrated on both synthetic data as well as three different computational imaging tasks: detecting cancerous image regions in prostate histopathology, differentiating high and low grade cancer in breast histopathology, and detecting cancerous metavoxels in prostate magnetic resonance spectroscopy. For each task, the relationships between 3 distinct classifiers (k-nearest neighbor, naive Bayes, Support Vector Machine) are explored. Further quantitative evaluation in terms of interquartile range (IQR) suggests that our approach consistently yields error rates with lower variability (mean IQRs of 0.0070, 0.0127, and 0.0140) than a traditional RRS approach (mean IQRs of 0.0297, 0.0779, and 0.305) that does not employ cross-validation sampling for all three datasets. PMID:25993029

Adaptive Bayes classifiers for remotely sensed data

NASA Technical Reports Server (NTRS)

Raulston, H. S.; Pace, M. O.; Gonzalez, R. C.

1975-01-01

An algorithm is developed for a learning, adaptive, statistical pattern classifier for remotely sensed data. The estimation procedure consists of two steps: (1) an optimal stochastic approximation of the parameters of interest, and (2) a projection of the parameters in time and space. The results reported are for Gaussian data in which the mean vector of each class may vary with time or position after the classifier is trained.

Predicting drug-induced liver injury in human with Naïve Bayes classifier approach.

PubMed

Zhang, Hui; Ding, Lan; Zou, Yi; Hu, Shui-Qing; Huang, Hai-Guo; Kong, Wei-Bao; Zhang, Ji

2016-10-01

Drug-induced liver injury (DILI) is one of the major safety concerns in drug development. Although various toxicological studies assessing DILI risk have been developed, these methods were not sufficient in predicting DILI in humans. Thus, developing new tools and approaches to better predict DILI risk in humans has become an important and urgent task. In this study, we aimed to develop a computational model for assessment of the DILI risk with using a larger scale human dataset and Naïve Bayes classifier. The established Naïve Bayes prediction model was evaluated by 5-fold cross validation and an external test set. For the training set, the overall prediction accuracy of the 5-fold cross validation was 94.0 %. The sensitivity, specificity, positive predictive value and negative predictive value were 97.1, 89.2, 93.5 and 95.1 %, respectively. The test set with the concordance of 72.6 %, sensitivity of 72.5 %, specificity of 72.7 %, positive predictive value of 80.4 %, negative predictive value of 63.2 %. Furthermore, some important molecular descriptors related to DILI risk and some toxic/non-toxic fragments were identified. Thus, we hope the prediction model established here would be employed for the assessment of human DILI risk, and the obtained molecular descriptors and substructures should be taken into consideration in the design of new candidate compounds to help medicinal chemists rationally select the chemicals with the best prospects to be effective and safe.

A SVM-based method for sentiment analysis in Persian language

NASA Astrophysics Data System (ADS)

Hajmohammadi, Mohammad Sadegh; Ibrahim, Roliana

2013-03-01

Persian language is the official language of Iran, Tajikistan and Afghanistan. Local online users often represent their opinions and experiences on the web with written Persian. Although the information in those reviews is valuable to potential consumers and sellers, the huge amount of web reviews make it difficult to give an unbiased evaluation to a product. In this paper, standard machine learning techniques SVM and naive Bayes are incorporated into the domain of online Persian Movie reviews to automatically classify user reviews as positive or negative and performance of these two classifiers is compared with each other in this language. The effects of feature presentations on classification performance are discussed. We find that accuracy is influenced by interaction between the classification models and the feature options. The SVM classifier achieves as well as or better accuracy than naive Bayes in Persian movie. Unigrams are proved better features than bigrams and trigrams in capturing Persian sentiment orientation.

Application of a Hidden Bayes Naive Multiclass Classifier in Network Intrusion Detection

ERIC Educational Resources Information Center

Koc, Levent

2013-01-01

With increasing Internet connectivity and traffic volume, recent intrusion incidents have reemphasized the importance of network intrusion detection systems for combating increasingly sophisticated network attacks. Techniques such as pattern recognition and the data mining of network events are often used by intrusion detection systems to classify…

Wood identification of Dalbergia nigra (CITES Appendix I) using quantitative wood anatomy, principal components analysis and naive Bayes classification.

PubMed

Gasson, Peter; Miller, Regis; Stekel, Dov J; Whinder, Frances; Zieminska, Kasia

2010-01-01

Dalbergia nigra is one of the most valuable timber species of its genus, having been traded for over 300 years. Due to over-exploitation it is facing extinction and trade has been banned under CITES Appendix I since 1992. Current methods, primarily comparative wood anatomy, are inadequate for conclusive species identification. This study aims to find a set of anatomical characters that distinguish the wood of D. nigra from other commercially important species of Dalbergia from Latin America. Qualitative and quantitative wood anatomy, principal components analysis and naïve Bayes classification were conducted on 43 specimens of Dalbergia, eight D. nigra and 35 from six other Latin American species. Dalbergia cearensis and D. miscolobium can be distinguished from D. nigra on the basis of vessel frequency for the former, and ray frequency for the latter. Principal components analysis was unable to provide any further basis for separating the species. Naïve Bayes classification using the four characters: minimum vessel diameter; frequency of solitary vessels; mean ray width; and frequency of axially fused rays, classified all eight D. nigra correctly with no false negatives, but there was a false positive rate of 36.36 %. Wood anatomy alone cannot distinguish D. nigra from all other commercially important Dalbergia species likely to be encountered by customs officials, but can be used to reduce the number of specimens that would need further study.

Fuzzy Naive Bayesian model for medical diagnostic decision support.

PubMed

Wagholikar, Kavishwar B; Vijayraghavan, Sundararajan; Deshpande, Ashok W

2009-01-01

This work relates to the development of computational algorithms to provide decision support to physicians. The authors propose a Fuzzy Naive Bayesian (FNB) model for medical diagnosis, which extends the Fuzzy Bayesian approach proposed by Okuda. A physician's interview based method is described to define a orthogonal fuzzy symptom information system, required to apply the model. For the purpose of elaboration and elicitation of characteristics, the algorithm is applied to a simple simulated dataset, and compared with conventional Naive Bayes (NB) approach. As a preliminary evaluation of FNB in real world scenario, the comparison is repeated on a real fuzzy dataset of 81 patients diagnosed with infectious diseases. The case study on simulated dataset elucidates that FNB can be optimal over NB for diagnosing patients with imprecise-fuzzy information, on account of the following characteristics - 1) it can model the information that, values of some attributes are semantically closer than values of other attributes, and 2) it offers a mechanism to temper exaggerations in patient information. Although the algorithm requires precise training data, its utility for fuzzy training data is argued for. This is supported by the case study on infectious disease dataset, which indicates optimality of FNB over NB for the infectious disease domain. Further case studies on large datasets are required to establish utility of FNB.

Development and validation of classifiers and variable subsets for predicting nursing home admission.

PubMed

Nuutinen, Mikko; Leskelä, Riikka-Leena; Suojalehto, Ella; Tirronen, Anniina; Komssi, Vesa

2017-04-13

In previous years a substantial number of studies have identified statistically important predictors of nursing home admission (NHA). However, as far as we know, the analyses have been done at the population-level. No prior research has analysed the prediction accuracy of a NHA model for individuals. This study is an analysis of 3056 longer-term home care customers in the city of Tampere, Finland. Data were collected from the records of social and health service usage and RAI-HC (Resident Assessment Instrument - Home Care) assessment system during January 2011 and September 2015. The aim was to find out the most efficient variable subsets to predict NHA for individuals and validate the accuracy. The variable subsets of predicting NHA were searched by sequential forward selection (SFS) method, a variable ranking metric and the classifiers of logistic regression (LR), support vector machine (SVM) and Gaussian naive Bayes (GNB). The validation of the results was guaranteed using randomly balanced data sets and cross-validation. The primary performance metrics for the classifiers were the prediction accuracy and AUC (average area under the curve). The LR and GNB classifiers achieved 78% accuracy for predicting NHA. The most important variables were RAI MAPLE (Method for Assigning Priority Levels), functional impairment (RAI IADL, Activities of Daily Living), cognitive impairment (RAI CPS, Cognitive Performance Scale), memory disorders (diagnoses G30-G32 and F00-F03) and the use of community-based health-service and prior hospital use (emergency visits and periods of care). The accuracy of the classifier for individuals was high enough to convince the officials of the city of Tampere to integrate the predictive model based on the findings of this study as a part of home care information system. Further work need to be done to evaluate variables that are modifiable and responsive to interventions.

Segmentation of white blood cells and comparison of cell morphology by linear and naïve Bayes classifiers.

PubMed

Prinyakupt, Jaroonrut; Pluempitiwiriyawej, Charnchai

2015-06-30

Blood smear microscopic images are routinely investigated by haematologists to diagnose most blood diseases. However, the task is quite tedious and time consuming. An automatic detection and classification of white blood cells within such images can accelerate the process tremendously. In this paper we propose a system to locate white blood cells within microscopic blood smear images, segment them into nucleus and cytoplasm regions, extract suitable features and finally, classify them into five types: basophil, eosinophil, neutrophil, lymphocyte and monocyte. Two sets of blood smear images were used in this study's experiments. Dataset 1, collected from Rangsit University, were normal peripheral blood slides under light microscope with 100× magnification; 555 images with 601 white blood cells were captured by a Nikon DS-Fi2 high-definition color camera and saved in JPG format of size 960 × 1,280 pixels at 15 pixels per 1 μm resolution. In dataset 2, 477 cropped white blood cell images were downloaded from CellaVision.com. They are in JPG format of size 360 × 363 pixels. The resolution is estimated to be 10 pixels per 1 μm. The proposed system comprises a pre-processing step, nucleus segmentation, cell segmentation, feature extraction, feature selection and classification. The main concept of the segmentation algorithm employed uses white blood cell's morphological properties and the calibrated size of a real cell relative to image resolution. The segmentation process combined thresholding, morphological operation and ellipse curve fitting. Consequently, several features were extracted from the segmented nucleus and cytoplasm regions. Prominent features were then chosen by a greedy search algorithm called sequential forward selection. Finally, with a set of selected prominent features, both linear and naïve Bayes classifiers were applied for performance comparison. This system was tested on normal peripheral blood smear slide images from two datasets. Two sets

On Algorithms for Generating Computationally Simple Piecewise Linear Classifiers

DTIC Science & Technology

1989-05-01

suffers. - Waveform classification, e.g. speech recognition, seismic analysis (i.e. discrimination between earthquakes and nuclear explosions), target...assuming Gaussian distributions (B-G) d) Bayes classifier with probability densities estimated with the k-N-N method (B- kNN ) e) The -arest neighbour...range of classifiers are chosen including a fast, easy computable and often used classifier (B-G), reliable and complex classifiers (B- kNN and NNR

A native Bayesian classifier based routing protocol for VANETS

NASA Astrophysics Data System (ADS)

Bao, Zhenshan; Zhou, Keqin; Zhang, Wenbo; Gong, Xiaolei

2016-12-01

Geographic routing protocols are one of the most hot research areas in VANET (Vehicular Ad-hoc Network). However, there are few routing protocols can take both the transmission efficient and the usage of ratio into account. As we have noticed, different messages in VANET may ask different quality of service. So we raised a Native Bayesian Classifier based routing protocol (Naive Bayesian Classifier-Greedy, NBC-Greedy), which can classify and transmit different messages by its emergency degree. As a result, we can balance the transmission efficient and the usage of ratio with this protocol. Based on Matlab simulation, we can draw a conclusion that NBC-Greedy is more efficient and stable than LR-Greedy and GPSR.

Comparing supervised learning methods for classifying sex, age, context and individual Mudi dogs from barking.

PubMed

Larrañaga, Ana; Bielza, Concha; Pongrácz, Péter; Faragó, Tamás; Bálint, Anna; Larrañaga, Pedro

2015-03-01

Barking is perhaps the most characteristic form of vocalization in dogs; however, very little is known about its role in the intraspecific communication of this species. Besides the obvious need for ethological research, both in the field and in the laboratory, the possible information content of barks can also be explored by computerized acoustic analyses. This study compares four different supervised learning methods (naive Bayes, classification trees, [Formula: see text]-nearest neighbors and logistic regression) combined with three strategies for selecting variables (all variables, filter and wrapper feature subset selections) to classify Mudi dogs by sex, age, context and individual from their barks. The classification accuracy of the models obtained was estimated by means of [Formula: see text]-fold cross-validation. Percentages of correct classifications were 85.13 % for determining sex, 80.25 % for predicting age (recodified as young, adult and old), 55.50 % for classifying contexts (seven situations) and 67.63 % for recognizing individuals (8 dogs), so the results are encouraging. The best-performing method was [Formula: see text]-nearest neighbors following a wrapper feature selection approach. The results for classifying contexts and recognizing individual dogs were better with this method than they were for other approaches reported in the specialized literature. This is the first time that the sex and age of domestic dogs have been predicted with the help of sound analysis. This study shows that dog barks carry ample information regarding the caller's indexical features. Our computerized analysis provides indirect proof that barks may serve as an important source of information for dogs as well.

Adaptive classifier for steel strip surface defects

NASA Astrophysics Data System (ADS)

Jiang, Mingming; Li, Guangyao; Xie, Li; Xiao, Mang; Yi, Li

2017-01-01

Surface defects detection system has been receiving increased attention as its precision, speed and less cost. One of the most challenges is reacting to accuracy deterioration with time as aged equipment and changed processes. These variables will make a tiny change to the real world model but a big impact on the classification result. In this paper, we propose a new adaptive classifier with a Bayes kernel (BYEC) which update the model with small sample to it adaptive for accuracy deterioration. Firstly, abundant features were introduced to cover lots of information about the defects. Secondly, we constructed a series of SVMs with the random subspace of the features. Then, a Bayes classifier was trained as an evolutionary kernel to fuse the results from base SVMs. Finally, we proposed the method to update the Bayes evolutionary kernel. The proposed algorithm is experimentally compared with different algorithms, experimental results demonstrate that the proposed method can be updated with small sample and fit the changed model well. Robustness, low requirement for samples and adaptive is presented in the experiment.

Classifying Facial Actions

PubMed Central

Donato, Gianluca; Bartlett, Marian Stewart; Hager, Joseph C.; Ekman, Paul; Sejnowski, Terrence J.

2010-01-01

The Facial Action Coding System (FACS) [23] is an objective method for quantifying facial movement in terms of component actions. This system is widely used in behavioral investigations of emotion, cognitive processes, and social interaction. The coding is presently performed by highly trained human experts. This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. These techniques include analysis of facial motion through estimation of optical flow; holistic spatial analysis, such as principal component analysis, independent component analysis, local feature analysis, and linear discriminant analysis; and methods based on the outputs of local filters, such as Gabor wavelet representations and local principal components. Performance of these systems is compared to naive and expert human subjects. Best performances were obtained using the Gabor wavelet representation and the independent component representation, both of which achieved 96 percent accuracy for classifying 12 facial actions of the upper and lower face. The results provide converging evidence for the importance of using local filters, high spatial frequencies, and statistical independence for classifying facial actions. PMID:21188284

An explanatory analysis of driver injury severity in rear-end crashes using a decision table/Naïve Bayes (DTNB) hybrid classifier.

PubMed

Chen, Cong; Zhang, Guohui; Yang, Jinfu; Milton, John C; Alcántara, Adélamar Dely

2016-05-01

Rear-end crashes are a major type of traffic crashes in the U.S. Of practical necessity is a comprehensive examination of its mechanism that results in injuries and fatalities. Decision table (DT) and Naïve Bayes (NB) methods have both been used widely but separately for solving classification problems in multiple areas except for traffic safety research. Based on a two-year rear-end crash dataset, this paper applies a decision table/Naïve Bayes (DTNB) hybrid classifier to select the deterministic attributes and predict driver injury outcomes in rear-end crashes. The test results show that the hybrid classifier performs reasonably well, which was indicated by several performance evaluation measurements, such as accuracy, F-measure, ROC, and AUC. Fifteen significant attributes were found to be significant in predicting driver injury severities, including weather, lighting conditions, road geometry characteristics, driver behavior information, etc. The extracted decision rules demonstrate that heavy vehicle involvement, a comfortable traffic environment, inferior lighting conditions, two-lane rural roadways, vehicle disabled damage, and two-vehicle crashes would increase the likelihood of drivers sustaining fatal injuries. The research limitations on data size, data structure, and result presentation are also summarized. The applied methodology and estimation results provide insights for developing effective countermeasures to alleviate rear-end crash injury severities and improve traffic system safety performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of protein-interacting nucleotides in a RNA sequence using composition profile of tri-nucleotides.

PubMed

Panwar, Bharat; Raghava, Gajendra P S

2015-04-01

The RNA-protein interactions play a diverse role in the cells, thus identification of RNA-protein interface is essential for the biologist to understand their function. In the past, several methods have been developed for predicting RNA interacting residues in proteins, but limited efforts have been made for the identification of protein-interacting nucleotides in RNAs. In order to discriminate protein-interacting and non-interacting nucleotides, we used various classifiers (NaiveBayes, NaiveBayesMultinomial, BayesNet, ComplementNaiveBayes, MultilayerPerceptron, J48, SMO, RandomForest, SMO and SVM(light)) for prediction model development using various features and achieved highest 83.92% sensitivity, 84.82 specificity, 84.62% accuracy and 0.62 Matthew's correlation coefficient by SVM(light) based models. We observed that certain tri-nucleotides like ACA, ACC, AGA, CAC, CCA, GAG, UGA, and UUU preferred in protein-interaction. All the models have been developed using a non-redundant dataset and are evaluated using five-fold cross validation technique. A web-server called RNApin has been developed for the scientific community (http://crdd.osdd.net/raghava/rnapin/). Copyright © 2015 Elsevier Inc. All rights reserved.

The Analysis Performance Method Naive Bayes Andssvm Determine Pattern Groups of Disease

NASA Astrophysics Data System (ADS)

Sitanggang, Rianto; Tulus; Situmorang, Zakarias

2017-12-01

Information is a very important element and into the daily needs of the moment, to get a precise and accurate information is not easy, this research can help decision makers and make a comparison. Researchers perform data mining techniques to analyze the performance of methods and algorithms naïve Bayes methods Smooth Support Vector Machine (ssvm) in the grouping of the disease.The pattern of disease that is often suffered by people in the group can be in the detection area of the collection of information contained in the medical record. Medical records have infromasi disease by patients in coded according to standard WHO. Processing of medical record data to find patterns of this group of diseases that often occur in this community take the attribute address, sex, type of disease, and age. Determining the next analysis is grouping of four ersebut attribute. From the results of research conducted on the dataset fever diabete mellitus, naïve Bayes method produces an average value of 99% and an accuracy and SSVM method produces an average value of 93% accuracy

A review and experimental study on the application of classifiers and evolutionary algorithms in EEG-based brain-machine interface systems

NASA Astrophysics Data System (ADS)

Tahernezhad-Javazm, Farajollah; Azimirad, Vahid; Shoaran, Maryam

2018-04-01

Objective. Considering the importance and the near-future development of noninvasive brain-machine interface (BMI) systems, this paper presents a comprehensive theoretical-experimental survey on the classification and evolutionary methods for BMI-based systems in which EEG signals are used. Approach. The paper is divided into two main parts. In the first part, a wide range of different types of the base and combinatorial classifiers including boosting and bagging classifiers and evolutionary algorithms are reviewed and investigated. In the second part, these classifiers and evolutionary algorithms are assessed and compared based on two types of relatively widely used BMI systems, sensory motor rhythm-BMI and event-related potentials-BMI. Moreover, in the second part, some of the improved evolutionary algorithms as well as bi-objective algorithms are experimentally assessed and compared. Main results. In this study two databases are used, and cross-validation accuracy (CVA) and stability to data volume (SDV) are considered as the evaluation criteria for the classifiers. According to the experimental results on both databases, regarding the base classifiers, linear discriminant analysis and support vector machines with respect to CVA evaluation metric, and naive Bayes with respect to SDV demonstrated the best performances. Among the combinatorial classifiers, four classifiers, Bagg-DT (bagging decision tree), LogitBoost, and GentleBoost with respect to CVA, and Bagging-LR (bagging logistic regression) and AdaBoost (adaptive boosting) with respect to SDV had the best performances. Finally, regarding the evolutionary algorithms, single-objective invasive weed optimization (IWO) and bi-objective nondominated sorting IWO algorithms demonstrated the best performances. Significance. We present a general survey on the base and the combinatorial classification methods for EEG signals (sensory motor rhythm and event-related potentials) as well as their optimization methods

A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem.

PubMed

Dehzangi, Abdollah; Paliwal, Kuldip; Sharma, Alok; Dehzangi, Omid; Sattar, Abdul

2013-01-01

Better understanding of structural class of a given protein reveals important information about its overall folding type and its domain. It can also be directly used to provide critical information on general tertiary structure of a protein which has a profound impact on protein function determination and drug design. Despite tremendous enhancements made by pattern recognition-based approaches to solve this problem, it still remains as an unsolved issue for bioinformatics that demands more attention and exploration. In this study, we propose a novel feature extraction model that incorporates physicochemical and evolutionary-based information simultaneously. We also propose overlapped segmented distribution and autocorrelation-based feature extraction methods to provide more local and global discriminatory information. The proposed feature extraction methods are explored for 15 most promising attributes that are selected from a wide range of physicochemical-based attributes. Finally, by applying an ensemble of different classifiers namely, Adaboost.M1, LogitBoost, naive Bayes, multilayer perceptron (MLP), and support vector machine (SVM) we show enhancement of the protein structural class prediction accuracy for four popular benchmarks.

Simple hybrid method for fine microaneurysm detection from non-dilated diabetic retinopathy retinal images.

PubMed

Sopharak, Akara; Uyyanonvara, Bunyarit; Barman, Sarah

2013-01-01

Microaneurysms detection is an important task in computer aided diagnosis of diabetic retinopathy. Microaneurysms are the first clinical sign of diabetic retinopathy, a major cause of vision loss in diabetic patients. Early microaneurysm detection can help reduce the incidence of blindness. Automatic detection of microaneurysms is still an open problem due to their tiny sizes, low contrast and also similarity with blood vessels. It is particularly very difficult to detect fine microaneurysms, especially from non-dilated pupils and that is the goal of this paper. Simple yet effective methods are used. They are coarse segmentation using mathematic morphology and fine segmentation using naive Bayes classifier. A total of 18 microaneurysms features are proposed in this paper and they are extracted for naive Bayes classifier. The detected microaneurysms are validated by comparing at pixel level with ophthalmologists' hand-drawn ground-truth. The sensitivity, specificity, precision and accuracy are 85.68, 99.99, 83.34 and 99.99%, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Impaired P600 in neuroleptic naive patients with first-episode schizophrenia.

PubMed

Papageorgiou, C; Kontaxakis, V P; Havaki-Kontaxaki, B J; Stamouli, S; Vasios, C; Asvestas, P; Matsopoulos, G K; Kontopantelis, E; Rabavilas, A; Uzunoglu, N; Christodoulou, G N

2001-09-17

Deficits of working memory (WM) are recognized as an important pathological feature in schizophrenia. Since the P600 component of event related potentials has been hypothesized that represents aspects of second-pass parsing processes of information processing, and is related to WM, the present study focuses on P600 elicited during a WM test in drug-naive first-episode schizophrenics (FES) compared to healthy controls. We examined 16 drug-naive first-episode schizophrenic patients and 23 healthy controls matched for age and sex. Compared with controls schizophrenic patients showed reduced P600 amplitude on left temporoparietal region and increased P600 amplitude on left occipital region. With regard to the latency, the patients exhibited significantly prolongation on right temporoparietal region. The obtained pattern of differences classified correctly 89.20% of patients. Memory performance of patients was also significantly impaired relative to controls. Our results suggest that second-pass parsing process of information processing, as indexed by P600, elicited during a WM test, is impaired in FES. Moreover, these findings lend support to the view that the auditory WM in schizophrenia involves or affects a circuitry including temporoparietal and occipital brain areas.

An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.

PubMed

He, Jian; Bai, Shuang; Wang, Xiaoyi

2017-06-16

Falls are one of the main health risks among the elderly. A fall detection system based on inertial sensors can automatically detect fall event and alert a caregiver for immediate assistance, so as to reduce injuries causing by falls. Nevertheless, most inertial sensor-based fall detection technologies have focused on the accuracy of detection while neglecting quantization noise caused by inertial sensor. In this paper, an activity model based on tri-axial acceleration and gyroscope is proposed, and the difference between activities of daily living (ADLs) and falls is analyzed. Meanwhile, a Kalman filter is proposed to preprocess the raw data so as to reduce noise. A sliding window and Bayes network classifier are introduced to develop a wearable fall detection system, which is composed of a wearable motion sensor and a smart phone. The experiment shows that the proposed system distinguishes simulated falls from ADLs with a high accuracy of 95.67%, while sensitivity and specificity are 99.0% and 95.0%, respectively. Furthermore, the smart phone can issue an alarm to caregivers so as to provide timely and accurate help for the elderly, as soon as the system detects a fall.

A Novel Feature Selection Technique for Text Classification Using Naïve Bayes.

PubMed

Dey Sarkar, Subhajit; Goswami, Saptarsi; Agarwal, Aman; Aktar, Javed

2014-01-01

With the proliferation of unstructured data, text classification or text categorization has found many applications in topic classification, sentiment analysis, authorship identification, spam detection, and so on. There are many classification algorithms available. Naïve Bayes remains one of the oldest and most popular classifiers. On one hand, implementation of naïve Bayes is simple and, on the other hand, this also requires fewer amounts of training data. From the literature review, it is found that naïve Bayes performs poorly compared to other classifiers in text classification. As a result, this makes the naïve Bayes classifier unusable in spite of the simplicity and intuitiveness of the model. In this paper, we propose a two-step feature selection method based on firstly a univariate feature selection and then feature clustering, where we use the univariate feature selection method to reduce the search space and then apply clustering to select relatively independent feature sets. We demonstrate the effectiveness of our method by a thorough evaluation and comparison over 13 datasets. The performance improvement thus achieved makes naïve Bayes comparable or superior to other classifiers. The proposed algorithm is shown to outperform other traditional methods like greedy search based wrapper or CFS.

Relevance popularity: A term event model based feature selection scheme for text classification.

PubMed

Feng, Guozhong; An, Baiguo; Yang, Fengqin; Wang, Han; Zhang, Libiao

2017-01-01

Feature selection is a practical approach for improving the performance of text classification methods by optimizing the feature subsets input to classifiers. In traditional feature selection methods such as information gain and chi-square, the number of documents that contain a particular term (i.e. the document frequency) is often used. However, the frequency of a given term appearing in each document has not been fully investigated, even though it is a promising feature to produce accurate classifications. In this paper, we propose a new feature selection scheme based on a term event Multinomial naive Bayes probabilistic model. According to the model assumptions, the matching score function, which is based on the prediction probability ratio, can be factorized. Finally, we derive a feature selection measurement for each term after replacing inner parameters by their estimators. On a benchmark English text datasets (20 Newsgroups) and a Chinese text dataset (MPH-20), our numerical experiment results obtained from using two widely used text classifiers (naive Bayes and support vector machine) demonstrate that our method outperformed the representative feature selection methods.

Muscle categorization using PDF estimation and Naive Bayes classification.

PubMed

Adel, Tameem M; Smith, Benn E; Stashuk, Daniel W

2012-01-01

The structure of motor unit potentials (MUPs) and their times of occurrence provide information about the motor units (MUs) that created them. As such, electromyographic (EMG) data can be used to categorize muscles as normal or suffering from a neuromuscular disease. Using pattern discovery (PD) allows clinicians to understand the rationale underlying a certain muscle characterization; i.e. it is transparent. Discretization is required in PD, which leads to some loss in accuracy. In this work, characterization techniques that are based on estimating probability density functions (PDFs) for each muscle category are implemented. Characterization probabilities of each motor unit potential train (MUPT) are obtained from these PDFs and then Bayes rule is used to aggregate the MUPT characterization probabilities to calculate muscle level probabilities. Even though this technique is not as transparent as PD, its accuracy is higher than the discrete PD. Ultimately, the goal is to use a technique that is based on both PDFs and PD and make it as transparent and as efficient as possible, but first it was necessary to thoroughly assess how accurate a fully continuous approach can be. Using gaussian PDF estimation achieved improvements in muscle categorization accuracy over PD and further improvements resulted from using feature value histograms to choose more representative PDFs; for instance, using log-normal distribution to represent skewed histograms.

Mono-isotope Prediction for Mass Spectra Using Bayes Network.

PubMed

Li, Hui; Liu, Chunmei; Rwebangira, Mugizi Robert; Burge, Legand

2014-12-01

Mass spectrometry is one of the widely utilized important methods to study protein functions and components. The challenge of mono-isotope pattern recognition from large scale protein mass spectral data needs computational algorithms and tools to speed up the analysis and improve the analytic results. We utilized naïve Bayes network as the classifier with the assumption that the selected features are independent to predict mono-isotope pattern from mass spectrometry. Mono-isotopes detected from validated theoretical spectra were used as prior information in the Bayes method. Three main features extracted from the dataset were employed as independent variables in our model. The application of the proposed algorithm to publicMo dataset demonstrates that our naïve Bayes classifier is advantageous over existing methods in both accuracy and sensitivity.

Enhancement of gesture recognition for contactless interface using a personalized classifier in the operating room.

PubMed

Cho, Yongwon; Lee, Areum; Park, Jongha; Ko, Bemseok; Kim, Namkug

2018-07-01

Contactless operating room (OR) interfaces are important for computer-aided surgery, and have been developed to decrease the risk of contamination during surgical procedures. In this study, we used Leap Motion™, with a personalized automated classifier, to enhance the accuracy of gesture recognition for contactless interfaces. This software was trained and tested on a personal basis that means the training of gesture per a user. We used 30 features including finger and hand data, which were computed, selected, and fed into a multiclass support vector machine (SVM), and Naïve Bayes classifiers and to predict and train five types of gestures including hover, grab, click, one peak, and two peaks. Overall accuracy of the five gestures was 99.58% ± 0.06, and 98.74% ± 3.64 on a personal basis using SVM and Naïve Bayes classifiers, respectively. We compared gesture accuracy across the entire dataset and used SVM and Naïve Bayes classifiers to examine the strength of personal basis training. We developed and enhanced non-contact interfaces with gesture recognition to enhance OR control systems. Copyright © 2018 Elsevier B.V. All rights reserved.

The impact of modeling the dependencies among patient findings on classification accuracy and calibration.

PubMed Central

Monti, S.; Cooper, G. F.

1998-01-01

We present a new Bayesian classifier for computer-aided diagnosis. The new classifier builds upon the naive-Bayes classifier, and models the dependencies among patient findings in an attempt to improve its performance, both in terms of classification accuracy and in terms of calibration of the estimated probabilities. This work finds motivation in the argument that highly calibrated probabilities are necessary for the clinician to be able to rely on the model's recommendations. Experimental results are presented, supporting the conclusion that modeling the dependencies among findings improves calibration. PMID:9929288

Development of novel in silico model for developmental toxicity assessment by using naïve Bayes classifier method.

PubMed

Zhang, Hui; Ren, Ji-Xia; Kang, Yan-Li; Bo, Peng; Liang, Jun-Yu; Ding, Lan; Kong, Wei-Bao; Zhang, Ji

2017-08-01

Toxicological testing associated with developmental toxicity endpoints are very expensive, time consuming and labor intensive. Thus, developing alternative approaches for developmental toxicity testing is an important and urgent task in the drug development filed. In this investigation, the naïve Bayes classifier was applied to develop a novel prediction model for developmental toxicity. The established prediction model was evaluated by the internal 5-fold cross validation and external test set. The overall prediction results for the internal 5-fold cross validation of the training set and external test set were 96.6% and 82.8%, respectively. In addition, four simple descriptors and some representative substructures of developmental toxicants were identified. Thus, we hope the established in silico prediction model could be used as alternative method for toxicological assessment. And these obtained molecular information could afford a deeper understanding on the developmental toxicants, and provide guidance for medicinal chemists working in drug discovery and lead optimization. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of Interruption Behavior by Naive Encoders.

ERIC Educational Resources Information Center

Coon, Christine A.; Schwanenflugel, Paula J.

1996-01-01

Determines the characteristics of interactions that influence judgments of interruption behavior in naive observers. Asks subjects to decide whether an example of an interruption was an interruption and then rate it in terms of how "good" or "bad" it was. Finds that naive observers use some of the same features described in…

Risk of Erectile Dysfunction in Transfusion-naive Thalassemia Men

PubMed Central

Chen, Yu-Guang; Lin, Te-Yu; Lin, Cheng-Li; Dai, Ming-Shen; Ho, Ching-Liang; Kao, Chia-Hung

2015-01-01

Abstract Based on the mechanism of pathophysiology, thalassemia major or transfusion-dependent thalassemia patients may have an increased risk of developing organic erectile dysfunction resulting from hypogonadism. However, there have been few studies investigating the association between erectile dysfunction and transfusion-naive thalassemia populations. We constructed a population-based cohort study to elucidate the association between transfusion-naive thalassemia populations and organic erectile dysfunction This nationwide population-based cohort study involved analyzing data from 1998 to 2010 obtained from the Taiwanese National Health Insurance Research Database, with a follow-up period extending to the end of 2011. We identified men with transfusion-naive thalassemia and selected a comparison cohort that was frequency-matched with these according to age, and year of diagnosis thalassemia at a ratio of 1 thalassemia man to 4 control men. We analyzed the risks for transfusion-naive thalassemia men and organic erectile dysfunction by using Cox proportional hazards regression models. In this study, 588 transfusion-naive thalassemia men and 2337 controls were included. Total 12 patients were identified within the thalassaemia group and 10 within the control group. The overall risks for developing organic erectile dysfunction were 4.56-fold in patients with transfusion-naive thalassemia men compared with the comparison cohort after we adjusted for age and comorbidities. Our long-term cohort study results showed that in transfusion-naive thalassemia men, there was a higher risk for the development of organic erectile dysfunction, particularly in those patients with comorbidities. PMID:25837766

Neuropsychological Test Selection for Cognitive Impairment Classification: A Machine Learning Approach

PubMed Central

Williams, Jennifer A.; Schmitter-Edgecombe, Maureen; Cook, Diane J.

2016-01-01

Introduction Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was to determine the fewest number of clinical measures required to accurately classify participants as healthy older adult, mild cognitive impairment (MCI) or dementia using a suite of classification techniques. Methods Two variable selection machine learning models (i.e., naive Bayes, decision tree), a logistic regression, and two participant datasets (i.e., clinical diagnosis, clinical dementia rating; CDR) were explored. Participants classified using clinical diagnosis criteria included 52 individuals with dementia, 97 with MCI, and 161 cognitively healthy older adults. Participants classified using CDR included 154 individuals CDR = 0, 93 individuals with CDR = 0.5, and 25 individuals with CDR = 1.0+. Twenty-seven demographic, psychological, and neuropsychological variables were available for variable selection. Results No significant difference was observed between naive Bayes, decision tree, and logistic regression models for classification of both clinical diagnosis and CDR datasets. Participant classification (70.0 – 99.1%), geometric mean (60.9 – 98.1%), sensitivity (44.2 – 100%), and specificity (52.7 – 100%) were generally satisfactory. Unsurprisingly, the MCI/CDR = 0.5 participant group was the most challenging to classify. Through variable selection only 2 – 9 variables were required for classification and varied between datasets in a clinically meaningful way. Conclusions The current study results reveal that machine learning techniques can accurately classifying cognitive impairment and reduce the number of measures required for diagnosis. PMID:26332171

Equating an expert system to a classifier in order to evaluate the expert system

NASA Technical Reports Server (NTRS)

Odell, Patrick L.

1989-01-01

A strategy to evaluate an expert system is formulated. The strategy proposed is based on finding an equivalent classifier to an expert system and evaluate that classifier with respect to an optimal classifier, a Bayes classifier. Here it is shown that for the rules considered an equivalent classifier exists. Also, a brief consideration of meta and meta-meta rules is included. Also, a taxonomy of expert systems is presented and an assertion made that an equivalent classifier exists for each type of expert system in the taxonomy with associated sets of underlying assumptions.

Human Naive T Cells Express Functional CXCL8 and Promote Tumorigenesis.

PubMed

Crespo, Joel; Wu, Ke; Li, Wei; Kryczek, Ilona; Maj, Tomasz; Vatan, Linda; Wei, Shuang; Opipari, Anthony W; Zou, Weiping

2018-05-25

Naive T cells are thought to be functionally quiescent. In this study, we studied and compared the phenotype, cytokine profile, and potential function of human naive CD4 + T cells in umbilical cord and peripheral blood. We found that naive CD4 + T cells, but not memory T cells, expressed high levels of chemokine CXCL8. CXCL8 + naive T cells were preferentially enriched CD31 + T cells and did not express T cell activation markers or typical Th effector cytokines, including IFN-γ, IL-4, IL-17, and IL-22. In addition, upon activation, naive T cells retained high levels of CXCL8 expression. Furthermore, we showed that naive T cell-derived CXCL8 mediated neutrophil migration in the in vitro migration assay, supported tumor sphere formation, and promoted tumor growth in an in vivo human xenograft model. Thus, human naive T cells are phenotypically and functionally heterogeneous and can carry out active functions in immune responses. Copyright © 2018 by The American Association of Immunologists, Inc.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry.

PubMed

Silva, Fabrício R; Vidotti, Vanessa G; Cremasco, Fernanda; Dias, Marcelo; Gomi, Edson S; Costa, Vital P

2013-01-01

To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

A discrete wavelet based feature extraction and hybrid classification technique for microarray data analysis.

PubMed

Bennet, Jaison; Ganaprakasam, Chilambuchelvan Arul; Arputharaj, Kannan

2014-01-01

Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN), naive Bayes, and support vector machine (SVM). Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT) and moving window technique (MWT) is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

[Naïve Bayes classification for classifying injury-cause groups from Emergency Room data in the Friuli Venezia Giulia region (Northern Italy)].

PubMed

Valent, Francesca; Clagnan, Elena; Zanier, Loris

2014-01-01

to assess whether Naïve Bayes Classification could be used to classify injury causes from the Emergency Room (ER) database, because in the Friuli Venezia Giulia Region (Northern Italy) the electronic ER data have never been used to study the epidemiology of injuries, because the proportion of generic "accidental" causes is much higher than that of injuries with a specific cause. application of the Naïve Bayes Classification method to the regional ER database. sensitivity, specificity, positive and negative predictive values, agreement, and the kappa statistic were calculated for the train dataset and the distribution of causes of injury for the test dataset. on 22.248 records with known cause, the classifications assigned by the model agreed moderately (kappa =0.53) with those assigned by ER personnel. The model was then used on 76.660 unclassified cases. Although sensitivity and positive predictive value of the method were generally poor, mainly due to limitations in the ER data, it allowed to estimate for the first time the frequency of specific injury causes in the Region. the model was useful to provide the "big picture" of non-fatal injuries in the Region. To improve the collection of injury data at the ER, the options available for injury classification in the ER software are being revised to make categories exhaustive and mutually exclusive.

Derivation of novel human ground state naive pluripotent stem cells.

PubMed

Gafni, Ohad; Weinberger, Leehee; Mansour, Abed AlFatah; Manor, Yair S; Chomsky, Elad; Ben-Yosef, Dalit; Kalma, Yael; Viukov, Sergey; Maza, Itay; Zviran, Asaf; Rais, Yoach; Shipony, Zohar; Mukamel, Zohar; Krupalnik, Vladislav; Zerbib, Mirie; Geula, Shay; Caspi, Inbal; Schneir, Dan; Shwartz, Tamar; Gilad, Shlomit; Amann-Zalcenstein, Daniela; Benjamin, Sima; Amit, Ido; Tanay, Amos; Massarwa, Rada; Novershtern, Noa; Hanna, Jacob H

2013-12-12

Mouse embryonic stem (ES) cells are isolated from the inner cell mass of blastocysts, and can be preserved in vitro in a naive inner-cell-mass-like configuration by providing exogenous stimulation with leukaemia inhibitory factor (LIF) and small molecule inhibition of ERK1/ERK2 and GSK3β signalling (termed 2i/LIF conditions). Hallmarks of naive pluripotency include driving Oct4 (also known as Pou5f1) transcription by its distal enhancer, retaining a pre-inactivation X chromosome state, and global reduction in DNA methylation and in H3K27me3 repressive chromatin mark deposition on developmental regulatory gene promoters. Upon withdrawal of 2i/LIF, naive mouse ES cells can drift towards a primed pluripotent state resembling that of the post-implantation epiblast. Although human ES cells share several molecular features with naive mouse ES cells, they also share a variety of epigenetic properties with primed murine epiblast stem cells (EpiSCs). These include predominant use of the proximal enhancer element to maintain OCT4 expression, pronounced tendency for X chromosome inactivation in most female human ES cells, increase in DNA methylation and prominent deposition of H3K27me3 and bivalent domain acquisition on lineage regulatory genes. The feasibility of establishing human ground state naive pluripotency in vitro with equivalent molecular and functional features to those characterized in mouse ES cells remains to be defined. Here we establish defined conditions that facilitate the derivation of genetically unmodified human naive pluripotent stem cells from already established primed human ES cells, from somatic cells through induced pluripotent stem (iPS) cell reprogramming or directly from blastocysts. The novel naive pluripotent cells validated herein retain molecular characteristics and functional properties that are highly similar to mouse naive ES cells, and distinct from conventional primed human pluripotent cells. This includes competence in the generation

The Preference for Symmetry in Flower-Naive and Not-so-Naive Bumblebees

ERIC Educational Resources Information Center

Plowright, C. M. S.; Evans, S. A.; Leung, J. Chew; Collin, C. A.

2011-01-01

Truly flower-naive bumblebees, with no prior rewarded experience for visits on any visual patterns outside the colony, were tested for their choice of bilaterally symmetric over asymmetric patterns in a radial-arm maze. No preference for symmetry was found. Prior training with rewarded black and white disks did, however, lead to a significant…

Know your data: understanding implicit usage versus explicit action in video content classification

NASA Astrophysics Data System (ADS)

Yew, Jude; Shamma, David A.

2011-02-01

In this paper, we present a method for video category classification using only social metadata from websites like YouTube. In place of content analysis, we utilize communicative and social contexts surrounding videos as a means to determine a categorical genre, e.g. Comedy, Music. We hypothesize that video clips belonging to different genre categories would have distinct signatures and patterns that are reflected in their collected metadata. In particular, we define and describe social metadata as usage or action to aid in classification. We trained a Naive Bayes classifier to predict categories from a sample of 1,740 YouTube videos representing the top five genre categories. Using just a small number of the available metadata features, we compare the classifications produced by our Naive Bayes classifier with those provided by the uploader of that particular video. Compared to random predictions with the YouTube data (21% accurate), our classifier attained a mediocre 33% accuracy in predicting video genres. However, we found that the accuracy of our classifier significantly improves by nominal factoring of the explicit data features. By factoring the ratings of the videos in the dataset, the classifier was able to accurately predict the genres of 75% of the videos. We argue that the patterns of social activity found in the metadata are not just meaningful in their own right, but are indicative of the meaning of the shared video content. The results presented by this project represents a first step in investigating the potential meaning and significance of social metadata and its relation to the media experience.

Automated Detection of Driver Fatigue Based on AdaBoost Classifier with EEG Signals.

PubMed

Hu, Jianfeng

2017-01-01

Purpose: Driving fatigue has become one of the important causes of road accidents, there are many researches to analyze driver fatigue. EEG is becoming increasingly useful in the measuring fatigue state. Manual interpretation of EEG signals is impossible, so an effective method for automatic detection of EEG signals is crucial needed. Method: In order to evaluate the complex, unstable, and non-linear characteristics of EEG signals, four feature sets were computed from EEG signals, in which fuzzy entropy (FE), sample entropy (SE), approximate Entropy (AE), spectral entropy (PE), and combined entropies (FE + SE + AE + PE) were included. All these feature sets were used as the input vectors of AdaBoost classifier, a boosting method which is fast and highly accurate. To assess our method, several experiments including parameter setting and classifier comparison were conducted on 28 subjects. For comparison, Decision Trees (DT), Support Vector Machine (SVM) and Naive Bayes (NB) classifiers are used. Results: The proposed method (combination of FE and AdaBoost) yields superior performance than other schemes. Using FE feature extractor, AdaBoost achieves improved area (AUC) under the receiver operating curve of 0.994, error rate (ERR) of 0.024, Precision of 0.969, Recall of 0.984, F1 score of 0.976, and Matthews correlation coefficient (MCC) of 0.952, compared to SVM (ERR at 0.035, Precision of 0.957, Recall of 0.974, F1 score of 0.966, and MCC of 0.930 with AUC of 0.990), DT (ERR at 0.142, Precision of 0.857, Recall of 0.859, F1 score of 0.966, and MCC of 0.716 with AUC of 0.916) and NB (ERR at 0.405, Precision of 0.646, Recall of 0.434, F1 score of 0.519, and MCC of 0.203 with AUC of 0.606). It shows that the FE feature set and combined feature set outperform other feature sets. AdaBoost seems to have better robustness against changes of ratio of test samples for all samples and number of subjects, which might therefore aid in the real-time detection of driver fatigue

Automated Detection of Driver Fatigue Based on AdaBoost Classifier with EEG Signals

PubMed Central

Hu, Jianfeng

2017-01-01

Purpose: Driving fatigue has become one of the important causes of road accidents, there are many researches to analyze driver fatigue. EEG is becoming increasingly useful in the measuring fatigue state. Manual interpretation of EEG signals is impossible, so an effective method for automatic detection of EEG signals is crucial needed. Method: In order to evaluate the complex, unstable, and non-linear characteristics of EEG signals, four feature sets were computed from EEG signals, in which fuzzy entropy (FE), sample entropy (SE), approximate Entropy (AE), spectral entropy (PE), and combined entropies (FE + SE + AE + PE) were included. All these feature sets were used as the input vectors of AdaBoost classifier, a boosting method which is fast and highly accurate. To assess our method, several experiments including parameter setting and classifier comparison were conducted on 28 subjects. For comparison, Decision Trees (DT), Support Vector Machine (SVM) and Naive Bayes (NB) classifiers are used. Results: The proposed method (combination of FE and AdaBoost) yields superior performance than other schemes. Using FE feature extractor, AdaBoost achieves improved area (AUC) under the receiver operating curve of 0.994, error rate (ERR) of 0.024, Precision of 0.969, Recall of 0.984, F1 score of 0.976, and Matthews correlation coefficient (MCC) of 0.952, compared to SVM (ERR at 0.035, Precision of 0.957, Recall of 0.974, F1 score of 0.966, and MCC of 0.930 with AUC of 0.990), DT (ERR at 0.142, Precision of 0.857, Recall of 0.859, F1 score of 0.966, and MCC of 0.716 with AUC of 0.916) and NB (ERR at 0.405, Precision of 0.646, Recall of 0.434, F1 score of 0.519, and MCC of 0.203 with AUC of 0.606). It shows that the FE feature set and combined feature set outperform other feature sets. AdaBoost seems to have better robustness against changes of ratio of test samples for all samples and number of subjects, which might therefore aid in the real-time detection of driver fatigue

Sensitivity and specificity of machine learning classifiers and spectral domain OCT for the diagnosis of glaucoma.

PubMed

Vidotti, Vanessa G; Costa, Vital P; Silva, Fabrício R; Resende, Graziela M; Cremasco, Fernanda; Dias, Marcelo; Gomi, Edson S

2012-06-15

Purpose. To investigate the sensitivity and specificity of machine learning classifiers (MLC) and spectral domain optical coherence tomography (SD-OCT) for the diagnosis of glaucoma. Methods. Sixty-two patients with early to moderate glaucomatous visual field damage and 48 healthy individuals were included. All subjects underwent a complete ophthalmologic examination, achromatic standard automated perimetry, and RNFL imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, California, USA). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters. Subsequently, the following MLCs were tested: Classification Tree (CTREE), Random Forest (RAN), Bagging (BAG), AdaBoost M1 (ADA), Ensemble Selection (ENS), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Naive-Bayes (NB), and Support Vector Machine (SVM). Areas under the ROC curves (aROCs) obtained for each parameter and each MLC were compared. Results. The mean age was 57.0±9.2 years for healthy individuals and 59.9±9.0 years for glaucoma patients (p=0.103). Mean deviation values were -4.1±2.4 dB for glaucoma patients and -1.5±1.6 dB for healthy individuals (p<0.001). The SD-OCT parameters with the greater aROCs were inferior quadrant (0.813), average thickness (0.807), 7 o'clock position (0.765), and 6 o'clock position (0.754). The aROCs from classifiers varied from 0.785 (ADA) to 0.818 (BAG). The aROC obtained with BAG was not significantly different from the aROC obtained with the best single SD-OCT parameter (p=0.93). Conclusions. The SD-OCT showed good diagnostic accuracy in a group of patients with early glaucoma. In this series, MLCs did not improve the sensitivity and specificity of SD-OCT for the diagnosis of glaucoma.

Increased naive CD4+ and B lymphocyte subsets are associated with body mass loss and drive relative lymphocytosis in anorexia nervosa patients.

PubMed

Elegido, Ana; Graell, Montserrat; Andrés, Patricia; Gheorghe, Alina; Marcos, Ascensión; Nova, Esther

2017-03-01

Anorexia nervosa (AN) is an atypical form of malnutrition with peculiar changes in the immune system. We hypothesized that different lymphocyte subsets are differentially affected by malnutrition in AN, and thus, our aim was to investigate the influence of body mass loss on the variability of lymphocyte subsets in AN patients. A group of 66 adolescent female patients, aged 12-17 years, referred for their first episode of either AN or feeding or eating disorders not elsewhere classified were studied upon admission (46 AN-restricting subtype, 11 AN-binge/purging subtype, and 9 feeding or eating disorders not elsewhere classified). Ninety healthy adolescents served as controls. White blood cells and lymphocyte subsets were analyzed by flow cytometry. Relationships with the body mass index (BMI) z score were assessed in linear models adjusted by diagnostic subtype and age. Leukocyte numbers were lower in AN patients than in controls, and relative lymphocytosis was observed in AN-restricting subtype. Lower CD8 + , NK, and memory CD8 + counts were found in eating disorder patients compared with controls. No differences were found for CD4 + counts or naive and memory CD4 + subsets between the groups. Negative associations between lymphocyte percentage and the BMI z score, as well as between the B cell counts, naive CD4 + percentage and counts, and the BMI z score, were found. In conclusion, increased naive CD4 + and B lymphocyte subsets associated with body mass loss drive the relative lymphocytosis observed in AN patients, which reflects an adaptive mechanism to preserve the adaptive immune response. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

PubMed

Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

2017-06-21

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction

Combining deep residual neural network features with supervised machine learning algorithms to classify diverse food image datasets.

PubMed

McAllister, Patrick; Zheng, Huiru; Bond, Raymond; Moorhead, Anne

2018-04-01

Obesity is increasing worldwide and can cause many chronic conditions such as type-2 diabetes, heart disease, sleep apnea, and some cancers. Monitoring dietary intake through food logging is a key method to maintain a healthy lifestyle to prevent and manage obesity. Computer vision methods have been applied to food logging to automate image classification for monitoring dietary intake. In this work we applied pretrained ResNet-152 and GoogleNet convolutional neural networks (CNNs), initially trained using ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset with MatConvNet package, to extract features from food image datasets; Food 5K, Food-11, RawFooT-DB, and Food-101. Deep features were extracted from CNNs and used to train machine learning classifiers including artificial neural network (ANN), support vector machine (SVM), Random Forest, and Naive Bayes. Results show that using ResNet-152 deep features with SVM with RBF kernel can accurately detect food items with 99.4% accuracy using Food-5K validation food image dataset and 98.8% with Food-5K evaluation dataset using ANN, SVM-RBF, and Random Forest classifiers. Trained with ResNet-152 features, ANN can achieve 91.34%, 99.28% when applied to Food-11 and RawFooT-DB food image datasets respectively and SVM with RBF kernel can achieve 64.98% with Food-101 image dataset. From this research it is clear that using deep CNN features can be used efficiently for diverse food item image classification. The work presented in this research shows that pretrained ResNet-152 features provide sufficient generalisation power when applied to a range of food image classification tasks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Enhancing atlas based segmentation with multiclass linear classifiers

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

Sdika, Michaël, E-mail: michael.sdika@creatis.insa-lyon.fr

Purpose: To present a method to enrich atlases for atlas based segmentation. Such enriched atlases can then be used as a single atlas or within a multiatlas framework. Methods: In this paper, machine learning techniques have been used to enhance the atlas based segmentation approach. The enhanced atlas defined in this work is a pair composed of a gray level image alongside an image of multiclass classifiers with one classifier per voxel. Each classifier embeds local information from the whole training dataset that allows for the correction of some systematic errors in the segmentation and accounts for the possible localmore » registration errors. The authors also propose to use these images of classifiers within a multiatlas framework: results produced by a set of such local classifier atlases can be combined using a label fusion method. Results: Experiments have been made on the in vivo images of the IBSR dataset and a comparison has been made with several state-of-the-art methods such as FreeSurfer and the multiatlas nonlocal patch based method of Coupé or Rousseau. These experiments show that their method is competitive with state-of-the-art methods while having a low computational cost. Further enhancement has also been obtained with a multiatlas version of their method. It is also shown that, in this case, nonlocal fusion is unnecessary. The multiatlas fusion can therefore be done efficiently. Conclusions: The single atlas version has similar quality as state-of-the-arts multiatlas methods but with the computational cost of a naive single atlas segmentation. The multiatlas version offers a improvement in quality and can be done efficiently without a nonlocal strategy.« less

Comparing Action Gestures and Classifier Verbs of Motion: Evidence from Australian Sign Language, Taiwan Sign Language, and Nonsigners' Gestures without Speech

ERIC Educational Resources Information Center

Schembri, Adam; Jones, Caroline; Burnham, Denis

2005-01-01

Recent research into signed languages indicates that signs may share some properties with gesture, especially in the use of space in classifier constructions. A prediction of this proposal is that there will be similarities in the representation of motion events by sign-naive gesturers and by native signers of unrelated signed languages. This…

Probabilistic Multi-Person Tracking Using Dynamic Bayes Networks

NASA Astrophysics Data System (ADS)

Klinger, T.; Rottensteiner, F.; Heipke, C.

2015-08-01

Tracking-by-detection is a widely used practice in recent tracking systems. These usually rely on independent single frame detections that are handled as observations in a recursive estimation framework. If these observations are imprecise the generated trajectory is prone to be updated towards a wrong position. In contrary to existing methods our novel approach uses a Dynamic Bayes Network in which the state vector of a recursive Bayes filter, as well as the location of the tracked object in the image are modelled as unknowns. These unknowns are estimated in a probabilistic framework taking into account a dynamic model, and a state-of-the-art pedestrian detector and classifier. The classifier is based on the Random Forest-algorithm and is capable of being trained incrementally so that new training samples can be incorporated at runtime. This allows the classifier to adapt to the changing appearance of a target and to unlearn outdated features. The approach is evaluated on a publicly available benchmark. The results confirm that our approach is well suited for tracking pedestrians over long distances while at the same time achieving comparatively good geometric accuracy.

On the classification techniques in data mining for microarray data classification

NASA Astrophysics Data System (ADS)

Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

Do the Naive Know Best? The Predictive Power of Naive Ratings of Couple Interactions

ERIC Educational Resources Information Center

Baucom, Katherine J. W.; Baucom, Brian R.; Christensen, Andrew

2012-01-01

We examined the utility of naive ratings of communication patterns and relationship quality in a large sample of distressed couples. Untrained raters assessed 10-min videotaped interactions from 134 distressed couples who participated in both problem-solving and social support discussions at each of 3 time points (pre-therapy, post-therapy, and…

Blocking the recruitment of naive CD4+ T cells reverses immunosuppression in breast cancer

PubMed Central

Su, Shicheng; Liao, Jianyou; Liu, Jiang; Huang, Di; He, Chonghua; Chen, Fei; Yang, LinBing; Wu, Wei; Chen, Jianing; Lin, Ling; Zeng, Yunjie; Ouyang, Nengtai; Cui, Xiuying; Yao, Herui; Su, Fengxi; Huang, Jian-dong; Lieberman, Judy; Liu, Qiang; Song, Erwei

2017-01-01

The origin of tumor-infiltrating Tregs, critical mediators of tumor immunosuppression, is unclear. Here, we show that tumor-infiltrating naive CD4+ T cells and Tregs in human breast cancer have overlapping TCR repertoires, while hardly overlap with circulating Tregs, suggesting that intratumoral Tregs mainly develop from naive T cells in situ rather than from recruited Tregs. Furthermore, the abundance of naive CD4+ T cells and Tregs is closely correlated, both indicating poor prognosis for breast cancer patients. Naive CD4+ T cells adhere to tumor slices in proportion to the abundance of CCL18-producing macrophages. Moreover, adoptively transferred human naive CD4+ T cells infiltrate human breast cancer orthotopic xenografts in a CCL18-dependent manner. In human breast cancer xenografts in humanized mice, blocking the recruitment of naive CD4+ T cells into tumor by knocking down the expression of PITPNM3, a CCL18 receptor, significantly reduces intratumoral Tregs and inhibits tumor progression. These findings suggest that breast tumor-infiltrating Tregs arise from chemotaxis of circulating naive CD4+ T cells that differentiate into Tregs in situ. Inhibiting naive CD4+ T cell recruitment into tumors by interfering with PITPNM3 recognition of CCL18 may be an attractive strategy for anticancer immunotherapy. PMID:28290464

Automated Classification of Pathology Reports.

PubMed

Oleynik, Michel; Finger, Marcelo; Patrão, Diogo F C

2015-01-01

This work develops an automated classifier of pathology reports which infers the topography and the morphology classes of a tumor using codes from the International Classification of Diseases for Oncology (ICD-O). Data from 94,980 patients of the A.C. Camargo Cancer Center was used for training and validation of Naive Bayes classifiers, evaluated by the F1-score. Measures greater than 74% in the topographic group and 61% in the morphologic group are reported. Our work provides a successful baseline for future research for the classification of medical documents written in Portuguese and in other domains.

Naive Juveniles Are More Likely to Become Breeders after Witnessing Predator Mobbing.

PubMed

Griesser, Michael; Suzuki, Toshitaka N

2017-01-01

Responding appropriately during the first predatory attack in life is often critical for survival. In many social species, naive juveniles acquire this skill from conspecifics, but its fitness consequences remain virtually unknown. Here we experimentally demonstrate how naive juvenile Siberian jays (Perisoreus infaustus) derive a long-term fitness benefit from witnessing knowledgeable adults mobbing their principal predator, the goshawk (Accipiter gentilis). Siberian jays live in family groups of two to six individuals that also can include unrelated nonbreeders. Field observations showed that Siberian jays encounter predators only rarely, and, indeed, naive juveniles do not respond to predator models when on their own but do when observing other individuals mobbing them. Predator exposure experiments demonstrated that naive juveniles had a substantially higher first-winter survival after observing knowledgeable group members mobbing a goshawk model, increasing their likelihood of acquiring a breeding position later in life. Previous research showed that naive individuals may learn from others how to respond to predators, care for offspring, or choose mates, generally assuming that social learning has long-term fitness consequences without empirical evidence. Our results demonstrate a long-term fitness benefit of vertical social learning for naive individuals in the wild, emphasizing its evolutionary importance in animals, including humans.

Two separate defects affecting true naive or virtual memory T cell precursors combine to reduce naive T cell responses with aging.

PubMed

Renkema, Kristin R; Li, Gang; Wu, Angela; Smithey, Megan J; Nikolich-Žugich, Janko

2014-01-01

Naive T cell responses are eroded with aging. We and others have recently shown that unimmunized old mice lose ≥ 70% of Ag-specific CD8 T cell precursors and that many of the remaining precursors acquire a virtual (central) memory (VM; CD44(hi)CD62L(hi)) phenotype. In this study, we demonstrate that unimmunized TCR transgenic (TCRTg) mice also undergo massive VM conversion with age, exhibiting rapid effector function upon both TCR and cytokine triggering. Age-related VM conversion in TCRTg mice directly depended on replacement of the original TCRTg specificity by endogenous TCRα rearrangements, indicating that TCR signals must be critical in VM conversion. Importantly, we found that VM conversion had adverse functional effects in both old wild-type and old TCRTg mice; that is, old VM, but not old true naive, T cells exhibited blunted TCR-mediated, but not IL-15-mediated, proliferation. This selective proliferative senescence correlated with increased apoptosis in old VM cells in response to peptide, but decreased apoptosis in response to homeostatic cytokines IL-7 and IL-15. Our results identify TCR as the key factor in differential maintenance and function of Ag-specific precursors in unimmunized mice with aging, and they demonstrate that two separate age-related defects--drastic reduction in true naive T cell precursors and impaired proliferative capacity of their VM cousins--combine to reduce naive T cell responses with aging.

Accuracy of Bayes and Logistic Regression Subscale Probabilities for Educational and Certification Tests

ERIC Educational Resources Information Center

Rudner, Lawrence

2016-01-01

In the machine learning literature, it is commonly accepted as fact that as calibration sample sizes increase, Naïve Bayes classifiers initially outperform Logistic Regression classifiers in terms of classification accuracy. Applied to subtests from an on-line final examination and from a highly regarded certification examination, this study shows…

Biomarker selection and classification of "-omics" data using a two-step bayes classification framework.

PubMed

Assawamakin, Anunchai; Prueksaaroon, Supakit; Kulawonganunchai, Supasak; Shaw, Philip James; Varavithya, Vara; Ruangrajitpakorn, Taneth; Tongsima, Sissades

2013-01-01

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

Naive Theories of Social Groups

ERIC Educational Resources Information Center

Rhodes, Marjorie

2012-01-01

Four studies examined children's (ages 3-10, Total N = 235) naive theories of social groups, in particular, their expectations about how group memberships constrain social interactions. After introduction to novel groups of people, preschoolers (ages 3-5) reliably expected agents from one group to harm members of the other group (rather than…

Bayes' Theorem: An Old Tool Applicable to Today's Classroom Measurement Needs. ERIC/AE Digest.

ERIC Educational Resources Information Center

Rudner, Lawrence M.

This digest introduces ways of responding to the call for criterion-referenced information using Bayes' Theorem, a method that was coupled with criterion-referenced testing in the early 1970s (see R. Hambleton and M. Novick, 1973). To illustrate Bayes' Theorem, an example is given in which the goal is to classify an examinee as being a master or…

Computer-aided diagnosis with potential application to rapid detection of disease outbreaks.

PubMed

Burr, Tom; Koster, Frederick; Picard, Rick; Forslund, Dave; Wokoun, Doug; Joyce, Ed; Brillman, Judith; Froman, Phil; Lee, Jack

2007-04-15

Our objectives are to quickly interpret symptoms of emergency patients to identify likely syndromes and to improve population-wide disease outbreak detection. We constructed a database of 248 syndromes, each syndrome having an estimated probability of producing any of 85 symptoms, with some two-way, three-way, and five-way probabilities reflecting correlations among symptoms. Using these multi-way probabilities in conjunction with an iterative proportional fitting algorithm allows estimation of full conditional probabilities. Combining these conditional probabilities with misdiagnosis error rates and incidence rates via Bayes theorem, the probability of each syndrome is estimated. We tested a prototype of computer-aided differential diagnosis (CADDY) on simulated data and on more than 100 real cases, including West Nile Virus, Q fever, SARS, anthrax, plague, tularaemia and toxic shock cases. We conclude that: (1) it is important to determine whether the unrecorded positive status of a symptom means that the status is negative or that the status is unknown; (2) inclusion of misdiagnosis error rates produces more realistic results; (3) the naive Bayes classifier, which assumes all symptoms behave independently, is slightly outperformed by CADDY, which includes available multi-symptom information on correlations; as more information regarding symptom correlations becomes available, the advantage of CADDY over the naive Bayes classifier should increase; (4) overlooking low-probability, high-consequence events is less likely if the standard output summary is augmented with a list of rare syndromes that are consistent with observed symptoms, and (5) accumulating patient-level probabilities across a larger population can aid in biosurveillance for disease outbreaks. c 2007 John Wiley & Sons, Ltd.

Hyperspectral remote sensing study of harmful algal blooms in the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Nie, Yixiang

Recent development of hyperspectral remote sensing provides capability to identify and classify harmful algal blooms beyond the estimation of chlorophyll concentrations. This study uses hyperspectral data to extract spectral signatures, classify algal blooms, and map the spatial distribution of the algal blooms in the upper Chesapeake Bay. Furthermore, water quality parameters from ground stations have been used together with remote sensing data to provide better understanding of the formation and transformation of the life cycle of harmful algal blooms, and the cause of their outbreaks in the upper Chesapeake Bay. The present results show a strong and significant positive correlation between chlorophyll concentrations and total organic nitrogen concentrations. This relation suggests that total organic nitrogen played an important role in triggering the harmful algal blooms in the upper Chesapeake Bay in this study. This study establishes an integrated approach which combines hyperspectral imaging with multispectral ocean color remote sensing data and traditional water quality monitoring system in the study of harmful algal blooms in small water bodies such as the Chesapeake Bay. Presently, remote sensing is well integrated into the research community, but is less commonly used by resource managers. This dissertation couples remote sensing technologies with specific monitoring programs. The present results will help natural resource managers, local authorities, and the public to utilize an integrated approach in order to better understand, evaluate, preserve, and restore the health of the Chesapeake Bay waters and habitats.

Naive Theory of Biology: The Pre-School Child's Explanation of Death

ERIC Educational Resources Information Center

Vlok, Milandre; de Witt, Marike W.

2012-01-01

This article explains the naive theory of biology that the pre-school child uses to explain the cause of death. The empirical investigation showed that the young participants do use a naive theory of biology to explain function and do make reference to "vitalistic causality" in explaining organ function. Furthermore, most of these…

Protein classification based on text document classification techniques.

PubMed

Cheng, Betty Yee Man; Carbonell, Jaime G; Klein-Seetharaman, Judith

2005-03-01

The need for accurate, automated protein classification methods continues to increase as advances in biotechnology uncover new proteins. G-protein coupled receptors (GPCRs) are a particularly difficult superfamily of proteins to classify due to extreme diversity among its members. Previous comparisons of BLAST, k-nearest neighbor (k-NN), hidden markov model (HMM) and support vector machine (SVM) using alignment-based features have suggested that classifiers at the complexity of SVM are needed to attain high accuracy. Here, analogous to document classification, we applied Decision Tree and Naive Bayes classifiers with chi-square feature selection on counts of n-grams (i.e. short peptide sequences of length n) to this classification task. Using the GPCR dataset and evaluation protocol from the previous study, the Naive Bayes classifier attained an accuracy of 93.0 and 92.4% in level I and level II subfamily classification respectively, while SVM has a reported accuracy of 88.4 and 86.3%. This is a 39.7 and 44.5% reduction in residual error for level I and level II subfamily classification, respectively. The Decision Tree, while inferior to SVM, outperforms HMM in both level I and level II subfamily classification. For those GPCR families whose profiles are stored in the Protein FAMilies database of alignments and HMMs (PFAM), our method performs comparably to a search against those profiles. Finally, our method can be generalized to other protein families by applying it to the superfamily of nuclear receptors with 94.5, 97.8 and 93.6% accuracy in family, level I and level II subfamily classification respectively. Copyright 2005 Wiley-Liss, Inc.

Textual and visual content-based anti-phishing: a Bayesian approach.

PubMed

Zhang, Haijun; Liu, Gang; Chow, Tommy W S; Liu, Wenyin

2011-10-01

A novel framework using a Bayesian approach for content-based phishing web page detection is presented. Our model takes into account textual and visual contents to measure the similarity between the protected web page and suspicious web pages. A text classifier, an image classifier, and an algorithm fusing the results from classifiers are introduced. An outstanding feature of this paper is the exploration of a Bayesian model to estimate the matching threshold. This is required in the classifier for determining the class of the web page and identifying whether the web page is phishing or not. In the text classifier, the naive Bayes rule is used to calculate the probability that a web page is phishing. In the image classifier, the earth mover's distance is employed to measure the visual similarity, and our Bayesian model is designed to determine the threshold. In the data fusion algorithm, the Bayes theory is used to synthesize the classification results from textual and visual content. The effectiveness of our proposed approach was examined in a large-scale dataset collected from real phishing cases. Experimental results demonstrated that the text classifier and the image classifier we designed deliver promising results, the fusion algorithm outperforms either of the individual classifiers, and our model can be adapted to different phishing cases. © 2011 IEEE

Phytoplankton and nutrient dynamics in Winyah Bay, SC.

NASA Astrophysics Data System (ADS)

Boneillo, G. E.; Brooks, S. S.; Brown, S. L.; Woodford, K. M.; Wright, C. R.

2016-02-01

Winyah Bay is a coastal plain estuary located in South Carolina that has been classified for a moderate risk of Eutrophication by NOAA. Winyah Bay receives freshwater input from four rivers, the Waccamaw, Sampit, Black, and Pee Dee Rivers. The Waccamaw, Sampit and Black River are blackwater systems that discharge elevated amounts of colored dissolved organic matter. During the summer and fall of 2015, bioassay experiments were performed to simultaneously examine both light and nutrient (nitrogen & phosphate) limitation throughout Winyah Bay. Sampling stations near the mouth of the Waccamaw and Sampit Rivers showed that phytoplankton were light limited in the late summer instead of nutrient limited. These stations were located in the industrialized area of the bay and typically had the highest nutrient concentrations and highest turbidity, with Secchi depths typically less than 0.5 meters. Results indicated that phytoplankton may be nitrogen limited near the mouth of Winyah Bay, where nutrient concentrations and turbidity were observed to be lower than locations further upstream. There was also an observed dissolved oxygen and pH gradient during the summer of 2015. Dissolved oxygen levels less than 4.0 mg/L were routinely observed near the industrialized head of the estuary and corresponded with lower pH values.

An Investigation to Improve Classifier Accuracy for Myo Collected Data

DTIC Science & Technology

2017-02-01

distribution is unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT A naïve Bayes classifier trained with 1,360 samples from 17 volunteers performs at...movement data from 17 volunteers . Each volunteer performed 8 gestures (Freeze, Rally Point, Hurry Up, Down, Come, Stop, Line Abreast Formation, and Vehicle...line chart was plotted for each gesture’s feature (e.g., Pitch, xAcc) per user. All 10 recorded samples of a particular gesture for a single volunteer

Calcium-mediated shaping of naive CD4 T-cell phenotype and function

PubMed Central

Guichard, Vincent; Bonilla, Nelly; Durand, Aurélie; Audemard-Verger, Alexandra; Guilbert, Thomas; Martin, Bruno

2017-01-01

Continuous contact with self-major histocompatibility complex ligands is essential for the survival of naive CD4 T cells. We have previously shown that the resulting tonic TCR signaling also influences their fate upon activation by increasing their ability to differentiate into induced/peripheral regulatory T cells. To decipher the molecular mechanisms governing this process, we here focus on the TCR signaling cascade and demonstrate that a rise in intracellular calcium levels is sufficient to modulate the phenotype of mouse naive CD4 T cells and to increase their sensitivity to regulatory T-cell polarization signals, both processes relying on calcineurin activation. Accordingly, in vivo calcineurin inhibition leads the most self-reactive naive CD4 T cells to adopt the phenotype of their less self-reactive cell-counterparts. Collectively, our findings demonstrate that calcium-mediated activation of the calcineurin pathway acts as a rheostat to shape both the phenotype and effector potential of naive CD4 T cells in the steady-state. PMID:29239722

LORETA functional imaging in antipsychotic-naive and olanzapine-, clozapine- and risperidone-treated patients with schizophrenia.

PubMed

Tislerova, Barbora; Brunovsky, Martin; Horacek, Jiri; Novak, Tomas; Kopecek, Miloslav; Mohr, Pavel; Krajca, Vladimír

2008-01-01

The aim of our study was to detect changes in the distribution of electrical brain activity in schizophrenic patients who were antipsychotic naive and those who received treatment with clozapine, olanzapine or risperidone. We included 41 subjects with schizophrenia (antipsychotic naive = 11; clozapine = 8; olanzapine = 10; risperidone = 12) and 20 healthy controls. Low-resolution brain electromagnetic tomography was computed from 19-channel electroencephalography for the frequency bands delta, theta, alpha-1, alpha-2, beta-1, beta-2 and beta-3. We compared antipsychotic-naive subjects with healthy controls and medicated patients. (1) Comparing antipsychotic-naive subjects and controls we found a general increase in the slow delta and theta frequencies over the fronto-temporo-occipital cortex, particularly in the temporolimbic structures, an increase in alpha-1 and alpha-2 in the temporal cortex and an increase in beta-1 and beta-2 in the temporo-occipital and posterior limbic structures. (2) Comparing patients who received clozapine and those who were antipsychotic naive, we found an increase in delta and theta frequencies in the anterior cingulate and medial frontal cortex, and a decrease in alpha-1 and beta-2 in the occipital structures. (3) Comparing patients taking olanzapine with those who were antipsychotic naive, there was an increase in theta frequencies in the anterior cingulum, a decrease in alpha-1, beta-2 and beta-3 in the occipital cortex and posterior limbic structures, and a decrease in beta-3 in the frontotemporal cortex and anterior cingulum. (4) In patients taking risperidone, we found no significant changes from those who were antipsychotic naive. Our results in antipsychotic-naive patients are in agreement with existing functional findings. Changes in those taking clozapine and olanzapine versus those who were antipsychotic naive suggest a compensatory mechanism in the neurobiological substrate for schizophrenia. The lack of difference in

Inputs and spatial distribution patterns of Cr in Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Miao, Zhenqing; Huang, Xinmin; Wei, Linzhen; Feng, Ming

2018-03-01

Cr pollution in marine bays has been one of the critical environmental issues, and understanding the input and spatial distribution patterns is essential to pollution control. In according to the source strengths of the major pollution sources, the input patterns of pollutants to marine bay include slight, moderate and heavy, and the spatial distribution are corresponding to three block models respectively. This paper analyzed input patterns and distributions of Cr in Jiaozhou Bay, eastern China based on investigation on Cr in surface waters during 1979-1983. Results showed that the input strengths of Cr in Jiaozhou Bay could be classified as moderate input and slight input, and the input strengths were 32.32-112.30 μg L-1 and 4.17-19.76 μg L-1, respectively. The input patterns of Cr included two patterns of moderate input and slight input, and the horizontal distributions could be defined by means of Block Model 2 and Block Model 3, respectively. In case of moderate input pattern via overland runoff, Cr contents were decreasing from the estuaries to the bay mouth, and the distribution pattern was parallel. In case of moderate input pattern via marine current, Cr contents were decreasing from the bay mouth to the bay, and the distribution pattern was parallel to circular. The Block Models were able to reveal the transferring process of various pollutants, and were helpful to understand the distributions of pollutants in marine bay.

Prediction of Endocrine System Affectation in Fisher 344 Rats by Food Intake Exposed with Malathion, Applying Naïve Bayes Classifier and Genetic Algorithms

PubMed Central

Mora, Juan David Sandino; Hurtado, Darío Amaya; Sandoval, Olga Lucía Ramos

2016-01-01

Background: Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. Methods: It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#. Results: There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months. Conclusions: The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands. PMID:27833725

Prediction of Endocrine System Affectation in Fisher 344 Rats by Food Intake Exposed with Malathion, Applying Naïve Bayes Classifier and Genetic Algorithms.

PubMed

Mora, Juan David Sandino; Hurtado, Darío Amaya; Sandoval, Olga Lucía Ramos

2016-01-01

Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#. There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months. The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands.

Using empirical Bayes predictors from generalized linear mixed models to test and visualize associations among longitudinal outcomes.

PubMed

Mikulich-Gilbertson, Susan K; Wagner, Brandie D; Grunwald, Gary K; Riggs, Paula D; Zerbe, Gary O

2018-01-01

Medical research is often designed to investigate changes in a collection of response variables that are measured repeatedly on the same subjects. The multivariate generalized linear mixed model (MGLMM) can be used to evaluate random coefficient associations (e.g. simple correlations, partial regression coefficients) among outcomes that may be non-normal and differently distributed by specifying a multivariate normal distribution for their random effects and then evaluating the latent relationship between them. Empirical Bayes predictors are readily available for each subject from any mixed model and are observable and hence, plotable. Here, we evaluate whether second-stage association analyses of empirical Bayes predictors from a MGLMM, provide a good approximation and visual representation of these latent association analyses using medical examples and simulations. Additionally, we compare these results with association analyses of empirical Bayes predictors generated from separate mixed models for each outcome, a procedure that could circumvent computational problems that arise when the dimension of the joint covariance matrix of random effects is large and prohibits estimation of latent associations. As has been shown in other analytic contexts, the p-values for all second-stage coefficients that were determined by naively assuming normality of empirical Bayes predictors provide a good approximation to p-values determined via permutation analysis. Analyzing outcomes that are interrelated with separate models in the first stage and then associating the resulting empirical Bayes predictors in a second stage results in different mean and covariance parameter estimates from the maximum likelihood estimates generated by a MGLMM. The potential for erroneous inference from using results from these separate models increases as the magnitude of the association among the outcomes increases. Thus if computable, scatterplots of the conditionally independent empirical Bayes

What Fits into a Mirror: Naive Beliefs about the Field of View

ERIC Educational Resources Information Center

Bianchi, Ivana; Savardi, Ugo

2012-01-01

Research on naive physics and naive optics have shown that people hold surprising beliefs about everyday phenomena that are in contrast with what they see. In this article, we investigated what adults expect to be the field of view of a mirror from various viewpoints. The studies presented here confirm that humans have difficulty dealing with the…

Impaired processing speed and attention in first-episode drug naive schizophrenia with deficit syndrome.

PubMed

Chen, Ce; Jiang, Wenhui; Zhong, Na; Wu, Jin; Jiang, Haifeng; Du, Jiang; Li, Ye; Ma, Xiancang; Zhao, Min; Hashimoto, Kenji; Gao, Chengge

2014-11-01

Although first-episode drug naive patients with schizophrenia are known to show cognitive impairment, the cognitive performances of these patients, who suffer deficit syndrome, compared with those who suffer non-deficit syndrome is undetermined. The aim of this study was to compare cognitive performances in first-episode drug-naive schizophrenia with deficit syndrome or non-deficit syndrome. First-episode drug naive patients (n=49) and medicated patients (n=108) with schizophrenia, and age, sex, and education matched healthy controls (n=57 for the first-episode group, and n=128 for the medicated group) were enrolled. Patients were divided into deficit or non-deficit syndrome groups, using the Schedule for Deficit Syndrome. Cognitive performance was assessed using the CogState computerized cognitive battery. All cognitive domains in first-episode drug naive and medicated patients showed significant impairment compared with their respective control groups. Furthermore, cognitive performance in first-episode drug naive patients was significantly worse than in medicated patients. Interestingly, the cognitive performance markers of processing speed and attention, in first-episode drug naive patients with deficit syndrome, were both significantly worse than in equivalent patients without deficit syndrome. In contrast, no differences in cognitive performance were found between the two groups of medicated patients. In conclusion, this study found that first-episode drug naive schizophrenia with deficit syndrome showed significantly impaired processing speed and attention, compared with patients with non-deficit syndrome. These findings highlight processing speed and attention as potential targets for pharmacological and psychosocial interventions in first-episode schizophrenia with deficit syndrome, since these domains are associated with social outcomes. Copyright © 2014 Elsevier B.V. All rights reserved.

Characterizing Seagrass Exposure to Light Attenuation and Turbidity Associated with Dredging Activity in the Gulf Intracoastal Waterway, Sarasota Bay, Florida

DTIC Science & Technology

2016-11-01

exposure to dredged material plumes. Sarasota Bay, a 56-mile long coastal lagoon located in southwest Florida, stretches from Anna Maria Sound at... Protection classifies the waters of Sarasota Bay and Tampa Bay as Outstanding Florida Waters. Portions of Gulf Intracoastal Waterway (GIWW) that...constructed between 1960 and 1967 (Alperin 1983). The channel between these two rivers was routed east of the barrier islands or keys to protect the

Automatically classifying sentences in full-text biomedical articles into Introduction, Methods, Results and Discussion.

PubMed

Agarwal, Shashank; Yu, Hong

2009-12-01

Biomedical texts can be typically represented by four rhetorical categories: Introduction, Methods, Results and Discussion (IMRAD). Classifying sentences into these categories can benefit many other text-mining tasks. Although many studies have applied different approaches for automatically classifying sentences in MEDLINE abstracts into the IMRAD categories, few have explored the classification of sentences that appear in full-text biomedical articles. We first evaluated whether sentences in full-text biomedical articles could be reliably annotated into the IMRAD format and then explored different approaches for automatically classifying these sentences into the IMRAD categories. Our results show an overall annotation agreement of 82.14% with a Kappa score of 0.756. The best classification system is a multinomial naïve Bayes classifier trained on manually annotated data that achieved 91.95% accuracy and an average F-score of 91.55%, which is significantly higher than baseline systems. A web version of this system is available online at-http://wood.ims.uwm.edu/full_text_classifier/.

'Educated' dendritic cells act as messengers from memory to naive T helper cells.

PubMed

Alpan, Oral; Bachelder, Eric; Isil, Eda; Arnheiter, Heinz; Matzinger, Polly

2004-06-01

Ingested antigens lead to the generation of effector T cells that secrete interleukin 4 (IL-4) rather than interferon-gamma (IFN-gamma) and are capable of influencing naive T cells in their immediate environment to do the same. Using chimeric mice generated by aggregation of two genotypically different embryos, we found that the conversion of a naive T cell occurs only if it can interact with the same antigen-presenting cell, although not necessarily the same antigen, as the effector T cell. Using a two-step culture system in vitro, we found that antigen-presenting dendritic cells can act as 'temporal bridges' to relay information from orally immunized memory CD4 T cells to naive CD4 T cells. The orally immunized T cells use IL-4 and IL-10 (but not CD40 ligand) to 'educate' dendritic cells, which in turn induce naive T cells to produce the same cytokines as those produced by the orally immunized memory T cells.

Top predators affect the composition of naive protist communities, but only in their early-successional stage.

PubMed

Zander, Axel; Gravel, Dominique; Bersier, Louis-Félix; Gray, Sarah M

2016-02-01

Introduced top predators have the potential to disrupt community dynamics when prey species are naive to predation. The impact of introduced predators may also vary depending on the stage of community development. Early-succession communities are likely to have small-bodied and fast-growing species, but are not necessarily good at defending against predators. In contrast, late-succession communities are typically composed of larger-bodied species that are more predator resistant relative to small-bodied species. Yet, these aspects are greatly neglected in invasion studies. We therefore tested the effect of top predator presence on early- and late-succession communities that were either naive or non-naive to top predators. We used the aquatic community held within the leaves of Sarracenia purpurea. In North America, communities have experienced the S. purpurea top predator and are therefore non-naive. In Europe, this predator is not present and its niche has not been filled, making these communities top-predator naive. We collected early- and late-succession communities from two non-naive and two naive sites, which are climatically similar. We then conducted a common-garden experiment, with and without the presence of the top predator, in which we recorded changes in community composition, body size spectra, bacterial density, and respiration. We found that the top predator had no statistical effect on global measures of community structure and functioning. However, it significantly altered protist composition, but only in naive, early-succession communities, highlighting that the state of community development is important for understanding the impact of invasion.

Children and Adolescents' Understandings of Family Resemblance: A Study of Naive Inheritance Concepts

ERIC Educational Resources Information Center

Williams, Joanne M.

2012-01-01

This paper aims to provide developmental data on two connected naive inheritance concepts and to explore the coherence of children's naive biology knowledge. Two tasks examined children and adolescents' (4, 7, 10, and 14 years) conceptions of phenotypic resemblance across kin (in physical characteristics, disabilities, and personality traits). The…

Novel naïve Bayes classification models for predicting the chemical Ames mutagenicity.

PubMed

Zhang, Hui; Kang, Yan-Li; Zhu, Yuan-Yuan; Zhao, Kai-Xia; Liang, Jun-Yu; Ding, Lan; Zhang, Teng-Guo; Zhang, Ji

2017-06-01

Prediction of drug candidates for mutagenicity is a regulatory requirement since mutagenic compounds could pose a toxic risk to humans. The aim of this investigation was to develop a novel prediction model of mutagenicity by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test sets. For comparison, the recursive partitioning classifier prediction model was also established and other various reported prediction models of mutagenicity were collected. Among these methods, the prediction performance of naïve Bayes classifier established here displayed very well and stable, which yielded average overall prediction accuracies for the internal 5-fold cross validation of the training set and external test set I set were 89.1±0.4% and 77.3±1.5%, respectively. The concordance of the external test set II with 446 marketed drugs was 90.9±0.3%. In addition, four simple molecular descriptors (e.g., Apol, No. of H donors, Num-Rings and Wiener) related to mutagenicity and five representative substructures of mutagens (e.g., aromatic nitro, hydroxyl amine, nitroso, aromatic amine and N-methyl-N-methylenemethanaminum) produced by ECFP_14 fingerprints were identified. We hope the established naïve Bayes prediction model can be applied to risk assessment processes; and the obtained important information of mutagenic chemicals can guide the design of chemical libraries for hit and lead optimization. Copyright © 2017 Elsevier B.V. All rights reserved.

A Neuro-Fuzzy Approach in the Classification of Students' Academic Performance

PubMed Central

2013-01-01

Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam results and other related factors as input variables and labeled students based on their expected academic performance. The results showed that the proposed approach achieved a high accuracy. The results were also compared with those obtained from other well-known classification approaches, including support vector machine, Naive Bayes, neural network, and decision tree approaches. The comparative analysis indicated that the neuro-fuzzy approach performed better than the others. It is expected that this work may be used to support student admission procedures and to strengthen the services of educational institutions. PMID:24302928

A neuro-fuzzy approach in the classification of students' academic performance.

PubMed

Do, Quang Hung; Chen, Jeng-Fung

2013-01-01

Classifying the student academic performance with high accuracy facilitates admission decisions and enhances educational services at educational institutions. The purpose of this paper is to present a neuro-fuzzy approach for classifying students into different groups. The neuro-fuzzy classifier used previous exam results and other related factors as input variables and labeled students based on their expected academic performance. The results showed that the proposed approach achieved a high accuracy. The results were also compared with those obtained from other well-known classification approaches, including support vector machine, Naive Bayes, neural network, and decision tree approaches. The comparative analysis indicated that the neuro-fuzzy approach performed better than the others. It is expected that this work may be used to support student admission procedures and to strengthen the services of educational institutions.

IL-7-Induced Proliferation of Human Naive CD4 T-Cells Relies on Continued Thymic Activity.

PubMed

Silva, Susana L; Albuquerque, Adriana S; Matoso, Paula; Charmeteau-de-Muylder, Bénédicte; Cheynier, Rémi; Ligeiro, Dário; Abecasis, Miguel; Anjos, Rui; Barata, João T; Victorino, Rui M M; Sousa, Ana E

2017-01-01

Naive CD4 T-cell maintenance is critical for immune competence. We investigated here the fine-tuning of homeostatic mechanisms of the naive compartment to counteract the loss of de novo CD4 T-cell generation. Adults thymectomized in early childhood during corrective cardiac surgery were grouped based on presence or absence of thymopoiesis and compared with age-matched controls. We found that the preservation of the CD31 - subset was independent of the thymus and that its size is tightly controlled by peripheral mechanisms, including prolonged cell survival as attested by Bcl-2 levels. Conversely, a significant contraction of the CD31 + naive subset was observed in the absence of thymic activity. This was associated with impaired responses of purified naive CD4 T-cells to IL-7, namely, in vitro proliferation and upregulation of CD31 expression, which likely potentiated the decline in recent thymic emigrants. Additionally, we found no apparent constraint in the differentiation of naive cells into the memory compartment in individuals completely lacking thymic activity despite upregulation of DUSP6 , a phosphatase associated with increased TCR threshold. Of note, thymectomized individuals featuring some degree of thymopoiesis were able to preserve the size and diversity of the naive CD4 compartment, further arguing against complete thymectomy in infancy. Overall, our data suggest that robust peripheral mechanisms ensure the homeostasis of CD31 - naive CD4 pool and point to the requirement of continuous thymic activity to the maintenance of IL-7-driven homeostatic proliferation of CD31 + naive CD4 T-cells, which is essential to secure T-cell diversity throughout life.

Early Remission Is a Realistic Target in a Majority of Patients with DMARD-naive Rheumatoid Arthritis.

PubMed

Rannio, Tuomas; Asikainen, Juha; Kokko, Arto; Hannonen, Pekka; Sokka, Tuulikki

2016-04-01

We analyzed remission rates at 3 and 12 months in patients with rheumatoid arthritis (RA) who were naive for disease-modifying antirheumatic drugs (DMARD) and who were treated in a Finnish rheumatology clinic from 2008 to 2011. We compared remission rates and drug treatments between patients with RA and patients with undifferentiated arthritis (UA). Data from all DMARD-naive RA and UA patients from the healthcare district were collected using software that includes demographic and clinical characteristics, disease activity, medications, and patient-reported outcomes. Our rheumatology clinic applies the treat-to-target principle, electronic monitoring of patients, and multidisciplinary care. Out of 409 patients, 406 had data for classification by the 2010 RA criteria of the American College of Rheumatology/European League Against Rheumatism. A total of 68% were female, and mean age (SD) was 58 (16) years. Respectively, 56%, 60%, and 68% were positive for anticyclic citrullinated peptide antibodies (anti-CCP), rheumatoid factor (RF), and RF/anti-CCP, and 19% had erosive disease. The median (interquartile range) duration of symptoms was 6 (4-12) months. A total of 310 were classified as RA and 96 as UA. The patients with UA were younger, had better functional status and lower disease activity, and were more often seronegative than the patients with RA. The 28-joint Disease Activity Score (3 variables) remission rates of RA and UA patients at 3 months were 67% and 58% (p = 0.13), and at 12 months, 71% and 79%, respectively (p = 0.16). Sustained remission was observed in 57%/56% of RA/UA patients. Patients with RA used more conventional synthetic DMARD combinations than did patients with UA. None used biological DMARD at 3 months, and only 2.7%/1.1% of the patients (RA/UA) used them at 12 months (p = 0.36). Remarkably high remission rates are achievable in real-world DMARD-naive patients with RA or UA.

Risk of erectile dysfunction in transfusion-naive thalassemia men: a nationwide population-based retrospective cohort study.

PubMed

Chen, Yu-Guang; Lin, Te-Yu; Lin, Cheng-Li; Dai, Ming-Shen; Ho, Ching-Liang; Kao, Chia-Hung

2015-04-01

Based on the mechanism of pathophysiology, thalassemia major or transfusion-dependent thalassemia patients may have an increased risk of developing organic erectile dysfunction resulting from hypogonadism. However, there have been few studies investigating the association between erectile dysfunction and transfusion-naive thalassemia populations. We constructed a population-based cohort study to elucidate the association between transfusion-naive thalassemia populations and organic erectile dysfunction. This nationwide population-based cohort study involved analyzing data from 1998 to 2010 obtained from the Taiwanese National Health Insurance Research Database, with a follow-up period extending to the end of 2011. We identified men with transfusion-naive thalassemia and selected a comparison cohort that was frequency-matched with these according to age, and year of diagnosis thalassemia at a ratio of 1 thalassemia man to 4 control men. We analyzed the risks for transfusion-naive thalassemia men and organic erectile dysfunction by using Cox proportional hazards regression models. In this study, 588 transfusion-naive thalassemia men and 2337 controls were included. Total 12 patients were identified within the thalassaemia group and 10 within the control group. The overall risks for developing organic erectile dysfunction were 4.56-fold in patients with transfusion-naive thalassemia men compared with the comparison cohort after we adjusted for age and comorbidities. Our long-term cohort study results showed that in transfusion-naive thalassemia men, there was a higher risk for the development of organic erectile dysfunction, particularly in those patients with comorbidities.

Evaluation of the impact of chitosan/DNA nanoparticles on the differentiation of human naive CD4+ T cells

NASA Astrophysics Data System (ADS)

Liu, Lanxia; Bai, Yuanyuan; Zhu, Dunwan; Song, Liping; Wang, Hai; Dong, Xia; Zhang, Hailing; Leng, Xigang

2011-06-01

Chitosan (CS) is one of the most widely studied polymers in non-viral gene delivery since it is a cationic polysaccharide that forms nanoparticles with DNA and hence protects the DNA against digestion by DNase. However, the impact of CS/DNA nanoparticle on the immune system still remains poorly understood. Previous investigations did not found CS/DNA nanoparticles had any significant impact on the function of human and murine macrophages. To date, little is known about the interaction between CS/DNA nanoparticles and naive CD4+ T cells. This study was designed to investigate whether CS/DNA nanoparticles affect the initial differentiation direction of human naive CD4+ T cells. The indirect impact of CS/DNA nanoparticles on naive CD4+ T cell differentiation was investigated by incubating the nanoparticles with human macrophage THP-1 cells in one chamber of a transwell co-incubation system, with the enriched human naive CD4+ T cells being placed in the other chamber of the transwell. The nanoparticles were also co-incubated with the naive CD4+ T cells to explore their direct impact on naive CD4+ T cell differentiation by measuring the release of IL-4 and IFN-γ from the cells. It was demonstrated that CS/DNA nanoparticles induced slightly elevated production of IL-12 by THP-1 cells, possibly owing to the presence of CpG motifs in the plasmid. However, this macrophage stimulating activity was much less significant as compared with lipopolysaccharide and did not impact on the differentiation of the naive CD4+ T cells. It was also demonstrated that, when directly exposed to the naive CD4+ T cells, the nanoparticles induced neither the activation of the naive CD4+ T cells in the absence of recombinant cytokines (recombinant human IL-4 or IFN-γ) that induce naive CD4+ T cell polarization, nor any changes in the differentiation direction of naive CD4+ T cells in the presence of the corresponding cytokines.

Predicting healthcare associated infections using patients' experiences

NASA Astrophysics Data System (ADS)

Pratt, Michael A.; Chu, Henry

2016-05-01

Healthcare associated infections (HAI) are a major threat to patient safety and are costly to health systems. Our goal is to predict the HAI performance of a hospital using the patients' experience responses as input. We use four classifiers, viz. random forest, naive Bayes, artificial feedforward neural networks, and the support vector machine, to perform the prediction of six types of HAI. The six types include blood stream, urinary tract, surgical site, and intestinal infections. Experiments show that the random forest and support vector machine perform well across the six types of HAI.

75 FR 29891 - Special Local Regulation; Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-28

...-AA08 Special Local Regulation; Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay... Lighthouse Dock, Fire Island, NY due to the annual Maggie Fischer Memorial Great South Bay Cross Bay Swim..., Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, NY, in the Federal Register (74...

Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data.

PubMed

Garcia-Chimeno, Yolanda; Garcia-Zapirain, Begonya; Gomez-Beldarrain, Marian; Fernandez-Ruanova, Begonya; Garcia-Monco, Juan Carlos

2017-04-13

Feature selection methods are commonly used to identify subsets of relevant features to facilitate the construction of models for classification, yet little is known about how feature selection methods perform in diffusion tensor images (DTIs). In this study, feature selection and machine learning classification methods were tested for the purpose of automating diagnosis of migraines using both DTIs and questionnaire answers related to emotion and cognition - factors that influence of pain perceptions. We select 52 adult subjects for the study divided into three groups: control group (15), subjects with sporadic migraine (19) and subjects with chronic migraine and medication overuse (18). These subjects underwent magnetic resonance with diffusion tensor to see white matter pathway integrity of the regions of interest involved in pain and emotion. The tests also gather data about pathology. The DTI images and test results were then introduced into feature selection algorithms (Gradient Tree Boosting, L1-based, Random Forest and Univariate) to reduce features of the first dataset and classification algorithms (SVM (Support Vector Machine), Boosting (Adaboost) and Naive Bayes) to perform a classification of migraine group. Moreover we implement a committee method to improve the classification accuracy based on feature selection algorithms. When classifying the migraine group, the greatest improvements in accuracy were made using the proposed committee-based feature selection method. Using this approach, the accuracy of classification into three types improved from 67 to 93% when using the Naive Bayes classifier, from 90 to 95% with the support vector machine classifier, 93 to 94% in boosting. The features that were determined to be most useful for classification included are related with the pain, analgesics and left uncinate brain (connected with the pain and emotions). The proposed feature selection committee method improved the performance of migraine diagnosis

Can single classifiers be as useful as model ensembles to produce benthic seabed substratum maps?

NASA Astrophysics Data System (ADS)

Turner, Joseph A.; Babcock, Russell C.; Hovey, Renae; Kendrick, Gary A.

2018-05-01

Numerous machine-learning classifiers are available for benthic habitat map production, which can lead to different results. This study highlights the performance of the Random Forest (RF) classifier, which was significantly better than Classification Trees (CT), Naïve Bayes (NB), and a multi-model ensemble in terms of overall accuracy, Balanced Error Rate (BER), Kappa, and area under the curve (AUC) values. RF accuracy was often higher than 90% for each substratum class, even at the most detailed level of the substratum classification and AUC values also indicated excellent performance (0.8-1). Total agreement between classifiers was high at the broadest level of classification (75-80%) when differentiating between hard and soft substratum. However, this sharply declined as the number of substratum categories increased (19-45%) including a mix of rock, gravel, pebbles, and sand. The model ensemble, produced from the results of all three classifiers by majority voting, did not show any increase in predictive performance when compared to the single RF classifier. This study shows how a single classifier may be sufficient to produce benthic seabed maps and model ensembles of multiple classifiers.

Speaker gender identification based on majority vote classifiers

NASA Astrophysics Data System (ADS)

Mezghani, Eya; Charfeddine, Maha; Nicolas, Henri; Ben Amar, Chokri

2017-03-01

Speaker gender identification is considered among the most important tools in several multimedia applications namely in automatic speech recognition, interactive voice response systems and audio browsing systems. Gender identification systems performance is closely linked to the selected feature set and the employed classification model. Typical techniques are based on selecting the best performing classification method or searching optimum tuning of one classifier parameters through experimentation. In this paper, we consider a relevant and rich set of features involving pitch, MFCCs as well as other temporal and frequency-domain descriptors. Five classification models including decision tree, discriminant analysis, nave Bayes, support vector machine and k-nearest neighbor was experimented. The three best perming classifiers among the five ones will contribute by majority voting between their scores. Experimentations were performed on three different datasets spoken in three languages: English, German and Arabic in order to validate language independency of the proposed scheme. Results confirm that the presented system has reached a satisfying accuracy rate and promising classification performance thanks to the discriminating abilities and diversity of the used features combined with mid-level statistics.

33 CFR 100.124 - Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, New York.

Code of Federal Regulations, 2011 CFR

2011-07-01

... South Bay Cross Bay Swim, Great South Bay, New York. 100.124 Section 100.124 Navigation and Navigable... NAVIGABLE WATERS § 100.124 Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, New York. (a) Regulated area. All navigable waters of Great South Bay, NY within a 100 yard radius of each...

The Hayflick Limit May Determine the Effective Clonal Diversity of Naive T Cells.

PubMed

Ndifon, Wilfred; Dushoff, Jonathan

2016-06-15

Having a large number of sufficiently abundant T cell clones is important for adequate protection against diseases. However, as shown in this paper and elsewhere, between young adulthood and >70 y of age the effective clonal diversity of naive CD4/CD8 T cells found in human blood declines by a factor of >10. (Effective clonal diversity accounts for both the number and the abundance of T cell clones.) The causes of this observation are incompletely understood. A previous study proposed that it might result from the emergence of certain rare, replication-enhancing mutations in T cells. In this paper, we propose an even simpler explanation: that it results from the loss of T cells that have attained replicative senescence (i.e., the Hayflick limit). Stochastic numerical simulations of naive T cell population dynamics, based on experimental parameters, show that the rate of homeostatic T cell proliferation increases after the age of ∼60 y because naive T cells collectively approach replicative senescence. This leads to a sharp decline of effective clonal diversity after ∼70 y, in agreement with empirical data. A mathematical analysis predicts that, without an increase in the naive T cell proliferation rate, this decline will occur >50 yr later than empirically observed. These results are consistent with a model in which exhaustion of the proliferative capacity of naive T cells causes a sharp decline of their effective clonal diversity and imply that therapeutic potentiation of thymopoiesis might either prevent or reverse this outcome. Copyright © 2016 by The American Association of Immunologists, Inc.

Novel naïve Bayes classification models for predicting the carcinogenicity of chemicals.

PubMed

Zhang, Hui; Cao, Zhi-Xing; Li, Meng; Li, Yu-Zhi; Peng, Cheng

2016-11-01

The carcinogenicity prediction has become a significant issue for the pharmaceutical industry. The purpose of this investigation was to develop a novel prediction model of carcinogenicity of chemicals by using a naïve Bayes classifier. The established model was validated by the internal 5-fold cross validation and external test set. The naïve Bayes classifier gave an average overall prediction accuracy of 90 ± 0.8% for the training set and 68 ± 1.9% for the external test set. Moreover, five simple molecular descriptors (e.g., AlogP, Molecular weight (M W ), No. of H donors, Apol and Wiener) considered as important for the carcinogenicity of chemicals were identified, and some substructures related to the carcinogenicity were achieved. Thus, we hope the established naïve Bayes prediction model could be applied to filter early-stage molecules for this potential carcinogenicity adverse effect; and the identified five simple molecular descriptors and substructures of carcinogens would give a better understanding of the carcinogenicity of chemicals, and further provide guidance for medicinal chemists in the design of new candidate drugs and lead optimization, ultimately reducing the attrition rate in later stages of drug development. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of Pollution Level in Zolotoy Rog Bay (Peter the Great Gulf, the Sea of Japan)

NASA Astrophysics Data System (ADS)

Kazachkova, Y.; Lazareva, L.; Petukhov, V.

2017-11-01

The results of the hydrochemical research of water and bottom sediments of the Zolotoy Rog Bay in July 2015 are presented below. It is shown that, as a result of a large amount of polluted sewage entering The Zolotoy Rog Bay, the concentrations of organic substances (BOD5) and petroleum hydrocarbons in the water exceed the MPC. The concentrations of heavy metals in soils exceed both the background level and the level of permissible values. As a result of the calculation of the bottom accumulation (CBA) coefficient for oil hydrocarbons, the situation in the Zolotoy Rog Bay can be classified as an ecological disaster. According to the total pollution index (Zc) of heavy metals, the bottom sediments of the Zolotoy Rog Bay are characterized as strongly and very strongly polluted.

Naive B cells generate regulatory T cells in the presence of a mature immunologic synapse.

PubMed

Reichardt, Peter; Dornbach, Bastian; Rong, Song; Beissert, Stefan; Gueler, Faikah; Loser, Karin; Gunzer, Matthias

2007-09-01

Naive B cells are ineffective antigen-presenting cells and are considered unable to activate naive T cells. However, antigen-specific contact of these cells leads to stable cell pairs that remain associated over hours in vivo. The physiologic role of such pairs has not been evaluated. We show here that antigen-specific conjugates between naive B cells and naive T cells display a mature immunologic synapse in the contact zone that is absent in T-cell-dendritic-cell (DC) pairs. B cells induce substantial proliferation but, contrary to DCs, no loss of L-selectin in T cells. Surprisingly, while DC-triggered T cells develop into normal effector cells, B-cell stimulation over 72 hours induces regulatory T cells inhibiting priming of fresh T cells in a contact-dependent manner in vitro. In vivo, the regulatory T cells home to lymph nodes where they potently suppress immune responses such as in cutaneous hypersensitivity and ectopic allogeneic heart transplant rejection. Our finding might help to explain old observations on tolerance induction by B cells, identify the mature immunologic synapse as a central functional module of this process, and suggest the use of naive B-cell-primed regulatory T cells, "bTregs," as a useful approach for therapeutic intervention in adverse adaptive immune responses.

Opinion mining feature-level using Naive Bayes and feature extraction based analysis dependencies

NASA Astrophysics Data System (ADS)

Sanda, Regi; Baizal, Z. K. Abdurahman; Nhita, Fhira

2015-12-01

Development of internet and technology, has major impact and providing new business called e-commerce. Many e-commerce sites that provide convenience in transaction, and consumers can also provide reviews or opinions on products that purchased. These opinions can be used by consumers and producers. Consumers to know the advantages and disadvantages of particular feature of the product. Procuders can analyse own strengths and weaknesses as well as it's competitors products. Many opinions need a method that the reader can know the point of whole opinion. The idea emerged from review summarization that summarizes the overall opinion based on sentiment and features contain. In this study, the domain that become the main focus is about the digital camera. This research consisted of four steps 1) giving the knowledge to the system to recognize the semantic orientation of an opinion 2) indentify the features of product 3) indentify whether the opinion gives a positive or negative 4) summarizing the result. In this research discussed the methods such as Naï;ve Bayes for sentiment classification, and feature extraction algorithm based on Dependencies Analysis, which is one of the tools in Natural Language Processing (NLP) and knowledge based dictionary which is useful for handling implicit features. The end result of research is a summary that contains a bunch of reviews from consumers on the features and sentiment. With proposed method, accuration for sentiment classification giving 81.2 % for positive test data, 80.2 % for negative test data, and accuration for feature extraction reach 90.3 %.

33 CFR 167.103 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach. 167.103 Section 167.103 Navigation and Navigable... the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach. (a) A separation...

33 CFR 167.102 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 2 2012-07-01 2012-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach. 167.102 Section 167.102 Navigation and....102 In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach. (a) A...

33 CFR 167.103 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 2 2012-07-01 2012-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach. 167.103 Section 167.103 Navigation and Navigable... the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach. (a) A separation...

33 CFR 167.103 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 2 2014-07-01 2014-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach. 167.103 Section 167.103 Navigation and Navigable... the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach. (a) A separation...

33 CFR 167.102 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 2 2013-07-01 2013-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach. 167.102 Section 167.102 Navigation and....102 In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach. (a) A...

33 CFR 167.102 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 2 2014-07-01 2014-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach. 167.102 Section 167.102 Navigation and....102 In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach. (a) A...

33 CFR 167.103 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 2 2013-07-01 2013-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach. 167.103 Section 167.103 Navigation and Navigable... the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Buzzards Bay approach. (a) A separation...

33 CFR 167.102 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach. 167.102 Section 167.102 Navigation and....102 In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Narragansett Bay approach. (a) A...

33 CFR 100.124 - Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, New York.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, New York. 100.124 Section 100.124 Navigation and Navigable... NAVIGABLE WATERS § 100.124 Maggie Fischer Memorial Great South Bay Cross Bay Swim, Great South Bay, New York...

An automated approach to the design of decision tree classifiers

NASA Technical Reports Server (NTRS)

Argentiero, P.; Chin, P.; Beaudet, P.

1980-01-01

The classification of large dimensional data sets arising from the merging of remote sensing data with more traditional forms of ancillary data is considered. Decision tree classification, a popular approach to the problem, is characterized by the property that samples are subjected to a sequence of decision rules before they are assigned to a unique class. An automated technique for effective decision tree design which relies only on apriori statistics is presented. This procedure utilizes a set of two dimensional canonical transforms and Bayes table look-up decision rules. An optimal design at each node is derived based on the associated decision table. A procedure for computing the global probability of correct classfication is also provided. An example is given in which class statistics obtained from an actual LANDSAT scene are used as input to the program. The resulting decision tree design has an associated probability of correct classification of .76 compared to the theoretically optimum .79 probability of correct classification associated with a full dimensional Bayes classifier. Recommendations for future research are included.

Naive T-cell receptor transgenic T cells help memory B cells produce antibody

PubMed Central

Duffy, Darragh; Yang, Chun-Ping; Heath, Andrew; Garside, Paul; Bell, Eric B

2006-01-01

Injection of the same antigen following primary immunization induces a classic secondary response characterized by a large quantity of high-affinity antibody of an immunoglobulin G class produced more rapidly than in the initial response – the products of memory B cells are qualitatively distinct from that of the original naive B lymphocytes. Very little is known of the help provided by the CD4 T cells that stimulate memory B cells. Using antigen-specific T-cell receptor transgenic CD4 T cells (DO11.10) as a source of help, we found that naive transgenic T cells stimulated memory B cells almost as well (in terms of quantity and speed) as transgenic T cells that had been recently primed. There was a direct correlation between serum antibody levels and the number of naive transgenic T cells transferred. Using T cells from transgenic interleukin-2-deficient mice we showed that interleukin-2 was not required for a secondary response, although it was necessary for a primary response. The results suggested that the signals delivered by CD4 T cells and required by memory B cells for their activation were common to both antigen-primed and naive CD4 T cells. PMID:17067314

IL-21 sustains CD28 expression on IL-15-activated human naive CD8+ T cells.

PubMed

Alves, Nuno L; Arosa, Fernando A; van Lier, René A W

2005-07-15

Human naive CD8+ T cells are able to respond in an Ag-independent manner to IL-7 and IL-15. Whereas IL-7 largely maintains CD8+ T cells in a naive phenotype, IL-15 drives these cells to an effector phenotype characterized, among other features, by down-regulation of the costimulatory molecule CD28. We evaluated the influence of the CD4+ Th cell-derived common gamma-chain cytokine IL-21 on cytokine-induced naive CD8+ T cell activation. Stimulation with IL-21 did not induce division and only slightly increased IL-15-induced proliferation of naive CD8+ T cells. Strikingly, however, IL-15-induced down-modulation of CD28 was completely prevented by IL-21 at the protein and transcriptional level. Subsequent stimulation via combined TCR/CD3 and CD28 triggering led to a markedly higher production of IL-2 and IFN-gamma in IL-15/IL-21-stimulated cells compared with IL-15-stimulated T cells. Our data show that IL-21 modulates the phenotype of naive CD8+ T cells that have undergone IL-15 induced homeostatic proliferation and preserves their responsiveness to CD28 ligands.

Left Ventricular Strain in Chemotherapy-Naive and Radiotherapy-Naive Patients With Cancer.

PubMed

Tadic, Marijana; Genger, Martin; Baudisch, Ana; Kelle, Sebastian; Cuspidi, Cesare; Belyavskiy, Evgeny; Burkhardt, Franziska; Venneri, Lucia; Attanasio, Philipp; Pieske, Burkert

2018-03-01

We sought to investigate left ventricular (LV) function and mechanics in patients with cancer before they received chemotherapy or radiotherapy, as well as the relationship between cancer and reduced LV multidirectional strain in the whole study population. The retrospective study involved 122 chemotherapy- and radiotherapy-naive patients with cancer and 45 age- and sex-matched controls with a cardiovascular risk profile similar to that of the patients with cancer. All the patients underwent echocardiographic examination before introduction of chemotherapy or radiotherapy. LV longitudinal (-19.1% ± 2.1% vs -17.8% ± 3.5%; P = 0.022), circumferential (-22.9% ± 3.5% vs -20.1% ± 4.1%; P < 0.001), and radial (40.5% ± 8.8% vs 35.2% ± 10.7%; P = 0.004) strain was significantly lower in the patients with cancer than in the control group. Endocardial and midmyocardial longitudinal LV strain was significantly reduced in the patients with cancer compared with the controls, whereas epicardial longitudinal strain was similar between these groups. Endocardial, midmyocardial, and epicardial circumferential strain was significantly lower in the chemotherapy- or radiotherapy-naive patients with cancer than in the controls. Cancer was associated with reduced longitudinal (odds ratio [OR], 9.0; 95% confidence interval [CI], 2.20-23.50; P < 0.001), reduced circumferential (OR, 7.1; 95% CI, 3.80-20.40; P < 0.001), and reduced radial strain (OR, 7.2; 95% CI, 3.41-25.10; P < 0.001) independent of age, sex, body mass index, diabetes, and hypertension. LV mechanics was impaired in the patients with cancer compared with the controls even before initiation of chemotherapy and radiotherapy. Cancer and hypertension were associated with reduced LV multidirectional strain independent of other clinical parameters. The present results indicate that cancer itself potentially induces cardiac remodelling independent of chemotherapy and radiotherapy. Copyright © 2017 Canadian

A comparison of supervised classification methods for the prediction of substrate type using multibeam acoustic and legacy grain-size data.

PubMed

Stephens, David; Diesing, Markus

2014-01-01

Detailed seabed substrate maps are increasingly in demand for effective planning and management of marine ecosystems and resources. It has become common to use remotely sensed multibeam echosounder data in the form of bathymetry and acoustic backscatter in conjunction with ground-truth sampling data to inform the mapping of seabed substrates. Whilst, until recently, such data sets have typically been classified by expert interpretation, it is now obvious that more objective, faster and repeatable methods of seabed classification are required. This study compares the performances of a range of supervised classification techniques for predicting substrate type from multibeam echosounder data. The study area is located in the North Sea, off the north-east coast of England. A total of 258 ground-truth samples were classified into four substrate classes. Multibeam bathymetry and backscatter data, and a range of secondary features derived from these datasets were used in this study. Six supervised classification techniques were tested: Classification Trees, Support Vector Machines, k-Nearest Neighbour, Neural Networks, Random Forest and Naive Bayes. Each classifier was trained multiple times using different input features, including i) the two primary features of bathymetry and backscatter, ii) a subset of the features chosen by a feature selection process and iii) all of the input features. The predictive performances of the models were validated using a separate test set of ground-truth samples. The statistical significance of model performances relative to a simple baseline model (Nearest Neighbour predictions on bathymetry and backscatter) were tested to assess the benefits of using more sophisticated approaches. The best performing models were tree based methods and Naive Bayes which achieved accuracies of around 0.8 and kappa coefficients of up to 0.5 on the test set. The models that used all input features didn't generally perform well, highlighting the need for

33 CFR 110.78 - Sturgeon Bay, Sturgeon Bay, Wis.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Sturgeon Bay, Sturgeon Bay, Wis. 110.78 Section 110.78 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY ANCHORAGES ANCHORAGE REGULATIONS Special Anchorage Areas § 110.78 Sturgeon Bay, Sturgeon Bay, Wis. (a) Area 1...

33 CFR 110.78 - Sturgeon Bay, Sturgeon Bay, Wis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Sturgeon Bay, Sturgeon Bay, Wis. 110.78 Section 110.78 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY ANCHORAGES ANCHORAGE REGULATIONS Special Anchorage Areas § 110.78 Sturgeon Bay, Sturgeon Bay, Wis. (a) Area 1...

33 CFR 110.78 - Sturgeon Bay, Sturgeon Bay, Wis.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Sturgeon Bay, Sturgeon Bay, Wis. 110.78 Section 110.78 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY ANCHORAGES ANCHORAGE REGULATIONS Special Anchorage Areas § 110.78 Sturgeon Bay, Sturgeon Bay, Wis. (a) Area 1...

33 CFR 110.78 - Sturgeon Bay, Sturgeon Bay, Wis.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Sturgeon Bay, Sturgeon Bay, Wis. 110.78 Section 110.78 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY ANCHORAGES ANCHORAGE REGULATIONS Special Anchorage Areas § 110.78 Sturgeon Bay, Sturgeon Bay, Wis. (a) Area 1...

Children's Conceptions of Mental Illness: A Naive Theory Approach

ERIC Educational Resources Information Center

Fox, Claudine; Buchanan-Barrow, Eithne; Barrett, Martyn

2010-01-01

This paper reports two studies that investigated children's conceptions of mental illness using a naive theory approach, drawing upon a conceptual framework for analysing illness representations which distinguishes between the identity, causes, consequences, curability, and timeline of an illness. The studies utilized semi-structured interviewing…

Mathematical Model of Naive T Cell Division and Survival IL-7 Thresholds.

PubMed

Reynolds, Joseph; Coles, Mark; Lythe, Grant; Molina-París, Carmen

2013-01-01

We develop a mathematical model of the peripheral naive T cell population to study the change in human naive T cell numbers from birth to adulthood, incorporating thymic output and the availability of interleukin-7 (IL-7). The model is formulated as three ordinary differential equations: two describe T cell numbers, in a resting state and progressing through the cell cycle. The third is introduced to describe changes in IL-7 availability. Thymic output is a decreasing function of time, representative of the thymic atrophy observed in aging humans. Each T cell is assumed to possess two interleukin-7 receptor (IL-7R) signaling thresholds: a survival threshold and a second, higher, proliferation threshold. If the IL-7R signaling strength is below its survival threshold, a cell may undergo apoptosis. When the signaling strength is above the survival threshold, but below the proliferation threshold, the cell survives but does not divide. Signaling strength above the proliferation threshold enables entry into cell cycle. Assuming that individual cell thresholds are log-normally distributed, we derive population-average rates for apoptosis and entry into cell cycle. We have analyzed the adiabatic change in homeostasis as thymic output decreases. With a parameter set representative of a healthy individual, the model predicts a unique equilibrium number of T cells. In a parameter range representative of persistent viral or bacterial infection, where naive T cell cycle progression is impaired, a decrease in thymic output may result in the collapse of the naive T cell repertoire.

Highly efficient gene transfer in naive human T cells with a murine leukemia virus-based vector.

PubMed

Dardalhon, V; Jaleco, S; Rebouissou, C; Ferrand, C; Skander, N; Swainson, L; Tiberghien, P; Spits, H; Noraz, N; Taylor, N

2000-08-01

Retroviral vectors based on the Moloney murine leukemia virus (MuLV) have become the primary tool for gene delivery into hematopoietic cells, but clinical trials have been hampered by low transduction efficiencies. Recently, we and others have shown that gene transfer of MuLV-based vectors into T cells can be significantly augmented using a fibronectin-facilitated protocol. Nevertheless, the relative abilities of naive (CD45RA(+)) and memory (CD45RO(+)) lymphocyte subsets to be transduced has not been assessed. Although naive T cells demonstrate a restricted cytokine profile following antigen stimulation and a decreased susceptibility to infection with human immunodeficiency virus, it was not clear whether they could be efficiently infected with a MuLV vector. This study describes conditions that permitted gene transfer of an enhanced green fluorescent protein-expressing retroviral vector in more than 50% of naive umbilical cord (UC) blood and peripheral blood (PB) T cells following CD3/CD28 ligation. Moreover, treatment of naive T cells with interleukin-7 resulted in the maintenance of a CD45RA phenotype and gene transfer levels approached 20%. Finally, it was determined that parameters for optimal transduction of CD45RA(+) T cells isolated from PB and UC blood differed: transduction of the UC cells was significantly increased by the presence of autologous mononuclear cells (24.5% versus 56.5%). Because naive T cells harbor a receptor repertoire that allows them to respond to novel antigens, the development of protocols targeting their transduction is crucial for gene therapy applications. This approach will also allow the functions of exogenous genes to be evaluated in primary nontransformed naive T cells.

Naive vs. Sophisticated Methods of Forecasting Public Library Circulations.

ERIC Educational Resources Information Center

Brooks, Terrence A.

1984-01-01

Two sophisticated--autoregressive integrated moving average (ARIMA), straight-line regression--and two naive--simple average, monthly average--forecasting techniques were used to forecast monthly circulation totals of 34 public libraries. Comparisons of forecasts and actual totals revealed that ARIMA and monthly average methods had smallest mean…

Details: Elevation of Plate Typical Bay, SectionThrough Plate Typical Bay, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Details: Elevation of Plate Typical Bay, Section-Through Plate Typical Bay, Section-Through Plate Center Bay, Elevation of Plate Center Bay - Contoocook Covered Bridge, Spanning Contoocook River, Hopkinton, Merrimack County, NH

Imported case of acute respiratory tract infection associated with a member of species nelson bay orthoreovirus.

PubMed

Yamanaka, Atsushi; Iwakiri, Akira; Yoshikawa, Tomoki; Sakai, Kouji; Singh, Harpal; Himeji, Daisuke; Kikuchi, Ikuo; Ueda, Akira; Yamamoto, Seigo; Miura, Miho; Shioyama, Yoko; Kawano, Kimiko; Nagaishi, Tokiko; Saito, Minako; Minomo, Masumi; Iwamoto, Naoyasu; Hidaka, Yoshio; Sohma, Hirotoshi; Kobayashi, Takeshi; Kanai, Yuta; Kawagishi, Takehiro; Nagata, Noriyo; Fukushi, Shuetsu; Mizutani, Tetsuya; Tani, Hideki; Taniguchi, Satoshi; Fukuma, Aiko; Shimojima, Masayuki; Kurane, Ichiro; Kageyama, Tsutomu; Odagiri, Takato; Saijo, Masayuki; Morikawa, Shigeru

2014-01-01

A Japanese man suffered from acute respiratory tract infection after returning to Japan from Bali, Indonesia in 2007. Miyazaki-Bali/2007, a strain of the species of Nelson Bay orthoreovirus, was isolated from the patient's throat swab using Vero cells, in which syncytium formation was observed. This is the sixth report describing a patient with respiratory tract infection caused by an orthoreovirus classified to the species of Nelson Bay orthoreovirus. Given the possibility that all of the patients were infected in Malaysia and Indonesia, prospective surveillance on orthoreovirus infections should be carried out in Southeast Asia. Furthermore, contact surveillance study suggests that the risk of human-to-human infection of the species of Nelson Bay orthoreovirus would seem to be low.

Privacy-Preserving Evaluation of Generalization Error and Its Application to Model and Attribute Selection

NASA Astrophysics Data System (ADS)

Sakuma, Jun; Wright, Rebecca N.

Privacy-preserving classification is the task of learning or training a classifier on the union of privately distributed datasets without sharing the datasets. The emphasis of existing studies in privacy-preserving classification has primarily been put on the design of privacy-preserving versions of particular data mining algorithms, However, in classification problems, preprocessing and postprocessing— such as model selection or attribute selection—play a prominent role in achieving higher classification accuracy. In this paper, we show generalization error of classifiers in privacy-preserving classification can be securely evaluated without sharing prediction results. Our main technical contribution is a new generalized Hamming distance protocol that is universally applicable to preprocessing and postprocessing of various privacy-preserving classification problems, such as model selection in support vector machine and attribute selection in naive Bayes classification.

Delineation of landform and lithologic units for Ecological Landtype-Association analysis in Glacier Bay National Park, Southeast Alaska

USGS Publications Warehouse

Brew, David A.

2008-01-01

In this study, landforms were classified-by using topographic maps and personal experience-into eight categories similar to those used by the U.S. Forest Service. The 90 bedrock-lithologic units on the current Glacier Bay geologic map were classified into 13 generalized lithologic units corresponding exactly to those used by the U.S. Forest Service. Incomplete storm-track, storm-intensity, and limited climatic information have also been compiled.

33 CFR 80.1114 - San Pedro Bay-Anaheim Bay, CA.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false San Pedro Bay-Anaheim Bay, CA. 80... INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Pacific Coast § 80.1114 San Pedro Bay—Anaheim Bay, CA. (a) A line drawn across the seaward extremities of the Anaheim Bay Entrance Jetties; thence to Long...

33 CFR 80.1114 - San Pedro Bay-Anaheim Bay, CA.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false San Pedro Bay-Anaheim Bay, CA. 80... INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Pacific Coast § 80.1114 San Pedro Bay—Anaheim Bay, CA. (a) A line drawn across the seaward extremities of the Anaheim Bay Entrance Jetties; thence to Long...

33 CFR 80.1114 - San Pedro Bay-Anaheim Bay, CA.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false San Pedro Bay-Anaheim Bay, CA. 80... INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Pacific Coast § 80.1114 San Pedro Bay—Anaheim Bay, CA. (a) A line drawn across the seaward extremities of the Anaheim Bay Entrance Jetties; thence to Long...

33 CFR 80.1114 - San Pedro Bay-Anaheim Bay, CA.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false San Pedro Bay-Anaheim Bay, CA. 80... INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Pacific Coast § 80.1114 San Pedro Bay—Anaheim Bay, CA. (a) A line drawn across the seaward extremities of the Anaheim Bay Entrance Jetties; thence to Long...

33 CFR 80.1114 - San Pedro Bay-Anaheim Bay, CA.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false San Pedro Bay-Anaheim Bay, CA. 80... INTERNATIONAL NAVIGATION RULES COLREGS DEMARCATION LINES Pacific Coast § 80.1114 San Pedro Bay—Anaheim Bay, CA. (a) A line drawn across the seaward extremities of the Anaheim Bay Entrance Jetties; thence to Long...

33 CFR 100.911 - Bay City Airshow, Bay City, MI.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Bay City Airshow, Bay City, MI. 100.911 Section 100.911 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY REGATTAS AND MARINE PARADES SAFETY OF LIFE ON NAVIGABLE WATERS § 100.911 Bay City Airshow, Bay City, MI. (a...

33 CFR 100.911 - Bay City Airshow, Bay City, MI.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Bay City Airshow, Bay City, MI. 100.911 Section 100.911 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY REGATTAS AND MARINE PARADES SAFETY OF LIFE ON NAVIGABLE WATERS § 100.911 Bay City Airshow, Bay City, MI. (a...

33 CFR 100.911 - Bay City Airshow, Bay City, MI.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Bay City Airshow, Bay City, MI. 100.911 Section 100.911 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY REGATTAS AND MARINE PARADES SAFETY OF LIFE ON NAVIGABLE WATERS § 100.911 Bay City Airshow, Bay City, MI. (a...

33 CFR 100.911 - Bay City Airshow, Bay City, MI.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Bay City Airshow, Bay City, MI. 100.911 Section 100.911 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY REGATTAS AND MARINE PARADES SAFETY OF LIFE ON NAVIGABLE WATERS § 100.911 Bay City Airshow, Bay City, MI. (a...

33 CFR 100.911 - Bay City Airshow, Bay City, MI.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Bay City Airshow, Bay City, MI. 100.911 Section 100.911 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY REGATTAS AND MARINE PARADES SAFETY OF LIFE ON NAVIGABLE WATERS § 100.911 Bay City Airshow, Bay City, MI. (a...

Bayes classification of interferometric TOPSAR data

NASA Technical Reports Server (NTRS)

Michel, T. R.; Rodriguez, E.; Houshmand, B.; Carande, R.

1995-01-01

We report the Bayes classification of terrain types at different sites using airborne interferometric synthetic aperture radar (INSAR) data. A Gaussian maximum likelihood classifier was applied on multidimensional observations derived from the SAR intensity, the terrain elevation model, and the magnitude of the interferometric correlation. Training sets for forested, urban, agricultural, or bare areas were obtained either by selecting samples with known ground truth, or by k-means clustering of random sets of samples uniformly distributed across all sites, and subsequent assignments of these clusters using ground truth. The accuracy of the classifier was used to optimize the discriminating efficiency of the set of features that was chosen. The most important features include the SAR intensity, a canopy penetration depth model, and the terrain slope. We demonstrate the classifier's performance across sites using a unique set of training classes for the four main terrain categories. The scenes examined include San Francisco (CA) (predominantly urban and water), Mount Adams (WA) (forested with clear cuts), Pasadena (CA) (urban with mountains), and Antioch Hills (CA) (water, swamps, fields). Issues related to the effects of image calibration and the robustness of the classification to calibration errors are explored. The relative performance of single polarization Interferometric data classification is contrasted against classification schemes based on polarimetric SAR data.

A hybrid approach to select features and classify diseases based on medical data

NASA Astrophysics Data System (ADS)

AbdelLatif, Hisham; Luo, Jiawei

2018-03-01

Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

Using a food-web model to assess the trophic structure and energy flows in Daya Bay, China

NASA Astrophysics Data System (ADS)

Chen, Zuozhi; Xu, Shannan; Qiu, Yongsong

2015-12-01

Daya Bay, is one of the largest and most important semi-closed bays along the southern coast of China. Due to the favorable geomorphological and climatic conditions, this bay has become an important conservation zone of aquatic germplasm resources in South China Sea. To characterize the trophic structure, ecosystem properties and keystone species, a food-web model for Daya Bay has been developed by the means of a mass-balance approach using the Ecopath with Ecosim software. The mean trophic transfer efficiency for the entire ecosystem as a whole is 10.9% while the trophic level II is 5.1%. The primary- and secondary-producers, including phytoplankton, zooplankton and micro-zoobenthos demonstrated the important overall impacts on the rest of the groups based on mixed trophic impact (MIT) analysis and are classified as the keystone groups. The analysis of ecosystem attributes indicated that ecosystem of Daya Bay can be categorized as an immature one and/or is in the degraded stage. A comparison of this model with other coastal ecosystems, including Kuosheng Bay, Tongoy Bay, Beibu Gulf and Cadiz Gulf, underpinned that the ecosystem of Daye Bay is an obviously stressed system and is more vulnerable to the external disturbance. In general, our study indicates that a holistic approach is needed to minimize the impacts of anthropogenic activities to ensure the sustainability of the ecosystem in the future.

Telomerase Is Involved in IL-7-Mediated Differential Survival of Naive and Memory CD4+ T Cells1

PubMed Central

Yang, Yinhua; An, Jie; Weng, Nan-ping

2008-01-01

IL-7 plays an essential role in T cell maintenance and survival. The survival effect of IL-7 is thought to be mediated through regulation of Bcl2 family proteins. After a comparative analysis of IL-7-induced growth and cell death of human naive and memory CD4+ T cells, we observed that more memory CD4+ T cells underwent cell division and proceeded to apoptosis than naive cells in response to IL-7. However, IL-7-induced expressions of Bcl2 family members (Bcl2, Bcl-xL, Bax, and Bad) were similar between naive and memory cells. Instead, we found that IL-7 induced higher levels of telomerase activity in naive cells than in memory cells, and the levels of IL-7-induced telomerase activity had a significant inverse correlation with cell death in CD4+ T cells. Furthermore, we showed that reducing expression of telomerase reverse transcriptase and telomerase activity significantly increased cell death of IL-7-cultured CD4+ T cells. Together, these findings demonstrate that telomerase is involved in IL-7-mediated differential survival of naive and memory CD4+ T cells. PMID:18322183

BayeSED: A GENERAL APPROACH TO FITTING THE SPECTRAL ENERGY DISTRIBUTION OF GALAXIES

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

Han, Yunkun; Han, Zhanwen, E-mail: hanyk@ynao.ac.cn, E-mail: zhanwenhan@ynao.ac.cn

2014-11-01

We present a newly developed version of BayeSED, a general Bayesian approach to the spectral energy distribution (SED) fitting of galaxies. The new BayeSED code has been systematically tested on a mock sample of galaxies. The comparison between the estimated and input values of the parameters shows that BayeSED can recover the physical parameters of galaxies reasonably well. We then applied BayeSED to interpret the SEDs of a large K{sub s} -selected sample of galaxies in the COSMOS/UltraVISTA field with stellar population synthesis models. Using the new BayeSED code, a Bayesian model comparison of stellar population synthesis models has beenmore » performed for the first time. We found that the 2003 model by Bruzual and Charlot, statistically speaking, has greater Bayesian evidence than the 2005 model by Maraston for the K{sub s} -selected sample. In addition, while setting the stellar metallicity as a free parameter obviously increases the Bayesian evidence of both models, varying the initial mass function has a notable effect only on the Maraston model. Meanwhile, the physical parameters estimated with BayeSED are found to be generally consistent with those obtained using the popular grid-based FAST code, while the former parameters exhibit more natural distributions. Based on the estimated physical parameters of the galaxies in the sample, we qualitatively classified the galaxies in the sample into five populations that may represent galaxies at different evolution stages or in different environments. We conclude that BayeSED could be a reliable and powerful tool for investigating the formation and evolution of galaxies from the rich multi-wavelength observations currently available. A binary version of the BayeSED code parallelized with Message Passing Interface is publicly available at https://bitbucket.org/hanyk/bayesed.« less

BayeSED: A General Approach to Fitting the Spectral Energy Distribution of Galaxies

NASA Astrophysics Data System (ADS)

Han, Yunkun; Han, Zhanwen

2014-11-01

We present a newly developed version of BayeSED, a general Bayesian approach to the spectral energy distribution (SED) fitting of galaxies. The new BayeSED code has been systematically tested on a mock sample of galaxies. The comparison between the estimated and input values of the parameters shows that BayeSED can recover the physical parameters of galaxies reasonably well. We then applied BayeSED to interpret the SEDs of a large Ks -selected sample of galaxies in the COSMOS/UltraVISTA field with stellar population synthesis models. Using the new BayeSED code, a Bayesian model comparison of stellar population synthesis models has been performed for the first time. We found that the 2003 model by Bruzual & Charlot, statistically speaking, has greater Bayesian evidence than the 2005 model by Maraston for the Ks -selected sample. In addition, while setting the stellar metallicity as a free parameter obviously increases the Bayesian evidence of both models, varying the initial mass function has a notable effect only on the Maraston model. Meanwhile, the physical parameters estimated with BayeSED are found to be generally consistent with those obtained using the popular grid-based FAST code, while the former parameters exhibit more natural distributions. Based on the estimated physical parameters of the galaxies in the sample, we qualitatively classified the galaxies in the sample into five populations that may represent galaxies at different evolution stages or in different environments. We conclude that BayeSED could be a reliable and powerful tool for investigating the formation and evolution of galaxies from the rich multi-wavelength observations currently available. A binary version of the BayeSED code parallelized with Message Passing Interface is publicly available at https://bitbucket.org/hanyk/bayesed.

Mycofier: a new machine learning-based classifier for fungal ITS sequences.

PubMed

Delgado-Serrano, Luisa; Restrepo, Silvia; Bustos, Jose Ricardo; Zambrano, Maria Mercedes; Anzola, Juan Manuel

2016-08-11

The taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool for fungal ITS1 sequences for large environmental surveys. This study describes the development of a machine learning-based classifier for the taxonomical assignment of fungal ITS1 sequences at the genus level. A fungal ITS1 sequence database was built using curated data. Training and test sets were generated from it. A Naïve Bayesian classifier was built using features from the primary sequence with an accuracy of 87 % in the classification at the genus level. The final model was based on a Naïve Bayes algorithm using ITS1 sequences from 510 fungal genera. This classifier, denoted as Mycofier, provides similar classification accuracy compared to BLASTN, but the database used for the classification contains curated data and the tool, independent of alignment, is more efficient and contributes to the field, given the lack of an accurate classification tool for large data from fungal ITS1 sequences. The software and source code for Mycofier are freely available at https://github.com/ldelgado-serrano/mycofier.git .

Automatic classification of small bowel mucosa alterations in celiac disease for confocal laser endomicroscopy

NASA Astrophysics Data System (ADS)

Boschetto, Davide; Di Claudio, Gianluca; Mirzaei, Hadis; Leong, Rupert; Grisan, Enrico

2016-03-01

Celiac disease (CD) is an immune-mediated enteropathy triggered by exposure to gluten and similar proteins, affecting genetically susceptible persons, increasing their risk of different complications. Small bowels mucosa damage due to CD involves various degrees of endoscopically relevant lesions, which are not easily recognized: their overall sensitivity and positive predictive values are poor even when zoom-endoscopy is used. Confocal Laser Endomicroscopy (CLE) allows skilled and trained experts to qualitative evaluate mucosa alteration such as a decrease in goblet cells density, presence of villous atrophy or crypt hypertrophy. We present a method for automatically classifying CLE images into three different classes: normal regions, villous atrophy and crypt hypertrophy. This classification is performed after a features selection process, in which four features are extracted from each image, through the application of homomorphic filtering and border identification through Canny and Sobel operators. Three different classifiers have been tested on a dataset of 67 different images labeled by experts in three classes (normal, VA and CH): linear approach, Naive-Bayes quadratic approach and a standard quadratic analysis, all validated with a ten-fold cross validation. Linear classification achieves 82.09% accuracy (class accuracies: 90.32% for normal villi, 82.35% for VA and 68.42% for CH, sensitivity: 0.68, specificity 1.00), Naive Bayes analysis returns 83.58% accuracy (90.32% for normal villi, 70.59% for VA and 84.21% for CH, sensitivity: 0.84 specificity: 0.92), while the quadratic analysis achieves a final accuracy of 94.03% (96.77% accuracy for normal villi, 94.12% for VA and 89.47% for CH, sensitivity: 0.89, specificity: 0.98).

33 CFR 165.1182 - Safety/Security Zone: San Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., Carquinez Strait, and Suisun Bay, CA. (a) Regulated area. The following area is established as a moving... Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA. 165.1182 Section 165.1182 Navigation and... vessels transit from a line drawn between San Francisco Main Ship Channel buoys 7 and 8 (LLNR 4190 & 4195...

33 CFR 165.1182 - Safety/Security Zone: San Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., Carquinez Strait, and Suisun Bay, CA. (a) Regulated area. The following area is established as a moving... Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA. 165.1182 Section 165.1182 Navigation and... vessels transit from a line drawn between San Francisco Main Ship Channel buoys 7 and 8 (LLNR 4190 & 4195...

33 CFR 165.1182 - Safety/Security Zone: San Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., Carquinez Strait, and Suisun Bay, CA. (a) Regulated area. The following area is established as a moving... Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA. 165.1182 Section 165.1182 Navigation and... vessels transit from a line drawn between San Francisco Main Ship Channel buoys 7 and 8 (LLNR 4190 & 4195...

33 CFR 165.1182 - Safety/Security Zone: San Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., Carquinez Strait, and Suisun Bay, CA. (a) Regulated area. The following area is established as a moving... Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA. 165.1182 Section 165.1182 Navigation and... vessels transit from a line drawn between San Francisco Main Ship Channel buoys 7 and 8 (LLNR 4190 & 4195...

33 CFR 165.1182 - Safety/Security Zone: San Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., Carquinez Strait, and Suisun Bay, CA. (a) Regulated area. The following area is established as a moving... Francisco Bay, San Pablo Bay, Carquinez Strait, and Suisun Bay, CA. 165.1182 Section 165.1182 Navigation and... vessels transit from a line drawn between San Francisco Main Ship Channel buoys 7 and 8 (LLNR 4190 & 4195...

Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption.

PubMed

Chandrasekaran, Jeyamala; Thiruvengadam, S J

2015-01-01

Owing to the growth of high performance network technologies, multimedia applications over the Internet are increasing exponentially. Applications like video conferencing, video-on-demand, and pay-per-view depend upon encryption algorithms for providing confidentiality. Video communication is characterized by distinct features such as large volume, high redundancy between adjacent frames, video codec compliance, syntax compliance, and application specific requirements. Naive approaches for video encryption encrypt the entire video stream with conventional text based cryptographic algorithms. Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. This research work aims at enhancing the speed of naive approaches through chaos based S-box design. Chaotic equations are popularly known for randomness, extreme sensitivity to initial conditions, and ergodicity. The proposed methodology employs two-dimensional discrete Henon map for (i) generation of dynamic and key-dependent S-box that could be integrated with symmetric algorithms like Blowfish and Data Encryption Standard (DES) and (ii) generation of one-time keys for simple substitution ciphers. The proposed design is tested for randomness, nonlinearity, avalanche effect, bit independence criterion, and key sensitivity. Experimental results confirm that chaos based S-box design and key generation significantly reduce the computational cost of video encryption with no compromise in security.

Naive (commonsense) geography and geobrowser usability after ten years of Google Earth

NASA Astrophysics Data System (ADS)

Hamerlinck, J. D.

2016-04-01

In 1995, the concept of ‘naive geography’ was formally introduced as an area of cognitive geographic information science representing ‘the body of knowledge that people have about the surrounding geographic world’ and reflecting ‘the way people think and reason about geographic space and time, both consciously and subconsciously’. The need to incorporate such commonsense knowledge and reasoning into design of geospatial technologies was identified but faced challenges in formalizing these relationships and processes in software implementation. Ten years later, the Google Earth geobrowser was released, marking the beginning of a new era of open access to, and application of, geographic data and information in society. Fast-forward to today, and the opportunity presents itself to take stock of twenty years of naive geography and a decade of the ubiquitous virtual globe. This paper introduces an ongoing research effort to explore the integration of naive (or commonsense) geography concepts in the Google Earth geobrowser virtual globe and their possible impact on Google Earth's usability, utility, and usefulness. A multi-phase methodology is described, combining usability reviews and usability testing with use-case scenarios involving the U.S.-Canadian Yellowstone to Yukon Initiative. Initial progress on a usability review combining cognitive walkthroughs and heuristics evaluation is presented.

Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption

PubMed Central

Chandrasekaran, Jeyamala; Thiruvengadam, S. J.

2015-01-01

Owing to the growth of high performance network technologies, multimedia applications over the Internet are increasing exponentially. Applications like video conferencing, video-on-demand, and pay-per-view depend upon encryption algorithms for providing confidentiality. Video communication is characterized by distinct features such as large volume, high redundancy between adjacent frames, video codec compliance, syntax compliance, and application specific requirements. Naive approaches for video encryption encrypt the entire video stream with conventional text based cryptographic algorithms. Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. This research work aims at enhancing the speed of naive approaches through chaos based S-box design. Chaotic equations are popularly known for randomness, extreme sensitivity to initial conditions, and ergodicity. The proposed methodology employs two-dimensional discrete Henon map for (i) generation of dynamic and key-dependent S-box that could be integrated with symmetric algorithms like Blowfish and Data Encryption Standard (DES) and (ii) generation of one-time keys for simple substitution ciphers. The proposed design is tested for randomness, nonlinearity, avalanche effect, bit independence criterion, and key sensitivity. Experimental results confirm that chaos based S-box design and key generation significantly reduce the computational cost of video encryption with no compromise in security. PMID:26550603

Three Naive Questions: Addressed to the Modern Educational Optimism

ERIC Educational Resources Information Center

Krstic, Predrag

2016-01-01

This paper aims to question anew the popular and supposedly self-evident affirmation of education, in its modern incarnation as in its historical notion. The "naive" questions suggest that we have recently taken for granted that education ought to be for the masses, that it ought to be upbringing, and that it is better than ignorance.…

Modified Mahalanobis Taguchi System for Imbalance Data Classification

PubMed Central

2017-01-01

The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA). PMID:28811820

Ensemble Classifiers for Predicting HIV-1 Resistance from Three Rule-Based Genotypic Resistance Interpretation Systems.

PubMed

Raposo, Letícia M; Nobre, Flavio F

2017-08-30

Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.

Intra-articular clearance of labeled dextrans from naive and arthritic rat knee joints.

PubMed

Mwangi, Timothy K; Berke, Ian M; Nieves, Eduardo H; Bell, Richard D; Adams, Samuel B; Setton, Lori A

2018-05-26

Determine the effects of arthritis on the trans-synovial clearance of small and large model compounds following local delivery to the knee joint in a rat model. Intra-articular delivery was studied in rat knee joints in an osteoarthritis model of joint instability (medial collateral ligament and meniscus transection model or MMT). Fluorescently-labeled 10 kDa or 500 kDa dextran was injected in the arthritic or unoperated control (naive) joints 3 weeks after surgical destabilization, and the temporal clearance pattern was evaluated via in vivo regional fluorescence imaging, dextran concentrations in plasma and draining lymph nodes, and by quantification of fluorescence in histological synovium sections. Together these data were used to evaluate the effect of osteoarthritis and solute size on the rate of drug clearance from the joint. Clearance of 10 kDa dextran from the joint space quantified using in vivo fluorescence imaging of the knee joint region was not significantly different between naive and MMT joints. In contrast, clearance of 500 kDa dextran was significantly reduced for MMT joints when compared to naive joints by fluorescence in vivo imaging. Drug accumulation in lymph nodes and plasma were lower for the 500 kDa dextran as compared to 10 kDa dextran, and lymph node levels were further reduced with the presence of osteoarthritis. Furthermore, synovium was significantly thicker in MMT joints than in naive joints and image analysis of joint tissue sections revealed different trans-synovial distributions of 10 and 500 kDa dextran. Large macromolecules were retained in the arthritic joint longer than in the healthy joint, while smaller molecules were cleared similarly in healthy and arthritic joints. In vivo fluorescence imaging, plasma and lymph node concentrations, and spatial distributions of drug fluorescence identified differences in higher molecular weight clearance between naive and arthritic disease states. Findings may relate to a

Classifying short genomic fragments from novel lineages using composition and homology

PubMed Central

2011-01-01

Background The assignment of taxonomic attributions to DNA fragments recovered directly from the environment is a vital step in metagenomic data analysis. Assignments can be made using rank-specific classifiers, which assign reads to taxonomic labels from a predetermined level such as named species or strain, or rank-flexible classifiers, which choose an appropriate taxonomic rank for each sequence in a data set. The choice of rank typically depends on the optimal model for a given sequence and on the breadth of taxonomic groups seen in a set of close-to-optimal models. Homology-based (e.g., LCA) and composition-based (e.g., PhyloPythia, TACOA) rank-flexible classifiers have been proposed, but there is at present no hybrid approach that utilizes both homology and composition. Results We first develop a hybrid, rank-specific classifier based on BLAST and Naïve Bayes (NB) that has comparable accuracy and a faster running time than the current best approach, PhymmBL. By substituting LCA for BLAST or allowing the inclusion of suboptimal NB models, we obtain a rank-flexible classifier. This hybrid classifier outperforms established rank-flexible approaches on simulated metagenomic fragments of length 200 bp to 1000 bp and is able to assign taxonomic attributions to a subset of sequences with few misclassifications. We then demonstrate the performance of different classifiers on an enhanced biological phosphorous removal metagenome, illustrating the advantages of rank-flexible classifiers when representative genomes are absent from the set of reference genomes. Application to a glacier ice metagenome demonstrates that similar taxonomic profiles are obtained across a set of classifiers which are increasingly conservative in their classification. Conclusions Our NB-based classification scheme is faster than the current best composition-based algorithm, Phymm, while providing equally accurate predictions. The rank-flexible variant of NB, which we term ε-NB, is

Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema

NASA Astrophysics Data System (ADS)

Kotropoulos, Constantine; Arce, Gonzalo R.

2009-12-01

Two distinct two-class pattern recognition problems are studied, namely, the detection of male subjects who are diagnosed with vocal fold paralysis against male subjects who are diagnosed as normal and the detection of female subjects who are suffering from vocal fold edema against female subjects who do not suffer from any voice pathology. To do so, utterances of the sustained vowel "ah" are employed from the Massachusetts Eye and Ear Infirmary database of disordered speech. Linear prediction coefficients extracted from the aforementioned utterances are used as features. The receiver operating characteristic curve of the linear classifier, that stems from the Bayes classifier when Gaussian class conditional probability density functions with equal covariance matrices are assumed, is derived. The optimal operating point of the linear classifier is specified with and without reject option. First results using utterances of the "rainbow passage" are also reported for completeness. The reject option is shown to yield statistically significant improvements in the accuracy of detecting the voice pathologies under study.

Left-Turn Bays

DOT National Transportation Integrated Search

1996-05-01

The topic of left-turn bays (left-turn lanes) involves the following three issues: 1.) Warrants; 2.) Bay Length and 3.) Design Details. This discussion paper deals with warrants and bay length -- including queue storage at signalized and unsignalized...

33 CFR 100.919 - International Bay City River Roar, Bay City, MI.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false International Bay City River Roar, Bay City, MI. 100.919 Section 100.919 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF... Bay City River Roar, Bay City, MI. (a) Regulated Area. A regulated area is established to include all...

33 CFR 100.919 - International Bay City River Roar, Bay City, MI.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false International Bay City River Roar, Bay City, MI. 100.919 Section 100.919 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF... Bay City River Roar, Bay City, MI. (a) Regulated Area. A regulated area is established to include all...

Expert and Naive Raters Using the PAG: Does it Matter?

ERIC Educational Resources Information Center

Cornelius, Edwin T.; And Others

1984-01-01

Questions the observed correlation between job experts and naive raters using the Position Analysis Questionnaire (PAQ); and conducts a replication of the Smith and Hakel study (1979) with college students (N=39). Concluded that PAQ ratings from job experts and college students are not equivalent and therefore are not interchangeable. (LLL)

An automated approach to the design of decision tree classifiers

NASA Technical Reports Server (NTRS)

Argentiero, P.; Chin, R.; Beaudet, P.

1982-01-01

An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

Right lateralized white matter abnormalities in first-episode, drug-naive paranoid schizophrenia.

PubMed

Guo, Wenbin; Liu, Feng; Liu, Zhening; Gao, Keming; Xiao, Changqing; Chen, Huafu; Zhao, Jingping

2012-11-30

Numerous studies in first-episode schizophrenia suggest the involvement of white matter (WM) abnormalities in multiple regions underlying the pathogenesis of this condition. However, there has never been a neuroimaging study in patients with first-episode, drug-naive paranoid schizophrenia by using tract-based spatial statistics (TBSS) method. Here, we used diffusion tensor imaging (DTI) with TBSS method to investigate the brain WM integrity in patients with first-episode, drug-naive paranoid schizophrenia. Twenty patients with first-episode, drug-naive paranoid schizophrenia and 26 healthy subjects matched with age, gender, and education level were scanned with DTI. An automated TBSS approach was employed to analyze the data. Voxel-wise statistics revealed that patients with paranoid schizophrenia had decreased fractional anisotropy (FA) values in the right superior longitudinal fasciculus (SLF) II, the right fornix, the right internal capsule, and the right external capsule compared to healthy subjects. Patients did not have increased FA values in any brain regions compared to healthy subjects. There was no correlation between the FA values in any brain regions and patient demographics and the severity of illness. Our findings suggest right-sided alterations of WM integrity in the WM tracts of cortical and subcortical regions may play an important role in the pathogenesis of paranoid schizophrenia. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Online breakage detection of multitooth tools using classifier ensembles for imbalanced data

NASA Astrophysics Data System (ADS)

Bustillo, Andrés; Rodríguez, Juan J.

2014-12-01

Cutting tool breakage detection is an important task, due to its economic impact on mass production lines in the automobile industry. This task presents a central limitation: real data-sets are extremely imbalanced because breakage occurs in very few cases compared with normal operation of the cutting process. In this paper, we present an analysis of different data-mining techniques applied to the detection of insert breakage in multitooth tools. The analysis applies only one experimental variable: the electrical power consumption of the tool drive. This restriction profiles real industrial conditions more accurately than other physical variables, such as acoustic or vibration signals, which are not so easily measured. Many efforts have been made to design a method that is able to identify breakages with a high degree of reliability within a short period of time. The solution is based on classifier ensembles for imbalanced data-sets. Classifier ensembles are combinations of classifiers, which in many situations are more accurate than individual classifiers. Six different base classifiers are tested: Decision Trees, Rules, Naïve Bayes, Nearest Neighbour, Multilayer Perceptrons and Logistic Regression. Three different balancing strategies are tested with each of the classifier ensembles and compared to their performance with the original data-set: Synthetic Minority Over-Sampling Technique (SMOTE), undersampling and a combination of SMOTE and undersampling. To identify the most suitable data-mining solution, Receiver Operating Characteristics (ROC) graph and Recall-precision graph are generated and discussed. The performance of logistic regression ensembles on the balanced data-set using the combination of SMOTE and undersampling turned out to be the most suitable technique. Finally a comparison using industrial performance measures is presented, which concludes that this technique is also more suited to this industrial problem than the other techniques presented in

Thinking Process of Naive Problem Solvers to Solve Mathematical Problems

ERIC Educational Resources Information Center

Mairing, Jackson Pasini

2017-01-01

Solving problems is not only a goal of mathematical learning. Students acquire ways of thinking, habits of persistence and curiosity, and confidence in unfamiliar situations by learning to solve problems. In fact, there were students who had difficulty in solving problems. The students were naive problem solvers. This research aimed to describe…

The Profession of Psychology Scale: Sophisticated and Naive Students' Responses

ERIC Educational Resources Information Center

Rosenthal, Gary T.; Soper, Barlow; Rachal, Chris; McKnight, Richard R.; Price, A. W.

2004-01-01

The Profession of Psychology Scale (Rosenthal, McKnight & Price, 2001) was used to investigate whether taking more psychology courses results in a more accurate understanding of what is required to become a psychologist. Data indicate that though misconceptions exist in both Naive students (those who had not completed any psychology courses) and…

IL-15 induces antigen-independent expansion and differentiation of human naive CD8+ T cells in vitro.

PubMed

Alves, Nuno L; Hooibrink, Berend; Arosa, Fernando A; van Lier, René A W

2003-10-01

Recent studies in mice have shown that although interleukin 15 (IL-15) plays an important role in regulating homeostasis of memory CD8+ T cells, it has no apparent function in controlling homeostatic proliferation of naive T cells. We here assessed the influence of IL-15 on antigen-independent expansion and differentiation of human CD8+ T cells. Both naive and primed human T cells divided in response to IL-15. In this process, naive CD8+ T cells successively down-regulated CD45RA and CD28 but maintained CD27 expression. Concomitant with these phenotypic changes, naive cells acquired the ability to produce interferon gamma (IFN-gamma) and tumor necrosis factor alpha (TNF-alpha), expressed perforin and granzyme B, and acquired cytotoxic properties. Primed CD8+ T cells, from both noncytotoxic (CD45RA-CD27+) and cytotoxic (CD45RA+CD27-) subsets, responded to IL-15 and yielded ample numbers of cytokine-secreting and cytotoxic effector cells. In summary, all human CD8+ T-cell subsets had the ability to respond to IL-15, which suggests a generic influence of this cytokine on CD8+ T-cell homeostasis in man.

Naive and effector B-cell subtypes are increased in chronic rhinosinusitis with polyps.

PubMed

Miljkovic, Dijana; Psaltis, Alkis; Wormald, Peter-John; Vreugde, Sarah

2018-01-01

Recent studies demonstrated that B cells and their chemoattractants are elevated in the nasal mucosa of patients with chronic rhinosinusitis (CRS) with nasal polyposis (CRSwNP). However, the presence of naive B cells and of plasmablasts and memory B-cell subsets in the mucosa and periphery of the same patient with CRS is yet to be characterized. Here we sought to quantify naive, plasmablasts, and memory B cells in mucosal tissue and peripheral blood of patients with CRSwNP, patients with CRS without nasal polyps (CRSsNP), and control patients. Polyps, mucosa, and peripheral blood samples were prospectively collected from the patients with CRS and from the non-CRS controls. We used flow cytometry to distinguish among naive, plasmablast, and memory B cells in sinus tissue and peripheral blood. A total of 45 patients were recruited for the study. The patients with CRSwNP had significantly increased mucosal B-cell numbers versus the controls (3.39 ± 4.05% versus 0.39 ± 1.05% of live cells; p < 0.01, Kruskal-Wallis test), which included naive B cells (0.61 ± 0.94 versus 0.11 ± 0.24% of live cells; p < 0.03, Kruskal-Wallis test), plasmablasts (0.06 ± 0.26 versus 0.00 ± 0.00% of live cells; p < 0.055, Kruskal-Wallis test), and memory B cells (0.62 ± 1.26 versus 0.05 ± 0.15% of live cells; p < 0.02, Kruskal-Wallis test). Our study identified increased frequencies of different B-cell subtypes in the mucosa of patients with CRSwNP but not in the peripheral blood. We also found that patients with CRSwNP had significantly increased B-cell subtypes compared with the patients with CRSsNP and the controls. These results implied a potential role for mucosal B cells in the ongoing inflammation in patients with CRSwNP.

77 FR 70891 - Safety Zone; Bay Bridge Construction, San Francisco Bay, San Francisco, CA

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-28

...-AA00 Safety Zone; Bay Bridge Construction, San Francisco Bay, San Francisco, CA AGENCY: Coast Guard... the navigable waters of the San Francisco Bay near Yerba Buena Island, CA in support of the Bay Bridge... construction of the Bay Bridge, the safety zone is necessary to provide for the safety of mariners transiting...

33 CFR 100.112 - Swim the Bay, Narragansett Bay, Narragansett, RI.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Swim the Bay, Narragansett Bay, Narragansett, RI. 100.112 Section 100.112 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY REGATTAS AND MARINE PARADES SAFETY OF LIFE ON NAVIGABLE WATERS § 100.112 Swim the Bay...

A Workshop for High School Students on Naive Set Theory

ERIC Educational Resources Information Center

Wegner, Sven-Ake

2014-01-01

In this article we present the prototype of a workshop on naive set theory designed for high school students in or around the seventh year of primary education. Our concept is based on two events which the author organized in 2006 and 2010 for students of elementary school and high school, respectively. The article also includes a practice report…

Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics

PubMed Central

Ruvindy, Rendy; White III, Richard Allen; Neilan, Brett Anthony; Burns, Brendan Paul

2016-01-01

Modern microbial mats are potential analogues of some of Earth's earliest ecosystems. Excellent examples can be found in Shark Bay, Australia, with mats of various morphologies. To further our understanding of the functional genetic potential of these complex microbial ecosystems, we conducted for the first time shotgun metagenomic analyses. We assembled metagenomic next-generation sequencing data to classify the taxonomic and metabolic potential across diverse morphologies of marine mats in Shark Bay. The microbial community across taxonomic classifications using protein-coding and small subunit rRNA genes directly extracted from the metagenomes suggests that three phyla Proteobacteria, Cyanobacteria and Bacteriodetes dominate all marine mats. However, the microbial community structure between Shark Bay and Highbourne Cay (Bahamas) marine systems appears to be distinct from each other. The metabolic potential (based on SEED subsystem classifications) of the Shark Bay and Highbourne Cay microbial communities were also distinct. Shark Bay metagenomes have a metabolic pathway profile consisting of both heterotrophic and photosynthetic pathways, whereas Highbourne Cay appears to be dominated almost exclusively by photosynthetic pathways. Alternative non-rubisco-based carbon metabolism including reductive TCA cycle and 3-hydroxypropionate/4-hydroxybutyrate pathways is highly represented in Shark Bay metagenomes while not represented in Highbourne Cay microbial mats or any other mat forming ecosystems investigated to date. Potentially novel aspects of nitrogen cycling were also observed, as well as putative heavy metal cycling (arsenic, mercury, copper and cadmium). Finally, archaea are highly represented in Shark Bay and may have critical roles in overall ecosystem function in these modern microbial mats. PMID:26023869

75 FR 36292 - Safety Zone; Bay Swim III, Presque Isle Bay, Erie, PA

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-25

... of Presque Isle Bay, Lake Erie, near Erie, Pennsylvania between 9 a.m. to 11 a.m. on June 26, 2010.... The safety zone will encompass specified waters of Presque Isle Bay, Erie, Pennsylvania starting at...-AA00 Safety Zone; Bay Swim III, Presque Isle Bay, Erie, PA AGENCY: Coast Guard, DHS. ACTION: Temporary...

Structure, age and origin of the bay-mouth shoal deposits, Chesapeake Bay, Virginia

USGS Publications Warehouse

Colman, Steven M.; Berquist, C.R.; Hobbs, C. H.

1988-01-01

The mouth of Chesapeake Bay contains a distinctive shoal complex and related deposits that result from the complex interaction of three different processes: (1) progradation of a barrier spit at the southern end of the Delmarva Peninsula, (2) strong, reversing tidal currents that transport and rework sediment brought to the bay mouth from the north, and (3) landward (bayward) net non-tidal circulation and sediment transport. Together, these processes play a major role in changing the configuration of the estuary and filling it with sediment. The deposits at the mouth of the bay hold keys both to the evolution of the bay during the Holocene transgression and to the history of previous generations of the bay. The deposit associated with the shoals at the mouth of the bay, the bay-mouth sand, is a distinct stratigraphic unit composed mostly of uniform, gray, fine sand. The position and internal structure of the unit shows that it is related to near-present sea level, and thus is less than a few thousand years old. The processes affecting the upper surface of the deposit and the patterns of erosion and deposition at this surface are complex, but the geometry and structure of the deposit indicate that it is a coherent unit that is prograding bayward and tending to fill the estuary. The source of the bay-mouth sand is primarily outside the bay in the nearshore zone of the Delmarva Peninsula and on the inner continental shelf. The internal structure of the deposit, its surface morphology, its heavy-mineral composition, bottom-current studies, comparative bathymetry, and sediment budgets all suggest that sand is brought to the bay mouth by southerly longshore drift along the Delmarva Peninsula and then swept into the bay. In addition to building the southward- and bayward-prograding bay-mouth sand, these processes result in sand deposition tens of kilometers into the bay. ?? 1988.

33 CFR 162.125 - Sturgeon Bay and the Sturgeon Bay Ship Canal, Wisc.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Sturgeon Bay and the Sturgeon Bay Ship Canal, Wisc. 162.125 Section 162.125 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) PORTS AND WATERWAYS SAFETY INLAND WATERWAYS NAVIGATION REGULATIONS § 162.125 Sturgeon Bay and the Sturgeon Bay Ship...

Bioinvasion in a Brazilian bay: filling gaps in the knowledge of southwestern Atlantic biota.

PubMed

Ignacio, Barbara L; Julio, Luciana M; Junqueira, Andrea O R; Ferreira-Silva, Maria A G

2010-09-29

Biological invasions are a major cause of global species change. Nevertheless, knowledge about the distribution and ecology of introduced species is regionally biased, and many gaps in knowledge exist for most developing countries. To study the zoobenthos on the hard substratum of the Ilha Grande Bay, a survey was conducted on both natural and artificial substrata at three depths and seven sites. The species recorded were classified as native, cryptogenic or introduced. Multivariate analyses were conducted to assess the prevalence of introduced species in these communities and to compare the distribution of species on natural and artificial substrata of this bay to identify possible discrepancies in habitat use. Of the 61 species, 25 were cryptogenic, 10 were introduced and 26 were native. Similar numbers of introduced species were found on both natural and artificial substrata, though the community composition was significantly different between them. We also compared the species composition of the Ilha Grande Bay survey to other inventories taken around the world. The highest similarities were found between the Ilha Grande Bay inventory and the Atlantic coastal region (Tampa Bay, USA and the Gulf of Mexico), American Samoa and Pearl Harbor (USA) inventories. This study presents the first published comprehensive list of hard substratum sessile marine invertebrate species in a Brazilian bay. The high percentage of cryptogenic species reveals gaps in both zoological records and information on introduced species for the Brazilian coast. The introduced species successfully colonized different sites in the Ilha Grande Bay, including both natural and artificial substrata. In addition, we find that artificial structures may not be good surrogates for natural rocky shores and may represent an ecological threat. Comparisons with other inventories suggest a history of broad-scale invasion, though more evidence is needed to support this conclusion.

Machine learning approaches to diagnosis and laterality effects in semantic dementia discourse.

PubMed

Garrard, Peter; Rentoumi, Vassiliki; Gesierich, Benno; Miller, Bruce; Gorno-Tempini, Maria Luisa

2014-06-01

Advances in automatic text classification have been necessitated by the rapid increase in the availability of digital documents. Machine learning (ML) algorithms can 'learn' from data: for instance a ML system can be trained on a set of features derived from written texts belonging to known categories, and learn to distinguish between them. Such a trained system can then be used to classify unseen texts. In this paper, we explore the potential of the technique to classify transcribed speech samples along clinical dimensions, using vocabulary data alone. We report the accuracy with which two related ML algorithms [naive Bayes Gaussian (NBG) and naive Bayes multinomial (NBM)] categorized picture descriptions produced by: 32 semantic dementia (SD) patients versus 10 healthy, age-matched controls; and SD patients with left- (n = 21) versus right-predominant (n = 11) patterns of temporal lobe atrophy. We used information gain (IG) to identify the vocabulary features that were most informative to each of these two distinctions. In the SD versus control classification task, both algorithms achieved accuracies of greater than 90%. In the right- versus left-temporal lobe predominant classification, NBM achieved a high level of accuracy (88%), but this was achieved by both NBM and NBG when the features used in the training set were restricted to those with high values of IG. The most informative features for the patient versus control task were low frequency content words, generic terms and components of metanarrative statements. For the right versus left task the number of informative lexical features was too small to support any specific inferences. An enriched feature set, including values derived from Quantitative Production Analysis (QPA) may shed further light on this little understood distinction. Copyright © 2013 Elsevier Ltd. All rights reserved.

Pb’s high sedimentation inside the bay mouth of Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Miao, Zhenqing; Huang, Xinmin; Wei, Linzhen; Feng, Ming

2017-12-01

Sedimentation is one of the key environmental behaviors of pollutants in the ocean. This paper analyzed the seasonal and temporal variations of Pb’s sedimentation process in Jiaozhou Bay in 1987. Results showed that Pb contents in bottom waters in Jiaozhou Bay in May, July and November 1987 were 1.87-2.60 μg L-1, 15.11-19.68 μg L-1 and 11.08-15.18 μg L-1, and the pollution levels of Pb in May, July and November 1987 were slight, heavy and heavy, respectively. In May 1987, there was low sedimentation process in waters in the outside of the bay mouth, yet were high sedimentation process in waters in the middle and inside of the bay mouth. In July and November 1987, there was low sedimentation process in waters in the outside of the bay mouth, yet were high sedimentation process in waters in the inside of the bay mouth. The seasonal-temporal variation of sedimentation processes of Pb were determined by the variations of sources input and the vertical water’s effect.

The effect of heavy metal contamination on the bacterial community structure at Jiaozhou Bay, China.

PubMed

Yao, Xie-Feng; Zhang, Jiu-Ming; Tian, Li; Guo, Jian-Hua

In this study, determination of heavy metal parameters and microbiological characterization of marine sediments obtained from two heavily polluted sites and one low-grade contaminated reference station at Jiaozhou Bay in China were carried out. The microbial communities found in the sampled marine sediments were studied using PCR-DGGE (denaturing gradient gel electrophoresis) fingerprinting profiles in combination with multivariate analysis. Clustering analysis of DGGE and matrix of heavy metals displayed similar occurrence patterns. On this basis, 17 samples were classified into two clusters depending on the presence or absence of the high level contamination. Moreover, the cluster of highly contaminated samples was further classified into two sub-groups based on the stations of their origin. These results showed that the composition of the bacterial community is strongly influenced by heavy metal variables present in the sediments found in the Jiaozhou Bay. This study also suggested that metagenomic techniques such as PCR-DGGE fingerprinting in combination with multivariate analysis is an efficient method to examine the effect of metal contamination on the bacterial community structure. Copyright © 2016 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Map showing thickness of young bay mud, southern San Francisco Bay, California

USGS Publications Warehouse

McDonald, Sandra D.; Nichols, Donald R.; Wright, Nancy A.; Atwater, Brian

1978-01-01

Soft water-saturated estuarine deposits less than 10,000 years old underlie the southern part of San Francisco bay and the present and former marshlands that border the bay. Known locally as bay mud or as young bay mud, these deposits, and the estuarine environment that produces them, are of major importance in making decision on land use and development in the San Francisco Bay area. Knowledge of the distribution, thickness, and physical properties of young bay mud is critical to the feasibility, design, and maintenance of structures built on it. Fore this reason, numerous attempts have been made in the past to map or describe these characteristics (Mitchell, 1963; Goldman, 1969; McDonald and Nichols, 1974). The accompanying map of bay-mud thickness significantly revises part of an earlier compilation by Kahle and Goldman (1969) and includes new data from approximately 2400 boreholes, most of which have been drilled during the past 15 years. It also incorporates information on historic margins of San Francisco Bay and its tidal marshes (Nichols and Wright, 1971). Although this map was compelled mostly from data gathered during foundation investigations and construction projects, it is mostly from data gathered during foundation investigations and construction projects, it is not a substitute for such studies. Rather, the map provides regional information for land-use planning, seismic zonation, and design of foundation investigations.

77 FR 14276 - Regulated Navigation Area; Little Bay Bridge Construction, Little Bay, Portsmouth, NH

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-09

...-AA11 Regulated Navigation Area; Little Bay Bridge Construction, Little Bay, Portsmouth, NH AGENCY... under and surrounding the Little Bay and General Sullivan Bridges in order to facilitate construction of the Little Bay Bridge between Newington, NH and Dover, NH. This temporary interim rule is necessary to...

A 10-Gene Classifier for Indeterminate Thyroid Nodules: Development and Multicenter Accuracy Study

PubMed Central

González, Hernán E.; Martínez, José R.; Vargas-Salas, Sergio; Solar, Antonieta; Veliz, Loreto; Cruz, Francisco; Arias, Tatiana; Loyola, Soledad; Horvath, Eleonora; Tala, Hernán; Traipe, Eufrosina; Meneses, Manuel; Marín, Luis; Wohllk, Nelson; Diaz, René E.; Véliz, Jesús; Pineda, Pedro; Arroyo, Patricia; Mena, Natalia; Bracamonte, Milagros; Miranda, Giovanna; Bruce, Elsa

2017-01-01

Background: In most of the world, diagnostic surgery remains the most frequent approach for indeterminate thyroid cytology. Although several molecular tests are available for testing in centralized commercial laboratories in the United States, there are no available kits for local laboratory testing. The aim of this study was to develop a prototype in vitro diagnostic (IVD) gene classifier for the further characterization of nodules with an indeterminate thyroid cytology. Methods: In a first stage, the expression of 18 genes was determined by quantitative polymerase chain reaction (qPCR) in a broad histopathological spectrum of 114 fresh-tissue biopsies. Expression data were used to train several classifiers by supervised machine learning approaches. Classifiers were tested in an independent set of 139 samples. In a second stage, the best classifier was chosen as a model to develop a multiplexed-qPCR IVD prototype assay, which was tested in a prospective multicenter cohort of fine-needle aspiration biopsies. Results: In tissue biopsies, the best classifier, using only 10 genes, reached an optimal and consistent performance in the ninefold cross-validated testing set (sensitivity 93% and specificity 81%). In the multicenter cohort of fine-needle aspiration biopsy samples, the 10-gene signature, built into a multiplexed-qPCR IVD prototype, showed an area under the curve of 0.97, a positive predictive value of 78%, and a negative predictive value of 98%. By Bayes' theorem, the IVD prototype is expected to achieve a positive predictive value of 64–82% and a negative predictive value of 97–99% in patients with a cancer prevalence range of 20–40%. Conclusions: A new multiplexed-qPCR IVD prototype is reported that accurately classifies thyroid nodules and may provide a future solution suitable for local reference laboratory testing. PMID:28521616

HIV-1 drug resistance mutations emerging on darunavir therapy in PI-naive and -experienced patients in the UK.

PubMed

El Bouzidi, Kate; White, Ellen; Mbisa, Jean L; Sabin, Caroline A; Phillips, Andrew N; Mackie, Nicola; Pozniak, Anton L; Tostevin, Anna; Pillay, Deenan; Dunn, David T

2016-12-01

Darunavir is considered to have a high genetic barrier to resistance. Most darunavir-associated drug resistance mutations (DRMs) have been identified through correlation of baseline genotype with virological response in clinical trials. However, there is little information on DRMs that are directly selected by darunavir in clinical settings. We examined darunavir DRMs emerging in clinical practice in the UK. Baseline and post-exposure protease genotypes were compared for individuals in the UK Collaborative HIV Cohort Study who had received darunavir; analyses were stratified for PI history. A selection analysis was used to compare the evolution of subtype B proteases in darunavir recipients and matched PI-naive controls. Of 6918 people who had received darunavir, 386 had resistance tests pre- and post-exposure. Overall, 2.8% (11/386) of these participants developed emergent darunavir DRMs. The prevalence of baseline DRMs was 1.0% (2/198) among PI-naive participants and 13.8% (26/188) among PI-experienced participants. Emergent DRMs developed in 2.0% of the PI-naive group (4 mutations) and 3.7% of the PI-experienced group (12 mutations). Codon 77 was positively selected in the PI-naive darunavir cases, but not in the control group. Our findings suggest that although emergent darunavir resistance is rare, it may be more common among PI-experienced patients than those who are PI-naive. Further investigation is required to explore whether codon 77 is a novel site involved in darunavir susceptibility. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.

Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.

PubMed

Yourganov, Grigori; Schmah, Tanya; Churchill, Nathan W; Berman, Marc G; Grady, Cheryl L; Strother, Stephen C

2014-08-01

The field of fMRI data analysis is rapidly growing in sophistication, particularly in the domain of multivariate pattern classification. However, the interaction between the properties of the analytical model and the parameters of the BOLD signal (e.g. signal magnitude, temporal variance and functional connectivity) is still an open problem. We addressed this problem by evaluating a set of pattern classification algorithms on simulated and experimental block-design fMRI data. The set of classifiers consisted of linear and quadratic discriminants, linear support vector machine, and linear and nonlinear Gaussian naive Bayes classifiers. For linear discriminant, we used two methods of regularization: principal component analysis, and ridge regularization. The classifiers were used (1) to classify the volumes according to the behavioral task that was performed by the subject, and (2) to construct spatial maps that indicated the relative contribution of each voxel to classification. Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps. In simulated data sets, we performed an additional evaluation of spatial maps with ROC analysis. We varied the magnitude, temporal variance and connectivity of simulated fMRI signal and identified the optimal classifier for each simulated environment. Overall, the best performers were linear and quadratic discriminants (operating on principal components of the data matrix) and, in some rare situations, a nonlinear Gaussian naïve Bayes classifier. The results from the simulated data were supported by within-subject analysis of experimental fMRI data, collected in a study of aging. This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI. Copyright © 2014 Elsevier Inc. All rights reserved.

Edoxaban vs. warfarin in vitamin K antagonist experienced and naive patients with atrial fibrillation†.

PubMed

O'Donoghue, Michelle L; Ruff, Christian T; Giugliano, Robert P; Murphy, Sabina A; Grip, Laura T; Mercuri, Michele F; Rutman, Howard; Shi, Minggao; Kania, Grzegorz; Cermak, Ondrej; Braunwald, Eugene; Antman, Elliott M

2015-06-14

Edoxaban is an oral, once-daily factor Xa inhibitor that is non-inferior to well-managed warfarin in patients with atrial fibrillation (AF) for the prevention of stroke and systemic embolic events (SEEs). We examined the efficacy and safety of edoxaban vs. warfarin in patients who were vitamin K antagonist (VKA) naive or experienced. ENGAGE AF-TIMI 48 randomized 21 105 patients with AF at moderate-to-high risk of stroke to once-daily edoxaban vs. warfarin. Subjects were followed for a median of 2.8 years. The primary efficacy endpoint was stroke or SEE. As a pre-specified subgroup, we analysed outcomes for those with or without prior VKA experience (>60 consecutive days). Higher-dose edoxaban significantly reduced the risk of stroke or SEE in patients who were VKA naive [hazard ratio (HR) 0.71, 95% confidence interval (CI) 0.56-0.90] and was similar to warfarin in the VKA experienced (HR 1.01, 95% CI 0.82-1.24; P interaction = 0.028). Lower-dose edoxaban was similar to warfarin for stroke or SEE prevention in patients who were VKA naive (HR 0.92, 95% CI 0.73-1.15), but was inferior to warfarin in those who were VKA experienced (HR 1.31, 95% 1.08-1.60; P interaction = 0.019). Both higher-dose and lower-dose edoxaban regimens significantly reduced the risk of major bleeding regardless of prior VKA experience (P interaction = 0.90 and 0.71, respectively). In patients with AF, edoxaban appeared to demonstrate greater efficacy compared with warfarin in patients who were VKA naive than VKA experienced. Edoxaban significantly reduced major bleeding compared with warfarin regardless of prior VKA exposure. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

Oral immunisation of naive and primed animals with transgenic potato tubers expressing LT-B.

PubMed

Lauterslager, T G; Florack, D E; van der Wal, T J; Molthoff, J W; Langeveld, J P; Bosch, D; Boersma, W J; Hilgers, L A

2001-03-21

The efficacy of edible vaccines produced in potato tubers was examined in mice. Transgenic plants were developed by Agrobacterium tumefaciens-mediated transformation. The antigen selected was the non-toxic B subunit of the Escherichia coli enterotoxin (recLT-B). A synthetic gene coding for recLT-B was made and optimised for expression in potato tubers and accumulation in the endoplasmic reticulum. Introduction of this gene under control of the tuber-specific patatin promoter in potato plants resulted in the production of functional, i.e. Gm1-binding, recLT-B pentamers in tubers. Selected tubers containing about 13 microg of recLT-B per gram fresh weight were used for immunisation. Subcutaneous immunisation with an extract of recLT-B tubers yielded high antibody titres in serum that were similar to those obtained with bacterial recLT-B. The efficacy of oral administration of recLT-B tubers was determined by measuring mucosal and systemic immune responses in naive and primed mice. Animals were primed by subcutaneous injection of an extract of recLT-B tuber plus adjuvant. Naive and primed mice were fed 5 g of tubers ( approximately 65 microg of recLT-B) or were intubated intragastrically with 0.4 ml of tuber extract ( approximately 2 microg of recLT-B). In naive mice, feeding recLT-B tubers or intubation of tuber extract did not induce detectable anti-LT antibody titres. In primed animals, however, oral immunisation resulted in significant anti-LT IgA antibody responses in serum and faeces. Intragastric intubation of tuber extract revealed higher responses than feeding of tubers. These results indicate clearly that functional recLT-B can be produced in potato tubers, that this recombinant protein is immunogenic and that oral administration thereof elicits both systemic and local IgA responses in parentally primed, but not naive, animals.

78 FR 38580 - Special Local Regulation; Tall Ships Celebration Bay City, Bay City, MI

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-27

...-AA08 Special Local Regulation; Tall Ships Celebration Bay City, Bay City, MI AGENCY: Coast Guard, DHS... regulatory act for the celebration specific to Bay City, MI, the Coast Guard recently published a separate... various events throughout the Great Lakes this summer, to include the Tall Ships Celebration Bay City...

Implementation of mutual information and bayes theorem for classification microarray data

NASA Astrophysics Data System (ADS)

Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

2018-03-01

Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

Naive and effector B-cell subtypes are increased in chronic rhinosinusitis with polyps

PubMed Central

Miljkovic, Dijana; Psaltis, Alkis; Wormald, Peter-John

2018-01-01

Background: Recent studies demonstrated that B cells and their chemoattractants are elevated in the nasal mucosa of patients with chronic rhinosinusitis (CRS) with nasal polyposis (CRSwNP). However, the presence of naive B cells and of plasmablasts and memory B-cell subsets in the mucosa and periphery of the same patient with CRS is yet to be characterized. Objective: Here we sought to quantify naive, plasmablasts, and memory B cells in mucosal tissue and peripheral blood of patients with CRSwNP, patients with CRS without nasal polyps (CRSsNP), and control patients. Methods: Polyps, mucosa, and peripheral blood samples were prospectively collected from the patients with CRS and from the non-CRS controls. We used flow cytometry to distinguish among naive, plasmablast, and memory B cells in sinus tissue and peripheral blood. Results: A total of 45 patients were recruited for the study. The patients with CRSwNP had significantly increased mucosal B-cell numbers versus the controls (3.39 ± 4.05% versus 0.39 ± 1.05% of live cells; p < 0.01, Kruskal-Wallis test), which included naive B cells (0.61 ± 0.94 versus 0.11 ± 0.24% of live cells; p < 0.03, Kruskal-Wallis test), plasmablasts (0.06 ± 0.26 versus 0.00 ± 0.00% of live cells; p < 0.055, Kruskal-Wallis test), and memory B cells (0.62 ± 1.26 versus 0.05 ± 0.15% of live cells; p < 0.02, Kruskal-Wallis test). Conclusion: Our study identified increased frequencies of different B-cell subtypes in the mucosa of patients with CRSwNP but not in the peripheral blood. We also found that patients with CRSwNP had significantly increased B-cell subtypes compared with the patients with CRSsNP and the controls. These results implied a potential role for mucosal B cells in the ongoing inflammation in patients with CRSwNP. PMID:29336281

James Bay

Atmospheric Science Data Center

2013-04-17

article title:  Hudson Bay and James Bay, Canada   ... which scatters more light in the backward direction. This example illustrates how multi-angle viewing can distinguish physical structures ... MD. The MISR data were obtained from the NASA Langley Research Center Atmospheric Science Data Center in Hampton, VA. Image ...

The Effect of Naive Ideas on Students' Reasoning about Electricity and Magnetism

ERIC Educational Resources Information Center

Leppavirta, Johanna

2012-01-01

Traditional multiple-choice concept inventories measure students' critical conceptual understanding and are designed to reveal students' naive or alternate ideas. The overall scores, however, give little information about the state of students' knowledge and the consistency of reasoning. This study investigates whether students have consistent…

Chesapeake Bay study

NASA Technical Reports Server (NTRS)

Love, W. J.

1972-01-01

The objectives and scope of the Chesapeake Bay study are discussed. The physical, chemical, biological, political, and social phenomena of concern to the Chesapeake Bay area are included in the study. The construction of a model of the bay which will provide a means of accurately studying the interaction of the ecological factors is described. The application of the study by management organizations for development, enhancement, conservation, preservation, and restoration of the resources is examined.

CD72 ligation regulates defective naive newborn B cell responses.

PubMed

Howard, L M; Reen, D J

1997-02-01

The biological basis for reduced Ig production by naive newborn B cells compared to adult peripheral blood B cells is not fully understood. In a Con A + IL-2 T cell-dependent system using "competent" adult T cells, adult B cells produced large amounts of IgM, IgG, and IgA, while cord B cells were restricted to low levels of only IgM production. Cord B cell activation was also diminished. The contribution of specific B-T cell contact-mediated events to the diminished cord B cell response in this system, using mAbs to CD40, CD28, CD80, and CD72, were investigated, as well as regulation of B cell Ig production by cytokines. alphaCD72 ligation increased cord B cell activation and IgM production, but did not affect adult B cells. Blocking alphaCD40 mAb inhibited cord B cell Ig production completely, but only partly inhibited adult B cell Ig production even at high concentration, suggesting a greater sensitivity of cord B cells to disruption of the CD40-CD40L interaction. Addition of IL-10 did not increase cord B cell Ig production, while adult B cell Ig production was increased. However, combined addition of IL-10 and alphaCD72 significantly increased cord B cell Ig production over that in the presence of either alphaCD72 or IL-10 alone, but had no effect on adult B cells over that of IL-10 alone. These data suggest that the diminished T cell-dependent response of cord B cells is due to reduced or absent CD72 ligation. CD72 ligation plays an important role in the induction of primary responses by naive B cells. CD72 modulation of naive B cell sensitivity to IL-10 stimulation may have implications in the induction of class switch, which is deficient in newborn B cells. Since all T cells express CD5 constitutively, these data also suggest the existence of another ligand for CD72.

Mid-Bay Islands Hydrodynamics and Sedimentation Modeling Study, Chesapeake Bay

DTIC Science & Technology

2006-08-01

largest estuary in the United States, extending more than 150 miles from its seaward end at the Atlantic Ocean to the bayward end at the entrance to...water enters the bay from more than 150 major rivers and streams at approximately 80,000 cu ft/sec. Ocean tides enter the bay through the Atlantic ...Ocean entrance and C&D Canal. The mean range of tides in the bay varies from approximately 1 ft on the western shore to 3 ft at the Atlantic Ocean

Children's Naive Theories of Intelligence Influence Their Metacognitive Judgments

ERIC Educational Resources Information Center

Miele, David B.; Son, Lisa K.; Metcalfe, Janet

2013-01-01

Recent studies have shown that the metacognitive judgments adults infer from their experiences of encoding effort vary in accordance with their naive theories of intelligence. To determine whether this finding extends to elementary schoolchildren, a study was conducted in which 27 third graders (M[subscript age] = 8.27) and 24 fifth graders…

Breast cancer Ki67 expression preoperative discrimination by DCE-MRI radiomics features

NASA Astrophysics Data System (ADS)

Ma, Wenjuan; Ji, Yu; Qin, Zhuanping; Guo, Xinpeng; Jian, Xiqi; Liu, Peifang

2018-02-01

To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are associated with Ki67 expression of breast cancer. In this institutional review board approved retrospective study, we collected 377 cases Chinese women who were diagnosed with invasive breast cancer in 2015. This cohort included 53 low-Ki67 expression (Ki67 proliferation index less than 14%) and 324 cases with high-Ki67 expression (Ki67 proliferation index more than 14%). A binary-classification of low- vs. high- Ki67 expression was performed. A set of 52 quantitative radiomics features, including morphological, gray scale statistic, and texture features, were extracted from the segmented lesion area. Three most common machine learning classification methods, including Naive Bayes, k-Nearest Neighbor and support vector machine with Gaussian kernel, were employed for the classification and the least absolute shrink age and selection operator (LASSO) method was used to select most predictive features set for the classifiers. Classification performance was evaluated by the area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. The model that used Naive Bayes classification method achieved the best performance than the other two methods, yielding 0.773 AUC value, 0.757 accuracy, 0.777 sensitivity and 0.769 specificity. Our study showed that quantitative radiomics imaging features of breast tumor extracted from DCE-MRI are associated with breast cancer Ki67 expression. Future larger studies are needed in order to further evaluate the findings.

Recent thymic emigrants and mature naive T cells exhibit differential DNA methylation at key cytokine loci.

PubMed

Berkley, Amy M; Hendricks, Deborah W; Simmons, Kalynn B; Fink, Pamela J

2013-06-15

Recent thymic emigrants (RTEs) are the youngest T cells in the lymphoid periphery and exhibit phenotypic and functional characteristics distinct from those of their more mature counterparts in the naive peripheral T cell pool. We show in this study that the Il2 and Il4 promoter regions of naive CD4(+) RTEs are characterized by site-specific hypermethylation compared with those of both mature naive (MN) T cells and the thymocyte precursors of RTEs. Thus, RTEs do not merely occupy a midpoint between the thymus and the mature T cell pool, but represent a distinct transitional T cell population. Furthermore, RTEs and MN T cells exhibit distinct CpG DNA methylation patterns both before and after activation. Compared with MN T cells, RTEs express higher levels of several enzymes that modify DNA methylation, and inhibiting methylation during culture allows RTEs to reach MN T cell levels of cytokine production. Collectively, these data suggest that the functional differences that distinguish RTEs from MN T cells are influenced by epigenetic mechanisms and provide clues to a mechanistic basis for postthymic maturation.

Improving imbalanced scientific text classification using sampling strategies and dictionaries.

PubMed

Borrajo, L; Romero, R; Iglesias, E L; Redondo Marey, C M

2011-09-15

Many real applications have the imbalanced class distribution problem, where one of the classes is represented by a very small number of cases compared to the other classes. One of the systems affected are those related to the recovery and classification of scientific documentation. Sampling strategies such as Oversampling and Subsampling are popular in tackling the problem of class imbalance. In this work, we study their effects on three types of classifiers (Knn, SVM and Naive-Bayes) when they are applied to search on the PubMed scientific database. Another purpose of this paper is to study the use of dictionaries in the classification of biomedical texts. Experiments are conducted with three different dictionaries (BioCreative, NLPBA, and an ad-hoc subset of the UniProt database named Protein) using the mentioned classifiers and sampling strategies. Best results were obtained with NLPBA and Protein dictionaries and the SVM classifier using the Subsampling balancing technique. These results were compared with those obtained by other authors using the TREC Genomics 2005 public corpus. Copyright 2011 The Author(s). Published by Journal of Integrative Bioinformatics.

Identifying typical physical activity on smartphone with varying positions and orientations.

PubMed

Miao, Fen; He, Yi; Liu, Jinlei; Li, Ye; Ayoola, Idowu

2015-04-13

Traditional activity recognition solutions are not widely applicable due to a high cost and inconvenience to use with numerous sensors. This paper aims to automatically recognize physical activity with the help of the built-in sensors of the widespread smartphone without any limitation of firm attachment to the human body. By introducing a method to judge whether the phone is in a pocket, we investigated the data collected from six positions of seven subjects, chose five signals that are insensitive to orientation for activity classification. Decision trees (J48), Naive Bayes and Sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs. The experimental results based on 8,097 activity data demonstrated that the J48 classifier produced the best performance with an average recognition accuracy of 89.6% during the three classifiers, and thus would serve as the optimal online classifier. The utilization of the built-in sensors of the smartphone to recognize typical physical activities without any limitation of firm attachment is feasible.

Applying Data Mining Techniques to Improve Breast Cancer Diagnosis.

PubMed

Diz, Joana; Marreiros, Goreti; Freitas, Alberto

2016-09-01

In the field of breast cancer research, and more than ever, new computer aided diagnosis based systems have been developed aiming to reduce diagnostic tests false-positives. Within this work, we present a data mining based approach which might support oncologists in the process of breast cancer classification and diagnosis. The present study aims to compare two breast cancer datasets and find the best methods in predicting benign/malignant lesions, breast density classification, and even for finding identification (mass / microcalcification distinction). To carry out these tasks, two matrices of texture features extraction were implemented using Matlab, and classified using data mining algorithms, on WEKA. Results revealed good percentages of accuracy for each class: 89.3 to 64.7 % - benign/malignant; 75.8 to 78.3 % - dense/fatty tissue; 71.0 to 83.1 % - finding identification. Among the different tests classifiers, Naive Bayes was the best to identify masses texture, and Random Forests was the first or second best classifier for the majority of tested groups.

Integrating Entropy-Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard.

PubMed

Liu, Rui; Chen, Yun; Wu, Jianping; Gao, Lei; Barrett, Damian; Xu, Tingbao; Li, Xiaojuan; Li, Linyi; Huang, Chang; Yu, Jia

2017-04-01

Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies. © 2016 Society for Risk Analysis.

76 FR 38020 - Safety Zone; Bay Point Fireworks, Bay Point Marina; Marblehead, OH

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-29

...-AA00 Safety Zone; Bay Point Fireworks, Bay Point Marina; Marblehead, OH AGENCY: Coast Guard, DHS... from portions of Lake Erie for the Bay Point Fireworks. This temporary safety zone is necessary to protect spectators and vessels from the hazards associated with fireworks displays. DATES: This regulation...

78 FR 30765 - Safety Zone; Bay Village Independence Day Fireworks, Lake Erie, Bay Village, OH

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-23

...-AA00 Safety Zone; Bay Village Independence Day Fireworks, Lake Erie, Bay Village, OH AGENCY: Coast... zone on Lake Erie, Bay Village, OH. This safety zone is intended to restrict vessels from a portion of Lake Erie during the Bay Village Independence Day Fireworks display. This temporary safety zone is...

77 FR 39420 - Safety Zone; Bay Village Independence Day Fireworks, Lake Erie, Bay Village, OH

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-03

...-AA00 Safety Zone; Bay Village Independence Day Fireworks, Lake Erie, Bay Village, OH AGENCY: Coast... zone on Lake Erie, Bay Village, OH. This safety zone is intended to restrict vessels from a portion of Lake Erie during the Bay Village Independence Day Fireworks display. This temporary safety zone is...

75 FR 54771 - Safety Zone; Thunder on the Bay, Chesapeake Bay, Buckroe Beach Park, Hampton, VA

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-09

...-AA00 Safety Zone; Thunder on the Bay, Chesapeake Bay, Buckroe Beach Park, Hampton, VA AGENCY: Coast... safety zone on the navigable waters of Chesapeake Bay in Hampton, VA in support of the Thunder on the Bay.... 0 2. Add Sec. 165.T05-0755 to read as follows: Sec. 165.T05-0755 Safety Zone; Thunder on the Bay...

77 FR 44140 - Drawbridge Operation Regulation; Sturgeon Bay Ship Canal, Sturgeon Bay, WI

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-27

... Maple-Oregon Bridges so vehicular traffic congestion would not develop on downtown Sturgeon Bay streets... movement of vehicular traffic in Sturgeon Bay. The Sturgeon Bay Ship Canal is approximately 8.6 miles long... significant increase in vehicular and vessel traffic during the peak tourist and navigation season between...

75 FR 8297 - Tongass National Forest, Thorne Bay Ranger District, Thorne Bay, AK

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-24

..., Thorne Bay, AK AGENCY: Forest Service, USDA. ACTION: Cancellation of Notice of intent to prepare an... Roberts, Zone Planner, Thorne Bay Ranger District, Tongass National Forest, P.O. Box 19001, Thorne Bay, AK 99919, telephone: 907-828-3250. SUPPLEMENTARY INFORMATION: The 47,007-acre Kosciusko Project Area is...

Content-based image retrieval for interstitial lung diseases using classification confidence

NASA Astrophysics Data System (ADS)

Dash, Jatindra Kumar; Mukhopadhyay, Sudipta; Prabhakar, Nidhi; Garg, Mandeep; Khandelwal, Niranjan

2013-02-01

Content Based Image Retrieval (CBIR) system could exploit the wealth of High-Resolution Computed Tomography (HRCT) data stored in the archive by finding similar images to assist radiologists for self learning and differential diagnosis of Interstitial Lung Diseases (ILDs). HRCT findings of ILDs are classified into several categories (e.g. consolidation, emphysema, ground glass, nodular etc.) based on their texture like appearances. Therefore, analysis of ILDs is considered as a texture analysis problem. Many approaches have been proposed for CBIR of lung images using texture as primitive visual content. This paper presents a new approach to CBIR for ILDs. The proposed approach makes use of a trained neural network (NN) to find the output class label of query image. The degree of confidence of the NN classifier is analyzed using Naive Bayes classifier that dynamically takes a decision on the size of the search space to be used for retrieval. The proposed approach is compared with three simple distance based and one classifier based texture retrieval approaches. Experimental results show that the proposed technique achieved highest average percentage precision of 92.60% with lowest standard deviation of 20.82%.

DEXAMETHASONE IMPLANT FOR DIABETIC MACULAR EDEMA IN NAIVE COMPARED WITH REFRACTORY EYES: The International Retina Group Real-Life 24-Month Multicenter Study. The IRGREL-DEX Study.

PubMed

Iglicki, Matias; Busch, Catharina; Zur, Dinah; Okada, Mali; Mariussi, Miriana; Chhablani, Jay Kumar; Cebeci, Zafer; Fraser-Bell, Samantha; Chaikitmongkol, Voraporn; Couturier, Aude; Giancipoli, Ermete; Lupidi, Marco; Rodríguez-Valdés, Patricio J; Rehak, Matus; Fung, Adrian Tien-Chin; Goldstein, Michaella; Loewenstein, Anat

2018-04-24

To investigate efficacy and safety of repeated dexamethasone (DEX) implants over 24 months, in diabetic macular edema (DME) eyes that were treatment naive compared with eyes refractory to anti-vascular endothelial growth factor treatment, in a real-life environment. This multicenter international retrospective study assessed best-corrected visual acuity and central subfield thickness (CST) of naive and refractory eyes to anti-vascular endothelial growth factor injections treated with dexamethasone implants. Safety data (intraocular pressure rise and cataract surgery) were recorded. A total of 130 eyes from 125 patients were included. Baseline best-corrected visual acuity and CST were similar for naive (n = 71) and refractory eyes (n = 59). Both groups improved significantly in vision after 24 months (P < 0.001). However, naive eyes gained statistically significantly more vision than refractory eyes (+11.3 ± 10.0 vs. 7.3 ± 2.7 letters, P = 0.01) and were more likely to gain ≥10 letters (OR 3.31, 95% CI 1.19-9.24, P = 0.02). At 6, 12, and 24 months, CST was significantly decreased compared with baseline in both naive and refractory eyes; however, CST was higher in refractory eyes than in naive eyes (CST 279 ± 61 vs. 313 ± 125 μm, P = 0.10). Over a follow-up of 24 months, vision improved in diabetic macular edema eyes after treatment with dexamethasone implants, both in eyes that were treatment naive and eyes refractory to anti-vascular endothelial growth factor treatment; however, improvement was greater in naive eyes.

Physical processes in a coupled bay-estuary coastal system: Whitsand Bay and Plymouth Sound

NASA Astrophysics Data System (ADS)

Uncles, R. J.; Stephens, J. A.; Harris, C.

2015-09-01

Whitsand Bay and Plymouth Sound are located in the southwest of England. The Bay and Sound are separated by the ∼2-3 km-wide Rame Peninsula and connected by ∼10-20 m-deep English Channel waters. Results are presented from measurements of waves and currents, drogue tracking, surveys of salinity, temperature and turbidity during stratified and unstratified conditions, and bed sediment surveys. 2D and 3D hydrodynamic models are used to explore the generation of tidally- and wind-driven residual currents, flow separation and the formation of the Rame eddy, and the coupling between the Bay and the Sound. Tidal currents flow around the Rame Peninsula from the Sound to the Bay between approximately 3 h before to 2 h after low water and form a transport path between them that conveys lower salinity, higher turbidity waters from the Sound to the Bay. These waters are then transported into the Bay as part of the Bay-mouth limb of the Rame eddy and subsequently conveyed to the near-shore, east-going limb and re-circulated back towards Rame Head. The Simpson-Hunter stratification parameter indicates that much of the Sound and Bay are likely to stratify thermally during summer months. Temperature stratification in both is pronounced during summer and is largely determined by coastal, deeper-water stratification offshore. Small tidal stresses in the Bay are unable to move bed sediment of the observed sizes. However, the Bay and Sound are subjected to large waves that are capable of driving a substantial bed-load sediment transport. Measurements show relatively low levels of turbidity, but these respond rapidly to, and have a strong correlation with, wave height.

Circulation in a bay influenced by flooding of a river discharging outside the bay

NASA Astrophysics Data System (ADS)

Kakehi, Shigeho; Takagi, Takamasa; Okabe, Katsuaki; Takayanagi, Kazufumi

2017-03-01

To investigate the influence of a river discharging outside a bay on circulation in the bay, we carried out current and salinity measurements from mooring systems and hydrographic observations in Matsushima Bay, Japan, and off the Naruse River, which discharges outside the bay. Previously, enhancement of horizontal circulation in the bay induced by increased freshwater input from the Naruse River was reported to have degraded the seedling yield of wild Pacific oysters in the bay, but the freshwater inflow from the river was not directly measured. Our hydrographic observations in Katsugigaura Strait, approximately 3 km southwest of the Naruse River mouth, detected freshwater derived from the river. The mooring data revealed that freshwater discharged by the river flowed into Matsushima Bay via the strait and that the freshwater transport increased when the river was in flood. The inflow through straits other than Katsugigaura was estimated by a box model analysis to be 26-145 m3 s-1 under normal river discharge conditions, and it decreased to 6 m3 s-1 during flood conditions. During flood events, the salt and water budgets in the bay were maintained by the horizontal circulation: inflow occurred mainly via Katsugigaura Strait, and outflow was mainly via other straits.

Nicotinic Acid Adenine Dinucleotide Phosphate Plays a Critical Role in Naive and Effector Murine T Cells but Not Natural Regulatory T Cells*

PubMed Central

Ali, Ramadan A.; Camick, Christina; Wiles, Katherine; Walseth, Timothy F.; Slama, James T.; Bhattacharya, Sumit; Giovannucci, David R.; Wall, Katherine A.

2016-01-01

Nicotinic acid adenine dinucleotide phosphate (NAADP), the most potent Ca2+ mobilizing second messenger discovered to date, has been implicated in Ca2+ signaling in some lymphomas and T cell clones. In contrast, the role of NAADP in Ca2+ signaling or the identity of the Ca2+ stores targeted by NAADP in conventional naive T cells is less clear. In the current study, we demonstrate the importance of NAADP in the generation of Ca2+ signals in murine naive T cells. Combining live-cell imaging methods and a pharmacological approach using the NAADP antagonist Ned-19, we addressed the involvement of NAADP in the generation of Ca2+ signals evoked by TCR stimulation and the role of this signal in downstream physiological end points such as proliferation, cytokine production, and other responses to stimulation. We demonstrated that acidic compartments in addition to the endoplasmic reticulum were the Ca2+ stores that were sensitive to NAADP in naive T cells. NAADP was shown to evoke functionally relevant Ca2+ signals in both naive CD4 and naive CD8 T cells. Furthermore, we examined the role of this signal in the activation, proliferation, and secretion of effector cytokines by Th1, Th2, Th17, and CD8 effector T cells. Overall, NAADP exhibited a similar profile in mediating Ca2+ release in effector T cells as in their counterpart naive T cells and seemed to be equally important for the function of these different subsets of effector T cells. This profile was not observed for natural T regulatory cells. PMID:26728458

Classifying environmentally significant urban land uses with satellite imagery.

PubMed

Park, Mi-Hyun; Stenstrom, Michael K

2008-01-01

We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.

Tidal and residual circulation in a semi-arid bay: Coquimbo Bay, Chile

NASA Astrophysics Data System (ADS)

Valle-Levinson, Arnoldo; Moraga, Julio; Olivares, Jorge; Blanco, José Luis

2000-11-01

Velocity profiles and time-series data were combined with conductivity-temperature-depth (CTD) casts to describe the general circulation at tidal and subtidal scales in a bay of semi-arid climate, Coquimbo Bay (˜30°S), Chile. This was the first study that used a towed acoustic Doppler current profiler (ADCP) in coastal Chilean waters and is one of the very few in semi-arid bays. The ADCP was towed for two semi-diurnal tidal cycles in early austral autumn, between March 23 and 24, 1997 along a triangular trajectory that covered most of the bay. Additional data consisted of moored current meters and CTD casts. The observations indicated the presence of a surface layer, above the pycnocline, that showed predominantly diurnal variability forced by the breeze regime and by tides. The tidal circulation in the surface layer featured amplitudes of 10 cm/s within an anticyclonic gyre that occupied most of the bay. The subtidal circulation in the surface was characterized by a pair of counter-rotating gyres. The northernmost three-fourths of the bay showed an anticyclonic gyre, and the observations over the southern fourth implied a cyclonic gyre. The subtidal anticyclonic gyre had a counterpart rotating in opposite direction within a lower layer, underneath the pycnocline. The lower layer showed semidiurnal variability in addition to diurnal variability and was insulated by the pycnocline from heat and momentum fluxes through the air-water interface. Circulations that resemble estuarine and anti-estuarine patterns were found associated with the subtidal gyres. A horizontal divergence related to a 10 cm/s near-surface outflow around Point Tortuga, to the south of the bay entrance, allowed the development of upward motion off the Point, as evidenced by the tilt of the isopycnals at the entrance to the bay.

Health Problems Discovery from Motion-Capture Data of Elderly

NASA Astrophysics Data System (ADS)

Pogorelc, B.; Gams, M.

Rapid aging of the population of the developed countries could exceed the society's capacity for taking care for them. In order to help solving this problem, we propose a system for automatic discovery of health problems from motion-capture data of gait of elderly. The gait of the user is captured with the motion capture system, which consists of tags attached to the body and sensors situated in the apartment. Position of the tags is acquired by the sensors and the resulting time series of position coordinates are analyzed with machine learning algorithms in order to identify the specific health problem. We propose novel features for training a machine learning classifier that classifies the user's gait into: i) normal, ii) with hemiplegia, iii) with Parkinson's disease, iv) with pain in the back and v) with pain in the leg. Results show that naive Bayes needs more tags and less noise to reach classification accuracy of 98 % than support vector machines for 99 %.

Classification of older adults with/without a fall history using machine learning methods.

PubMed

Lin Zhang; Ou Ma; Fabre, Jennifer M; Wood, Robert H; Garcia, Stephanie U; Ivey, Kayla M; McCann, Evan D

2015-01-01

Falling is a serious problem in an aged society such that assessment of the risk of falls for individuals is imperative for the research and practice of falls prevention. This paper introduces an application of several machine learning methods for training a classifier which is capable of classifying individual older adults into a high risk group and a low risk group (distinguished by whether or not the members of the group have a recent history of falls). Using a 3D motion capture system, significant gait features related to falls risk are extracted. By training these features, classification hypotheses are obtained based on machine learning techniques (K Nearest-neighbour, Naive Bayes, Logistic Regression, Neural Network, and Support Vector Machine). Training and test accuracies with sensitivity and specificity of each of these techniques are assessed. The feature adjustment and tuning of the machine learning algorithms are discussed. The outcome of the study will benefit the prediction and prevention of falls.

Simultaneous learning and filtering without delusions: a Bayes-optimal combination of Predictive Inference and Adaptive Filtering.

PubMed

Kneissler, Jan; Drugowitsch, Jan; Friston, Karl; Butz, Martin V

2015-01-01

Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF). PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than 10-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

Homeostasis of naive and memory CD4+ T cells: IL-2 and IL-7 differentially regulate the balance between proliferation and Fas-mediated apoptosis.

PubMed

Jaleco, Sara; Swainson, Louise; Dardalhon, Valérie; Burjanadze, Maryam; Kinet, Sandrina; Taylor, Naomi

2003-07-01

Cytokines play a crucial role in the maintenance of polyclonal naive and memory T cell populations. It has previously been shown that ex vivo, the IL-7 cytokine induces the proliferation of naive recent thymic emigrants (RTE) isolated from umbilical cord blood but not mature adult-derived naive and memory human CD4(+) T cells. We find that the combination of IL-2 and IL-7 strongly promotes the proliferation of RTE, whereas adult CD4(+) T cells remain relatively unresponsive. Immunological activity is controlled by a balance between proliferation and apoptotic cell death. However, the relative contributions of IL-2 and IL-7 in regulating these processes in the absence of MHC/peptide signals are not known. Following exposure to either IL-2 or IL-7 alone, RTE, as well as mature naive and memory CD4(+) T cells, are rendered only minimally sensitive to Fas-mediated cell death. However, in the presence of the two cytokines, Fas engagement results in a high level of caspase-dependent apoptosis in both RTE as well as naive adult CD4(+) T cells. In contrast, equivalently treated memory CD4(+) T cells are significantly less sensitive to Fas-induced cell death. The increased susceptibility of RTE and naive CD4(+) T cells to Fas-induced apoptosis correlates with a significantly higher IL-2/IL-7-induced Fas expression on these T cell subsets than on memory CD4(+) T cells. Thus, IL-2 and IL-7 regulate homeostasis by modulating the equilibrium between proliferation and apoptotic cell death in RTE and mature naive and memory T cell subsets.

Chesapeake Bay TMDL

EPA Pesticide Factsheets

In 2010 EPA established the Chesapeake Bay TMDL, a comprehensive pollution diet with accountability measures to restore clean water in the bay and local waters. It set limits for nutrients and sediment to meet water quality standards across the watershed

77 FR 38488 - Safety Zone; Alexandria Bay Chamber of Commerce, St. Lawrence River, Alexandria Bay, NY

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-28

... 1625-AA00 Safety Zone; Alexandria Bay Chamber of Commerce, St. Lawrence River, Alexandria Bay, NY... temporary safety zone on the St. Lawrence River, Alexandria Bay, New York. This safety zone is intended to restrict vessels from a portion of the St. Lawrence River during the Alexandria Bay Chamber of Commerce...

Impairment of DNA Methylation Maintenance Is the Main Cause of Global Demethylation in Naive Embryonic Stem Cells.

PubMed

von Meyenn, Ferdinand; Iurlaro, Mario; Habibi, Ehsan; Liu, Ning Qing; Salehzadeh-Yazdi, Ali; Santos, Fátima; Petrini, Edoardo; Milagre, Inês; Yu, Miao; Xie, Zhenqing; Kroeze, Leonie I; Nesterova, Tatyana B; Jansen, Joop H; Xie, Hehuang; He, Chuan; Reik, Wolf; Stunnenberg, Hendrik G

2016-06-16

Global demethylation is part of a conserved program of epigenetic reprogramming to naive pluripotency. The transition from primed hypermethylated embryonic stem cells (ESCs) to naive hypomethylated ones (serum-to-2i) is a valuable model system for epigenetic reprogramming. We present a mathematical model, which accurately predicts global DNA demethylation kinetics. Experimentally, we show that the main drivers of global demethylation are neither active mechanisms (Aicda, Tdg, and Tet1-3) nor the reduction of de novo methylation. UHRF1 protein, the essential targeting factor for DNMT1, is reduced upon transition to 2i, and so is recruitment of the maintenance methylation machinery to replication foci. Concurrently, there is global loss of H3K9me2, which is needed for chromatin binding of UHRF1. These mechanisms synergistically enforce global DNA hypomethylation in a replication-coupled fashion. Our observations establish the molecular mechanism for global demethylation in naive ESCs, which has key parallels with those operating in primordial germ cells and early embryos. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

33 CFR 334.762 - Naval Support Activity Panama City; North Bay and West Bay; restricted areas.

Code of Federal Regulations, 2011 CFR

2011-07-01

... City; North Bay and West Bay; restricted areas. 334.762 Section 334.762 Navigation and Navigable Waters... REGULATIONS § 334.762 Naval Support Activity Panama City; North Bay and West Bay; restricted areas. (a) The..., Naval Support Activity, Panama City Florida, and such agencies as he/she may designate. [73 FR 52927...

33 CFR 334.762 - Naval Support Activity Panama City; North Bay and West Bay; restricted areas.

Code of Federal Regulations, 2010 CFR

2010-07-01

... City; North Bay and West Bay; restricted areas. 334.762 Section 334.762 Navigation and Navigable Waters... REGULATIONS § 334.762 Naval Support Activity Panama City; North Bay and West Bay; restricted areas. (a) The..., Naval Support Activity, Panama City Florida, and such agencies as he/she may designate. [73 FR 52927...

Nicotinic Acid Adenine Dinucleotide Phosphate Plays a Critical Role in Naive and Effector Murine T Cells but Not Natural Regulatory T Cells.

PubMed

Ali, Ramadan A; Camick, Christina; Wiles, Katherine; Walseth, Timothy F; Slama, James T; Bhattacharya, Sumit; Giovannucci, David R; Wall, Katherine A

2016-02-26

Nicotinic acid adenine dinucleotide phosphate (NAADP), the most potent Ca(2+) mobilizing second messenger discovered to date, has been implicated in Ca(2+) signaling in some lymphomas and T cell clones. In contrast, the role of NAADP in Ca(2+) signaling or the identity of the Ca(2+) stores targeted by NAADP in conventional naive T cells is less clear. In the current study, we demonstrate the importance of NAADP in the generation of Ca(2+) signals in murine naive T cells. Combining live-cell imaging methods and a pharmacological approach using the NAADP antagonist Ned-19, we addressed the involvement of NAADP in the generation of Ca(2+) signals evoked by TCR stimulation and the role of this signal in downstream physiological end points such as proliferation, cytokine production, and other responses to stimulation. We demonstrated that acidic compartments in addition to the endoplasmic reticulum were the Ca(2+) stores that were sensitive to NAADP in naive T cells. NAADP was shown to evoke functionally relevant Ca(2+) signals in both naive CD4 and naive CD8 T cells. Furthermore, we examined the role of this signal in the activation, proliferation, and secretion of effector cytokines by Th1, Th2, Th17, and CD8 effector T cells. Overall, NAADP exhibited a similar profile in mediating Ca(2+) release in effector T cells as in their counterpart naive T cells and seemed to be equally important for the function of these different subsets of effector T cells. This profile was not observed for natural T regulatory cells. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Interleukin-7 induces HIV replication in primary naive T cells through a nuclear factor of activated T cell (NFAT)-dependent pathway

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

Managlia, Elizabeth Z.; Landay, Alan; Al-Harthi, Lena

2006-07-05

Interleukin (IL)-7 plays several roles critical to T cell maturation, survival, and homeostasis. Because of these functions, IL-7 is under investigation as an immune-modulator for therapeutic use in lymphopenic clinical conditions, including HIV. We reported that naive T cells, typically not permissive to HIV, can be productively infected when pre-treated with IL-7. We evaluated the mechanism by which IL-7-mediates this effect. IL-7 potently up-regulated the transcriptional factor NFAT, but had no effect on NF{kappa}B. Blocking NFAT activity using a number of reagents, such as Cyclosporin A, FK-506, or the NFAT-specific inhibitor known as VIVIT peptide, all markedly reduced IL-7-mediated inductionmore » of HIV replication in naive T cells. Additional neutralization of cytokines present in IL-7-treated cultures and/or those that have NFAT-binding sequences within their promotors indicated that IL-10, IL-4, and most significantly IFN{gamma}, all contribute to IL-7-induction of HIV productive replication in naive T cells. These data clarify the mechanism by which IL-7 can overcome the block to HIV productive infection in naive T cells, despite their quiescent cell status. These findings are relevant to the treatment of HIV disease and understanding HIV pathogenesis in the naive CD4+ T cell compartment, especially in light of the vigorous pursuit of IL-7 as an in vivo immune modulator.« less

33 CFR 110.224 - San Francisco Bay, San Pablo Bay, Carquinez Strait, Suisun Bay, Sacramento River, San Joaquin...

Code of Federal Regulations, 2014 CFR

2014-07-01

... Bay, Sacramento River, San Joaquin River, and connecting waters, CA. (a) General regulations. (1..., Carquinez Strait, Suisun Bay, Sacramento River, San Joaquin River, and connecting waters, CA. 110.224... notified to move by the Captain of the Port. (4) No vessel may anchor within a tunnel, cable, or pipeline...

33 CFR 110.224 - San Francisco Bay, San Pablo Bay, Carquinez Strait, Suisun Bay, Sacramento River, San Joaquin...

Code of Federal Regulations, 2013 CFR

2013-07-01

... Bay, Sacramento River, San Joaquin River, and connecting waters, CA. (a) General regulations. (1..., Carquinez Strait, Suisun Bay, Sacramento River, San Joaquin River, and connecting waters, CA. 110.224... notified to move by the Captain of the Port. (4) No vessel may anchor within a tunnel, cable, or pipeline...

33 CFR 110.224 - San Francisco Bay, San Pablo Bay, Carquinez Strait, Suisun Bay, Sacramento River, San Joaquin...

Code of Federal Regulations, 2012 CFR

2012-07-01

... Bay, Sacramento River, San Joaquin River, and connecting waters, CA. (a) General regulations. (1..., Carquinez Strait, Suisun Bay, Sacramento River, San Joaquin River, and connecting waters, CA. 110.224... notified to move by the Captain of the Port. (4) No vessel may anchor within a tunnel, cable, or pipeline...

Bay-Ocean Coupling and the Proximal Fate of Water-Borne Material Exported from San Francisco Bay

NASA Astrophysics Data System (ADS)

Largier, J. L.

2012-12-01

The coupling between San Francisco Bay and the ocean is poorly known: how ocean waters intrude into bay and how bay waters flow out into the ocean. Here we address the outflow from the Bay with a view to describing the proximal fate of water-borne material in the coastal ocean, specifically finer particles and dissolved material. Flow trajectories longer than that in the tidal jet are thus the focus of this study - time scales of hours to days. We present data collected in both winter/runoff and spring/upwelling seasons that reflect the importance of tides and also the importance of wind, which introduces either northward or southward along-coast flow. Southward flow is offshore and typically this Bay effluent is removed from nearshore waters. In contrast, northward flow tends to remain attached to shore, and there is persistent presence of Bay waters in the surface layer up to Point Reyes, only occasionally separated from the coast by local upwelling within Drakes Bay. Perhaps most dramatic is outflow during winter storms, when wind is southerly and pushes water on shore in Drakes Bay as well as inducing an intense flow around Point Reyes, which turns cyclonically to reconnect with the shore in the vicinity of Bodega Bay before forming a wind-accelerated coast-attached current that looks very much like a coastal buoyancy current. This is the time when large volumes of low-salinity and high-load waters are exported from the Bay.

Clinical and Mucosal Immune Correlates of HIV-1 Semen Levels in Antiretroviral-Naive Men

PubMed Central

Marsh, Angie K.; Huibner, Sanja; Shahabi, Kamnoosh; Liu, Cindy; Contente, Tania; Nagelkerke, Nico J. D.; Kovacs, Colin; Benko, Erika; Price, Lance; MacDonald, Kelly S.; Kaul, Rupert

2017-01-01

Abstract Background. This study was done to characterize parameters associated with semen human immunodeficiency virus (HIV)-1 ribonucleic acid (RNA) viral load (VL) variability in HIV-infected, therapy-naive men. Methods. Paired blood and semen samples were collected from 30 HIV-infected, therapy-naive men who have sex with men, and 13 participants were observed longitudinally for up to 1 year. Human immunodeficiency virus RNA, bacterial load by 16S RNA, herpesvirus (Epstein-Barr virus and cytomegalovirus [CMV]) shedding, and semen cytokines/chemokines were quantified, and semen T-cell subsets were assessed by multiparameter flow cytometry. Results. Semen HIV RNA was detected at 93% of visits, with >50% of men shedding high levels of virus (defined as >5000 copies/mL). In the baseline cross-sectional analysis, an increased semen HIV VL correlated with local CMV reactivation, the semen bacterial load, and semen inflammatory cytokines, particularly interleukin (IL)-8. T cells in semen were more activated than blood, and there was an increased frequency of Th17 cells and γδ-T-cells. Subsequent prospective analysis demonstrated striking interindividual variability in HIV and CMV shedding patterns, and only semen IL-8 levels and the blood VL were independently associated with semen HIV levels. Conclusions. Several clinical and immune parameters were associated with increased HIV semen levels in antiretroviral therapy-naive men, with induction of local proinflammatory cytokines potentially acting as a common pathway. PMID:28534034

Gradient Analysis and Classification of Carolina Bay Vegetation: A Framework for Bay Wetlands Conservation and Restoration

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

Diane De Steven,Ph.D.; Maureen Tone,PhD.

1997-10-01

This report address four project objectives: (1) Gradient model of Carolina bay vegetation on the SRS--The authors use ordination analyses to identify environmental and landscape factors that are correlated with vegetation composition. Significant factors can provide a framework for site-based conservation of existing diversity, and they may also be useful site predictors for potential vegetation in bay restorations. (2) Regional analysis of Carolina bay vegetation diversity--They expand the ordination analyses to assess the degree to which SRS bays encompass the range of vegetation diversity found in the regional landscape of South Carolina's western Upper Coastal Plain. Such comparisons can indicatemore » floristic status relative to regional potentials and identify missing species or community elements that might be re-introduced or restored. (3) Classification of vegetation communities in Upper Coastal Plain bays--They use cluster analysis to identify plant community-types at the regional scale, and explore how this classification may be functional with respect to significant environmental and landscape factors. An environmentally-based classification at the whole-bay level can provide a system of templates for managing bays as individual units and for restoring bays to desired plant communities. (4) Qualitative model for bay vegetation dynamics--They analyze present-day vegetation in relation to historic land uses and disturbances. The distinctive history of SRS bays provides the possibility of assessing pathways of post-disturbance succession. They attempt to develop a coarse-scale model of vegetation shifts in response to changing site factors; such qualitative models can provide a basis for suggesting management interventions that may be needed to maintain desired vegetation in protected or restored bays.« less

Training set optimization and classifier performance in a top-down diabetic retinopathy screening system

NASA Astrophysics Data System (ADS)

Wigdahl, J.; Agurto, C.; Murray, V.; Barriga, S.; Soliz, P.

2013-03-01

Diabetic retinopathy (DR) affects more than 4.4 million Americans age 40 and over. Automatic screening for DR has shown to be an efficient and cost-effective way to lower the burden on the healthcare system, by triaging diabetic patients and ensuring timely care for those presenting with DR. Several supervised algorithms have been developed to detect pathologies related to DR, but little work has been done in determining the size of the training set that optimizes an algorithm's performance. In this paper we analyze the effect of the training sample size on the performance of a top-down DR screening algorithm for different types of statistical classifiers. Results are based on partial least squares (PLS), support vector machines (SVM), k-nearest neighbor (kNN), and Naïve Bayes classifiers. Our dataset consisted of digital retinal images collected from a total of 745 cases (595 controls, 150 with DR). We varied the number of normal controls in the training set, while keeping the number of DR samples constant, and repeated the procedure 10 times using randomized training sets to avoid bias. Results show increasing performance in terms of area under the ROC curve (AUC) when the number of DR subjects in the training set increased, with similar trends for each of the classifiers. Of these, PLS and k-NN had the highest average AUC. Lower standard deviation and a flattening of the AUC curve gives evidence that there is a limit to the learning ability of the classifiers and an optimal number of cases to train on.

Brentuximab vedotin (SGN-35) in patients with transplant-naive relapsed/refractory Hodgkin lymphoma.

PubMed

Sasse, Stephanie; Rothe, Achim; Goergen, Helen; Eichenauer, Dennis A; Lohri, Andreas; Kreher, Stephan; Jäger, Ulrich; Bangard, Christopher; Kuhnert, Georg; Böll, Boris; von Tresckow, Bastian; Engert, Andreas

2013-10-01

Only limited data are available on the role of brentuximab vedotin (SGN-35) in transplant-naive relapsed or refractory patients with Hodgkin lymphoma (HL). We thus retrospectively analyzed 14 patients with primary refractory or relapsed HL who were treated with brentuximab vedotin as single agent in a named patient program, who had not received prior high-dose chemotherapy (HDCT) and autologous stem cell transplant (ASCT) due to refractory disease (n = 9), comorbidity (n = 4) and unknown reasons (n = 1). Brentuximab vedotin resulted in an overall response rate of 71% (10/14) with five complete responses (CRs). Five of those patients with refractory disease and four patients with relevant comorbidity responded. Consolidating ASCT (n = 4) or allogeneic SCT (n = 1) was performed in five patients. Median progression-free survival (PFS) was 9 months and the median overall survival (OS) was not reached. These data indicate the therapeutic efficacy of brentuximab vedotin in chemotherapy-refractory transplant-naive patients with HL.

77 FR 50921 - Safety Zone: Bay Bridge Load Transfer Safety Zone, San Francisco Bay, San Francisco, CA

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-23

...-AA00 Safety Zone: Bay Bridge Load Transfer Safety Zone, San Francisco Bay, San Francisco, CA AGENCY... the Bay Bridge Load Transfer Safety Zone from August 1, 2012 through October 31, 2012. This safety... Bay Bridge from the temporary suspension arrangement to the permanent suspension arrangement, the...

Seasonal sedimentary processes of the macrotidal flat in Gomso Bay, west coast of Korea

NASA Astrophysics Data System (ADS)

Woo, H.; Kang, J.; Choi, J.

2012-12-01

The tidal flats on the west coast of Korea have broad zones with gentle slopes and a macrotidal setting with 4 to 10 meters of tidal ranges. They are directly influenced by monsoons and heavily affected by waves in winter and tidal currents in summer. As a result, most western tidal flats show the seasonal changes of sedimentary features comprising sedimentation and/or erosion of sediments. Gomso bay in the mid-west of Korea is a funnel-shaped embayment with a wide entrance to the west. Tides are semidiurnal and macrotidal, with a mean tidal range of 433.8 cm. Digital elevation model (DEM) showed that the landward inner bay had mainly high elevations and the seaward outer bay had relatively low elevations. In particular, there are considerable gradients in the outer bay from area of high-water line to area of low-water line. The sedimentary analysis and monitoring short-term sedimentation rates were investigated to understand seasonal sedimentary processes of tidal flats in Gomso bay. The surface sediments in the bay were classified into five sedimentary facies in spring 2011. Generally, sandy sediments were dominated in the outer bay, whereas sandy mud sediments were distributed on the inner bay. The middle bay mainly consisted of muddy sand sediments. The percentages of sand decreased from outer to inner bay. The short-term sedimentation rates were obtained from three lines by burying a plate at sub-bottom depth and periodically measuring the changing sediment depth from February 2011 to February 2012. In the tidal flat at inner bay (KB- Line), the annual sedimentation rates were ranged -8.87 to 74.69 mm/year with the net deposition rate of 40.90 mm/year. The deposition occurred on KB-Line in spring, autumn and winter. The erosion was dominated on the tidal flats at middle (KH-Line) and outer bay (KM-Line) during autumn and winter with an annual erosion rate of -29.86 mm/year and -9.92 mm/year, respectively. The seasonal variations of sedimentation on these tidal

Seismic expression of the Chesapeake Bay impact crater: Structural and morphologic refinements based on new seismic data

USGS Publications Warehouse

Poag, C. Wylie; Hutchinson, Deborah R.; Colman, Steve M.; Lee, Myung W.; Dressler, B.O.; Sharpton, V.L.

1999-01-01

This work refines previous interpretations of the structure and morphology of the Chesapeake Bay impact crater on the basis of more than 1,200 km of multichannel and single-channel seismic reflection profiles collected in the bay and on the adjacent continental shelf. The outer rim, formed in sedimentary rocks, is irregularly circular, with an average diameter of ~85 km. A 20–25-km-wide annular trough separates the outer rim from an ovate, crystalline peak ring of ~200 m of maximum relief. The inner basin is 35–40 km in diameter, and at least 1.26 km deep. A crystalline(?) central peak, approximately 1 km high, is faintly imaged on three profiles, and also is indicated by a small positive Bouguer gravity anomaly. These features classify the crater as a complex peak-ring/central peak crater. Chesapeake Bay Crater is most comparable to the Ries and Popigai Craters on Earth; to protobasins on Mars, Mercury, and the Moon; and to type D craters on Venus.

33 CFR 167.101 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 2 2011-07-01 2011-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas. 167.101 Section 167.101 Navigation and Navigable... the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas. (a) A precautionary...

33 CFR 167.101 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 2 2013-07-01 2013-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas. 167.101 Section 167.101 Navigation and Navigable... the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas. (a) A precautionary...

33 CFR 167.101 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 2 2014-07-01 2014-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas. 167.101 Section 167.101 Navigation and Navigable... the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas. (a) A precautionary...

33 CFR 167.101 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 2 2012-07-01 2012-07-01 false In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas. 167.101 Section 167.101 Navigation and Navigable... the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: Precautionary areas. (a) A precautionary...

Genetic characterization and antiretroviral resistance mutations among treatment-naive HIV-infected individuals in Jiaxing, China.

PubMed

Guo, Jinlei; Yan, Yong; Zhang, Jiafeng; Ji, Jimei; Ge, Zhijian; Ge, Rui; Zhang, Xiaofei; Wang, Henghui; Chen, Zhongwen; Luo, Jianyong

2017-03-14

The aim of this study was to characterize HIV-1 genotypes and antiretroviral resistance mutations among treatment-naive HIV-infected individuals in Jiaxing, China. The HIV-1 partial polymerase (pol) genes in 93 of the 99 plasma samples were successfully amplified and analyzed. Phylogenetic analysis revealed the existence of five HIV-1 genotypes, of which the most prevalent genotype was CRF01_AE (38.7%), followed by CRF07_BC (34.4%), CRF08_BC (16.1%), subtype B/B' (5.4%), and CRF55_01B (2.1%). Besides, three types of unique recombination forms (URFs) were also observed, including C/F2/A1, CRF01_AE/B, and CRF08_BC/CRF07_BC. Among 93 amplicons, 46.2% had drug resistance-associated mutations, including 23.7% for protease inhibitors (PIs) mutations, 1.1% for nucleoside reverse transcriptase inhibitors (NRTIs) mutations, and 20.4% for non-nucleoside reverse transcriptase inhibitors (NNRTIs) mutations. Six (6.5%) out of 93 treatment-naive subjects were identified to be resistant to one or more NNRTIs, while resistance to NRTIs or PIs was not observed. Our study showed the genetic diversity of HIV-1 strains circulating in Jiaxing and a relative high proportion of antiretroviral resistance mutations among treatment-naive patients, indicating a serious challenge for HIV prevention and treatment program.

A Combined Omics Approach to Generate the Surface Atlas of Human Naive CD4+ T Cells during Early T-Cell Receptor Activation*

PubMed Central

Graessel, Anke; Hauck, Stefanie M.; von Toerne, Christine; Kloppmann, Edda; Goldberg, Tatyana; Koppensteiner, Herwig; Schindler, Michael; Knapp, Bettina; Krause, Linda; Dietz, Katharina; Schmidt-Weber, Carsten B.; Suttner, Kathrin

2015-01-01

Naive CD4+ T cells are the common precursors of multiple effector and memory T-cell subsets and possess a high plasticity in terms of differentiation potential. This stem-cell-like character is important for cell therapies aiming at regeneration of specific immunity. Cell surface proteins are crucial for recognition and response to signals mediated by other cells or environmental changes. Knowledge of cell surface proteins of human naive CD4+ T cells and their changes during the early phase of T-cell activation is urgently needed for a guided differentiation of naive T cells and may support the selection of pluripotent cells for cell therapy. Periodate oxidation and aniline-catalyzed oxime ligation technology was applied with subsequent quantitative liquid chromatography-tandem MS to generate a data set describing the surface proteome of primary human naive CD4+ T cells and to monitor dynamic changes during the early phase of activation. This led to the identification of 173 N-glycosylated surface proteins. To independently confirm the proteomic data set and to analyze the cell surface by an alternative technique a systematic phenotypic expression analysis of surface antigens via flow cytometry was performed. This screening expanded the previous data set, resulting in 229 surface proteins, which were expressed on naive unstimulated and activated CD4+ T cells. Furthermore, we generated a surface expression atlas based on transcriptome data, experimental annotation, and predicted subcellular localization, and correlated the proteomics result with this transcriptional data set. This extensive surface atlas provides an overall naive CD4+ T cell surface resource and will enable future studies aiming at a deeper understanding of mechanisms of T-cell biology allowing the identification of novel immune targets usable for the development of therapeutic treatments. PMID:25991687

Discharge, water-quality characteristics, and nutrient loads from McKay Bay, Delaney Creek, and East Bay, Tampa, Florida, 1991-1993

USGS Publications Warehouse

Stoker, Y.E.; Levesque, V.A.; Fritz, E.M.

1996-01-01

Nutrient enrichment in Tampa Bay has caused a decline in water quality in the estuary. Efforts to reduce the nutrient loading to Tampa Bay have resulted in improvement in water quality from 1981 to 1991. However, Tampa Bay still is onsidered enriched with nutrients. Water quality in East Bay (located at the northeastern part of Hillsborough Bay, which is an embayment in Tampa Bay) is not improving at the same rate as the rest of the bay. East Bay is the center of shipping activity in Tampa Bay and the seventh largest port in the United States. One of the primary cargoes is phosphate ore and related products such as fertilizer. The potential for nutrient loading to East Bay from shipping activities is high and has not previously been measured. Nitrogen and phosphorus loads from East Bay to Hillsborough Bay were measured during selected time periods during June 1992 through May 1993; these data were used to estimate seasonal and annual loads. These loads were evaluated to determine whether the loss of fertilizer products from shipping activities resulted in increased nutrient loading to Hillsborough Bay. Discharge was measured, and water-quality samples were collected at the head of East Bay (exiting McKay Bay), and at the mouth of East Bay. Discharge and nitrogen and phosphorus concentrations for the period June 1992 through May 1993 were used to compute loads. Discharges from McKay Bay, Delaney Creek, and East Bay are highly variable because of the effect of tide. Flow patterns during discharge measurements generally were unidirectional in McKay Bay and Delaney Creek, but more complex, bidirectional patterns were observed at the mouth of East Bay. Tidally affected discharge data were digitally filtered with the Godin filter to remove the effects of tide so that residual, or net, discharge could be determined. Daily mean discharge from McKay Bay ranged from -1,900 to 2,420 cubic feet per second; from Delaney Creek, -3.8 to 162 cubic feet per second; and from East

46 CFR 7.20 - Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and...

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 1 2013-10-01 2013-10-01 false Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and easterly entrance to Long Island Sound, NY. 7.20 Section 7.20... Atlantic Coast § 7.20 Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island...

46 CFR 7.20 - Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and...

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 1 2011-10-01 2011-10-01 false Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and easterly entrance to Long Island Sound, NY. 7.20 Section 7.20... Atlantic Coast § 7.20 Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island...

46 CFR 7.20 - Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and...

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 1 2014-10-01 2014-10-01 false Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and easterly entrance to Long Island Sound, NY. 7.20 Section 7.20... Atlantic Coast § 7.20 Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island...

46 CFR 7.20 - Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and...

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 1 2012-10-01 2012-10-01 false Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and easterly entrance to Long Island Sound, NY. 7.20 Section 7.20... Atlantic Coast § 7.20 Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island...

46 CFR 7.20 - Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and...

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island Sound and easterly entrance to Long Island Sound, NY. 7.20 Section 7.20... Atlantic Coast § 7.20 Nantucket Sound, Vineyard Sound, Buzzards Bay, Narragansett Bay, MA, Block Island...

CASCO BAY PLAN

EPA Science Inventory

Casco Bay lies at the heart of Maine's most populated area. The health of its waters, wetlands, and wildlife depend in large part on the activities of the quarter-million residents who live in its watershed. Less than 30 years ago, portions of Casco Bay were off-limits to recr...

78 FR 62293 - Safety Zone, Oyster Festival 30th Anniversary Fireworks Display, Oyster Bay; Oyster Bay, NY

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-15

... Safety Zone, Oyster Festival 30th Anniversary Fireworks Display, Oyster Bay; Oyster Bay, NY AGENCY: Coast... zone on the navigable waters of Oyster Bay near Oyster Bay, NY for the Oyster Festival 30th Anniversary... Oyster Festival 30th Anniversary Fireworks Display is scheduled for October 19, 2013 and is one of...

Chesapeake Bay: Introduction to an Ecosystem.

ERIC Educational Resources Information Center

Environmental Protection Agency, Washington, DC.

The Chesapeake Bay is the largest estuary in the contiguous United States. The Bay and its tidal tributaries make up the Chesapeake Bay ecosystem. This document, which focuses of various aspects of this ecosystem, is divided into four major parts. The first part traces the geologic history of the Bay, describes the overall physical structure of…

75 FR 16005 - Drawbridge Operation Regulation; Port of Coos Bay Railroad Bridge, Coos Bay, North Bend, OR

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-31

...-AA09 Drawbridge Operation Regulation; Port of Coos Bay Railroad Bridge, Coos Bay, North Bend, OR AGENCY... regulation for the Coos Bay Railroad Bridge, Coos Bay, mile 9.0, at North Bend, Oregon to delete the... necessary to make the sound signals used at the bridge consistent with other bridges in the area and to...

Minimum Bayes risk image correlation

NASA Technical Reports Server (NTRS)

Minter, T. C., Jr.

1980-01-01

In this paper, the problem of designing a matched filter for image correlation will be treated as a statistical pattern recognition problem. It is shown that, by minimizing a suitable criterion, a matched filter can be estimated which approximates the optimum Bayes discriminant function in a least-squares sense. It is well known that the use of the Bayes discriminant function in target classification minimizes the Bayes risk, which in turn directly minimizes the probability of a false fix. A fast Fourier implementation of the minimum Bayes risk correlation procedure is described.

Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis.

PubMed

Kim, Eunwoo; Park, HyunWook

2017-02-01

The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.

Bay BC's: A Multidisciplinary Approach To Teaching about the Chesapeake Bay.

ERIC Educational Resources Information Center

Slattery, Britt Eckhardt

The Chesapeake Bay is the largest estuary in North America, providing food and habitat for an abundance of fish and wildlife. This booklet provides lesson plans for lower elementary students introducing the Chesapeake, its inhabitants, and pollution problems, and suggesting ways that individuals can contribute to the Bay's restoration. Background…

75 FR 17329 - Safety Zone; Big Bay Fourth of July Fireworks, San Diego Bay, San Diego, CA

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-06

...-AA00 Safety Zone; Big Bay Fourth of July Fireworks, San Diego Bay, San Diego, CA AGENCY: Coast Guard... safety zone on the navigable waters of the San Diego Bay in support of the Big Bay July Fourth Show to Benefit the San Diego Armed Services YMCA. This temporary safety zone is necessary to provide for the...

Exploring the Autonomous Economic World of Children: A Mixed Methods Study of Kids' Naive Economic Theories Incorporating Ethnographic and Behavioral Economics Methodologies

ERIC Educational Resources Information Center

Jennings, Amanda Brooke

2017-01-01

Children construct meaning from their economic experiences in the form of naive theories and use these theories to explain the relationships between their actions and the outcomes. Inevitably, due to their lack of economic literacy, these theories will be incomplete. Through curriculum design that acknowledges and addresses these naive theories,…

In silico prediction of drug-induced myelotoxicity by using Naïve Bayes method.

PubMed

Zhang, Hui; Yu, Peng; Zhang, Teng-Guo; Kang, Yan-Li; Zhao, Xiao; Li, Yuan-Yuan; He, Jia-Hui; Zhang, Ji

2015-11-01

Drug-induced myelotoxicity usually leads to decrease the production of platelets, red cells, and white cells. Thus, early identification and characterization of myelotoxicity hazard in drug development is very necessary. The purpose of this investigation was to develop a prediction model of drug-induced myelotoxicity by using a Naïve Bayes classifier. For comparison, other prediction models based on support vector machine and single-hidden-layer feed-forward neural network  methods were also established. Among all the prediction models, the Naïve Bayes classification model showed the best prediction performance, which offered an average overall prediction accuracy of [Formula: see text] for the training set and [Formula: see text] for the external test set. The significant contributions of this study are that we first developed a Naïve Bayes classification model of drug-induced myelotoxicity adverse effect using a larger scale dataset, which could be employed for the prediction of drug-induced myelotoxicity. In addition, several important molecular descriptors and substructures of myelotoxic compounds have been identified, which should be taken into consideration in the design of new candidate compounds to produce safer and more effective drugs, ultimately reducing the attrition rate in later stages of drug development.

Classification of THz pulse signals using two-dimensional cross-correlation feature extraction and non-linear classifiers.

PubMed

Siuly; Yin, Xiaoxia; Hadjiloucas, Sillas; Zhang, Yanchun

2016-04-01

This work provides a performance comparison of four different machine learning classifiers: multinomial logistic regression with ridge estimators (MLR) classifier, k-nearest neighbours (KNN), support vector machine (SVM) and naïve Bayes (NB) as applied to terahertz (THz) transient time domain sequences associated with pixelated images of different powder samples. The six substances considered, although have similar optical properties, their complex insertion loss at the THz part of the spectrum is significantly different because of differences in both their frequency dependent THz extinction coefficient as well as differences in their refractive index and scattering properties. As scattering can be unquantifiable in many spectroscopic experiments, classification solely on differences in complex insertion loss can be inconclusive. The problem is addressed using two-dimensional (2-D) cross-correlations between background and sample interferograms, these ensure good noise suppression of the datasets and provide a range of statistical features that are subsequently used as inputs to the above classifiers. A cross-validation procedure is adopted to assess the performance of the classifiers. Firstly the measurements related to samples that had thicknesses of 2mm were classified, then samples at thicknesses of 4mm, and after that 3mm were classified and the success rate and consistency of each classifier was recorded. In addition, mixtures having thicknesses of 2 and 4mm as well as mixtures of 2, 3 and 4mm were presented simultaneously to all classifiers. This approach provided further cross-validation of the classification consistency of each algorithm. The results confirm the superiority in classification accuracy and robustness of the MLR (least accuracy 88.24%) and KNN (least accuracy 90.19%) algorithms which consistently outperformed the SVM (least accuracy 74.51%) and NB (least accuracy 56.86%) classifiers for the same number of feature vectors across all studies

In Vitro Measles Virus Infection of Human Lymphocyte Subsets Demonstrates High Susceptibility and Permissiveness of both Naive and Memory B Cells

PubMed Central

Laksono, Brigitta M.; Grosserichter-Wagener, Christina; de Vries, Rory D.; Langeveld, Simone A. G.; Brem, Maarten D.; van Dongen, Jacques J. M.; Koopmans, Marion P. G.

2018-01-01

ABSTRACT Measles is characterized by a transient immune suppression, leading to an increased risk of opportunistic infections. Measles virus (MV) infection of immune cells is mediated by the cellular receptor CD150, expressed by subsets of lymphocytes, dendritic cells, macrophages, and thymocytes. Previous studies showed that human and nonhuman primate memory T cells express higher levels of CD150 than naive cells and are more susceptible to MV infection. However, limited information is available about the CD150 expression and relative susceptibility to MV infection of B-cell subsets. In this study, we assessed the susceptibility and permissiveness of naive and memory T- and B-cell subsets from human peripheral blood or tonsils to in vitro MV infection. Our study demonstrates that naive and memory B cells express CD150, but at lower frequencies than memory T cells. Nevertheless, both naive and memory B cells proved to be highly permissive to MV infection. Furthermore, we assessed the susceptibility and permissiveness of various functionally distinct T and B cells, such as helper T (TH) cell subsets and IgG- and IgA-positive memory B cells, in peripheral blood and tonsils. We demonstrated that TH1TH17 cells and plasma and germinal center B cells were the subsets most susceptible and permissive to MV infection. Our study suggests that both naive and memory B cells, along with several other antigen-experienced lymphocytes, are important target cells of MV infection. Depletion of these cells potentially contributes to the pathogenesis of measles immune suppression. IMPORTANCE Measles is associated with immune suppression and is often complicated by bacterial pneumonia, otitis media, or gastroenteritis. Measles virus infects antigen-presenting cells and T and B cells, and depletion of these cells may contribute to lymphopenia and immune suppression. Measles has been associated with follicular exhaustion in lymphoid tissues in humans and nonhuman primates, emphasizing

Diurnal variation of oxygen and carbonate system parameters in Tampa Bay and Florida Bay

USGS Publications Warehouse

Yates, K.K.; Dufore, C.; Smiley, N.; Jackson, C.; Halley, R.B.

2007-01-01

Oxygen and carbonate system parameters were measured, in situ, over diurnal cycles in Tampa Bay and Florida Bay, Florida. All system parameters showed distinct diurnal trends in Tampa Bay with an average range of diurnal variation of 39.1 μmol kg− 1 for total alkalinity, 165.1 μmol kg− 1 for total CO2, 0.22 for pH, 0.093 mmol L− 1 for dissolved oxygen, and 218.1 μatm for pCO2. Average range of diurnal variation for system parameters in Tampa Bay was 73% to 93% of the seasonal range of variability for dissolved oxygen and pH. All system parameters measured in Florida Bay showed distinct variation over diurnal time-scales. However, clear diurnal trends were less evident. The average range of diurnal variability in Florida Bay was 62.8 μmol kg− 1 for total alkalinity, 130.4 μmol kg− 1 for total CO2, 0.13 for pH, 0.053 mmol L− 1 for dissolved oxygen, and 139.8 μatm for pCO2. The average range of diurnal variation was 14% to 102% of the seasonal ranges for these parameters. Diurnal variability in system parameters was most influenced by primary productivity and respiration of benthic communities in Tampa Bay, and by precipitation and dissolution of calcium carbonate in Florida Bay. Our data indicate that use of seasonal data sets without careful consideration of diurnal variability may impart significant error in calculations of annual carbon and oxygen budgets. These observations reinforce the need for higher temporal resolution measurements of oxygen and carbon system parameters in coastal ecosystems.

Discharge between San Antonio Bay and Aransas Bay, southern Gulf Coast, Texas, May-September 1999

USGS Publications Warehouse

East, Jeffery W.

2001-01-01

Along the Gulf Coast of Texas, many estuaries and bays are important habitat and nurseries for aquatic life. San Antonio Bay and Aransas Bay, located about 50 and 30 miles northeast, respectively, of Corpus Christi, are two important estuarine nurseries on the southern Gulf Coast of Texas (fig. 1). According to the Texas Parks and Wildlife Department, “Almost 80 percent of the seagrasses [along the Texas Gulf Coast] are located in the Laguna Madre, an estuary that begins just south of Corpus Christi Bay and runs southward 140 miles to South Padre Island. Most of the remaining seagrasses, about 45,000 acres, are located in the heavily traveled San Antonio, Aransas and Corpus Christi Bay areas” (Shook, 2000).Population growth has led to greater demands on water supplies in Texas. The Texas Water Development Board, the Texas Parks and Wildlife Department, and the Texas Natural Resource Conservation Commission have the cooperative task of determining inflows required to maintain the ecological health of the State’s streams, rivers, bays, and estuaries. To determine these inflow requirements, the three agencies collect data and conduct studies on the need for instream flows and freshwater/ saline water inflows to Texas estuaries.To assist in the determination of freshwater inflow requirements, the U.S. Geological Survey (USGS), in cooperation with the Texas Water Development Board, conducted a hydrographic survey of discharge (flow) between San Antonio Bay and Aransas Bay during the period May–September 1999. Automated instrumentation and acoustic technology were used to maximize the amount and quality of data that were collected, while minimizing personnel requirements. This report documents the discharge measured at two sites between the bays during May–September 1999 and describes the influences of meteorologic (wind and tidal) and hydrologic (freshwater inflow) conditions on discharge between the two bays. The movement of water between the bays is

Achieving ventricular rate control using metoprolol in β-blocker-naive patients vs patients on chronic β-blocker therapy.

PubMed

Kuang, Patricia; Mah, Nathan D; Barton, Cassie A; Miura, Andrea J; Tanas, Laura R; Ran, Ran

2016-03-01

The objective of the study is to evaluate the difference in ventricular rate control using an intravenous (IV) metoprolol regimen commonly used in clinical practice in patients receiving chronic β-blocker therapy compared to patients considered β-blocker naive admitted to the emergency department (ED) for atrial fibrillation (AF) with rapid ventricular rate. A single-center retrospective cohort study of adult ED patients who were admitted with a rapid ventricular rate of 120 beats per minute (bpm) or greater and treated with IV metoprolol was performed. Rate control was defined as either a decrease in ventricular rate to less than 100 bpm or a 20% decrease in heart rate to less than 120 bpm after metoprolol administration. Patient demographics, differences in length of stay, and adverse events were recorded. A total of 398 patients were included in the study, with 79.4% (n=316) receiving chronic β-blocker therapy. Patients considered to be β-blocker naive were more likely to achieve successful rate control with IV metoprolol compared to patients on chronic β-blocker therapy (56.1% vs 42.4%; P=.03). β-Blocker-naive status was associated with a shorter length of stay in comparison to patients receiving chronic β-blocker therapy (1.79 vs 2.64 days; P<.01). Intravenous metoprolol for the treatment of atrial fibrillation with rapid ventricular rate was associated with a higher treatment response in patients considered β-blocker naive compared to patients receiving chronic β-blocker therapy. Copyright © 2015 Elsevier Inc. All rights reserved.

[An integrated assessment method of ecological quality status in coastal waters: taking Tong'an Bay as a case].

PubMed

Chen, Zhao-hua; Wu, Hai-yan; Chen, Ke-liang; Chen, Qing-hui; Wu, Ji-chun; Zhang, Jing-fei

2011-07-01

Based on the integrated assessment methods of ecological quality status (EcoQS) in coastal waters abroad as well as the domestic related research status, 11 indices were selected from the biotic and physicochemical elements of water and sediment to built an integrated EcoQS assessment index system, and, with the comprehensive consideration of domestic and international evaluation standards, 5 levels of EcoQS classified as "high, good, moderate, poor, and bad" were determined. Then, an integrated assessment method of EcoQS in coastal waters was established by using analytic hierarchy process (AHP) and fuzzy mathematics method, and tested by the analysis of the correlations between the EcoQS grade and the major anthropogenic disturbances and pollutant concentrations of Tong' an Bay. The EcoQS of Tong' an Bay was assessed as moderate, i.e., the Bay was moderately disturbed and in transitional to poor status. The established integrated assessment method could not only reflect the major anthropogenic environmental pressure and risk factors, but also give an early warning of the pollutants satisfied by law in the study area.

Anterior Cingulate Volumetric Alterations in Treatment-Naive Adults with ADHD: A Pilot Study

ERIC Educational Resources Information Center

Makris, Nikos; Seidman, Larry J.; Valera, Eve M.; Biederman, Joseph; Monuteaux, Michael C.; Kennedy, David N.; Caviness, Verne S., Jr.; Bush, George; Crum, Katherine; Brown, Ariel B.; Faraone, Stephen V.

2010-01-01

Objective: We sought to examine preliminary results of brain alterations in anterior cingulate cortex (ACC) in treatment-naive adults with ADHD. The ACC is a central brain node for the integration of cognitive control and allocation of attention, affect and drive. Thus its anatomical alteration may give rise to impulsivity, hyperactivity and…

Combining contamination indexes, sediment quality guidelines and multivariate data analysis for metal pollution assessment in marine sediments of Cienfuegos Bay, Cuba.

PubMed

Peña-Icart, Mirella; Pereira-Filho, Edenir Rodrigues; Lopes Fialho, Lucimar; Nóbrega, Joaquim A; Alonso-Hernández, Carlos; Bolaños-Alvarez, Yoelvis; Pomares-Alfonso, Mario S

2017-02-01

The purpose of the present work was to combine several tools for assessing metal pollution in marine sediments from Cienfuegos Bay. Fourteen surface sediments collected in 2013 were evaluated. Concentrations of As, Cu, Ni, Zn and V decreased respect to those previous reported. The metal contamination was spatially distributed in the north and south parts of the bay. According to the contamination factor (CF) enrichment factor (EF) and index of geoaccumulation (I geo ), Cd and Cu were classified in that order as the most contaminated elements in most sediment. Comparison of the total metal concentrations with the threshold (TELs) and probable (PELs) effect levels in sediment quality guidelines suggested a more worrisome situation for Cu, of which concentrations were occasional associated with adverse biological effects in thirteen sediments, followed by Ni in nine sediments; while adverse effects were rarely associated with Cd. Probably, Cu could be considered as the most dangerous in the whole bay because it was classified in the high contamination levels by all indexes and, simultaneously, associated to occasional adverse effects in most samples. Despite the bioavailability was partially evaluated with the HCl method, the low extraction of Ni (<3% in all samples) and Cu (<55%, except sample 3) and the relative high extraction of Cd (50% or more, except sample 14) could be considered as an attenuating (Ni and Cu) or increasing (Cd) factor in the risk assessment of those element. Copyright © 2016. Published by Elsevier Ltd.

75 FR 11837 - Chesapeake Bay Watershed Initiative

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-12

... DEPARTMENT OF AGRICULTURE Commodity Credit Corporation Chesapeake Bay Watershed Initiative AGENCY...: Notice of availability of program funds for the Chesapeake Bay Watershed Initiative. SUMMARY: The... through the Chesapeake Bay Watershed Initiative for agricultural producers in the Chesapeake Bay watershed...

Urban Greening Bay Area

EPA Pesticide Factsheets

Information about the San Francisco Bay Water Quality Project (SFBWQP) Urban Greening Bay Area, a large-scale effort to re-envision urban landscapes to include green infrastructure (GI) making communities more livable and reducing stormwater runoff.

Concentration of PSP (Paralytic Shellfish Poisoning) Toxin On Shellfish From Inner Ambon Bay and Kao Bay North Halmahera

NASA Astrophysics Data System (ADS)

Pello, F. S.; Haumahu, S.; Huliselan, N. V.; Tuapattinaja, M. A.

2017-10-01

The Inner Ambon Bay and Kao Bay have potential on fisheries resources which one of them is molluscs. Molluscs especially for class bivalve have economical values and are consumed by coastal community. The research had been done to analyze saxitoxin (STX) concentration on bivalves from Kao Bay and Inner Ambon Bay. The Saxitoxin Elisa Test Kit Protocol was used to determine saxitoxin concentration. The measurement showed that the highest concentration of saxitoxin (392.42 µg STXeq/100g shellfish meat) was Gafrarium tumidum from Ambon Bay, whereas concentration of saxitoxin (321.83 µg STXeq/100g shellfish meat) was Mactra mera from Kao Bay

77 FR 30443 - Safety Zone; Alexandria Bay Chamber of Commerce, St. Lawrence River, Alexandria Bay, NY

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-23

...-AA00 Safety Zone; Alexandria Bay Chamber of Commerce, St. Lawrence River, Alexandria Bay, NY AGENCY... Commerce fireworks display. The safety zone established by this proposed rule is necessary to protect... spectators and vessels during the Alexandria Bay Chamber of Commerce fireworks display. Regulatory Analyses...

Raffaello Multi-Purpose Logistics Module (MPLM) in Discovery Cargo Bay

NASA Technical Reports Server (NTRS)

2005-01-01

Launched on July 26, 2005 from the Kennedy Space Center in Florida, STS-114 was classified as Logistics Flight 1. Among the Station-related activities of the mission were the delivery of new supplies and the replacement of one of the orbital outpost's Control Moment Gyroscopes (CMGs). STS-114 also carried the Raffaello Multi-Purpose Logistics Module (MPLM) and the External Stowage Platform-2. Back dropped by popcorn-like clouds, the MPLM can be seen in the cargo bay as Discovery undergoes rendezvous and docking operations. Cosmonaut Sergei K. Kriklev, Expedition 11 Commander, and John L. Phillips, NASA Space Station officer and flight engineer photographed the spacecraft from the International Space Station (ISS).

Raffaello Multi-Purpose Logistics Module (MPLM) in Discovery Cargo Bay

NASA Technical Reports Server (NTRS)

2005-01-01

Launched on July 26 2005 from the Kennedy Space Center in Florida, STS-114 was classified as Logistics Flight 1. Among the Station-related activities of the mission were the delivery of new supplies and the replacement of one of the orbital outpost's Control Moment Gyroscopes (CMGs). STS-114 also carried the Raffaello Multi-Purpose Logistics Module (MPLM) and the External Stowage Platform-2. Back dropped by popcorn-like clouds, the MPLM can be seen in the cargo bay as Discovery undergoes rendezvous and docking operations. Cosmonaut Sergei K. Kriklev, Expedition 11 Commander, and John L. Phillips, NASA Space Station officer and flight engineer photographed the spacecraft from the International Space Station (ISS).

Inorganic elemental determinations of marine traditional Chinese Medicine Meretricis concha from Jiaozhou Bay: The construction of inorganic elemental fingerprint based on chemometric analysis

NASA Astrophysics Data System (ADS)

Shao, Mingying; Li, Xuejie; Zheng, Kang; Jiang, Man; Yan, Cuiwei; Li, Yantuan

2016-04-01

The goal of this paper is to explore the relationship between the inorganic elemental fingerprint and the geographical origin identification of Meretricis concha, which is a commonly used marine traditional Chinese medicine (TCM) for the treatment of asthma and scald burns. For that, the inorganic elemental contents of Meretricis concha from five sampling points in Jiaozhou Bay have been determined by means of inductively coupled plasma optical emission spectrometry, and the comparative investigations based on the contents of 14 inorganic elements (Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se and Zn) of the samples from Jiaozhou Bay and the previous reported Rushan Bay were performed. It has been found that the samples from the two bays are approximately classified into two kinds using hierarchical cluster analysis, and a four-factor model based on principle component analysis could explain approximately 75% of the detection data, also linear discriminant analysis can be used to develop a prediction model to distinguish the samples from Jiaozhou Bay and Rushan Bay with accuracy of about 93%. The results of the present investigation suggested that the inorganic elemental fingerprint based on the combination of the measured elemental content and chemometric analysis is a promising approach for verifying the geographical origin of Meretricis concha, and this strategy should be valuable for the authenticity discrimination of some marine TCM.

Description of gravity cores from San Pablo Bay and Carquinez Strait, San Francisco Bay, California

USGS Publications Warehouse

Woodrow, Donald L.; John L. Chin,; Wong, Florence L.; Fregoso, Theresa A.; Jaffe, Bruce E.

2017-06-27

Seventy-two gravity cores were collected by the U.S. Geological Survey in 1990, 1991, and 2000 from San Pablo Bay and Carquinez Strait, California. The gravity cores collected within San Pablo Bay contain bioturbated laminated silts and sandy clays, whole and broken bivalve shells (mostly mussels), fossil tube structures, and fine-grained plant or wood fragments. Gravity cores from the channel wall of Carquinez Strait east of San Pablo Bay consist of sand and clay layers, whole and broken bivalve shells (less than in San Pablo Bay), trace fossil tubes, and minute fragments of plant material.

Detection of drug resistance-associated mutations in human immunodeficiency virus type 1 integrase derived from drug-naive individuals in Surabaya, Indonesia.

PubMed

Kotaki, Tomohiro; Khairunisa, Siti Qamariyah; Sukartiningrum, Septhia Dwi; Witaningrum, Adiana Mutamsari; Rusli, Musofa; Diansyah, M Noor; Arfijanto, M Vitanata; Rahayu, Retno Pudji; Nasronudin; Kameoka, Masanori

2014-05-01

Although human immunodeficiency virus type 1 (HIV-1) infection causes serious health problems in Indonesia, information in regard to drug resistance is limited. We performed a genotypic study on HIV-1 integrase derived from drug-naive individuals in Surabaya, Indonesia. Sequencing analysis revealed that no primary mutations associated with drug resistance to integrase inhibitors were detected; however, secondary mutations, V72I, L74I/M, V165I, V201I, I203M, and S230N, were detected in more than 5% of samples. In addition, V201I was conserved among all samples. Most integrase genes were classified into CRF01_AE genes. Interestingly, 40% of the CRF01_AE genes had an unusual insertion in the C-terminus of integrase. These mutations and insertions were considered natural polymorphisms since these mutations coincided with previous reports, and integrase inhibitors have not been used in Indonesia. Our results indicated that further studies may be required to assess the impact of these mutations on integrase inhibitors prior to their introduction into Indonesia.

Chesapeake Bay TMDL Document

EPA Pesticide Factsheets

This page provides the Total Maximum Daily Load (TMDL) report for the Chesapeake Bay. It includes the executive summary, main report, and appendices. The Chesapeake Bay TMDL was established by U.S. EPA Region 3 on December 29, 2010

Just-in-time adaptive classifiers-part II: designing the classifier.

PubMed

Alippi, Cesare; Roveri, Manuel

2008-12-01

Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.

KLF4 Nuclear Export Requires ERK Activation and Initiates Exit from Naive Pluripotency.

PubMed

Dhaliwal, Navroop K; Miri, Kamelia; Davidson, Scott; Tamim El Jarkass, Hala; Mitchell, Jennifer A

2018-04-10

Cooperative action of a transcription factor complex containing OCT4, SOX2, NANOG, and KLF4 maintains the naive pluripotent state; however, less is known about the mechanisms that disrupt this complex, initiating exit from pluripotency. We show that, as embryonic stem cells (ESCs) exit pluripotency, KLF4 protein is exported from the nucleus causing rapid decline in Nanog and Klf4 transcription; as a result, KLF4 is the first pluripotency transcription factor removed from transcription-associated complexes during differentiation. KLF4 nuclear export requires ERK activation, and phosphorylation of KLF4 by ERK initiates interaction of KLF4 with nuclear export factor XPO1, leading to KLF4 export. Mutation of the ERK phosphorylation site in KLF4 (S132) blocks KLF4 nuclear export, the decline in Nanog, Klf4, and Sox2 mRNA, and differentiation. These findings demonstrate that relocalization of KLF4 to the cytoplasm is a critical first step in exit from the naive pluripotent state and initiation of ESC differentiation. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Prevalence of Dyslipidemia Among Antiretroviral-Naive HIV-Infected Individuals in China

PubMed Central

Shen, Yinzhong; Wang, Jiangrong; Wang, Zhenyan; Qi, Tangkai; Song, Wei; Tang, Yang; Liu, Li; Zhang, Renfang; Lu, Hongzhou

2015-01-01

Abstract Little is known about the epidemiological features of dyslipidemia among antiretroviral-naive HIV-infected individuals in China. We used a cross-sectional study design to estimate the prevalence of dyslipidemia in this population, and to identify risk factors associated with the presence of dyslipidemia. One thousand five hundred and eighteen antiretroviral-naive HIV-infected individuals and 347 HIV-negative subjects in China were enrolled during 2009 to 2010. Demographics and medical histories were recorded. After an overnight fast, serum samples were collected to measure lipid levels. Factors associated with the presence of dyslipidemia were analyzed by logistic regression. Mean total cholesterol (TC), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL) levels were lower in HIV-positive than HIV-negative subjects, but mean triglyceride (TG) was higher in HIV-positive subjects. The overall prevalence of dyslipidemia in HIV-positive and HIV-negative groups did not differ (75.6% vs. 73.7%, P = 0.580). However, the prevalence of high TC (8.4% vs. 28.2%, P < 0.001) and high LDL (8.5% vs. 62.6%, P < 0.001) was lower in HIV-positive than HIV-negative subjects, and the prevalence of high TG (33.9% vs. 17.0%, P < 0.001) and low HDL (59.6% vs. 11.2%, P < 0.001) was higher in HIV-positive than HIV-negative subjects. Logistic analysis showed that HIV positivity was significantly associated with both an increased risk of high TG and low HDL and a decreased risk of high TC and high LDL. The mean levels of TC, of LDL and of HDL showed an increasing trend with increasing CD4 count in HIV-positive subjects. Multivariable logistic regression found that lower CD4 count was significantly associated with both an increased risk of high TG and low HDL and a decreased risk of high TC in HIV-positive subjects. Among antiretroviral-naive HIV-infected Chinese adults, there was a high prevalence of dyslipidemia characterized by

Economic Impact of Treatment Duration and Persistence with Basal Insulin in Previously Insulin-Naive Users.

PubMed

Kalirai, Samaneh; Duan, Ran; Liu, Dongju; Reed, Beverly L

2017-03-01

Although insulin is a well-established therapy that is associated with improved clinical outcomes, adherence and persistence with insulin regimens are poor in patients with type 2 diabetes mellitus (T2DM). Diabetes-related health care costs and the impact of insulin persistence patterns on these health care costs have been previously studied; however, these aspects of insulin therapy have limited data beyond the first year of use and have not been characterized among patients previously naive to basal insulin. To (a) describe and compare medical- and pharmacy-related costs, health care resource utilization, and comorbidities and complications during the initial year and second (experienced) year of basal insulin therapy, and (b) describe and compare the impact of continuous versus interrupted basal insulin use during each year. This was a retrospective observational database analysis using claims from multiple U.S. commercial health plans (Truven Health MarketScan) in previously insulin-naive patients with T2DM who were initiated on basal insulin. Data collected included all-cause and diabetes-related medical and pharmacy costs, health care resource utilization (i.e., number and type of outpatient visits, hospitalization, emergency department [ED] visits), medication use, and preselected comorbidities and complications. This cost analysis described and compared health care costs and resource use between the initial and experienced years and further compared health care costs and resource use between continuers and interrupters within each of those years. A total of 23,645 patients were included in the analysis; 12,224 were classified as continuers and 11,421 were classified as interrupters. Among all patients, mean increases from the initial year to the experienced year were observed for all-cause medical costs ($12,690-$13,408; P = 0.048), all-cause pharmacy costs ($6,253-$6,559; P < 0.001), and all-cause health care costs ($18,943-$19,967; P = 0.006), after

Learning accurate very fast decision trees from uncertain data streams

NASA Astrophysics Data System (ADS)

Liang, Chunquan; Zhang, Yang; Shi, Peng; Hu, Zhengguo

2015-12-01

Most existing works on data stream classification assume the streaming data is precise and definite. Such assumption, however, does not always hold in practice, since data uncertainty is ubiquitous in data stream applications due to imprecise measurement, missing values, privacy protection, etc. The goal of this paper is to learn accurate decision tree models from uncertain data streams for classification analysis. On the basis of very fast decision tree (VFDT) algorithms, we proposed an algorithm for constructing an uncertain VFDT tree with classifiers at tree leaves (uVFDTc). The uVFDTc algorithm can exploit uncertain information effectively and efficiently in both the learning and the classification phases. In the learning phase, it uses Hoeffding bound theory to learn from uncertain data streams and yield fast and reasonable decision trees. In the classification phase, at tree leaves it uses uncertain naive Bayes (UNB) classifiers to improve the classification performance. Experimental results on both synthetic and real-life datasets demonstrate the strong ability of uVFDTc to classify uncertain data streams. The use of UNB at tree leaves has improved the performance of uVFDTc, especially the any-time property, the benefit of exploiting uncertain information, and the robustness against uncertainty.

USGS Tampa Bay Pilot Study

USGS Publications Warehouse

Yates, K.K.; Cronin, T. M.; Crane, M.; Hansen, M.; Nayeghandi, A.; Swarzenski, P.; Edgar, T.; Brooks, G.R.; Suthard, B.; Hine, A.; Locker, S.; Willard, D.A.; Hastings, D.; Flower, B.; Hollander, D.; Larson, R.A.; Smith, K.

2007-01-01

Providing a web-based digital information management system of information for scientists and the public, including a system that supports the work of those officials who must make decisions that affect the state of the bay. The Tampa Bay Study is in its sixth year and will continue through September 2007. This paper presents a non-inclusive summary of key findings associated with the six primary project components listed above. Component 4 (above) is described in detail in the following chapter 13. More information on the Tampa Bay Study is available from our on-line digital information system for the Tampa Bay Study at http://gulfsci.usgs.gov.

Facility Layout Problems Using Bays: A Survey

NASA Astrophysics Data System (ADS)

Davoudpour, Hamid; Jaafari, Amir Ardestani; Farahani, Leila Najafabadi

2010-06-01

Layout design is one of the most important activities done by industrial Engineers. Most of these problems have NP hard Complexity. In a basic layout design, each cell is represented by a rectilinear, but not necessarily convex polygon. The set of fully packed adjacent polygons is known as a block layout (Asef-Vaziri and Laporte 2007). Block layout is divided by slicing tree and bay layout. In bay layout, departments are located in vertical columns or horizontal rows, bays. Bay layout is used in real worlds especially in concepts such as semiconductor and aisles. There are several reviews in facility layout; however none of them focus on bay layout. The literature analysis given here is not limited to specific considerations about bay layout design. We present a state of art review for bay layout considering some issues such as the used objectives, the techniques of solving and the integration methods in bay.

76 FR 37641 - Safety Zone; Independence Day Fireworks Celebration for the City of Half Moon Bay, Half Moon Bay, CA

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-28

...-AA00 Safety Zone; Independence Day Fireworks Celebration for the City of Half Moon Bay, Half Moon Bay... temporary safety zone in the navigable waters of Half Moon Bay, off of Pillar Point Harbor beach, Half Moon Bay, CA in support of the Independence Day Fireworks Celebration for the City of Half Moon Bay...

Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information

PubMed Central

2013-01-01

Background The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. Results In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL). It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i) vitamin interacting residues (VIRs), (ii) vitamin-A interacting residues (VAIRs), (iii) vitamin-B interacting residues (VBIRs) and (iv) pyridoxal-5-phosphate (vitamin B6) interacting residues (PLPIRs) have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM) features of protein sequences. Finally, we selected best performing SVM modules and obtained highest MCC of

Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information.

PubMed

Panwar, Bharat; Gupta, Sudheer; Raghava, Gajendra P S

2013-02-07

The vitamins are important cofactors in various enzymatic-reactions. In past, many inhibitors have been designed against vitamin binding pockets in order to inhibit vitamin-protein interactions. Thus, it is important to identify vitamin interacting residues in a protein. It is possible to detect vitamin-binding pockets on a protein, if its tertiary structure is known. Unfortunately tertiary structures of limited proteins are available. Therefore, it is important to develop in-silico models for predicting vitamin interacting residues in protein from its primary structure. In this study, first we compared protein-interacting residues of vitamins with other ligands using Two Sample Logo (TSL). It was observed that ATP, GTP, NAD, FAD and mannose preferred {G,R,K,S,H}, {G,K,T,S,D,N}, {T,G,Y}, {G,Y,W} and {Y,D,W,N,E} residues respectively, whereas vitamins preferred {Y,F,S,W,T,G,H} residues for the interaction with proteins. Furthermore, compositional information of preferred and non-preferred residues along with patterns-specificity was also observed within different vitamin-classes. Vitamins A, B and B6 preferred {F,I,W,Y,L,V}, {S,Y,G,T,H,W,N,E} and {S,T,G,H,Y,N} interacting residues respectively. It suggested that protein-binding patterns of vitamins are different from other ligands, and motivated us to develop separate predictor for vitamins and their sub-classes. The four different prediction modules, (i) vitamin interacting residues (VIRs), (ii) vitamin-A interacting residues (VAIRs), (iii) vitamin-B interacting residues (VBIRs) and (iv) pyridoxal-5-phosphate (vitamin B6) interacting residues (PLPIRs) have been developed. We applied various classifiers of SVM, BayesNet, NaiveBayes, ComplementNaiveBayes, NaiveBayesMultinomial, RandomForest and IBk etc., as machine learning techniques, using binary and Position-Specific Scoring Matrix (PSSM) features of protein sequences. Finally, we selected best performing SVM modules and obtained highest MCC of 0.53, 0.48, 0.61, 0

Chesapeake Bay Watershed - Protecting the Chesapeake Bay and its rivers through science, restoration, and partnership

USGS Publications Warehouse

,

2012-01-01

The Chesapeake Bay, the Nation's largest estuary, has been degraded due to the impact of human-population increase, which has doubled since 1950, resulting in degraded water quality, loss of habitat, and declines in populations of biological communities. Since the mid-1980s, the Chesapeake Bay Program (CBP), a multi-agency partnership which includes the Department of Interior (DOI), has worked to restore the Bay ecosystem. The U.S. Geological Survey (USGS) has the critical role of providing unbiased scientific information that is utilized to document and understand ecosystem change to help assess the effectiveness of restoration strategies in the Bay and its watershed. The USGS revised its Chesapeake Bay science plan for 2006-2011 to address the collective needs of the CBP, DOI, and USGS with a mission to provide integrated science for improved understanding and management of the Bay ecosystem. The USGS science themes for this mission are: Causes and consequences of land-use change; Impact of climate change and associated hazards; Factors affecting water quality and quantity; Ability of habitat to support fish and bird populations; and Synthesis and forecasting to improve ecosystem assessment, conservation, and restoration.

In Vitro Measles Virus Infection of Human Lymphocyte Subsets Demonstrates High Susceptibility and Permissiveness of both Naive and Memory B Cells.

PubMed

Laksono, Brigitta M; Grosserichter-Wagener, Christina; de Vries, Rory D; Langeveld, Simone A G; Brem, Maarten D; van Dongen, Jacques J M; Katsikis, Peter D; Koopmans, Marion P G; van Zelm, Menno C; de Swart, Rik L

2018-04-15

Measles is characterized by a transient immune suppression, leading to an increased risk of opportunistic infections. Measles virus (MV) infection of immune cells is mediated by the cellular receptor CD150, expressed by subsets of lymphocytes, dendritic cells, macrophages, and thymocytes. Previous studies showed that human and nonhuman primate memory T cells express higher levels of CD150 than naive cells and are more susceptible to MV infection. However, limited information is available about the CD150 expression and relative susceptibility to MV infection of B-cell subsets. In this study, we assessed the susceptibility and permissiveness of naive and memory T- and B-cell subsets from human peripheral blood or tonsils to in vitro MV infection. Our study demonstrates that naive and memory B cells express CD150, but at lower frequencies than memory T cells. Nevertheless, both naive and memory B cells proved to be highly permissive to MV infection. Furthermore, we assessed the susceptibility and permissiveness of various functionally distinct T and B cells, such as helper T (T H ) cell subsets and IgG- and IgA-positive memory B cells, in peripheral blood and tonsils. We demonstrated that T H 1T H 17 cells and plasma and germinal center B cells were the subsets most susceptible and permissive to MV infection. Our study suggests that both naive and memory B cells, along with several other antigen-experienced lymphocytes, are important target cells of MV infection. Depletion of these cells potentially contributes to the pathogenesis of measles immune suppression. IMPORTANCE Measles is associated with immune suppression and is often complicated by bacterial pneumonia, otitis media, or gastroenteritis. Measles virus infects antigen-presenting cells and T and B cells, and depletion of these cells may contribute to lymphopenia and immune suppression. Measles has been associated with follicular exhaustion in lymphoid tissues in humans and nonhuman primates, emphasizing the

Heavy metals pollution and pb isotopic signatures in surface sediments collected from Bohai Bay, North China.

PubMed

Gao, Bo; Lu, Jin; Hao, Hong; Yin, Shuhua; Yu, Xiao; Wang, Qiwen; Sun, Ke

2014-01-01

To investigate the characteristics and potential sources of heavy metals pollution, surface sediments collected from Bohai Bay, North China, were analyzed for the selected metals (Cd, Cr, Cu, Ni, Pb, and Zn). The Geoaccumulation Index was used to assess the level of heavy metal pollution. Pb isotopic compositions in sediments were also measured to effectively identify the potential Pb sources. The results showed that the average concentrations of Cd, Cr, Cu, Ni, Pb, and Zn were 0.15, 79.73, 28.70, 36.56, 25.63, and 72.83 mg/kg, respectively. The mean concentrations of the studied metals were slightly higher than the background values. However, the heavy metals concentrations in surface sediments in Bohai Bay were below the other important bays or estuaries in China. The assessment by Geoaccumulation Index indicated that Cr, Zn, and Cd were classified as "the unpolluted" level, while Ni, Cu, and Pb were ranked as "unpolluted to moderately polluted" level. The order of pollution level of heavy metals was: Pb > Ni > Cu > Cr > Zn > Cd. The Pb isotopic ratios in surface sediments varied from 1.159 to 1.185 for (206)Pb/(207)Pb and from 2.456 to 2.482 for (208)Pb/(207)Pb. Compared with Pb isotopic radios in other sources, Pb contaminations in the surface sediments of Bohai Bay may be controlled by the mix process of coal combustion, aerosol particles deposition, and natural sources.

33 CFR 165.1187 - Security Zones; Golden Gate Bridge and the San Francisco-Oakland Bay Bridge, San Francisco Bay...

Code of Federal Regulations, 2011 CFR

2011-07-01

... Bridge and the San Francisco-Oakland Bay Bridge, San Francisco Bay, California. 165.1187 Section 165.1187... Limited Access Areas Eleventh Coast Guard District § 165.1187 Security Zones; Golden Gate Bridge and the San Francisco-Oakland Bay Bridge, San Francisco Bay, California. (a) Location. All waters extending...

33 CFR 165.1187 - Security Zones; Golden Gate Bridge and the San Francisco-Oakland Bay Bridge, San Francisco Bay...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Bridge and the San Francisco-Oakland Bay Bridge, San Francisco Bay, California. 165.1187 Section 165.1187... Limited Access Areas Eleventh Coast Guard District § 165.1187 Security Zones; Golden Gate Bridge and the San Francisco-Oakland Bay Bridge, San Francisco Bay, California. (a) Location. All waters extending...

Big data analytics for early detection of breast cancer based on machine learning

NASA Astrophysics Data System (ADS)

Ivanova, Desislava

2017-12-01

This paper presents the concept and the modern advances in personalized medicine that rely on technology and review the existing tools for early detection of breast cancer. The breast cancer types and distribution worldwide is discussed. It is spent time to explain the importance of identifying the normality and to specify the main classes in breast cancer, benign or malignant. The main purpose of the paper is to propose a conceptual model for early detection of breast cancer based on machine learning for processing and analysis of medical big dataand further knowledge discovery for personalized treatment. The proposed conceptual model is realized by using Naive Bayes classifier. The software is written in python programming language and for the experiments the Wisconsin breast cancer database is used. Finally, the experimental results are presented and discussed.

Nutrients and Narragansett Bay

EPA Science Inventory

Narragansett Bay has been heavily fertilized by anthropogenic nutrients for almost 120 years. This presentation discusses the first introductions of human sources of nutrients to the Bay, via sewage and urban runoff, in the late 1890s through to the recent reductions in sewage ef...

Bay breeze climatology at two sites along the Chesapeake bay from 1986-2010: Implications for surface ozone.

PubMed

Stauffer, Ryan M; Thompson, Anne M

Hourly surface meteorological measurements were coupled with surface ozone (O 3 ) mixing ratio measurements at Hampton, Virginia and Baltimore, Maryland, two sites along the Chesapeake Bay in the Mid-Atlantic United States, to examine the behavior of surface O 3 during bay breeze events and quantify the impact of the bay breeze on local O 3 pollution. Analyses were performed for the months of May through September for the years 1986 to 2010. The years were split into three groups to account for increasingly stringent environmental regulations that reduced regional emissions of nitrogen oxides (NO x ): 1986-1994, 1995-2002, and 2003-2010. Each day in the 25-year record was marked either as a bay breeze day, a non-bay breeze day, or a rainy/cloudy day based on the meteorological data. Mean eight hour (8-h) averaged surface O 3 values during bay breeze events were 3 to 5 parts per billion by volume (ppbv) higher at Hampton and Baltimore than on non-bay breeze days in all year periods. Anomalies from mean surface O 3 were highest in the afternoon at both sites during bay breeze days in the 2003-2010 study period. In conjunction with an overall lowering of baseline O 3 after the 1995-2002 period, the percentage of total exceedances of the Environmental Protection Agency (EPA) 75 ppbv 8-h O 3 standard that occurred on bay breeze days increased at Hampton for 2003-2010, while remaining steady at Baltimore. These results suggest that bay breeze circulations are becoming more important to causing exceedance events at particular sites in the region, and support the hypothesis of Martins et al. (2012) that highly localized meteorology increasingly drives air quality events at Hampton.

A comparative study on entrepreneurial attitudes modeled with logistic regression and Bayes nets.

PubMed

López Puga, Jorge; García García, Juan

2012-11-01

Entrepreneurship research is receiving increasing attention in our context, as entrepreneurs are key social agents involved in economic development. We compare the success of the dichotomic logistic regression model and the Bayes simple classifier to predict entrepreneurship, after manipulating the percentage of missing data and the level of categorization in predictors. A sample of undergraduate university students (N = 1230) completed five scales (motivation, attitude towards business creation, obstacles, deficiencies, and training needs) and we found that each of them predicted different aspects of the tendency to business creation. Additionally, our results show that the receiver operating characteristic (ROC) curve is affected by the rate of missing data in both techniques, but logistic regression seems to be more vulnerable when faced with missing data, whereas Bayes nets underperform slightly when categorization has been manipulated. Our study sheds light on the potential entrepreneur profile and we propose to use Bayesian networks as an additional alternative to overcome the weaknesses of logistic regression when missing data are present in applied research.

Maraviroc: perspectives for use in antiretroviral-naive HIV-1-infected patients.

PubMed

Vandekerckhove, Linos; Verhofstede, Chris; Vogelaers, Dirk

2009-06-01

Maraviroc (Pfizer's UK-427857, Selzentry or Celsentri outside the USA) is the first agent in the new class of oral HIV-1 entry inhibitors to acquire approval by the US Food and Drug Administration and the European Medicine Agency. Considering the mechanism of action, it is expected that this drug will be effective only in a subpopulation of HIV-1-infected people, namely those harbouring the R5 virus. The favourable toxicity profile of the drug has been demonstrated in Phase III clinical trials in treatment-naive (MERIT) and treatment-experienced (MOTIVATE) patients. In the latter population, maraviroc showed a superior antiviral efficacy and immunological activity compared with optimized backbone therapy + placebo. However, in MERIT, a prospective double-blind, randomized trial in treatment-naive patients, maraviroc + zidovudine/lamivudine failed to prove non-inferiority to efavirenz + zidovudine/lamivudine as standard of care regimen in the 48 week intention-to-treat analysis. Using an assay with higher sensitivity for minority CXCR4-using (X4) HIV variants (the enhanced Trofile assay-Monogram), non-inferiority was reached for the maraviroc- versus efavirenz-based combination. These data indicate the important impact of the sensitivity of tropism testing on treatment outcome of maraviroc-containing regimens. This paper discusses both the prospective and retrospective analyses of the MERIT data and highlights the impact of these results on daily practice in HIV care.

BAY REGION ATMOSPHERIC CHEMISTRY EXPERIMENT (BRACE)

EPA Science Inventory

The Tampa Bay Estuary Program (TBEP) was formed in 1991 to assist the community in developing a comprehensive plan to restore and protect Tampa Bay. The ecological indicator of the health of the Bay is the coverage of seagrasses, historically in decline, which are important to...

78 FR 14185 - Safety Zone; MODU KULLUK; Kiliuda Bay, Kodiak Island, AK to Captains Bay, Unalaska Island, AK

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-05

... Mobile Offshore Drilling Unit (MODU) KULLUK currently located in Kiliuda Bay, Kodiak Island, Alaska with... large ocean-going drill vessel, while it is under tow from Kiliuda Bay, Kodiak Island to Captains Bay...

San Francisco and Bay Area, CA, USA

NASA Image and Video Library

1991-06-14

STS040-152-100 (5-14 June 1991) --- Although clouds obscure part of the city of San Francisco and the mouth of San Francisco Bay, development and physiographic features in the immediate vicinity of the bay are well displayed. The photograph clearly shows the eastern part of the city, including the Embarcadero, the Bay Bridge, which was damaged in the 1989 earthquake, and Candlestick Park, San Mateo, and Dumbarton Bridges, cross the southern portion of the bay. Vari-colored salt ponds also rim the southern Bay near Moffett Field. Highway 280 runs along the San Andreas fault south of the city. On the eastern margin of the bay are Berkeley the Sacramento River and the Haywood and Calaveras faults.

77 FR 21890 - Drawbridge Operation Regulation; Sturgeon Bay Ship Canal, Sturgeon Bay, WI

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-12

... Street and Maple-Oregon Bridges so vehicular traffic congestion would not develop on downtown Sturgeon... the efficient movement of vehicular traffic in Sturgeon Bay. The Sturgeon Bay Ship Canal is... experiences a significant increase in vehicular and vessel traffic during the peak tourist and navigation...

Application of texture analysis method for mammogram density classification

NASA Astrophysics Data System (ADS)

Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study

PubMed Central

Agniel, Denis; Beam, Andrew; Yorkgitis, Brian; Bicket, Mark; Homer, Mark; Fox, Kathe P; Knecht, Daniel B; McMahill-Walraven, Cheryl N; Palmer, Nathan; Kohane, Isaac

2018-01-01

Abstract Objective To quantify the effects of varying opioid prescribing patterns after surgery on dependence, overdose, or abuse in an opioid naive population. Design Retrospective cohort study. Setting Surgical claims from a linked medical and pharmacy administrative database of 37 651 619 commercially insured patients between 2008 and 2016. Participants 1 015 116 opioid naive patients undergoing surgery. Main outcome measures Use of oral opioids after discharge as defined by refills and total dosage and duration of use. The primary outcome was a composite of misuse identified by a diagnostic code for opioid dependence, abuse, or overdose. Results 568 612 (56.0%) patients received postoperative opioids, and a code for abuse was identified for 5906 patients (0.6%, 183 per 100 000 person years). Total duration of opioid use was the strongest predictor of misuse, with each refill and additional week of opioid use associated with an adjusted increase in the rate of misuse of 44.0% (95% confidence interval 40.8% to 47.2%, P<0.001), and 19.9% increase in hazard (18.5% to 21.4%, P<0.001), respectively. Conclusions Each refill and week of opioid prescription is associated with a large increase in opioid misuse among opioid naive patients. The data from this study suggest that duration of the prescription rather than dosage is more strongly associated with ultimate misuse in the early postsurgical period. The analysis quantifies the association of prescribing choices on opioid misuse and identifies levers for possible impact. PMID:29343479

GPU MrBayes V3.1: MrBayes on Graphics Processing Units for Protein Sequence Data.

PubMed

Pang, Shuai; Stones, Rebecca J; Ren, Ming-Ming; Liu, Xiao-Guang; Wang, Gang; Xia, Hong-ju; Wu, Hao-Yang; Liu, Yang; Xie, Qiang

2015-09-01

We present a modified GPU (graphics processing unit) version of MrBayes, called ta(MC)(3) (GPU MrBayes V3.1), for Bayesian phylogenetic inference on protein data sets. Our main contributions are 1) utilizing 64-bit variables, thereby enabling ta(MC)(3) to process larger data sets than MrBayes; and 2) to use Kahan summation to improve accuracy, convergence rates, and consequently runtime. Versus the current fastest software, we achieve a speedup of up to around 2.5 (and up to around 90 vs. serial MrBayes), and more on multi-GPU hardware. GPU MrBayes V3.1 is available from http://sourceforge.net/projects/mrbayes-gpu/. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Preliminary assessment of landslide-induced wave hazards, Tidal Inlet, Glacier Bay National Park, Alaska

USGS Publications Warehouse

Wieczorek, Gerald F.; Jakob, Matthias; Motyka, Roman J.; Zirnheld, Sandra L.; Craw, Patricia

2003-01-01

A large potential rock avalanche above the northern shore of Tidal Inlet, Glacier Bay National Park, Alaska, was investigated to determine hazards and risks of landslide-induced waves to cruise ships and other park visitors. Field and photographic examination revealed that the 5 to 10 million cubic meter landslide moved between AD 1892 and 1919 after the retreat of Little Ice Age glaciers from Tidal Inlet by AD 1890. The timing of landslide movement and the glacial history suggest that glacial debuttressing caused weakening of the slope and that the landslide could have been triggered by large earthquakes of 1899-1900 in Yakutat Bay. Evidence of recent movement includes fresh scarps, back-rotated blocks, and smaller secondary landslide movements. However, until there is evidence of current movement, the mass is classified as a dormant rock slump. An earthquake on the nearby active Fairweather fault system could reactivate the landslide and trigger a massive rock slump and debris avalanche into Tidal Inlet. Preliminary analyses show that waves induced by such a landslide could travel at speeds of 45 to 50 m/s and reach heights up to 76 m with wave runups of 200 m on the opposite shore of Tidal Inlet. Such waves would not only threaten vessels in Tidal Inlet, but would also travel into the western arm of Glacier Bay endangering large cruise ships and their passengers.

Virological Failure and HIV-1 Drug Resistance Mutations among Naive and Antiretroviral Pre-Treated Patients Entering the ESTHER Program of Calmette Hospital in Cambodia

PubMed Central

Limsreng, Setha; Him, Sovanvatey; Nouhin, Janin; Hak, Chanroeurn; Srun, Chanvatey; Viretto, Gerald; Ouk, Vara; Delfraissy, Jean Francois; Ségéral, Olivier

2014-01-01

Introduction In resource limited settings, patients entering an antiretroviral therapy (ART) program comprise ART naive and ART pre-treated patients who may show differential virological outcomes. Methods This retrospective study, conducted in 2010–2012 in the HIV clinic of Calmette Hospital located in Phnom Penh (Cambodia) assessed virological failure (VF) rates and patterns of drug resistance of naive and pre-treated patients. Naive and ART pre-treated patients were included when a Viral Load (VL) was performed during the first year of ART for naive subjects or at the first consultation for pre-treated individuals. Patients showing Virological failure (VF) (>1,000 copies/ml) underwent HIV DR genotyping testing. Interpretation of drug resistance mutations was done according to 2013 version 23 ANRS algorithms. Results On a total of 209 patients, 164 (78.4%) were naive and 45 (21.5%) were ART pre-treated. Their median initial CD4 counts were 74 cells/mm3 (IQR: 30–194) and 279 cells/mm3 (IQR: 103–455) (p<0.001), respectively. Twenty seven patients (12.9%) exhibited VF (95% CI: 8.6–18.2%), including 10 naive (10/164, 6.0%) and 17 pre-treated (17/45, 37.8%) patients (p<0.001). Among these viremic patients, twenty-two (81.4%) were sequenced in reverse transcriptase and protease coding regions. Overall, 19 (86.3%) harbored ≥1 drug resistance mutations (DRMs) whereas 3 (all belonging to pre-treated patients) harbored wild-types viruses. The most frequent DRMs were M184V (86.3%), K103N (45.5%) and thymidine analog mutations (TAMs) (40.9%). Two (13.3%) pre-treated patients harbored viruses that showed a multi-nucleos(t)ide resistance including Q151M, K65R, E33A/D, E44A/D mutations. Conclusion In Cambodia, VF rates were low for naive patients but the emergence of DRMs to NNRTI and 3TC occurred relatively quickly in this subgroup. In pre-treated patients, VF rates were much higher and TAMs were relatively common. HIV genotypic assays before ART initiation and for

Induction of cross-priming of naive CD8+ T lymphocytes by recombinant bacillus Calmette-Guerin that secretes heat shock protein 70-major membrane protein-II fusion protein.

PubMed

Mukai, Tetsu; Maeda, Yumi; Tamura, Toshiki; Matsuoka, Masanori; Tsukamoto, Yumiko; Makino, Masahiko

2009-11-15

Because Mycobacterium bovis bacillus Calmette-Guérin (BCG) unconvincingly activates human naive CD8(+) T cells, a rBCG (BCG-70M) that secretes a fusion protein comprising BCG-derived heat shock protein (HSP)70 and Mycobacterium leprae-derived major membrane protein (MMP)-II, one of the immunodominant Ags of M. leprae, was newly constructed to potentiate the ability of activating naive CD8(+) T cells through dendritic cells (DC). BCG-70M secreted HSP70-MMP-II fusion protein in vitro, which stimulated DC to produce IL-12p70 through TLR2. BCG-70M-infected DC activated not only memory and naive CD8(+) T cells, but also CD4(+) T cells of both types to produce IFN-gamma. The activation of these naive T cells by BCG-70M was dependent on the MHC and CD86 molecules on BCG-70M-infected DC, and was significantly inhibited by pretreatment of DC with chloroquine. Both brefeldin A and lactacystin significantly inhibited the activation of naive CD8(+) T cells by BCG-70M through DC. Thus, the CD8(+) T cell activation may be induced by cross-presentation of Ags through a TAP- and proteosome-dependent cytosolic pathway. When naive CD8(+) T cells were stimulated by BCG-70M-infected DC in the presence of naive CD4(+) T cells, CD62L(low)CD8(+) T cells and perforin-producing CD8(+) T cells were efficiently produced. MMP-II-reactive CD4(+) and CD8(+) memory T cells were efficiently produced in C57BL/6 mice by infection with BCG-70M. These results indicate that BCG-70M activated DC, CD4(+) T cells, and CD8(+) T cells, and the combination of HSP70 and MMP-II may be useful for inducing better T cell activation.

Draft Detailed Project Report and Draft Environmental Assessment. Neah Bay Navigation Improvements, Neah Bay, Washington

DTIC Science & Technology

1993-11-01

navigation improvements for Neah Bay, Clallam Bay, and Port Angeles was begun under the Puget Sound and Adjacent Waters, General Investigations authority. The...Regonnaissance Report and Plan of Study. Puget Sound and Adjacent Waters. Washington. Northern Olympic Peninsula Shallow-Draft Naviaation Study, August 1983...operators from having to make long trips from the fishing grounds near Neah Bay to ports farther east in the Strait of Juan de Fuca or in Puget Sound . 9 9

33 CFR 117.871 - Coos Bay.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 33 Navigation and Navigable Waters 1 2014-07-01 2014-07-01 false Coos Bay. 117.871 Section 117.871 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY BRIDGES DRAWBRIDGE OPERATION REGULATIONS Specific Requirements Oregon § 117.871 Coos Bay. The draw of the Port of Coos Bay railroad bridge...

33 CFR 117.871 - Coos Bay.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 33 Navigation and Navigable Waters 1 2013-07-01 2013-07-01 false Coos Bay. 117.871 Section 117.871 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY BRIDGES DRAWBRIDGE OPERATION REGULATIONS Specific Requirements Oregon § 117.871 Coos Bay. The draw of the Port of Coos Bay railroad bridge...

33 CFR 117.871 - Coos Bay.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 33 Navigation and Navigable Waters 1 2012-07-01 2012-07-01 false Coos Bay. 117.871 Section 117.871 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY BRIDGES DRAWBRIDGE OPERATION REGULATIONS Specific Requirements Oregon § 117.871 Coos Bay. The draw of the Port of Coos Bay railroad bridge...

33 CFR 117.871 - Coos Bay.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 33 Navigation and Navigable Waters 1 2011-07-01 2011-07-01 false Coos Bay. 117.871 Section 117.871 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY BRIDGES DRAWBRIDGE OPERATION REGULATIONS Specific Requirements Oregon § 117.871 Coos Bay. The draw of the Port of Coos Bay railroad bridge...

33 CFR 117.871 - Coos Bay.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false Coos Bay. 117.871 Section 117.871 Navigation and Navigable Waters COAST GUARD, DEPARTMENT OF HOMELAND SECURITY BRIDGES DRAWBRIDGE OPERATION REGULATIONS Specific Requirements Oregon § 117.871 Coos Bay. The draw of the Port of Coos Bay railroad bridge...

Cognitive Performance Under Electroconvulsive Therapy (ECT) in ECT-Naive Treatment-Resistant Patients With Major Depressive Disorder.

PubMed

Ziegelmayer, Christoph; Hajak, Göran; Bauer, Anne; Held, Marion; Rupprecht, Rainer; Trapp, Wolfgang

2017-06-01

Although electroconvulsive therapy (ECT) is considered a safe and highly effective treatment option for major depressive disorder, there are still some reservations with regard to possible adverse cognitive adverse effects. This is the case despite a large body of evidence showing that these deficits are transient and that there even seems to be a long-term improvement of cognitive functioning level. However, most data concerning cognitive adverse effects stem from studies using mixed samples of treatment-resistant and non-treatment-resistant as well as ECT-naive and non-ECT-naive subjects. Furthermore, neurocognitive measures might partly be sensitive to practice effects and improvements in depressive symptom level. We examined neurocognitive performance in a sample of 20 treatment-resistant and ECT-naive subjects using repeatable neurocognitive tests, whereas changes in depressive symptom level were controlled. Cognitive functioning level was assessed before (baseline), 1 week, and 6 months (follow-up 1 and 2) after (12 to) 15 sessions of unilateral ECT treatment. No adverse cognitive effects were observed in any of the cognitive domains examined. Instead, a significant improvement in verbal working memory performance was found from baseline to follow-up 2. When changes in depressive symptom levels were controlled statistically, this improvement was no longer seen. Although findings that ECT does not lead to longer lasting cognitive deficits caused by ECT were confirmed, our study adds evidence that previous results of a beneficial effect of ECT on cognition might be questioned.

Responses of upland herpetofauna to the restoration of Carolina Bays and thinning of forested Bay Margins.

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

Ledvina, Joseph A.

2008-05-01

Research on the effects of wetland restoration on reptiles and amphibians is becoming more common, but almost all of these studies have observed the colonization of recently disturbed habitats that were completely dry at the time of restoration. In a similar manner, investigations herpetofaunal responses to forest management have focused on clearcuts, and less intensive stand manipulations are not as well studied. To evaluate community and population responses of reptiles and amphibians to hydrology restoration and canopy removal in the interior of previously degraded Carolina bays, I monitored herpetofauna in the uplands adjacent to six historically degraded Carolina bays atmore » the Savannah River Site (SRS) in South Carolina for four years after restoration. To evaluate the effects of forest thinning on upland herpetofauna, forests were thinned in the margins of three of these bays. I used repeated measures ANOVA to compare species richness and diversity and the abundance of selected species and guilds between these bays and with those at three reference bays that were not historically drained and three control bays that remained degraded. I also used Non-metric Multidimensional Scaling (NMDS) to look for community-level patterns based treatments.« less

Dynamic system classifier.

PubMed

Pumpe, Daniel; Greiner, Maksim; Müller, Ewald; Enßlin, Torsten A

2016-07-01

Stochastic differential equations describe well many physical, biological, and sociological systems, despite the simplification often made in their derivation. Here the usage of simple stochastic differential equations to characterize and classify complex dynamical systems is proposed within a Bayesian framework. To this end, we develop a dynamic system classifier (DSC). The DSC first abstracts training data of a system in terms of time-dependent coefficients of the descriptive stochastic differential equation. Thereby the DSC identifies unique correlation structures within the training data. For definiteness we restrict the presentation of the DSC to oscillation processes with a time-dependent frequency ω(t) and damping factor γ(t). Although real systems might be more complex, this simple oscillator captures many characteristic features. The ω and γ time lines represent the abstract system characterization and permit the construction of efficient signal classifiers. Numerical experiments show that such classifiers perform well even in the low signal-to-noise regime.

A Bayes linear Bayes method for estimation of correlated event rates.

PubMed

Quigley, John; Wilson, Kevin J; Walls, Lesley; Bedford, Tim

2013-12-01

Typically, full Bayesian estimation of correlated event rates can be computationally challenging since estimators are intractable. When estimation of event rates represents one activity within a larger modeling process, there is an incentive to develop more efficient inference than provided by a full Bayesian model. We develop a new subjective inference method for correlated event rates based on a Bayes linear Bayes model under the assumption that events are generated from a homogeneous Poisson process. To reduce the elicitation burden we introduce homogenization factors to the model and, as an alternative to a subjective prior, an empirical method using the method of moments is developed. Inference under the new method is compared against estimates obtained under a full Bayesian model, which takes a multivariate gamma prior, where the predictive and posterior distributions are derived in terms of well-known functions. The mathematical properties of both models are presented. A simulation study shows that the Bayes linear Bayes inference method and the full Bayesian model provide equally reliable estimates. An illustrative example, motivated by a problem of estimating correlated event rates across different users in a simple supply chain, shows how ignoring the correlation leads to biased estimation of event rates. © 2013 Society for Risk Analysis.

Can-Evo-Ens: Classifier stacking based evolutionary ensemble system for prediction of human breast cancer using amino acid sequences.

PubMed

Ali, Safdar; Majid, Abdul

2015-04-01

The diagnostic of human breast cancer is an intricate process and specific indicators may produce negative results. In order to avoid misleading results, accurate and reliable diagnostic system for breast cancer is indispensable. Recently, several interesting machine-learning (ML) approaches are proposed for prediction of breast cancer. To this end, we developed a novel classifier stacking based evolutionary ensemble system "Can-Evo-Ens" for predicting amino acid sequences associated with breast cancer. In this paper, first, we selected four diverse-type of ML algorithms of Naïve Bayes, K-Nearest Neighbor, Support Vector Machines, and Random Forest as base-level classifiers. These classifiers are trained individually in different feature spaces using physicochemical properties of amino acids. In order to exploit the decision spaces, the preliminary predictions of base-level classifiers are stacked. Genetic programming (GP) is then employed to develop a meta-classifier that optimal combine the predictions of the base classifiers. The most suitable threshold value of the best-evolved predictor is computed using Particle Swarm Optimization technique. Our experiments have demonstrated the robustness of Can-Evo-Ens system for independent validation dataset. The proposed system has achieved the highest value of Area Under Curve (AUC) of ROC Curve of 99.95% for cancer prediction. The comparative results revealed that proposed approach is better than individual ML approaches and conventional ensemble approaches of AdaBoostM1, Bagging, GentleBoost, and Random Subspace. It is expected that the proposed novel system would have a major impact on the fields of Biomedical, Genomics, Proteomics, Bioinformatics, and Drug Development. Copyright © 2015 Elsevier Inc. All rights reserved.

33 CFR 165.1195 - Regulated Navigation Area; Humboldt Bay Bar Channel and Humboldt Bay Entrance Channel, Humboldt...

Code of Federal Regulations, 2010 CFR

2010-07-01

... Navigation Area (RNA) includes all navigable waters of the Humboldt Bay Bar Channel and the Humboldt Bay Entrance Channel, Humboldt Bay, California. (b) Definitions. As used in this section— COTP means the Captain of the Port as defined in Title 33, Code of Federal Regulations, Section 1.01-30 and 3.55-20...

33 CFR 165.1195 - Regulated Navigation Area; Humboldt Bay Bar Channel and Humboldt Bay Entrance Channel, Humboldt...

Code of Federal Regulations, 2011 CFR

2011-07-01

... Navigation Area (RNA) includes all navigable waters of the Humboldt Bay Bar Channel and the Humboldt Bay Entrance Channel, Humboldt Bay, California. (b) Definitions. As used in this section— COTP means the Captain of the Port as defined in Title 33, Code of Federal Regulations, Section 1.01-30 and 3.55-20...

33 CFR 165.1195 - Regulated Navigation Area; Humboldt Bay Bar Channel and Humboldt Bay Entrance Channel, Humboldt...

Code of Federal Regulations, 2012 CFR

2012-07-01

... Navigation Area (RNA) includes all navigable waters of the Humboldt Bay Bar Channel and the Humboldt Bay Entrance Channel, Humboldt Bay, California. (b) Definitions. As used in this section— COTP means the Captain of the Port as defined in Title 33, Code of Federal Regulations, Section 1.01-30 and 3.55-20...

33 CFR 165.1195 - Regulated Navigation Area; Humboldt Bay Bar Channel and Humboldt Bay Entrance Channel, Humboldt...

Code of Federal Regulations, 2013 CFR

2013-07-01

... Navigation Area (RNA) includes all navigable waters of the Humboldt Bay Bar Channel and the Humboldt Bay Entrance Channel, Humboldt Bay, California. (b) Definitions. As used in this section— COTP means the Captain of the Port as defined in Title 33, Code of Federal Regulations, Section 1.01-30 and 3.55-20...

33 CFR 165.1195 - Regulated Navigation Area; Humboldt Bay Bar Channel and Humboldt Bay Entrance Channel, Humboldt...

Code of Federal Regulations, 2014 CFR

2014-07-01

... Navigation Area (RNA) includes all navigable waters of the Humboldt Bay Bar Channel and the Humboldt Bay Entrance Channel, Humboldt Bay, California. (b) Definitions. As used in this section— COTP means the Captain of the Port as defined in Title 33, Code of Federal Regulations, Section 1.01-30 and 3.55-20...

Naive-like Conversion Overcomes the Limited Differentiation Capacity of Induced Pluripotent Stem Cells*

PubMed Central

Honda, Arata; Hatori, Masanori; Hirose, Michiko; Honda, Chizumi; Izu, Haruna; Inoue, Kimiko; Hirasawa, Ryutaro; Matoba, Shogo; Togayachi, Sumie; Miyoshi, Hiroyuki; Ogura, Atsuo

2013-01-01

Although induced pluripotent stem (iPS) cells are indistinguishable from ES cells in their expression of pluripotent markers, their differentiation into targeted cells is often limited. Here, we examined whether the limited capacity of iPS cells to differentiate into neural lineage cells could be mitigated by improving their base-line level of pluripotency, i.e. by converting them into the so-called “naive” state. In this study, we used rabbit iPS and ES cells because of the easy availability of both cell types and their typical primed state characters. Repeated passages of the iPS cells permitted their differentiation into early neural cell types (neural stem cells, neurons, and glial astrocytes) with efficiencies similar to ES cells. However, unlike ES cells, their ability to differentiate later into neural cells (oligodendrocytes) was severely compromised. In contrast, after these iPS cells had been converted to a naive-like state, they readily differentiated into mature oligodendrocytes developing characteristic ramified branches, which could not be attained even with ES cells. These results suggest that the naive-like conversion of iPS cells might endow them with a higher differentiation capacity. PMID:23880763

Personality matters: individual variation in reactions of naive bird predators to aposematic prey.

PubMed

Exnerová, Alice; Svádová, Katerina Hotová; Fucíková, Eva; Drent, Pieter; Stys, Pavel

2010-03-07

Variation in reactions to aposematic prey is common among conspecific individuals of bird predators. It may result from different individual experience but it also exists among naive birds. This variation may possibly be explained by the effect of personality--a complex of correlated, heritable behavioural traits consistent across contexts. In the great tit (Parus major), two extreme personality types have been defined. 'Fast' explorers are bold, aggressive and routine-forming; 'slow' explorers are shy, non-aggressive and innovative. Influence of personality type on unlearned reaction to aposematic prey, rate of avoidance learning and memory were tested in naive, hand-reared great tits from two opposite lines selected for exploration (slow against fast). The birds were subjected to a sequence of trials in which they were offered aposematic adult firebugs (Pyrrhocoris apterus). Slow birds showed a greater degree of unlearned wariness and learned to avoid the firebugs faster than fast birds. Although birds of both personality types remembered their experience, slow birds were more cautious in the memory test. We conclude that not only different species but also populations of predators that differ in proportions of personality types may have different impacts on survival of aposematic insects under natural conditions.

Florida Bay: A history of recent ecological changes

USGS Publications Warehouse

Fourqurean, J.W.; Robblee, M.B.

1999-01-01

Florida Bay is a unique subtropical estuary at the southern tip of the Florida peninsula. Recent ecological changes (seagrass die-off, algal blooms, increased turbidity) to the Florida Bay ecosystem have focused the attention of the public, commercial interests, scientists, and resource managers on the factors influencing the structure and function of Florida Bay. Restoring Florida Bay to some historic condition is the goal of resource managers, but what is not clear is what an anthropogenically-unaltered Florida Bay would look like. While there is general consensus that human activities have contributed to the changes occurring in the Florida Bay ecosystem, a high degree of natural system variability has made elucidation of the links between human activity and Florida Bay dynamics difficult. Paleoecological analyses, examination of long-term datasets, and directed measurements of aspects of the ecology of Florida Bay all contribute to our understanding of the behavior of the bay, and allow quantification of the magnitude of the recent ecological changes with respect to historical variability of the system.

Evolving optimised decision rules for intrusion detection using particle swarm paradigm

NASA Astrophysics Data System (ADS)

Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

2012-12-01

The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

Ideal discrimination of discrete clinical endpoints using multilocus genotypes.

PubMed

Hahn, Lance W; Moore, Jason H

2004-01-01

Multifactor Dimensionality Reduction (MDR) is a method for the classification and prediction of discrete clinical endpoints using attributes constructed from multilocus genotype data. Empirical studies with both real and simulated data suggest that MDR has good power for detecting gene-gene interactions in the absence of independent main effects. The purpose of this study is to develop an objective, theory-driven approach to evaluate the strengths and limitations of MDR. To accomplish this goal, we borrow concepts from ideal observer analysis used in visual perception to evaluate the theoretical limits of classifying and predicting discrete clinical endpoints using multilocus genotype data. We conclude that MDR ideally discriminates between low risk and high risk subjects using attributes constructed from multilocus genotype data. We also how that the classification approach used once a multilocus attribute is constructed is similar to that of a naive Bayes classifier. This study provides a theoretical foundation for the continued development, evaluation, and application of the MDR as a data mining tool in the domain of statistical genetics and genetic epidemiology.

Implementation and performance evaluation of acoustic denoising algorithms for UAV

NASA Astrophysics Data System (ADS)

Chowdhury, Ahmed Sony Kamal

Unmanned Aerial Vehicles (UAVs) have become popular alternative for wildlife monitoring and border surveillance applications. Elimination of the UAV's background noise and classifying the target audio signal effectively are still a major challenge. The main goal of this thesis is to remove UAV's background noise by means of acoustic denoising techniques. Existing denoising algorithms, such as Adaptive Least Mean Square (LMS), Wavelet Denoising, Time-Frequency Block Thresholding, and Wiener Filter, were implemented and their performance evaluated. The denoising algorithms were evaluated for average Signal to Noise Ratio (SNR), Segmental SNR (SSNR), Log Likelihood Ratio (LLR), and Log Spectral Distance (LSD) metrics. To evaluate the effectiveness of the denoising algorithms on classification of target audio, we implemented Support Vector Machine (SVM) and Naive Bayes classification algorithms. Simulation results demonstrate that LMS and Discrete Wavelet Transform (DWT) denoising algorithm offered superior performance than other algorithms. Finally, we implemented the LMS and DWT algorithms on a DSP board for hardware evaluation. Experimental results showed that LMS algorithm's performance is robust compared to DWT for various noise types to classify target audio signals.

Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

PubMed

Pashaei, Elnaz; Ozen, Mustafa; Aydin, Nizamettin

2015-08-01

Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classifier by applying Boosted C5.0 decision tree as the fitness function. To evaluate the effectiveness of our proposed method, it is implemented on 1 microarray dataset and 5 different medical data sets obtained from UCI machine learning databases. Moreover, the results of PSO + Boosted C5.0 implementation are compared to eight well-known benchmark classification methods (PSO+C4.5, support vector machine under the kernel of Radial Basis Function, Classification And Regression Tree (CART), C4.5 decision tree, C5.0 decision tree, Boosted C5.0 decision tree, Naive Bayes and Weighted K-Nearest neighbor). Repeated five-fold cross-validation method was used to justify the performance of classifiers. Experimental results show that our proposed method not only improve the performance of PSO+C4.5 but also obtains higher classification accuracy compared to the other classification methods.

Variation in the vitreoretinal configuration of Stage 4 retinopathy of prematurity in photocoagulated and treatment naive eyes undergoing vitrectomy

PubMed Central

Gadkari, Salil Sharad; Deshpande, Madan

2017-01-01

Purpose: We sought to document the difference in the vitreoretinal configuration of Stage 4 retinopathy of prematurity (ROP) in photocoagulated and treatment naive eyes undergoing vitrectomy and to correlate it with surgical complexity. Methods: Consecutive eyes posted for vitrectomy with Stage 4 ROP were documented preoperatively using a RetCam for the presence of peripheral traction (PT), presence of central traction just outside the arcades, and presence of traction extending to the lens. A note was made of the following intraoperative events: lensectomy, intraoperative bleeding, and iatrogenic breaks. Wilcoxon rank-sum test was used for analysis. Results: From a total of 46 eyes, 16 and 30 eyes were from the treated and treatment naive group, respectively. More eyes in the treated group had central (P < 0.0001) and lenticular traction (P = 0.022). More eyes in the untreated group had PT (P < 0.0001). A significant number of eyes without photocoagulation needed lensectomy (P = 0.042), and no difference in intraoperative bleeding (P = 0.94) was demonstrable. Iatrogenic retinotomy occurred in three eyes, all naive. Notably, age at surgery was more in the untreated group (P = 0.00008). Conclusion: Vasoproliferative activity in all retinopathies occurs at the junction of the ischemic and nonischemic retina. In the natural course of ROP, this takes place peripherally, at the ridge. In photocoagulated eyes, this junction is displaced posteriorly due to peripheral ablation. Treated eyes manifested with posterior proliferative changes and were more amenable to lens-sparing vitrectomy. Naive eyes were older when they underwent surgery to relieve PT with greater chances of lensectomy and iatrogenic breaks. PMID:28905829

Eastern Hudson Bay, Canada

NASA Image and Video Library

2017-12-08

Each winter sea ice forms over the salty waters of frigid northeastern Canada's Hudson Bay. As sunlight lengthens and weather warms, ice begins to break up and melt, with retreat typically starting in May and melt-out completed sometime in July. Since the 1970s, the timing of sea ice breakup in Hudson Bay has changed, with melting beginning earlier in the spring. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA’s Aqua satellite captured this a true-color image of Hudson Bay on March 26, 2013. Although snow still covers the surrounding land, ice has already begun to retreat from much of the eastern shore of the Bay visible in the image. A ring of bright white ice remains solidly frozen around the Belcher Islands in the southeast section of the Bay, but this ring is surrounded by blue waters and large chunks of ice. In the southwest, a similar situation is seen at Akimiski Island. The shelf of bright white ice gives way to open water in the south, as well as fractured, blue-tinted ice. The blue tint generally indicates water logging as ice begins to soften. The Aqua satellite captured a similar image of early ice melt on Hudson Bay on April 6, 2012. That image can be viewed at: modis.gsfc.nasa.gov/gallery/individual.php?db_date=2012-0... NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Chesapeake Bay Program Grant Guidance

EPA Pesticide Factsheets

Grant Guidance and appendices for the Chesapeake Bay Program that describes how the U.S. Environmental Protection Agency’s (EPA) Region 3’s Chesapeake Bay Program Office (CBPO) administers grant and cooperative agreement funds.

Subsurface structure of the East Bay Plain ground-water basin: San Francisco Bay to the Hayward fault, Alameda County, California

USGS Publications Warehouse

Catchings, R.D.; Borchers, J.W.; Goldman, M.R.; Gandhok, G.; Ponce, D.A.; Steedman, C.E.

2006-01-01

The area of California between the San Francisco Bay, San Pablo Bay, Santa Clara Valley, and the Diablo Ranges (East Bay Hills), commonly referred to as the 'East Bay', contains the East Bay Plain and Niles Cone ground-water basins. The area has a population of 1.46 million (2003 US Census), largely distributed among several cities, including Alameda, Berkeley, Fremont, Hayward, Newark, Oakland, San Leandro, San Lorenzo, and Union City. Major known tectonic structures in the East Bay area include the Hayward Fault and the Diablo Range to the east and a relatively deep sedimentary basin known as the San Leandro Basin beneath the eastern part of the bay. Known active faults, such as the Hayward, Calaveras, and San Andreas pose significant earthquake hazards to the region, and these and related faults also affect ground-water flow in the San Francisco Bay area. Because most of the valley comprising the San Francisco Bay area is covered by Holocene alluvium or water at the surface, our knowledge of the existence and locations of such faults, their potential hazards, and their effects on ground-water flow within the alluvial basins is incomplete. To better understand the subsurface stratigraphy and structures and their effects on ground-water and earthquake hazards, the U.S. Geological Survey (USGS), in cooperation with the East Bay Municipal Utility District (EBMUD), acquired a series of high-resolution seismic reflection and refraction profiles across the East Bay Plain near San Leandro in June 2002. In this report, we present results of the seismic imaging investigations, with emphasis on ground water.

The landscape pattern characteristics of coastal wetlands in Jiaozhou Bay under the impact of human activities.

PubMed

Gu, Dongqi; Zhang, Yuanzhi; Fu, Jun; Zhang, Xuliang

2007-01-01

In this study, we interpreted coastal wetland types from an ASTER satellite image in 2002, and then compared the results with the land-use status of coastal wetlands in 1952 to determine the wetland loss and degradation around Jiaozhou Bay. Seven types of wetland landscape were classified, namely: shallow open water, inter-tidal flats, estuarine water, brackish marshes, salt ponds, fishery ponds and ports. Several landscape pattern indices were analysed: the results indicate that the coastal wetlands have been seriously degraded. More and more natural wetlands have been transformed into artificial wetlands, which covered about 33.7% of the total wetlands in 2002. In addition, we used a defined model to assess the impacts of human activities on coastal wetlands. The results obtained show that the coastal wetlands of Jiaozhou Bay have suffered severe human disturbance. Effective coastal management and control is therefore needed to solve the issues of the coastal wetland loss and degradation existing in this area.

Impact of the Data Collection on Adverse Events of Anti-HIV Drugs cohort study on abacavir prescription among treatment-naive, HIV-infected patients in Canada.

PubMed

Antoniou, Tony; Gillis, Jennifer; Loutfy, Mona R; Cooper, Curtis; Hogg, Robert S; Klein, Marina B; Machouf, Nima; Montaner, Julio S G; Rourke, Sean B; Tsoukas, Chris; Raboud, Janet M

2014-01-01

To evaluate the trends in abacavir (ABC) prescription among antiretroviral (ARV) medication-naive individuals following the presentation of the Data Collection on Adverse Events of Anti-HIV Drugs (DAD) cohort study. We conducted a retrospective cohort study of ARV medication-naive individuals in the Canadian Observational Cohort (CANOC). Between January 1, 2000, and February 28, 2010, a total of 7280 ARV medication-naive patients were included in CANOC. We observed a significant change in the proportion of new ABC prescriptions immediately following the release of DAD (-11%; 95% confidence interval [CI]: -20% to -2.4%) and in the months following the presentation of these data (-0.66% per month; 95% CI: -1.2% to -0.073%). A post-DAD presentation decrease in the odds of being prescribed ABC versus tenofovir (TDF) was observed (adjusted odds ratio, 0.72 per year, 95% CI: 0.54-0.97). Presentation of the DAD was associated with a significant decrease in ABC use among ARV medication-naive, HIV-positive patients initiating therapy.

Plasma homovanillic acid levels and therapeutic outcome in schizophrenics: comparisons of neuroleptic-naive first-episode patients and patients with disease exacerbation due to neuroleptic discontinuance.

PubMed

Akiyama, K; Tsuchida, K; Kanzaki, A; Ujike, H; Hamamura, T; Kondo, K; Mutoh, S; Miyanagi, K; Kuroda, S; Otsuki, S

1995-11-15

Plasma homovanillic acid (pHVA) levels were measured and the Brief Psychiatric Rating Scale (BPRS) scores were evaluated in 26 schizophrenic patients who had either never been medicated (neuroleptic-naive, first-episode subjects) or whose condition had become exacerbated following neuroleptic discontinuance (exacerbated subjects). All the subjects received medication with a fixed dose of a neuroleptic (haloperidol or fluphenazine, both 9 mg/day) for the first week and variable doses for the subsequent 4 weeks. In the neuroleptic-naive subjects, pHVA levels increased significantly 1 week after starting the protocol; this increase correlated significantly with clinical improvement of the BPRS positive symptom scores at week 5. In the neuroleptic-naive subjects, pHVA levels had declined to the baseline level by week 5. In the exacerbated subjects, there were no significant correlations between pHVA level changes at week 1 and later improvements of the BPRS positive symptom scores. These results suggest that the rise in pHVA levels occurring within 1 week after starting a fixed neuroleptic dose may predict a favorable clinical response in neuroleptic-naive schizophrenic patients.

Comparative analysis of drug resistance mutations in the human immunodeficiency virus reverse transcriptase gene in patients who are non-responsive, responsive and naive to antiretroviral therapy.

PubMed

Misbah, Mohammad; Roy, Gaurav; Shahid, Mudassar; Nag, Nalin; Kumar, Suresh; Husain, Mohammad

2016-05-01

Drug resistance mutations in the Pol gene of human immunodeficiency virus 1 (HIV-1) are one of the critical factors associated with antiretroviral therapy (ART) failure in HIV-1 patients. The issue of resistance to reverse transcriptase inhibitors (RTIs) in HIV infection has not been adequately addressed in the Indian subcontinent. We compared HIV-1 reverse transcriptase (RT) gene sequences to identify mutations present in HIV-1 patients who were ART non-responders, ART responders and drug naive. Genotypic drug resistance testing was performed by sequencing a 655-bp region of the RT gene from 102 HIV-1 patients, consisting of 30 ART-non-responding, 35 ART-responding and 37 drug-naive patients. The Stanford HIV Resistance Database (HIVDBv 6.2), IAS-USA mutation list, ANRS_09/2012 algorithm, and Rega v8.02 algorithm were used to interpret the pattern of drug resistance. The majority of the sequences (96 %) belonged to subtype C, and a few of them (3.9 %) to subtype A1. The frequency of drug resistance mutations observed in ART-non-responding, ART-responding and drug-naive patients was 40.1 %, 10.7 % and 20.58 %, respectively. It was observed that in non-responders, multiple mutations were present in the same patient, while in responders, a single mutation was found. Some of the drug-naive patients had more than one mutation. Thymidine analogue mutations (TAMs), however, were found in non-responders and naive patients but not in responders. Although drug resistance mutations were widely distributed among ART non-responders, the presence of resistance mutations in the viruses of drug-naive patients poses a big concern in the absence of a genotyping resistance test.

Acute cognitive impact of antiseizure drugs in naive rodents and corneal-kindled mice.

PubMed

Barker-Haliski, Melissa L; Vanegas, Fabiola; Mau, Matthew J; Underwood, Tristan K; White, H Steve

2016-09-01

Some antiseizure drugs (ASDs) are associated with cognitive liability in patients with epilepsy, thus ASDs without this risk would be preferred. Little comparative pharmacology exists with ASDs in preclinical models of cognition. Few pharmacologic studies exist on the acute effects in rodents with chronic seizures. Predicting risk for cognitive impact with preclinical models may supply valuable ASD differentiation data. ASDs (phenytoin [PHT]; carbamazepine [CBZ]; valproic acid [VPA]; lamotrigine [LTG]; phenobarbital [PB]; tiagabine [TGB]; retigabine [RTG]; topiramate [TPM]; and levetiracetam [LEV]) were administered equivalent to maximal electroshock median effective dose ([ED50]; mice, rats), or median dose necessary to elicit minimal motor impairment (median toxic dose [TD50]; rats). Cognition models with naive adult rodents were novel object/place recognition (NOPR) task with CF-1 mice, and Morris water maze (MWM) with Sprague-Dawley rats. Selected ASDs were also administered to rats prior to testing in an open field. The effect of chronic seizures and ASD administration on cognitive performance in NOPR was also determined with corneal-kindled mice. Mice that did not achieve kindling criterion (partially kindled) were included to examine the effect of electrical stimulation on cognitive performance. Sham-kindled and age-matched mice were also tested. No ASD (ED50) affected latency to locate the MWM platform; TD50 of PB, RTG, TPM, and VPA reduced this latency. In naive mice, CBZ and VPA (ED50) reduced time with the novel object. Of interest, no ASD (ED50) affected performance of fully kindled mice in NOPR, whereas CBZ and LEV improved cognitive performance of partially kindled mice. Standardized approaches to the preclinical evaluation of an ASD's potential cognitive impact are needed to inform drug development. This study demonstrated acute, dose- and model-dependent effects of therapeutically relevant doses of ASDs on cognitive performance of naive mice and

Is Children's Naive Knowledge Consistent?: A Comparison of the Concepts of Sound and Heat

ERIC Educational Resources Information Center

Lautrey, Jacques; Mazens, Karine

2004-01-01

The aim of this study was to shed some light on the organization of naive knowledge, and on the process of conceptual change in everyday physics, more specifically regarding the concepts of sound and heat. Eighty-three 8-year-old children were interviewed individually in order to see if they attributed the properties of objects (such as…

Privacy-Preserving Classifier Learning

NASA Astrophysics Data System (ADS)

Brickell, Justin; Shmatikov, Vitaly

We present an efficient protocol for the privacy-preserving, distributed learning of decision-tree classifiers. Our protocol allows a user to construct a classifier on a database held by a remote server without learning any additional information about the records held in the database. The server does not learn anything about the constructed classifier, not even the user’s choice of feature and class attributes.

Bay Mills' Bold Approach

ERIC Educational Resources Information Center

Freedman, Eric

2011-01-01

It's a long, long way from Bay Mills Community College, near the shores of frigid Lake Superior, to Detroit. But distance, time and demographics aside, the school and the city are united by Bay Mills' status as the nation's only tribally controlled college that authorizes quasi-public schools, known officially as public school academies. And it's…

The reproducibility of adenosine monophosphate bronchial challenges in mild, steroid-naive asthmatics

PubMed Central

Singh, Dave; Fairwood, Jennifer; Murdoch, Robert; Weeks, Amanda; Russell, Paul; Roy, Kay; Langley, Steve; Woodcock, Ashley

2008-01-01

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT Repeated adenosine monophosphate (AMP) challenges are used to assess drug effects in asthma clinical trials, but may be prone to tachyphylaxis when repeated at short intervals. Possible tachyphylaxis at 12- and 24-h intervals has not been studied. WHAT THIS STUDY ADDS Clinically relevant tachyphylaxis after repeated AMP challenges does not occur when repeated at 12- and 24-h intervals. AMP challenges at these intervals can be used to assess drug effects in clinical trials. AIMS Repeated adenosine monophosphate (AMP) challenges are used to assess drug efficacy in clinical trials of mild, steroid-naive asthmatics. Refractoriness has been reported after repeated challenges over short intervals. This study evaluated possible tachyphylaxis after repeated AMP challenges at 12 and 24 h in mild, steroid-naive asthmatics. METHODS This was an open, three-way crossover study. Twenty-six steroid-naive asthmatic subjects were randomized to the following AMP challenge regimens separated by 7–14 days: (A) challenge at 08.00 h, repeated 24 h later; (B) challenge at 08.00 h, repeated 12 and 24 h later; (C) challenge at 20.00 h, repeated 12 h later. Comparisons within day were assessed using 90% confidence intervals (CIs). Non-inferiority approach taken with 1 doubling concentration (DC) as a clinically relevant difference. RESULTS Regimen A: Significant increase in AMP reactivity at 24 h. Mean DC difference was 0.6 (90% CI 0.24, 0.96). Regimen B: No evidence of difference between AMP reactivity at 08.00 h and a repeated challenge 12 h later. Repeated challenge at 24 h caused a significant increase in provocation concentration (PC)20 compared with 12 h (mean DC difference 0.48, 90% CI 0.02, 0.95) and 0 h (mean DC difference 0.82, 90% CI 0.49, 1.14 – the upper CI exceeds the criteria of 1 DC). Challenge regimen C: No difference between challenges; mean DC difference of 0.28 (90% CI −0.2, 0.76). CONCLUSION The small decline in AMP

Experience of dolutegravir in HIV-infected treatment-naive patients from a tertiary care University Hospital in Ireland

PubMed Central

Waqas, Sarmad; O’Connor, Mairead; Levey, Ciara; Mallon, Paddy; Sheehan, Gerard; Patel, Anjali; Avramovic, Gordana; Lambert, John S

2016-01-01

Objective: Dolutegravir, an HIV integrase inhibitor, is a relatively new treatment option. To assess the tolerability, side effects, and time to viral decline to non-detectable in patients newly started on dolutegravir. Methods: Retrospective health care record of 61 consecutive HIV treatment-naive patients started on dolutegravir was reviewed and analysed on SPSS. Results: The mean initial viral load was 160826.05 copies/mL (range, 79–1,126,617 copies/mL). HIV viral load became non-detectable in 63.9% of patients on dolutegravir within 3 months. In all, 60.7% of patients reported no side effects on dolutegravir; 98.4% of the patients claimed full compliance to their antiretrovirals. Conclusion: Dolutegravir was found to be efficacious and well tolerated in HIV-infected treatment-naive patients. PMID:27826447

Application of recurrence quantification analysis for the automated identification of epileptic EEG signals.

PubMed

Acharya, U Rajendra; Sree, S Vinitha; Chattopadhyay, Subhagata; Yu, Wenwei; Ang, Peng Chuan Alvin

2011-06-01

Epilepsy is a common neurological disorder that is characterized by the recurrence of seizures. Electroencephalogram (EEG) signals are widely used to diagnose seizures. Because of the non-linear and dynamic nature of the EEG signals, it is difficult to effectively decipher the subtle changes in these signals by visual inspection and by using linear techniques. Therefore, non-linear methods are being researched to analyze the EEG signals. In this work, we use the recorded EEG signals in Recurrence Plots (RP), and extract Recurrence Quantification Analysis (RQA) parameters from the RP in order to classify the EEG signals into normal, ictal, and interictal classes. Recurrence Plot (RP) is a graph that shows all the times at which a state of the dynamical system recurs. Studies have reported significantly different RQA parameters for the three classes. However, more studies are needed to develop classifiers that use these promising features and present good classification accuracy in differentiating the three types of EEG segments. Therefore, in this work, we have used ten RQA parameters to quantify the important features in the EEG signals.These features were fed to seven different classifiers: Support vector machine (SVM), Gaussian Mixture Model (GMM), Fuzzy Sugeno Classifier, K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC), Decision Tree (DT), and Radial Basis Probabilistic Neural Network (RBPNN). Our results show that the SVM classifier was able to identify the EEG class with an average efficiency of 95.6%, sensitivity and specificity of 98.9% and 97.8%, respectively.

Holocene sedimentation in Richardson Bay, California

USGS Publications Warehouse

Connor, Cathy L.

1983-01-01

Examination of foraminifers, diatoms, ostracodes, clay mineralogy, and sediment-size variation from 9 borehole sites along the salt-marsh margins of Richardson Bay reveals a record of gradual infilling of fine-grained estuarine sediments. Over the past 10,000 years this area was transformed from a V-shaped Pleistocene stream valley to a flat-floored arm of the San Francisco Bay estuary. A radiocarbon date obtained from a basal peat overlying nonmarine alluvial sand near the town of Mill Valley indicates that stable salt-marsh vegetation was present in the northwestern arm of Richardson Bay 4600?165 years ago and agrees within error limits with a Holocene sea-level curve developed by Atwater, Hedel, and Helley in 1977 for southern San Francisco Bay. The average sedimentation rate over the last 4600 years is estimated to be 0.2 cm/yr for the inner part of the bay. Comparison of early maps with updated versions as well as studies of marsh plant zonations in disturbed and nondisturbed areas shows that almost half of the marsh in Richardson Bay has been leveed or filled since 1899.

Deriving Chesapeake Bay Water Quality Standards

USGS Publications Warehouse

Tango, Peter J.; Batiuk, Richard A.

2013-01-01

Achieving and maintaining the water quality conditions necessary to protect the aquatic living resources of the Chesapeake Bay and its tidal tributaries has required a foundation of quantifiable water quality criteria. Quantitative criteria serve as a critical basis for assessing the attainment of designated uses and measuring progress toward meeting water quality goals of the Chesapeake Bay Program partnership. In 1987, the Chesapeake Bay Program partnership committed to defining the water quality conditions necessary to protect aquatic living resources. Under section 303(c) of the Clean Water Act, States and authorized tribes have the primary responsibility for adopting water quality standards into law or regulation. The Chesapeake Bay Program partnership worked with U.S. Environmental Protection Agency to develop and publish a guidance framework of ambient water quality criteria with designated uses and assessment procedures for dissolved oxygen, water clarity, and chlorophyll a for Chesapeake Bay and its tidal tributaries in 2003. This article reviews the derivation of the water quality criteria, criteria assessment protocols, designated use boundaries, and their refinements published in six addendum documents since 2003 and successfully adopted into each jurisdiction's water quality standards used in developing the Chesapeake Bay Total Maximum Daily Load.

Strain differences in the neural, behavioral, and molecular correlates of sweet and salty taste in naive, ethanol- and sucrose-exposed P and NP rats

PubMed Central

Coleman, Jamison; Williams, Ashley; Phan, Tam-Hao T.; Mummalaneni, Shobha; Melone, Pamela; Ren, ZuoJun; Zhou, Huiping; Mahavadi, Sunila; Murthy, Karnam S.; Katsumata, Tadayoshi; DeSimone, John A.

2011-01-01

Strain differences between naive, sucrose- and ethanol-exposed alcohol-preferring (P) and alcohol-nonpreferring (NP) rats were investigated in their consumption of ethanol, sucrose, and NaCl; chorda tympani (CT) nerve responses to sweet and salty stimuli; and gene expression in the anterior tongue of T1R3 and TRPV1/TRPV1t. Preference for 5% ethanol and 10% sucrose, CT responses to sweet stimuli, and T1R3 expression were greater in naive P rats than NP rats. The enhancement of the CT response to 0.5 M sucrose in the presence of varying ethanol concentrations (0.5–40%) in naive P rats was higher and shifted to lower ethanol concentrations than NP rats. Chronic ingestion of 5% sucrose or 5% ethanol decreased T1R3 mRNA in NP and P rats. Naive P rats also demonstrated bigger CT responses to NaCl+benzamil and greater TRPV1/TRPV1t expression. TRPV1t agonists produced biphasic effects on NaCl+benzamil CT responses, enhancing the response at low concentrations and inhibiting it at high concentrations. The concentration of a TRPV1/TRPV1t agonist (Maillard reacted peptides conjugated with galacturonic acid) that produced a maximum enhancement in the NaCl+benzamil CT response induced a decrease in NaCl intake and preference in P rats. In naive P rats and NP rats exposed to 5% ethanol in a no-choice paradigm, the biphasic TRPV1t agonist vs. NaCl+benzamil CT response profiles were higher and shifted to lower agonist concentrations than in naive NP rats. TRPV1/TRPV1t mRNA expression increased in NP rats but not in P rats exposed to 5% ethanol in a no-choice paradigm. We conclude that P and NP rats differ in T1R3 and TRPV1/TRPV1t expression and neural and behavioral responses to sweet and salty stimuli and to chronic sucrose and ethanol exposure. PMID:21849614

Strain differences in the neural, behavioral, and molecular correlates of sweet and salty taste in naive, ethanol- and sucrose-exposed P and NP rats.

PubMed

Coleman, Jamison; Williams, Ashley; Phan, Tam-Hao T; Mummalaneni, Shobha; Melone, Pamela; Ren, Zuojun; Zhou, Huiping; Mahavadi, Sunila; Murthy, Karnam S; Katsumata, Tadayoshi; DeSimone, John A; Lyall, Vijay

2011-11-01

Strain differences between naive, sucrose- and ethanol-exposed alcohol-preferring (P) and alcohol-nonpreferring (NP) rats were investigated in their consumption of ethanol, sucrose, and NaCl; chorda tympani (CT) nerve responses to sweet and salty stimuli; and gene expression in the anterior tongue of T1R3 and TRPV1/TRPV1t. Preference for 5% ethanol and 10% sucrose, CT responses to sweet stimuli, and T1R3 expression were greater in naive P rats than NP rats. The enhancement of the CT response to 0.5 M sucrose in the presence of varying ethanol concentrations (0.5-40%) in naive P rats was higher and shifted to lower ethanol concentrations than NP rats. Chronic ingestion of 5% sucrose or 5% ethanol decreased T1R3 mRNA in NP and P rats. Naive P rats also demonstrated bigger CT responses to NaCl+benzamil and greater TRPV1/TRPV1t expression. TRPV1t agonists produced biphasic effects on NaCl+benzamil CT responses, enhancing the response at low concentrations and inhibiting it at high concentrations. The concentration of a TRPV1/TRPV1t agonist (Maillard reacted peptides conjugated with galacturonic acid) that produced a maximum enhancement in the NaCl+benzamil CT response induced a decrease in NaCl intake and preference in P rats. In naive P rats and NP rats exposed to 5% ethanol in a no-choice paradigm, the biphasic TRPV1t agonist vs. NaCl+benzamil CT response profiles were higher and shifted to lower agonist concentrations than in naive NP rats. TRPV1/TRPV1t mRNA expression increased in NP rats but not in P rats exposed to 5% ethanol in a no-choice paradigm. We conclude that P and NP rats differ in T1R3 and TRPV1/TRPV1t expression and neural and behavioral responses to sweet and salty stimuli and to chronic sucrose and ethanol exposure.

Chesapeake Bay plume dynamics from LANDSAT

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.; Fedosh, M. S.

1981-01-01

LANDSAT images with enhancement and density slicing show that the Chesapeake Bay plume usually frequents the Virginia coast south of the Bay mouth. Southwestern (compared to northern) winds spread the plume easterly over a large area. Ebb tide images (compared to flood tide images) show a more dispersed plume. Flooding waters produce high turbidity levels over the shallow northern portion of the Bay mouth.

ASTER Images San Francisco Bay Area

NASA Image and Video Library

2000-04-26

This image of the San Francisco Bay region was acquired on March 3, 2000 by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite. With its 14 spectral bands from the visible to the thermal infrared wavelength region, and its high spatial resolution of 15 to 90 meters about 50 to 300 feet ), ASTER will image Earth for the next 6 years to map and monitor the changing surface of our planet. Image: This image covers an area 60 kilometers (37 miles) wide and 75 kilometers (47 miles) long in three bands of the reflected visible and infrared wavelength region. The combination of bands portrays vegetation in red, and urban areas in gray. Sediment in the Suisun Bay, San Pablo Bay, San Francisco Bay, and the Pacific Ocean shows up as lighter shades of blue. Along the west coast of the San Francisco Peninsula, strong surf can be seen as a white fringe along the shoreline. A powerful rip tide is visible extending westward from Daly City into the Pacific Ocean. In the lower right corner, the wetlands of the South San Francisco Bay National Wildlife Refuge appear as large dark blue and brown polygons. The high spatial resolution of ASTER allows fine detail to be observed in the scene. The main bridges of the area (San Mateo, San Francisco-Oakland Bay, Golden Gate, Richmond-San Rafael, Benicia-Martinez, and Carquinez) are easily picked out, connecting the different communities in the Bay area. Shadows of the towers along the Bay Bridge can be seen over the adjacent bay water. With enlargement the entire road network can be easily mapped; individual buildings are visible, including the shadows of the high-rises in downtown San Francisco. Inset: This enlargement of the San Francisco Airport highlights the high spatial resolution of ASTER. With further enlargement and careful examination, airplanes can be seen at the terminals. http://photojournal.jpl.nasa.gov/catalog/PIA02606

78 FR 59902 - Regulated Navigation Area; Special Buzzards Bay Vessel Regulation, Buzzards Bay, MA

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-30

... DEPARTMENT OF HOMELAND SECURITY Coast Guard 33 CFR Part 165 [Docket No. USCG-2011-0322] RIN 1625-AA11 Regulated Navigation Area; Special Buzzards Bay Vessel Regulation, Buzzards Bay, MA AGENCY: Coast Guard, DHS. ACTION: Notice of extension of comment period. SUMMARY: The Coast Guard is extending the...

19 CFR 7.11 - Guantanamo Bay Naval Station.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 1 2010-04-01 2010-04-01 false Guantanamo Bay Naval Station. 7.11 Section 7.11... TREASURY CUSTOMS RELATIONS WITH INSULAR POSSESSIONS AND GUANTANAMO BAY NAVAL STATION § 7.11 Guantanamo Bay Naval Station. Articles of foreign origin may enter the area (both land and water) of the Guantanamo Bay...

19 CFR 7.11 - Guantanamo Bay Naval Station.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 1 2011-04-01 2011-04-01 false Guantanamo Bay Naval Station. 7.11 Section 7.11... TREASURY CUSTOMS RELATIONS WITH INSULAR POSSESSIONS AND GUANTANAMO BAY NAVAL STATION § 7.11 Guantanamo Bay Naval Station. Articles of foreign origin may enter the area (both land and water) of the Guantanamo Bay...

Estimation of Freshwater Flow to Joe Bay, South Florida.

NASA Astrophysics Data System (ADS)

Zucker, M. A.; Hittle, C. D.

2002-05-01

During the last century, drainage canals were constructed as part of the Central and Southern Flood Control (C&SF) project. Flood control was achieved but degradation to the Everglades ecosystem was evident. Problems related to Florida Bay include sea grass die off, algae blooms, and extreme salinity conditions. Modifications to the C&SF project are proposed as part of the Comprehensive Everglades Restoration Plan (CERP). One objective of CERP is to improve the timing and distribution of freshwater flow within the Everglades ecosystem and to Florida Bay. Several CERP projects propose changes to the existing canal network that borders Everglades National Park (ENP) in southern Miami-Dade County. An examination of flows to Joe Bay, a small embayment on the northeastern shores of Florida Bay, has provided baseline information on current spatial and temporal water deliveries prior to CERP modifications. Understanding the existing complex water delivery system and the effects the system has on Everglades hydrology will provide a necessary benchmark against which to measure restoration success. The study was initiated by the U.S. Geological Survey (USGS) in May 1999 to estimate creek flows to Joe Bay and determine the relative amounts derived from Taylor Slough and overflow from the C-111 Canal. It is important to understand the source of freshwater to Joe Bay before it enters Florida Bay. Taylor Slough transports freshwater to northeastern Florida Bay from the northwest while overflow from the C-111 Canal provides freshwater to northeastern Florida Bay from the northeast. Joe Bay, receives part of the freshwater from each of these sources via sheet flow and small estuarine creeks, and subsequently discharges southward to northeastern Florida Bay via Trout Creek. Trout Creek contributes approximately 50 percent of the total freshwater flow to northeastern Florida Bay (Hittle 2001). Eight non-gaged creeks entering Joe Bay were selected for acoustic Doppler current

33 CFR 167.100 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: General.

Code of Federal Regulations, 2013 CFR

2013-07-01

... SEPARATION SCHEMES Description of Traffic Separation Schemes and Precautionary Areas § 167.100 In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: General. The traffic separation scheme in the...

33 CFR 167.100 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: General.

Code of Federal Regulations, 2014 CFR

2014-07-01

... SEPARATION SCHEMES Description of Traffic Separation Schemes and Precautionary Areas § 167.100 In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: General. The traffic separation scheme in the...

33 CFR 167.100 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: General.

Code of Federal Regulations, 2011 CFR

2011-07-01

... SEPARATION SCHEMES Description of Traffic Separation Schemes and Precautionary Areas § 167.100 In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: General. The traffic separation scheme in the...

33 CFR 167.100 - In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: General.

Code of Federal Regulations, 2012 CFR

2012-07-01

... SEPARATION SCHEMES Description of Traffic Separation Schemes and Precautionary Areas § 167.100 In the approaches to Narragansett Bay, RI, and Buzzards Bay, MA: General. The traffic separation scheme in the...

Recent results of Daya Bay reactor neutrino experiment

NASA Astrophysics Data System (ADS)

Leitner, R.; Daya Bay Collaboration

2017-04-01

The Daya Bay reactor neutrino experiment has been designed to precisely measure the least known neutrino mixing angle θ13. In March 2012, Daya Bay collaboration announced [Daya Bay Collaboration (F. P. An et al.), Observation of electron-antineutrino disappearance at Daya Bay, Phys. Rev. Lett. 108 (2012) 171803] the observation of non-zero value of sin2 ⁡ 2θ13. Because of large statistics of detected antineutrinos and excellent performance of the experiment, Daya Bay continuously improves the precision of world best measurement of sin2 ⁡ 2θ13. In addition it provides results on neutrino mass splitting Δ mee2 competitive with measurements of other experiments, results on precise measurement of reactor fluxes and on limits of the existence of hypothetical fourth neutrino. In this paper, we report the results available by the time of the 6th Capri workshop: the measurement of oscillation parameters sin2 ⁡ (2θ13) = 0.084 ± 0.005 and | Δmee2 | = (2.42 ± 0.11) ×10-3eV2 [Daya Bay Collaboration (F. P. An et al.), New Measurement of Antineutrino Oscillation with the Full Detector Configuration at Daya Bay, Phys. Rev. Lett. 115 (2015) no. 11, 111802], searches for sterile neutrinos [Daya Bay Collaboration (F. P. An et al.) Search for a Light Sterile Neutrino at Daya Bay, Phys. Rev. Lett. 113 (2014) 141802] and precise measurement of reactor neutrino flux [Daya Bay Collaboration (F. P. An et al.), Measurement of the Reactor Anti-neutrino Flux and Spectrum at Daya Bay, Phys. Rev. Lett. 116 (2016) no. 6, 061801]. These are based on 621 days of measurement, most of the data has been taken in full detector configuration. More precise results [Daya Bay Collaboration (F. P. An et al.), Measurement of electron antineutrino oscillation based on 1230 days of operation of the Daya Bay experiment, arxiv:arXiv:1610.04802] with 1230 days of operation have been presented few weeks later at the Neutrino 2016 conference.

Global Symmetries of Naive and Staggered Fermions in Arbitrary Dimensions

NASA Astrophysics Data System (ADS)

Kieburg, Mario; Würfel, Tim R.

2018-03-01

It is well-known that staggered fermions do not necessarily satisfy the same global symmetries as the continuum theory. We analyze the mechanism behind this phenomenon for arbitrary dimension and gauge group representation. For this purpose we vary the number of lattice sites between even and odd parity in each single direction. Since the global symmetries are manifest in the lowest eigenvalues of the Dirac operator, the spectral statistics and also the symmetry breaking pattern will be affected. We analyze these effects and compare our predictions with Monte-Carlo simulations of naive Dirac operators in the strong coupling limit. This proceeding is a summary of our work [1].

Predicting flight delay based on multiple linear regression

NASA Astrophysics Data System (ADS)

Ding, Yi

2017-08-01

Delay of flight has been regarded as one of the toughest difficulties in aviation control. How to establish an effective model to handle the delay prediction problem is a significant work. To solve the problem that the flight delay is difficult to predict, this study proposes a method to model the arriving flights and a multiple linear regression algorithm to predict delay, comparing with Naive-Bayes and C4.5 approach. Experiments based on a realistic dataset of domestic airports show that the accuracy of the proposed model approximates 80%, which is further improved than the Naive-Bayes and C4.5 approach approaches. The result testing shows that this method is convenient for calculation, and also can predict the flight delays effectively. It can provide decision basis for airport authorities.

78 FR 39610 - Safety Zone; Big Bay Boom, San Diego Bay; San Diego, CA

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-02

..., Protection of Children from Environmental Health Risks and Safety Risks. This rule is not an economically significant rule and does not create an environmental risk to health or risk to safety that may...-AA00 Safety Zone; Big Bay Boom, San Diego Bay; San Diego, CA AGENCY: Coast Guard, DHS. ACTION...

Classical Swine Fever Outbreak after Modified Live LOM Strain Vaccination in Naive Pigs, South Korea

PubMed Central

Je, Sang H.; Kwon, Taeyong; Yoo, Sung J.; Lee, Dong-Uk; Lee, SeungYoon; Richt, Juergen A.

2018-01-01

We report classical swine fever outbreaks occurring in naive pig herds on Jeju Island, South Korea, after the introduction of the LOM vaccine strain. Two isolates from sick pigs had >99% identity with the vaccine stain. LOM strain does not appear safe; its use in the vaccine should be reconsidered. PMID:29553332

The bay area wildfire forum

Treesearch

Todd E. Bruce

1995-01-01

Fire agencies throughout the San Francisco Bay Area formed a grassroots organization to influence a firesafe environment. The Bay Area Wildfire Forum (BAWF) was organized in 1992 to coordinate wildland fire training while promoting and encouraging further activities regarding wildland firefighting and fire prevention.

Zeb1-Hdac2-eNOS circuitry identifies early cardiovascular precursors in naive mouse embryonic stem cells.

PubMed

Cencioni, Chiara; Spallotta, Francesco; Savoia, Matteo; Kuenne, Carsten; Guenther, Stefan; Re, Agnese; Wingert, Susanne; Rehage, Maike; Sürün, Duran; Siragusa, Mauro; Smith, Jacob G; Schnütgen, Frank; von Melchner, Harald; Rieger, Michael A; Martelli, Fabio; Riccio, Antonella; Fleming, Ingrid; Braun, Thomas; Zeiher, Andreas M; Farsetti, Antonella; Gaetano, Carlo

2018-03-29

Nitric oxide (NO) synthesis is a late event during differentiation of mouse embryonic stem cells (mESC) and occurs after release from serum and leukemia inhibitory factor (LIF). Here we show that after release from pluripotency, a subpopulation of mESC, kept in the naive state by 2i/LIF, expresses endothelial nitric oxide synthase (eNOS) and endogenously synthesizes NO. This eNOS/NO-positive subpopulation (ESNO+) expresses mesendodermal markers and is more efficient in the generation of cardiovascular precursors than eNOS/NO-negative cells. Mechanistically, production of endogenous NO triggers rapid Hdac2 S-nitrosylation, which reduces association of Hdac2 with the transcriptional repression factor Zeb1, allowing mesendodermal gene expression. In conclusion, our results suggest that the interaction between Zeb1, Hdac2, and eNOS is required for early mesendodermal differentiation of naive mESC.

Short Term Sediment Exchange Between Marshes and Bays Using Beryllium-7 as a Tracer, Fourleague Bay, Louisiana.

NASA Astrophysics Data System (ADS)

Restreppo, G. A.; Bentley, S. J.; Xu, K.; Wang, J.

2016-12-01

Modern delta models focus on the availability and exchange of coarse sediment as one of the major factors of deltaic growth or decay. Fine-grained sediment exchange within a river's delta is relatively poorly understood, as is the impact that this exchange has on land building and land loss. To better understand the dynamics of fine grain sediment exchange between river mouth, adjacent bays, and marshland, sediment cores from Fourleague Bay, LA, were collected and analyzed for 7Be, a naturally occurring radioisotope that serves as a marker for recently deposited sediment. Time-series push cores were collected every two months at ten sites, five located across a longitudinal transect in the middle bay and five located along adjacent marshes, from May 2015 to May 2016. All sites fall within 11 to 28 km of the Atchafalaya Delta, along a gradient extending towards the open ocean. Cores were extruded in 2 cm intervals, dried, ground, and analyzed via gamma spectrometry for the presence of 7Be. Inventories of 7Be were then calculated and used to determine bimonthly sedimentation rates over the course twelve months. Sediment deposition on the bay floor and marsh surface were then compared to Atchafalaya River discharge, wind speed and direction, and wave action. Preliminary results indicate patterns of initial fluvial sediment transfer from river to bay floor, then bay floor to marsh surface, with decreasing fluvial influence towards the open ocean. Sediment transport from bay to marsh appears to be coupled with meteorological forcing that induces bay-floor sediment resuspension and the flooding of marsh surfaces. This indirect mechanism of fluvial sediment supply to wetland surfaces may extend the region of influence for sediment delivery from man-made river-sediment diversions.

Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics

PubMed Central

Belo, David; Gamboa, Hugo

2017-01-01

The paper presents results of machine learning approach accuracy applied analysis of cardiac activity. The study evaluates the diagnostics possibilities of the arterial hypertension by means of the short-term heart rate variability signals. Two groups were studied: 30 relatively healthy volunteers and 40 patients suffering from the arterial hypertension of II-III degree. The following machine learning approaches were studied: linear and quadratic discriminant analysis, k-nearest neighbors, support vector machine with radial basis, decision trees, and naive Bayes classifier. Moreover, in the study, different methods of feature extraction are analyzed: statistical, spectral, wavelet, and multifractal. All in all, 53 features were investigated. Investigation results show that discriminant analysis achieves the highest classification accuracy. The suggested approach of noncorrelated feature set search achieved higher results than data set based on the principal components. PMID:28831239

Identifying Wrist Fracture Patients with High Accuracy by Automatic Categorization of X-ray Reports

PubMed Central

de Bruijn, Berry; Cranney, Ann; O’Donnell, Siobhan; Martin, Joel D.; Forster, Alan J.

2006-01-01

The authors performed this study to determine the accuracy of several text classification methods to categorize wrist x-ray reports. We randomly sampled 751 textual wrist x-ray reports. Two expert reviewers rated the presence (n = 301) or absence (n = 450) of an acute fracture of wrist. We developed two information retrieval (IR) text classification methods and a machine learning method using a support vector machine (TC-1). In cross-validation on the derivation set (n = 493), TC-1 outperformed the two IR based methods and six benchmark classifiers, including Naive Bayes and a Neural Network. In the validation set (n = 258), TC-1 demonstrated consistent performance with 93.8% accuracy; 95.5% sensitivity; 92.9% specificity; and 87.5% positive predictive value. TC-1 was easy to implement and superior in performance to the other classification methods. PMID:16929046

Bayesian network modelling of upper gastrointestinal bleeding

NASA Astrophysics Data System (ADS)

Aisha, Nazziwa; Shohaimi, Shamarina; Adam, Mohd Bakri

2013-09-01

Bayesian networks are graphical probabilistic models that represent causal and other relationships between domain variables. In the context of medical decision making, these models have been explored to help in medical diagnosis and prognosis. In this paper, we discuss the Bayesian network formalism in building medical support systems and we learn a tree augmented naive Bayes Network (TAN) from gastrointestinal bleeding data. The accuracy of the TAN in classifying the source of gastrointestinal bleeding into upper or lower source is obtained. The TAN achieves a high classification accuracy of 86% and an area under curve of 92%. A sensitivity analysis of the model shows relatively high levels of entropy reduction for color of the stool, history of gastrointestinal bleeding, consistency and the ratio of blood urea nitrogen to creatinine. The TAN facilitates the identification of the source of GIB and requires further validation.

Naive helper T cells from BCG-vaccinated volunteers produce IFN-gamma and IL-5 to mycobacterial antigen-pulsed dendritic cells.

PubMed

Kowalewicz-Kulbat, Magdalena; Kaźmierczak, Dominik; Donevski, Stefan; Biet, Franck; Pestel, Joël; Rudnicka, Wiesława

2008-01-01

Mycobacterium bovis bacillus Calmette-Guérin (BCG) is a live vaccine that has been used in routine vaccination against tuberculosis for nearly 80 years. However, its efficacy is controversial. The failure of BCG vaccination may be at least partially explained by the induction of poor or inappropriate host responses. Dendritic cells (DCs) are likely to play a key role in the induction of immune response to mycobacteria by polarizing the reactivity of T lymphocytes toward a Th1 profile, contributing to the generation of protective cellular immunity against mycobacteria. In this study we aimed to investigate the production of Th1 and Th2 cytokines by naive CD4+ T cells to mycobacterial antigen-pulsed DCs in the group of young, healthy BCG vaccinated volunteers. The response of naive helper T cells was compared with the response of total blood lymphocytes. Our present results clearly showed that circulating naive CD45RA+CD4+ lymphocytes from BCG-vaccinated subjects can become effector helper cells producing IFN-gamma and IL-5 under the stimulation by autologous dendritic cells presenting mycobacterial protein antigen-PPD or infected with live M. bovis BCG bacilli.

Characteristic appearances of fundus autofluorescence in treatment-naive and active polypoidal choroidal vasculopathy: a retrospective study of 170 patients.

PubMed

Zhao, Xinyu; Xia, Song; Chen, Youxin

2018-06-01

To investigate the characteristic appearances of fundus autofluorescence (FAF) in patients with treatment-naive and active polypoidal choroidal vasculopathy (PCV). Cases with the diagnosis of treatment-naive and active PCV from November 2012 to May 2017 at Peking Union Medical College Hospital were retrospectively reviewed. All patients underwent comprehensive ophthalmologic examination. Autofluorescence (AF) findings were described at the retinal sites of the corresponding lesions identified and diagnosed using indocyanine green angiography and spectral-domain optical coherence tomography. One hundred seventy patients with 192 affected eyes were included. The logMAR BCVA of the patients were 0.53 ± 0.28. The six AF patterns of 243 polypoidal lesions were confluent hypo-AF with hyper-AF ring (49.8%), confluent hypo-AF (22.6%), hyper-AF with hypo-AF ring (3.7%), granular hypo-AF (7.0%), blocked hypo-AF due to hemorrhage (8.6%), and polyps without apparent AF changes (8.2%). For 146 branching vascular networks (BVNs), 97.3% were granular hypo-AF, and others were blocked hypo-AF due to hemorrhage. In eyes with treatment-naive and active PCV, the polypoidal lesions and BVNs induce characteristic FAF changes. FAF images provide reliable adjunct reference for the diagnosis of PCV.

Local classifier weighting by quadratic programming.

PubMed

Cevikalp, Hakan; Polikar, Robi

2008-10-01

It has been widely accepted that the classification accuracy can be improved by combining outputs of multiple classifiers. However, how to combine multiple classifiers with various (potentially conflicting) decisions is still an open problem. A rich collection of classifier combination procedures -- many of which are heuristic in nature -- have been developed for this goal. In this brief, we describe a dynamic approach to combine classifiers that have expertise in different regions of the input space. To this end, we use local classifier accuracy estimates to weight classifier outputs. Specifically, we estimate local recognition accuracies of classifiers near a query sample by utilizing its nearest neighbors, and then use these estimates to find the best weights of classifiers to label the query. The problem is formulated as a convex quadratic optimization problem, which returns optimal nonnegative classifier weights with respect to the chosen objective function, and the weights ensure that locally most accurate classifiers are weighted more heavily for labeling the query sample. Experimental results on several data sets indicate that the proposed weighting scheme outperforms other popular classifier combination schemes, particularly on problems with complex decision boundaries. Hence, the results indicate that local classification-accuracy-based combination techniques are well suited for decision making when the classifiers are trained by focusing on different regions of the input space.

Bayes and the Law.

PubMed

Fenton, Norman; Neil, Martin; Berger, Daniel

2016-06-01

Although the last forty years has seen considerable growth in the use of statistics in legal proceedings, it is primarily classical statistical methods rather than Bayesian methods that have been used. Yet the Bayesian approach avoids many of the problems of classical statistics and is also well suited to a broader range of problems. This paper reviews the potential and actual use of Bayes in the law and explains the main reasons for its lack of impact on legal practice. These include misconceptions by the legal community about Bayes' theorem, over-reliance on the use of the likelihood ratio and the lack of adoption of modern computational methods. We argue that Bayesian Networks (BNs), which automatically produce the necessary Bayesian calculations, provide an opportunity to address most concerns about using Bayes in the law.

Learning on the Big Bay

ERIC Educational Resources Information Center

Philp, Michael J.

1978-01-01

Anne Arundel Community College uses the Chesapeake Bay for a flexible ocean engineering technology program which includes mechanical, electrical, and environmental options for transfer and/or vocational students, and adult education programs covering such subjects as sailing, Bay history, boat building, scuba-diving, and marine biology. (RT)

[Quality level assessment of lowly efficient Tamarix chinensis secondary shrubs in Laizhou Bay of Yellow River Delta].

PubMed

Xia, Jiang-Bao; Liu, Yu-Ting; Zhu, Jin-Fang; Xu, Jing-Wei; Lu, Zhao-Hua; Liu, Jing-Tao; Liu, Qing

2013-06-01

Taking the Tamarix chinensis secondary shrubs in Laizhou Bay of Yellow River Delta as test objects, and by using synthetic factor method, this paper studied the main factors causing the lowly efficiency of T. chinensis secondary shrubs as well as the main parameters for the classification of lowly efficient T. chinensis secondary shrubs. A total of 24 indices including shrubs growth and soil physical and chemical properties were selected to determine the main affecting factors and parameters in evaluating and classifying the lowly efficient shrubs. There were no obvious correlations between the indices reflecting the shrubs growth and soil quality, and thus, only using shrub growth index to reflect the lowly efficiency level of T. chinensis was not enough, and it would be necessary to combine with soil quality factors to make a comprehensive evaluation. The principal factors reflecting the quality level of lowly efficient T. chinensis shrubs included soil salt content and moisture content, stand age, single tree's aboveground stem, leaf biomass, and basal diameter, followed by soil density, porosity, and soil nutrient status. The lowly efficient T. chinensis shrubs in the Bay could be classified into five types, namely, shrub with growth potential, slightly low quality shrub, moderately lowly efficient shrub, moderately low quality and lowly efficient shrub, and seriously low quality and lowly efficient shrub. The main features, low efficiency causes, and management measures of these shrubs were discussed based on the mean cluster value.

BOOK REVIEW OF "CHESAPEAKE BAY BLUES: SCIENCE, POLITICS, AND THE STRUGGLE TO SAVE THE BAY"

EPA Science Inventory

This is a book review of "Chesapeake Bay Blues: Science, Politics, and the Struggle to Save the Bay". This book is very well written and provides an easily understandable description of the political challenges faced by those proposing new or more stringent environmental regulat...

Latest results from Daya Bay

NASA Astrophysics Data System (ADS)

Vorobel, Vit; Daya Bay Collaboration

2017-07-01

The Daya Bay Reactor Neutrino Experiment was designed to measure θ 13, the smallest mixing angle in the three-neutrino mixing framework, with unprecedented precision. The experiment consists of eight functionally identical detectors placed underground at different baselines from three pairs of nuclear reactors in South China. Since Dec. 2011, the experiment has been running stably for more than 4 years, and has collected the largest reactor anti-neutrino sample to date. Daya Bay is able to greatly improve the precision on θ 13 and to make an independent measurement of the effective mass splitting in the electron antineutrino disappearance channel. Daya Bay can also perform a number of other precise measurements, such as a high-statistics determination of the absolute reactor antineutrino flux and spectrum, as well as a search for sterile neutrino mixing, among others. The most recent results from Daya Bay are discussed in this paper, as well as the current status and future prospects of the experiment.

Comparison of naïve Bayes and logistic regression for computer-aided diagnosis of breast masses using ultrasound imaging

NASA Astrophysics Data System (ADS)

Cary, Theodore W.; Cwanger, Alyssa; Venkatesh, Santosh S.; Conant, Emily F.; Sehgal, Chandra M.

2012-03-01

This study compares the performance of two proven but very different machine learners, Naïve Bayes and logistic regression, for differentiating malignant and benign breast masses using ultrasound imaging. Ultrasound images of 266 masses were analyzed quantitatively for shape, echogenicity, margin characteristics, and texture features. These features along with patient age, race, and mammographic BI-RADS category were used to train Naïve Bayes and logistic regression classifiers to diagnose lesions as malignant or benign. ROC analysis was performed using all of the features and using only a subset that maximized information gain. Performance was determined by the area under the ROC curve, Az, obtained from leave-one-out cross validation. Naïve Bayes showed significant variation (Az 0.733 +/- 0.035 to 0.840 +/- 0.029, P < 0.002) with the choice of features, but the performance of logistic regression was relatively unchanged under feature selection (Az 0.839 +/- 0.029 to 0.859 +/- 0.028, P = 0.605). Out of 34 features, a subset of 6 gave the highest information gain: brightness difference, margin sharpness, depth-to-width, mammographic BI-RADs, age, and race. The probabilities of malignancy determined by Naïve Bayes and logistic regression after feature selection showed significant correlation (R2= 0.87, P < 0.0001). The diagnostic performance of Naïve Bayes and logistic regression can be comparable, but logistic regression is more robust. Since probability of malignancy cannot be measured directly, high correlation between the probabilities derived from two basic but dissimilar models increases confidence in the predictive power of machine learning models for characterizing solid breast masses on ultrasound.

Status and Assessment of Chesapeake Bay Wildlife Contamination

USGS Publications Warehouse

Heinz, G.H.; Wiemeyer, Stanley N.; Clark, D.R.; Albers, P.H.; Henry, P.; Batiuk, R.A.

1992-01-01

As an integral component of its priority setting process, the Chesapeake Bay Program`s Toxics Subcommittee has sought the expertise of Chesapeake Bay researchers and managers in developing a series of Chesapeake Bay toxics status and assessment papers. In the report, evidence for historical and current contaminant effects on key bird species, mammals, reptiles and amphibians which inhabit the Chesapeake Bay basin is examined. For each group of wildlife species, a general overview of effects caused by specific toxic substances is followed by detailed accounts of contaminant effects on selected species. Sponsored by Environmental Protection Agency, Annapolis, MD. Chesapeake Bay Program.

The World's Students in Bay Area Universities.

ERIC Educational Resources Information Center

Duggan, Susan J.; Wollitzer, Peter A.

Results of a survey of international student exchange programs in the Bay Area of California are presented. Information is provided on the following: the top 10 countries of origin for Bay Area foreign students; 10 Bay Area institutions with the highest number of foreign students; 10 area institutions with the highest percent of full-time…

Quantum ensembles of quantum classifiers.

PubMed

Schuld, Maria; Petruccione, Francesco

2018-02-09

Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

Development of an online, publicly accessible naive Bayesian decision support tool for mammographic mass lesions based on the American College of Radiology (ACR) BI-RADS lexicon.

PubMed

Benndorf, Matthias; Kotter, Elmar; Langer, Mathias; Herda, Christoph; Wu, Yirong; Burnside, Elizabeth S

2015-06-01

To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. We used separate training data (1,276 lesions, 138 malignant) and validation data (1,177 lesions, 175 malignant). We created naïve Bayes (NB) classifiers from the training data with tenfold cross-validation. Our "inclusive model" comprised BI-RADS categories, BI-RADS descriptors, and age as predictive variables; our "descriptor model" comprised BI-RADS descriptors and age. The resulting NB classifiers were applied to the validation data. We evaluated and compared classifier performance with ROC-analysis. In the training data, the inclusive model yields an AUC of 0.959; the descriptor model yields an AUC of 0.910 (P < 0.001). The inclusive model is superior to the clinical performance (BI-RADS categories alone, P < 0.001); the descriptor model performs similarly. When applied to the validation data, the inclusive model yields an AUC of 0.935; the descriptor model yields an AUC of 0.876 (P < 0.001). Again, the inclusive model is superior to the clinical performance (P < 0.001); the descriptor model performs similarly. We consider our classifier a step towards a more uniform interpretation of combinations of BI-RADS descriptors. We provide our classifier at www.ebm-radiology.com/nbmm/index.html . • We provide a decision support tool for mammographic masses at www.ebm-radiology.com/nbmm/index.html . • Our tool may reduce variability of practice in BI-RADS category assignment. • A formal analysis of BI-RADS descriptors may enhance radiologists' diagnostic performance.

Phenotypic and Genotypic Shifts in Hepatitis B Virus in Treatment-Naive Patients, Taiwan, 2008-2012.

PubMed

Yeh, Chau-Ting; Liang, Kung-Hao; Chang, Ming-Ling; Hsu, Chao-Wei; Chen, Yi-Cheng; Lin, Chih-Lang; Lin, Wey-Ran; Lai, Ming-Wei

2017-05-01

We examined the characteristic changes of hepatitis B virus (HBV) in antiviral drug treatment-naive patients referred for pretreatment evaluation in Taiwan during 2008-2012. Over time, we observed substantial decreases in the prevalence of HBV e antigen (HBeAg) and increasing prevalence of the precore G1899A mutation and HBV-DNA levels in HBeAg-positive patients.

Insulin sensitivity and beta-cell function in protease inhibitor-treated and -naive human immunodeficiency virus-infected children.

PubMed

Bitnun, Ari; Sochett, Etienne; Dick, Paul T; To, Teresa; Jefferies, Craig; Babyn, Paul; Forbes, Jack; Read, Stanley; King, Susan M

2005-01-01

Previous pediatric studies have failed to demonstrate a clear association between protease inhibitor (PI) therapy and abnormal glucose homeostasis in HIV-infected children. To define more precisely the impact of PI therapy on glucose homeostasis in this population, we performed the insulin-modified frequent-sampling iv glucose tolerance test on 33 PI-treated and 15 PI-naive HIV-infected children. Other investigations included fasting serum lipids; glucose, insulin, and C-peptide; single-slice abdominal computed tomography; and, in a subset of PI-treated children, an oral glucose tolerance test. There were no differences between the two groups with respect to fasting serum insulin or C-peptide, homeostatic model assessment insulin resistance, or quantitative insulin sensitivity check index. The mean insulin sensitivity index of PI-treated and PI-naive children was 6.93 +/- 6.37 and 10.58 +/- 12.93 x 10(-4)min(-1) [microU/ml](-1), respectively (P = 0.17). The mean disposition index for the two groups was 1840 +/- 1575 and 3708 +/- 3005 x 10(-4)min(-1) (P = 0.013), respectively. After adjusting for potential confounding variables using multiple regression analysis, the insulin sensitivity index and disposition index of PI-treated children were significantly lower than that of PI-naive children (P = 0.01 for both). In PI-treated but not PI-naive children, insulin sensitivity correlated inversely with visceral adipose tissue area (r = -0.43, P = 0.01) and visceral to sc adipose tissue ratio (r = -0.49, P = 0.004). Mildly impaired glucose tolerance was noted in four of 21 PI-treated subjects tested. Our results demonstrate not only that PI therapy reduces insulin sensitivity in HIV-infected children but also that it impairs the beta-cell response to this reduction in insulin sensitivity and, in a subset of children, leads to the development of impaired glucose tolerance. The presence of insulin resistance, dyslipidemia, and the significant correlation of reduced insulin

The diabolo classifier

PubMed

Schwenk

1998-11-15

We present a new classification architecture based on autoassociative neural networks that are used to learn discriminant models of each class. The proposed architecture has several interesting properties with respect to other model-based classifiers like nearest-neighbors or radial basis functions: it has a low computational complexity and uses a compact distributed representation of the models. The classifier is also well suited for the incorporation of a priori knowledge by means of a problem-specific distance measure. In particular, we will show that tangent distance (Simard, Le Cun, & Denker, 1993) can be used to achieve transformation invariance during learning and recognition. We demonstrate the application of this classifier to optical character recognition, where it has achieved state-of-the-art results on several reference databases. Relations to other models, in particular those based on principal component analysis, are also discussed.

BayesMotif: de novo protein sorting motif discovery from impure datasets.

PubMed

Hu, Jianjun; Zhang, Fan

2010-01-18

Protein sorting is the process that newly synthesized proteins are transported to their target locations within or outside of the cell. This process is precisely regulated by protein sorting signals in different forms. A major category of sorting signals are amino acid sub-sequences usually located at the N-terminals or C-terminals of protein sequences. Genome-wide experimental identification of protein sorting signals is extremely time-consuming and costly. Effective computational algorithms for de novo discovery of protein sorting signals is needed to improve the understanding of protein sorting mechanisms. We formulated the protein sorting motif discovery problem as a classification problem and proposed a Bayesian classifier based algorithm (BayesMotif) for de novo identification of a common type of protein sorting motifs in which a highly conserved anchor is present along with a less conserved motif regions. A false positive removal procedure is developed to iteratively remove sequences that are unlikely to contain true motifs so that the algorithm can identify motifs from impure input sequences. Experiments on both implanted motif datasets and real-world datasets showed that the enhanced BayesMotif algorithm can identify anchored sorting motifs from pure or impure protein sequence dataset. It also shows that the false positive removal procedure can help to identify true motifs even when there is only 20% of the input sequences containing true motif instances. We proposed BayesMotif, a novel Bayesian classification based algorithm for de novo discovery of a special category of anchored protein sorting motifs from impure datasets. Compared to conventional motif discovery algorithms such as MEME, our algorithm can find less-conserved motifs with short highly conserved anchors. Our algorithm also has the advantage of easy incorporation of additional meta-sequence features such as hydrophobicity or charge of the motifs which may help to overcome the limitations of

Classification of iRBD and Parkinson's disease patients based on eye movements during sleep.

PubMed

Christensen, Julie A E; Koch, Henriette; Frandsen, Rune; Kempfner, Jacob; Arvastson, Lars; Christensen, Soren R; Sorensen, Helge B D; Jennum, Poul

2013-01-01

Patients suffering from the sleep disorder idiopathic rapid-eye-movement sleep behavior disorder (iRBD) have been observed to be in high risk of developing Parkinson's disease (PD). This makes it essential to analyze them in the search for PD biomarkers. This study aims at classifying patients suffering from iRBD or PD based on features reflecting eye movements (EMs) during sleep. A Latent Dirichlet Allocation (LDA) topic model was developed based on features extracted from two electrooculographic (EOG) signals measured as parts in full night polysomnographic (PSG) recordings from ten control subjects. The trained model was tested on ten other control subjects, ten iRBD patients and ten PD patients, obtaining a EM topic mixture diagram for each subject in the test dataset. Three features were extracted from the topic mixture diagrams, reflecting "certainty", "fragmentation" and "stability" in the timely distribution of the EM topics. Using a Naive Bayes (NB) classifier and the features "certainty" and "stability" yielded the best classification result and the subjects were classified with a sensitivity of 95 %, a specificity of 80% and an accuracy of 90 %. This study demonstrates in a data-driven approach, that iRBD and PD patients may exhibit abnorm form and/or timely distribution of EMs during sleep.

Differential effects of ibogaine on local cerebral glucose utilization in drug-naive and morphine-dependent rats.

PubMed

Levant, Beth; Pazdernik, Thomas L

2004-04-02

Ibogaine, a hallucinogenic indole alkaloid, has been proposed as a treatment for addiction to opioids and other drugs of abuse. The mechanism for its putative anti-addictive effects is unknown. In this study, the effects of ibogaine on local cerebral glucose utilization (LCGU) were determined in freely moving, drug-naive, or morphine-dependent adult, male, Sprague-Dawley rats using the [(14)C]2-deoxyglucose (2-DG) method. Morphine-dependent rats were treated with increasing doses of morphine (5-25 mg/kg, s.c., b.i.d.) and then maintained at 25 mg/kg (b.i.d.) for 4-7 days. For the 2-DG procedure, rats were injected with saline or ibogaine (40 mg/kg, i.p.). 2-DG was administered 1 h after administration of ibogaine. The rate of LCGU was determined by quantitative autoradiography in 46 brain regions. In drug-naive animals, ibogaine produced significant increases in LCGU in the parietal, cingulate, and occipital cortices and cerebellum compared to controls consistent with its activity as a hallucinogen and a tremorogen. Morphine-dependent rats had only minor alterations in LCGU at the time assessed in this experiment. However, in morphine-dependent animals, ibogaine produced a global decrease in LCGU that was greatest in brain regions such as the lateral and medial preoptic areas, nucleus of the diagonal band, nucleus accumbens shell, inferior colliculus, locus coeruleus, and flocculus compared to morphine-dependent animals treated with saline. These findings indicate that ibogaine produces distinctly different effects on LCGU in drug-naive and morphine-dependent rats. This suggests that different mechanisms may underlie ibogaine's hallucinogenic and anti-addictive effects.

Role of remote sensing in Bay measurements

NASA Technical Reports Server (NTRS)

Mugler, J. P., Jr.; Godfrey, J. P.; Hickman, G. D.; Hovis, W. G.; Pearson, A. O.; Weaver, K. N.

1978-01-01

Remote measurements of a number of surface or near surface parameters for baseline definition and specialized studies, remote measurements of episodic events, and remote measurements of the Bay lithosphere are considered in terms of characterizing and understanding the ecology of the Chesapeake Bay. Geologic processes and features best suited for information enhancement by remote sensing methods are identified. These include: (1) rates of sedimentation in the Bay; (2) rates of erosion of Bay shorelines; (3) spatial distribution and geometry of aquifers; (4) mapping of Karst terrain (sinkholes); and (5) mapping of fracture patterns. Recommendations for studying problem areas identified are given.

A Corpus-Based Approach for Automatic Thai Unknown Word Recognition Using Boosting Techniques

NASA Astrophysics Data System (ADS)

Techo, Jakkrit; Nattee, Cholwich; Theeramunkong, Thanaruk

While classification techniques can be applied for automatic unknown word recognition in a language without word boundary, it faces with the problem of unbalanced datasets where the number of positive unknown word candidates is dominantly smaller than that of negative candidates. To solve this problem, this paper presents a corpus-based approach that introduces a so-called group-based ranking evaluation technique into ensemble learning in order to generate a sequence of classification models that later collaborate to select the most probable unknown word from multiple candidates. Given a classification model, the group-based ranking evaluation (GRE) is applied to construct a training dataset for learning the succeeding model, by weighing each of its candidates according to their ranks and correctness when the candidates of an unknown word are considered as one group. A number of experiments have been conducted on a large Thai medical text to evaluate performance of the proposed group-based ranking evaluation approach, namely V-GRE, compared to the conventional naïve Bayes classifier and our vanilla version without ensemble learning. As the result, the proposed method achieves an accuracy of 90.93±0.50% when the first rank is selected while it gains 97.26±0.26% when the top-ten candidates are considered, that is 8.45% and 6.79% improvement over the conventional record-based naïve Bayes classifier and the vanilla version. Another result on applying only best features show 93.93±0.22% and up to 98.85±0.15% accuracy for top-1 and top-10, respectively. They are 3.97% and 9.78% improvement over naive Bayes and the vanilla version. Finally, an error analysis is given.

Linear dimension reduction and Bayes classification

NASA Technical Reports Server (NTRS)

Decell, H. P., Jr.; Odell, P. L.; Coberly, W. A.

1978-01-01

An explicit expression for a compression matrix T of smallest possible left dimension K consistent with preserving the n variate normal Bayes assignment of X to a given one of a finite number of populations and the K variate Bayes assignment of TX to that population was developed. The Bayes population assignment of X and TX were shown to be equivalent for a compression matrix T explicitly calculated as a function of the means and covariances of the given populations.

Gulf of Mexico integrated science - Tampa Bay study, the impact of groundwater and contaminants on Tampa Bay

USGS Publications Warehouse

Swarzenski, Peter W.

2005-01-01

Despite the recreational and economic value of coastal bays and estuaries, these ecosystems are often among our most 'troubled' natural environments. Urbanization, agriculture, mining, and shipping are just a few activities that can have a profound and lasting impact on the coastal zone. In order to maintain a healthy coastal ecosystem, it is crucial to develop reasonable management practices around expert scientific information. We still have much to learn about the quantity and quality of groundwater being discharged into Tampa Bay, Florida. We also need to improve our knowledge of a wide range of contaminants entering the bay and must be able to determine where they accumulate in seafloor sediments. Such buried contaminants can potentially be harmful to biota if they are released to the water column. U.S. Geological Survey (USGS) scientists and research partners from the University of South Florida (USF), the University of Florida (UF), and the Florida Marine Research Institute (FMRI) are mapping sources of groundwater, measuring groundwater flow into Tampa Bay, and assessing the impact of contaminants and sediments on bay water quality and ecosystem health.

Clew Bay, Ireland

NASA Image and Video Library

2016-07-26

Clew Bay is in County Mayo, Republic of Ireland. It contains Ireland's best example of sunken glacial drumlins. Clew Bay is associated with Grace O'Malley, the Pirate Queen during Elizabethan times; and Dorinish, a private island purchased by John Lennon. The drumlins are low hills formed from glacial sediment deposited at the end of the last Ice Age. The image was acquired May 31, 2016, covers an area of 22.5 by 26.2 km, and is located at 53.9 degrees north, 9.6 degrees west. http://photojournal.jpl.nasa.gov/catalog/PIA18670

East Bay Municipal Utility District Settlement

EPA Pesticide Factsheets

The East Bay Municipal Utility District and its seven member communities own and operate a separate sanitary sewer system, which serves approximately 650,000 customers on the eastern side of San Francisco Bay in California.

28 CFR 701.14 - Classified information.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 28 Judicial Administration 2 2013-07-01 2013-07-01 false Classified information. 701.14 Section... UNDER THE FREEDOM OF INFORMATION ACT § 701.14 Classified information. In processing a request for information that is classified or classifiable under Executive Order 12356 or any other Executive Order...

10. VIEW TO NORTHEAST FROM WITHIN SOUTHWEST BAY, LOOKING THROUGH ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

10. VIEW TO NORTHEAST FROM WITHIN SOUTHWEST BAY, LOOKING THROUGH CENTER BAY AND INTO NORTHEAST BAY. NOTE TRAVELING BRIDGE CRANE OVERHEAD AND SWINGING BOOM CRANES ATTACHED TO COLUMNS ON RIGHT AND LEFT. NOTE ALSO THE DIFFERENCE IN TRUSSES SUPPORTING CRANEWAY TRACKS FOR SIDE BAYS AND CENTER BAY. TRUSSES SUPPORTING CRANEWAY TRACKS IN SIDE BAYS (CENTER FOREGROUND AND FAR BACKGROUND) ARE HOWE TRUSSES WITH WOOD DIAGONALS AND STEEL VERTICALS. TRUSSES SUPPORTING CRANEWAY TRACKS IN CENTER BAY (MID BACKGROUND) ARE PRATT TRUSSES WITH WOOD VERTICALS AND DIAGONALS. - Rosie the Riveter National Historical Park, Auxiliary Plate Shop, 912 Harbour Way, Richmond, Contra Costa County, CA

78 FR 55216 - Safety Zone: Suisun Bay Electromagnetic Scan and Ordnance Recovery, Suisun Bay, Concord, CA

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-10

...-AA00 Safety Zone: Suisun Bay Electromagnetic Scan and Ordnance Recovery, Suisun Bay, Concord, CA AGENCY... (MOTCO) electromagnetic scan and ordnance recovery operations. These safety zones are established to... 10, 2013 that they intend to conduct an intrusive electromagnetic scan and ordnance recovery...

Assessing overland sediment transport to the Apalachicola River/Bay in Florida

NASA Astrophysics Data System (ADS)

Smar, D. E.; Hagen, S.; Daranpob, A.; Passeri, D.

2011-12-01

An ongoing study in Franklin County, Florida is focused on classifying the mechanisms of sediment transport from the overland areas to eventual deposition in the Apalachicola River and surrounding estuaries. Sediment cores and water column samples were collected at various locations along the Apalachicola River, its tributaries, and distributaries over a two-week period during the wet season. A preliminary particle size distribution analysis of the sediment cores and water column samples demonstrates decreasing particle sizes as the river and wetlands progress toward the ocean. Daily water samples from the mouth of the Apalachicola River and two distributaries reveal fluctuating total suspended solid (TSS) concentrations. To understand these deviations, flow rate and water level at each location is inspected. Because the nearest USGS gage is approximately 16 miles upstream from these sites, investigation of the hydrodynamic influences of sediment transport is conducted by developing a hydrodynamic model simulating river flow and tides in the Apalachicola River and bay system. With spatially accurate flow rates and water levels, an attempt can be made to correlate flow rate with fluctuating TSS concentrations. Precipitation events during the sampling period also support spikes in the TSS concentrations as expected. Assessing sediment transport to the river/bay system will lead to a better understanding of the regression or accretion of the river's alluvial fan and the marsh platform. High flow periods following extreme rain events (which are expected to intensify under global climate change) transport more sediment downstream, however, the interaction with tidal and sea level effects are still being analyzed. With rising sea levels, it is expected that the alluvial fan will recede and wetland areas may migrate inland gradually transforming existing dry lands such as pine forests into new wetland regions. Future work will include an analysis of the tidal cycle during

Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

PubMed

Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

2017-01-01

Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as

Prediction of cold and heat patterns using anthropometric measures based on machine learning.

PubMed

Lee, Bum Ju; Lee, Jae Chul; Nam, Jiho; Kim, Jong Yeol

2018-01-01

To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures can improve the predictive power to diagnose these patterns. Based on a total of 4,859 subjects (3,000 women and 1,859 men), statistical analyses using binary logistic regression were performed to assess the significance of the difference and the predictive power of each anthropometric measure, and binary logistic regression and Naive Bayes with the variable selection technique were used to assess the improvement in the predictive power of the patterns using the combined measures. In women, the strongest indicators for determining the cold and heat patterns among anthropometric measures were body mass index (BMI) and rib circumference; in men, the best indicator was BMI. In experiments using a combination of measures, the values of the area under the receiver operating characteristic curve in women were 0.776 by Naive Bayes and 0.772 by logistic regression, and the values in men were 0.788 by Naive Bayes and 0.779 by logistic regression. Individuals with a higher BMI have a tendency toward a heat pattern in both women and men. The use of a combination of anthropometric measures can slightly improve the diagnostic accuracy. Our findings can provide fundamental information for the diagnosis of cold and heat patterns based on body shape for personalized medicine.

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Lessons from monitoring water quality in San Francisco Bay

USGS Publications Warehouse

Cloern, J.E.; Schraga, T.S.; Lopez, C.B.; Labiosa, R.

2003-01-01

Bay Area residents feel a sense of responsibility to protect San Francisco Bay and keep it healthy. Some even dream about the recovery of fish stocks so they can sustain commercial fishing once again inside the Bay. How is our Bay doing? Is it highly polluted or pretty clean? How does its health compare with other estuaries in the United States? Are things getting better or worse? Does costly wastewater treatment have benefits? What are the biggest threats to the Bay and how can we reduce or eliminate those threats? How will the Bay change in the future? These questions can only be answered with investments in study and monitoring, and they are the driving force behind the Regional Monitoring Program (RMP). We describe here some selected results from water quality surveillance conducted by the U.S. Geological Survey (USGS) as one component of the RMP. We present results as lessons about how the Bay works as a complex dynamic system, and we show how these lessons are relevant to the broad RMP objectives supporting Bay protection and management.

The Neoglacial landscape and human history of Glacier Bay, Glacier Bay National Park and Preserve, southeast Alaska, USA

USGS Publications Warehouse

Connor, C.; Streveler, G.; Post, A.; Monteith, D.; Howell, W.

2009-01-01

The Neoglacial landscape of the Huna Tlingit homeland in Glacier Bay is recreated through new interpretations of the lower Bay's fjordal geomorphology, late Quaternary geology and its ethnographic landscape. Geological interpretation is enhanced by 38 radiocarbon dates compiled from published and unpublished sources, as well as 15 newly dated samples. Neoglacial changes in ice positions, outwash and lake extents are reconstructed for c. 5500?????"200 cal. yr ago, and portrayed as a set of three landscapes at 1600?????"1000, 500?????"300 and 300?????"200 cal. yr ago. This history reveals episodic ice advance towards the Bay mouth, transforming it from a fjordal seascape into a terrestrial environment dominated by glacier outwash sediments and ice-marginal lake features. This extensive outwash plain was building in lower Glacier Bay by at least 1600 cal. yr ago, and had filled the lower bay by 500 cal. yr ago. The geologic landscape evokes the human-described landscape found in the ethnographic literature. Neoglacial climate and landscape dynamism created difficult but endurable environmental conditions for the Huna Tlingit people living there. Choosing to cope with environmental hardship was perhaps preferable to the more severely deteriorating conditions outside of the Bay as well as conflicts with competing groups. The central portion of the outwash plain persisted until it was overridden by ice moving into Icy Strait between AD 1724?????"1794. This final ice advance was very abrupt after a prolonged still-stand, evicting the Huna Tlingit from their Glacier Bay homeland. ?? 2009 SAGE Publications.

Classifying Motion.

ERIC Educational Resources Information Center

Duzen, Carl; And Others

1992-01-01

Presents a series of activities that utilizes a leveling device to classify constant and accelerated motion. Applies this classification system to uniform circular motion and motion produced by gravitational force. (MDH)

Joint Task Force -Guantanamo Bay, Cuba: Open or Close?

DTIC Science & Technology

2013-03-01

Obama signed that executive order directing the closure of detention operations at Guantanamo Bay. Subsequently, despite domestically political and...domestically political and international scrutiny, detention operations at Guantanamo Bay, Cuba have evolved into the premier detention facility in the...operations at Guantanamo Bay. Subsequently, despite domestically political and international scrutiny, detention operations at Guantanamo Bay, Cuba

Algae Reefs in Shark Bay, Western Australia, Australia

NASA Technical Reports Server (NTRS)

1990-01-01

Numerous algae reefs are seen in Shark Bay, Western Australia, Australia (26.0S, 113.5E) especially in the southern portions of the bay. The south end is more saline because tidal flow in and out of the bay is restricted by sediment deposited at the north and central end of the bay opposite the mouth of the Wooramel River. This extremely arid region produces little sediment runoff so that the waters are very clear, saline and rich in algae.

Heterogeneous classifier fusion for ligand-based virtual screening: or, how decision making by committee can be a good thing.

PubMed

Riniker, Sereina; Fechner, Nikolas; Landrum, Gregory A

2013-11-25

The concept of data fusion - the combination of information from different sources describing the same object with the expectation to generate a more accurate representation - has found application in a very broad range of disciplines. In the context of ligand-based virtual screening (VS), data fusion has been applied to combine knowledge from either different active molecules or different fingerprints to improve similarity search performance. Machine-learning (ML) methods based on fusion of multiple homogeneous classifiers, in particular random forests, have also been widely applied in the ML literature. The heterogeneous version of classifier fusion - fusing the predictions from different model types - has been less explored. Here, we investigate heterogeneous classifier fusion for ligand-based VS using three different ML methods, RF, naïve Bayes (NB), and logistic regression (LR), with four 2D fingerprints, atom pairs, topological torsions, RDKit fingerprint, and circular fingerprint. The methods are compared using a previously developed benchmarking platform for 2D fingerprints which is extended to ML methods in this article. The original data sets are filtered for difficulty, and a new set of challenging data sets from ChEMBL is added. Data sets were also generated for a second use case: starting from a small set of related actives instead of diverse actives. The final fused model consistently outperforms the other approaches across the broad variety of targets studied, indicating that heterogeneous classifier fusion is a very promising approach for ligand-based VS. The new data sets together with the adapted source code for ML methods are provided in the Supporting Information .

Bristol Bay Assessment - Final Report (2014)

EPA Pesticide Factsheets

This is the final Bristol Bay assessment developed and peer reviewed by the Office of Research and Development in EPA. The purpose of this assessment is to provide a characterization of the biological and mineral resources of the Bristol Bay watershed.

76 FR 31851 - Safety Zone; Put-in-Bay Fireworks, Fox's the Dock Pier; South Bass Island, Put-in-Bay, OH

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-02

... DEPARTMENT OF HOMELAND SECURITY Coast Guard 33 CFR Part 165 [Docket No. USCG-2011-0417] RIN 1625-AA00 Safety Zone; Put-in-Bay Fireworks, Fox's the Dock Pier; South Bass Island, Put-in-Bay, OH AGENCY.... Add Sec. 165.T09-0417 as follows: Sec. 165.T09-0417 Safety Zone; Put-In-Bay Fireworks, Fox's the Dock...

SF Bay Delta TMDL Progress Assessment

EPA Pesticide Factsheets

EPA assessed the progress 14 TMDLs in the SF Bay Delta Estuary (SF Bay Delta) to determine if the actions called for in the TMDL were being accomplished and water quality was improving. Status and water quality reports can be found here.

Small molecule drug A-769662 and AMP synergistically activate naive AMPK independent of upstream kinase signaling.

PubMed

Scott, John W; Ling, Naomi; Issa, Samah M A; Dite, Toby A; O'Brien, Matthew T; Chen, Zhi-Ping; Galic, Sandra; Langendorf, Christopher G; Steinberg, Gregory R; Kemp, Bruce E; Oakhill, Jonathan S

2014-05-22

The AMP-activated protein kinase (AMPK) is a metabolic stress-sensing αβγ heterotrimer responsible for energy homeostasis, making it a therapeutic target for metabolic diseases such as type 2 diabetes and obesity. AMPK signaling is triggered by phosphorylation on the AMPK α subunit activation loop Thr172 by upstream kinases. Dephosphorylated, naive AMPK is thought to be catalytically inactive and insensitive to allosteric regulation by AMP and direct AMPK-activating drugs such as A-769662. Here we show that A-769662 activates AMPK independently of α-Thr172 phosphorylation, provided β-Ser108 is phosphorylated. Although neither A-769662 nor AMP individually stimulate the activity of dephosphorylated AMPK, together they stimulate >1,000-fold, bypassing the requirement for β-Ser108 phosphorylation. Consequently A-769662 and AMP together activate naive AMPK entirely allosterically and independently of upstream kinase signaling. These findings have important implications for development of AMPK-targeting therapeutics and point to possible combinatorial therapeutic strategies based on AMP and AMPK drugs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Toxic phytoplankton in San Francisco Bay

USGS Publications Warehouse

Rodgers, Kristine M.; Garrison, David L.; Cloern, James E.

1996-01-01

The Regional Monitoring Program (RMP) was conceived and designed to document the changing distribution and effects of trace substances in San Francisco Bay, with focus on toxic contaminants that have become enriched by human inputs. However, coastal ecosystems like San Francisco Bay also have potential sources of naturally-produced toxic substances that can disrupt food webs and, under extreme circumstances, become threats to public health. The most prevalent source of natural toxins is from blooms of algal species that can synthesize metabolites that are toxic to invertebrates or vertebrates. Although San Francisco Bay is nutrient-rich, it has so far apparently been immune from the epidemic of harmful algal blooms in the world’s nutrient-enriched coastal waters. This absence of acute harmful blooms does not imply that San Francisco Bay has unique features that preclude toxic blooms. No sampling program has been implemented to document the occurrence of toxin-producing algae in San Francisco Bay, so it is difficult to judge the likelihood of such events in the future. This issue is directly relevant to the goals of RMP because harmful species of phytoplankton have the potential to disrupt ecosystem processes that support animal populations, cause severe illness or death in humans, and confound the outcomes of toxicity bioassays such as those included in the RMP. Our purpose here is to utilize existing data on the phytoplankton community of San Francisco Bay to provide a provisional statement about the occurrence, distribution, and potential threats of harmful algae in this Estuary.

33 CFR 165.1197 - Security Zones; San Francisco Bay, San Pablo Bay, Carquinez Strait, Suisun Bay, California.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., Carquinez Strait, Suisun Bay, California. (a) Locations. The following areas are security zones: (1) Chevron... sea floor within approximately 100 yards of the Chevron Long Wharf, Richmond, CA, and encompasses all...

33 CFR 165.1197 - Security Zones; San Francisco Bay, San Pablo Bay, Carquinez Strait, Suisun Bay, California.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., Carquinez Strait, Suisun Bay, California. (a) Locations. The following areas are security zones: (1) Chevron... sea floor within approximately 100 yards of the Chevron Long Wharf, Richmond, CA, and encompasses all...

33 CFR 165.1197 - Security Zones; San Francisco Bay, San Pablo Bay, Carquinez Strait, Suisun Bay, California.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., Carquinez Strait, Suisun Bay, California. (a) Locations. The following areas are security zones: (1) Chevron... sea floor within approximately 100 yards of the Chevron Long Wharf, Richmond, CA, and encompasses all...

33 CFR 165.1197 - Security Zones; San Francisco Bay, San Pablo Bay, Carquinez Strait, Suisun Bay, California.

Code of Federal Regulations, 2014 CFR

2014-07-01