Marginal bone level changes in association with different vertical implant positions: a 3-year retrospective study

PubMed Central

2017-01-01

Purpose To retrospectively evaluate the relationship between the vertical position of the implant-abutment interface and marginal bone loss over 3 years using radiological analysis. Methods In total, 286 implant surfaces of 143 implants from 61 patients were analyzed. Panoramic radiographic images were taken immediately after implant installation and at 6, 12, and 36 months after loading. The implants were classified into 3 groups based on the vertical position of the implant-abutment interface: group A (above bone level), group B (at bone level), and group C (below bone level). The radiographs were analyzed by a single examiner. Results Changes in marginal bone levels of 0.99±1.45, 1.13±0.91, and 1.76±0.78 mm were observed at 36 months after loading in groups A, B, and C, respectively, and bone loss was significantly greater in group C than in groups A and B. Conclusions The vertical position of the implant-abutment interface may affect marginal bone level change. Marginal bone loss was significantly greater in cases where the implant-abutment interface was positioned below the marginal bone. Further long-term study is required to validate our results. PMID:28861287

A Filter Feature Selection Method Based on MFA Score and Redundancy Excluding and It's Application to Tumor Gene Expression Data Analysis.

PubMed

Li, Jiangeng; Su, Lei; Pang, Zenan

2015-12-01

Feature selection techniques have been widely applied to tumor gene expression data analysis in recent years. A filter feature selection method named marginal Fisher analysis score (MFA score) which is based on graph embedding has been proposed, and it has been widely used mainly because it is superior to Fisher score. Considering the heavy redundancy in gene expression data, we proposed a new filter feature selection technique in this paper. It is named MFA score+ and is based on MFA score and redundancy excluding. We applied it to an artificial dataset and eight tumor gene expression datasets to select important features and then used support vector machine as the classifier to classify the samples. Compared with MFA score, t test and Fisher score, it achieved higher classification accuracy.

Use of border information in the classification of mammographic masses

NASA Astrophysics Data System (ADS)

Varela, C.; Timp, S.; Karssemeijer, N.

2006-01-01

We are developing a new method to characterize the margin of a mammographic mass lesion to improve the classification of benign and malignant masses. Towards this goal, we designed features that measure the degree of sharpness and microlobulation of mass margins. We calculated these features in a border region of the mass defined as a thin band along the mass contour. The importance of these features in the classification of benign and malignant masses was studied in relation to existing features used for mammographic mass detection. Features were divided into three groups, each representing a different mass segment: the interior region of a mass, the border and the outer area. The interior and the outer area of a mass were characterized using contrast and spiculation measures. Classification was done in two steps. First, features representing each of the three mass segments were merged into a neural network classifier resulting in a single regional classification score for each segment. Secondly, a classifier combined the three single scores into a final output to discriminate between benign and malignant lesions. We compared the classification performance of each regional classifier and the combined classifier on a data set of 1076 biopsy proved masses (590 malignant and 486 benign) from 481 women included in the Digital Database for Screening Mammography. Receiver operating characteristic (ROC) analysis was used to evaluate the accuracy of the classifiers. The area under the ROC curve (Az) was 0.69 for the interior mass segment, 0.76 for the border segment and 0.75 for the outer mass segment. The performance of the combined classifier was 0.81 for image-based and 0.83 for case-based evaluation. These results show that the combination of information from different mass segments is an effective approach for computer-aided characterization of mammographic masses. An advantage of this approach is that it allows the assessment of the contribution of regions rather than individual features. Results suggest that the border and the outer areas contained the most valuable information for discrimination between benign and malignant masses.

One-millimeter cancer-free margin is curative for colorectal liver metastases: a propensity score case-match approach.

PubMed

Hamady, Zaed Z R; Lodge, J Peter A; Welsh, Fenella K; Toogood, Giles J; White, Alan; John, Timothy; Rees, Myrddin

2014-03-01

To investigate the influence of clear surgical resection margin width on disease recurrence rate after intentionally curative resection of colorectal liver metastases. There is consensus that a histological positive resection margin is a predictor of disease recurrence after resection of colorectal liver metastases. The dispute, however, over the width of cancer-free resection margin required is ongoing. Analysis of observational prospectively collected data for 2715 patients who underwent primary resection of colorectal liver metastases from 2 major hepatobiliary units in the United Kingdom. Histological cancer-free resection margin was classified as positive (if cancer cells present at less than 1 mm from the resection margin) or negative (if the distance between the cancer and the margin is 1 mm or more). The negative margin was further classified according to the distance from the tumor in millimeters. Predictors of disease-free survival were analyzed in univariate and multivariate analyses. A case-match analysis by a propensity score method was undertaken to reduce bias. A 1-mm cancer-free resection margin was sufficient to achieve 33% 5-year overall disease-free survival. Extra margin width did not add disease-free survival advantage (P > 0.05). After the propensity case-match analysis, there is no statistical difference in disease-free survival between patients with negative narrow and wider margin clearance [hazard ratio (HR) 1.0; 95% (confidence interval) CI: 0.9-1.2; P = 0.579 at 5-mm cutoff and HR 1.1; 95% CI: 0.96-1.3; P = 0.149 at 10-mm cutoff]. Patients with extrahepatic disease and positive lymph node primary tumor did not have disease-free survival advantage despite surgical margin clearance (9 months for <1-mm vs 12 months for ≥1-mm margin clearance; P = 0.062). One-mm cancer-free resection margin achieved in patients with colorectal liver metastases should now be considered the standard of care.

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).

Towards intraoperative surgical margin assessment and visualization using bioimpedance properties of the tissue

NASA Astrophysics Data System (ADS)

Khan, Shadab; Mahara, Aditya; Hyams, Elias S.; Schned, Alan; Halter, Ryan

2015-03-01

Prostate cancer (PCa) has a high 10-year recurrence rate, making PCa the second leading cause of cancer-specific mortality among men in the USA. PCa recurrences are often predicted by assessing the status of surgical margins (SM) with positive surgical margins (PSM) increasing the chances of biochemical recurrence by 2-4 times. To this end, an SM assessment system using Electrical Impedance Spectroscopy (EIS) was developed with a microendoscopic probe. This system measures the tissue bioimpedance over a range of frequencies (1 kHz to 1MHz), and computes a Composite Impedance Metric (CIM). CIM can be used to classify tissue as benign or cancerous. The system was used to collect the impedance spectra from excised prostates, which were obtained from men undergoing radical prostatectomy. The data revealed statistically significant (p<0.05) differences in the impedance properties of the benign and tumorous tissues, and between different tissue morphologies. To visualize the results of SM-assessment, a visualization tool using da Vinci stereo laparoscope is being developed. Together with the visualization tool, the EIS-based SM assessment system can be potentially used to intraoperatively classify tissues and display the results on the surgical console with a video feed of the surgical site, thereby augmenting a surgeon's view of the site and providing a potential solution to the intraoperative SM assessment needs.

Sustainable biomass production on Marginal Lands (SEEMLA)

NASA Astrophysics Data System (ADS)

Barbera, Federica; Baumgarten, Wibke; Pelikan, Vincent

2017-04-01

Sustainable biomass production on Marginal Lands (SEEMLA) The main objective of the H2020 funded EU project SEEMLA (acronym for Sustainable Exploitation of Biomass for Bioenergy from Marginal Lands in Europe) is the establishment of suitable innovative land-use strategies for a sustainable production of plant-based energy on marginal lands while improving general ecosystem services. The use of marginal lands (MagL) could contribute to the mitigation of the fast growing competition between traditional food production and production of renewable bio-resources on arable lands. SEEMLA focuses on the promotion of re-conversion of MagLs for the production of bioenergy through the direct involvement of farmers and forester, the strengthening of local small-scale supply chains, and the promotion of plantations of bioenergy plants on MagLs. Life cycle assessment is performed in order to analyse possible impacts on the environment. A soil quality rating tool is applied to define and classify MagL. Suitable perennial and woody bioenergy crops are selected to be grown in pilot areas in the partner countries Ukraine, Greece and Germany. SEEMLA is expected to contribute to an increasing demand of biomass for bioenergy production in order to meet the 2020 targets and beyond.

A Novel Locally Linear KNN Method With Applications to Visual Recognition.

PubMed

Liu, Qingfeng; Liu, Chengjun

2017-09-01

A locally linear K Nearest Neighbor (LLK) method is presented in this paper with applications to robust visual recognition. Specifically, the concept of an ideal representation is first presented, which improves upon the traditional sparse representation in many ways. The objective function based on a host of criteria for sparsity, locality, and reconstruction is then optimized to derive a novel representation, which is an approximation to the ideal representation. The novel representation is further processed by two classifiers, namely, an LLK-based classifier and a locally linear nearest mean-based classifier, for visual recognition. The proposed classifiers are shown to connect to the Bayes decision rule for minimum error. Additional new theoretical analysis is presented, such as the nonnegative constraint, the group regularization, and the computational efficiency of the proposed LLK method. New methods such as a shifted power transformation for improving reliability, a coefficients' truncating method for enhancing generalization, and an improved marginal Fisher analysis method for feature extraction are proposed to further improve visual recognition performance. Extensive experiments are implemented to evaluate the proposed LLK method for robust visual recognition. In particular, eight representative data sets are applied for assessing the performance of the LLK method for various visual recognition applications, such as action recognition, scene recognition, object recognition, and face recognition.

RBoost: Label Noise-Robust Boosting Algorithm Based on a Nonconvex Loss Function and the Numerically Stable Base Learners.

PubMed

Miao, Qiguang; Cao, Ying; Xia, Ge; Gong, Maoguo; Liu, Jiachen; Song, Jianfeng

2016-11-01

AdaBoost has attracted much attention in the machine learning community because of its excellent performance in combining weak classifiers into strong classifiers. However, AdaBoost tends to overfit to the noisy data in many applications. Accordingly, improving the antinoise ability of AdaBoost plays an important role in many applications. The sensitiveness to the noisy data of AdaBoost stems from the exponential loss function, which puts unrestricted penalties to the misclassified samples with very large margins. In this paper, we propose two boosting algorithms, referred to as RBoost1 and RBoost2, which are more robust to the noisy data compared with AdaBoost. RBoost1 and RBoost2 optimize a nonconvex loss function of the classification margin. Because the penalties to the misclassified samples are restricted to an amount less than one, RBoost1 and RBoost2 do not overfocus on the samples that are always misclassified by the previous base learners. Besides the loss function, at each boosting iteration, RBoost1 and RBoost2 use numerically stable ways to compute the base learners. These two improvements contribute to the robustness of the proposed algorithms to the noisy training and testing samples. Experimental results on the synthetic Gaussian data set, the UCI data sets, and a real malware behavior data set illustrate that the proposed RBoost1 and RBoost2 algorithms perform better when the training data sets contain noisy data.

Face recognition using total margin-based adaptive fuzzy support vector machines.

PubMed

Liu, Yi-Hung; Chen, Yen-Ting

2007-01-01

This paper presents a new classifier called total margin-based adaptive fuzzy support vector machines (TAF-SVM) that deals with several problems that may occur in support vector machines (SVMs) when applied to the face recognition. The proposed TAF-SVM not only solves the overfitting problem resulted from the outlier with the approach of fuzzification of the penalty, but also corrects the skew of the optimal separating hyperplane due to the very imbalanced data sets by using different cost algorithm. In addition, by introducing the total margin algorithm to replace the conventional soft margin algorithm, a lower generalization error bound can be obtained. Those three functions are embodied into the traditional SVM so that the TAF-SVM is proposed and reformulated in both linear and nonlinear cases. By using two databases, the Chung Yuan Christian University (CYCU) multiview and the facial recognition technology (FERET) face databases, and using the kernel Fisher's discriminant analysis (KFDA) algorithm to extract discriminating face features, experimental results show that the proposed TAF-SVM is superior to SVM in terms of the face-recognition accuracy. The results also indicate that the proposed TAF-SVM can achieve smaller error variances than SVM over a number of tests such that better recognition stability can be obtained.

Heidelberg retina tomograph measurements of the optic disc and parapapillary retina for detecting glaucoma analyzed by machine learning classifiers.

PubMed

Zangwill, Linda M; Chan, Kwokleung; Bowd, Christopher; Hao, Jicuang; Lee, Te-Won; Weinreb, Robert N; Sejnowski, Terrence J; Goldbaum, Michael H

2004-09-01

To determine whether topographical measurements of the parapapillary region analyzed by machine learning classifiers can detect early to moderate glaucoma better than similarly processed measurements obtained within the disc margin and to improve methods for optimization of machine learning classifier feature selection. One eye of each of 95 patients with early to moderate glaucomatous visual field damage and of each of 135 normal subjects older than 40 years participating in the longitudinal Diagnostic Innovations in Glaucoma Study (DIGS) were included. Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Dossenheim, Germany) mean height contour was measured in 36 equal sectors, both along the disc margin and in the parapapillary region (at a mean contour line radius of 1.7 mm). Each sector was evaluated individually and in combination with other sectors. Gaussian support vector machine (SVM) learning classifiers were used to interpret HRT sector measurements along the disc margin and in the parapapillary region, to differentiate between eyes with normal and glaucomatous visual fields and to compare the results with global and regional HRT parameter measurements. The area under the receiver operating characteristic (ROC) curve was used to measure diagnostic performance of the HRT parameters and to evaluate the cross-validation strategies and forward selection and backward elimination optimization techniques that were used to generate the reduced feature sets. The area under the ROC curve for mean height contour of the 36 sectors along the disc margin was larger than that for the mean height contour in the parapapillary region (0.97 and 0.85, respectively). Of the 36 individual sectors along the disc margin, those in the inferior region between 240 degrees and 300 degrees, had the largest area under the ROC curve (0.85-0.91). With SVM Gaussian techniques, the regional parameters showed the best ability to discriminate between normal eyes and eyes with glaucomatous visual field damage, followed by the global parameters, mean height contour measures along the disc margin, and mean height contour measures in the parapapillary region. The area under the ROC curve was 0.98, 0.94, 0.93, and 0.85, respectively. Cross-validation and optimization techniques demonstrated that good discrimination (99% of peak area under the ROC curve) can be obtained with a reduced number of HRT parameters. Mean height contour measurements along the disc margin discriminated between normal and glaucomatous eyes better than measurements obtained in the parapapillary region. Copyright Association for Research in Vision and Ophthalmology

Heidelberg Retina Tomograph Measurements of the Optic Disc and Parapapillary Retina for Detecting Glaucoma Analyzed by Machine Learning Classifiers

PubMed Central

Zangwill, Linda M.; Chan, Kwokleung; Bowd, Christopher; Hao, Jicuang; Lee, Te-Won; Weinreb, Robert N.; Sejnowski, Terrence J.; Goldbaum, Michael H.

2010-01-01

Purpose To determine whether topographical measurements of the parapapillary region analyzed by machine learning classifiers can detect early to moderate glaucoma better than similarly processed measurements obtained within the disc margin and to improve methods for optimization of machine learning classifier feature selection. Methods One eye of each of 95 patients with early to moderate glaucomatous visual field damage and of each of 135 normal subjects older than 40 years participating in the longitudinal Diagnostic Innovations in Glaucoma Study (DIGS) were included. Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Dossenheim, Germany) mean height contour was measured in 36 equal sectors, both along the disc margin and in the parapapillary region (at a mean contour line radius of 1.7 mm). Each sector was evaluated individually and in combination with other sectors. Gaussian support vector machine (SVM) learning classifiers were used to interpret HRT sector measurements along the disc margin and in the parapapillary region, to differentiate between eyes with normal and glaucomatous visual fields and to compare the results with global and regional HRT parameter measurements. The area under the receiver operating characteristic (ROC) curve was used to measure diagnostic performance of the HRT parameters and to evaluate the cross-validation strategies and forward selection and backward elimination optimization techniques that were used to generate the reduced feature sets. Results The area under the ROC curve for mean height contour of the 36 sectors along the disc margin was larger than that for the mean height contour in the parapapillary region (0.97 and 0.85, respectively). Of the 36 individual sectors along the disc margin, those in the inferior region between 240° and 300°, had the largest area under the ROC curve (0.85–0.91). With SVM Gaussian techniques, the regional parameters showed the best ability to discriminate between normal eyes and eyes with glaucomatous visual field damage, followed by the global parameters, mean height contour measures along the disc margin, and mean height contour measures in the parapapillary region. The area under the ROC curve was 0.98, 0.94, 0.93, and 0.85, respectively. Cross-validation and optimization techniques demonstrated that good discrimination (99% of peak area under the ROC curve) can be obtained with a reduced number of HRT parameters. Conclusions Mean height contour measurements along the disc margin discriminated between normal and glaucomatous eyes better than measurements obtained in the parapapillary region. PMID:15326133

Support Vector Machines for Differential Prediction

PubMed Central

Kuusisto, Finn; Santos Costa, Vitor; Nassif, Houssam; Burnside, Elizabeth; Page, David; Shavlik, Jude

2015-01-01

Machine learning is continually being applied to a growing set of fields, including the social sciences, business, and medicine. Some fields present problems that are not easily addressed using standard machine learning approaches and, in particular, there is growing interest in differential prediction. In this type of task we are interested in producing a classifier that specifically characterizes a subgroup of interest by maximizing the difference in predictive performance for some outcome between subgroups in a population. We discuss adapting maximum margin classifiers for differential prediction. We first introduce multiple approaches that do not affect the key properties of maximum margin classifiers, but which also do not directly attempt to optimize a standard measure of differential prediction. We next propose a model that directly optimizes a standard measure in this field, the uplift measure. We evaluate our models on real data from two medical applications and show excellent results. PMID:26158123

Support Vector Machines for Differential Prediction.

PubMed

Kuusisto, Finn; Santos Costa, Vitor; Nassif, Houssam; Burnside, Elizabeth; Page, David; Shavlik, Jude

Machine learning is continually being applied to a growing set of fields, including the social sciences, business, and medicine. Some fields present problems that are not easily addressed using standard machine learning approaches and, in particular, there is growing interest in differential prediction . In this type of task we are interested in producing a classifier that specifically characterizes a subgroup of interest by maximizing the difference in predictive performance for some outcome between subgroups in a population. We discuss adapting maximum margin classifiers for differential prediction. We first introduce multiple approaches that do not affect the key properties of maximum margin classifiers, but which also do not directly attempt to optimize a standard measure of differential prediction. We next propose a model that directly optimizes a standard measure in this field, the uplift measure. We evaluate our models on real data from two medical applications and show excellent results.

Correlation of in vitro challenge testing with consumer use testing for cosmetic products.

PubMed Central

Brannan, D K; Dille, J C; Kaufman, D J

1987-01-01

An in vitro microbial challenge test has been developed to predict the likelihood of consumer contamination of cosmetic products. The challenge test involved inoculating product at four concentrations (30, 50, 70, and 100%) with microorganisms known to contaminate cosmetics. Elimination of these microorganisms at each concentration was followed over a 28-day period. The test was used to classify products as poorly preserved, marginally preserved, or well preserved. Consumer use testing was then used to determine whether the test predicted the risk of actual consumer contamination. Products classified by the challenge test as poorly preserved returned 46 to 90% contaminated after use. Products classified by the challenge test as well preserved returned with no contamination. Marginally preserved products returned with 0 to 21% of the used units contaminated. As a result, the challenge test described can be accurately used to predict the risk of consumer contamination of cosmetic products. PMID:3662517

Multiple Ordinal Regression by Maximizing the Sum of Margins

PubMed Central

Hamsici, Onur C.; Martinez, Aleix M.

2016-01-01

Human preferences are usually measured using ordinal variables. A system whose goal is to estimate the preferences of humans and their underlying decision mechanisms requires to learn the ordering of any given sample set. We consider the solution of this ordinal regression problem using a Support Vector Machine algorithm. Specifically, the goal is to learn a set of classifiers with common direction vectors and different biases correctly separating the ordered classes. Current algorithms are either required to solve a quadratic optimization problem, which is computationally expensive, or are based on maximizing the minimum margin (i.e., a fixed margin strategy) between a set of hyperplanes, which biases the solution to the closest margin. Another drawback of these strategies is that they are limited to order the classes using a single ranking variable (e.g., perceived length). In this paper, we define a multiple ordinal regression algorithm based on maximizing the sum of the margins between every consecutive class with respect to one or more rankings (e.g., perceived length and weight). We provide derivations of an efficient, easy-to-implement iterative solution using a Sequential Minimal Optimization procedure. We demonstrate the accuracy of our solutions in several datasets. In addition, we provide a key application of our algorithms in estimating human subjects’ ordinal classification of attribute associations to object categories. We show that these ordinal associations perform better than the binary one typically employed in the literature. PMID:26529784

A semi-Markov model for mitosis segmentation in time-lapse phase contrast microscopy image sequences of stem cell populations.

PubMed

Liu, An-An; Li, Kang; Kanade, Takeo

2012-02-01

We propose a semi-Markov model trained in a max-margin learning framework for mitosis event segmentation in large-scale time-lapse phase contrast microscopy image sequences of stem cell populations. Our method consists of three steps. First, we apply a constrained optimization based microscopy image segmentation method that exploits phase contrast optics to extract candidate subsequences in the input image sequence that contains mitosis events. Then, we apply a max-margin hidden conditional random field (MM-HCRF) classifier learned from human-annotated mitotic and nonmitotic sequences to classify each candidate subsequence as a mitosis or not. Finally, a max-margin semi-Markov model (MM-SMM) trained on manually-segmented mitotic sequences is utilized to reinforce the mitosis classification results, and to further segment each mitosis into four predefined temporal stages. The proposed method outperforms the event-detection CRF model recently reported by Huh as well as several other competing methods in very challenging image sequences of multipolar-shaped C3H10T1/2 mesenchymal stem cells. For mitosis detection, an overall precision of 95.8% and a recall of 88.1% were achieved. For mitosis segmentation, the mean and standard deviation for the localization errors of the start and end points of all mitosis stages were well below 1 and 2 frames, respectively. In particular, an overall temporal location error of 0.73 ± 1.29 frames was achieved for locating daughter cell birth events.

Classification of Tidal Disruption Events Based on Stellar Orbital Properties

NASA Astrophysics Data System (ADS)

Hayasaki, Kimitake; Zhong, Shiyan; Li, Shuo; Berczik, Peter; Spurzem, Rainer

2018-03-01

We study the rates of tidal disruption of stars on bound to unbound orbits by intermediate-mass to supermassive black holes using high-accuracy direct N-body experiments. Stars from the star cluster approaching the black hole can have three types of orbit: eccentric, parabolic, and hyperbolic. Since the mass fallback rate shows different variabilities depending on the orbital type, we can classify tidal disruption events (TDEs) into three main categories: eccentric, parabolic, and hyperbolic. The respective TDEs are characterized by two critical values of the orbital eccentricity: the lower critical eccentricity is the one below which stars on eccentric orbits cause finite, intense accretion, and the upper critical eccentricity is the one above which stars on hyperbolic orbits cause no accretion. Moreover, we find that parabolic TDEs can be divided into three subclasses: precisely parabolic, marginally eccentric, and marginally hyperbolic. We analytically derive that the mass fallback rate of marginally eccentric TDEs can be flatter and slightly higher than the standard fallback rate proportional to t ‑5/3, whereas it can be flatter and lower for marginally hyperbolic TDEs. We confirm using N-body experiments that only a few eccentric, precisely parabolic, and hyperbolic TDEs can occur in a spherical stellar system with a single intermediate-mass to supermassive black hole. A substantial fraction of the stars approaching the black hole would cause marginally eccentric or marginally hyperbolic TDEs.

An ordinal classification approach for CTG categorization.

PubMed

Georgoulas, George; Karvelis, Petros; Gavrilis, Dimitris; Stylios, Chrysostomos D; Nikolakopoulos, George

2017-07-01

Evaluation of cardiotocogram (CTG) is a standard approach employed during pregnancy and delivery. But, its interpretation requires high level expertise to decide whether the recording is Normal, Suspicious or Pathological. Therefore, a number of attempts have been carried out over the past three decades for development automated sophisticated systems. These systems are usually (multiclass) classification systems that assign a category to the respective CTG. However most of these systems usually do not take into consideration the natural ordering of the categories associated with CTG recordings. In this work, an algorithm that explicitly takes into consideration the ordering of CTG categories, based on binary decomposition method, is investigated. Achieved results, using as a base classifier the C4.5 decision tree classifier, prove that the ordinal classification approach is marginally better than the traditional multiclass classification approach, which utilizes the standard C4.5 algorithm for several performance criteria.

An intelligent identification algorithm for the monoclonal picking instrument

NASA Astrophysics Data System (ADS)

Yan, Hua; Zhang, Rongfu; Yuan, Xujun; Wang, Qun

2017-11-01

The traditional colony selection is mainly operated by manual mode, which takes on low efficiency and strong subjectivity. Therefore, it is important to develop an automatic monoclonal-picking instrument. The critical stage of the automatic monoclonal-picking and intelligent optimal selection is intelligent identification algorithm. An auto-screening algorithm based on Support Vector Machine (SVM) is proposed in this paper, which uses the supervised learning method, which combined with the colony morphological characteristics to classify the colony accurately. Furthermore, through the basic morphological features of the colony, system can figure out a series of morphological parameters step by step. Through the establishment of maximal margin classifier, and based on the analysis of the growth trend of the colony, the selection of the monoclonal colony was carried out. The experimental results showed that the auto-screening algorithm could screen out the regular colony from the other, which meets the requirement of various parameters.

The role of deep-water sedimentary processes in shaping a continental margin: The Northwest Atlantic

USGS Publications Warehouse

Mosher, David C.; Campbell, D.C.; Gardner, J.V.; Piper, D.J.W.; Chaytor, Jason; Rebesco, M.

2017-01-01

The tectonic history of a margin dictates its general shape; however, its geomorphology is generally transformed by deep-sea sedimentary processes. The objective of this study is to show the influences of turbidity currents, contour currents and sediment mass failures on the geomorphology of the deep-water northwestern Atlantic margin (NWAM) between Blake Ridge and Hudson Trough, spanning about 32° of latitude and the shelf edge to the abyssal plain. This assessment is based on new multibeam echosounder data, global bathymetric models and sub-surface geophysical information.The deep-water NWAM is divided into four broad geomorphologic classifications based on their bathymetric shape: graded, above-grade, stepped and out-of-grade. These shapes were created as a function of the balance between sediment accumulation and removal that in turn were related to sedimentary processes and slope-accommodation. This descriptive method of classifying continental margins, while being non-interpretative, is more informative than the conventional continental shelf, slope and rise classification, and better facilitates interpretation concerning dominant sedimentary processes.Areas of the margin dominated by turbidity currents and slope by-pass developed graded slopes. If sediments did not by-pass the slope due to accommodation then an above grade or stepped slope resulted. Geostrophic currents created sedimentary bodies of a variety of forms and positions along the NWAM. Detached drifts form linear, above-grade slopes along their crests from the shelf edge to the deep basin. Plastered drifts formed stepped slope profiles. Sediment mass failure has had a variety of consequences on the margin morphology; large mass-failures created out-of-grade profiles, whereas smaller mass failures tended to remain on the slope and formed above-grade profiles at trough-mouth fans, or nearly graded profiles, such as offshore Cape Fear.

Agro-climatic zoning of Jatropha curcas as a subside for crop planning and implementation in Brazil.

PubMed

Yamada, Eliane S M; Sentelhas, Paulo C

2014-11-01

As jatropha (Jatropha curcas L.) is a recent crop in Brazil, the studies for defining its suitability for different regions are not yet available, even considering the promises about this plant as of high potential for marginal zones where poor soils and dry climate occur. Based on that, the present study had as objective to characterize the climatic conditions of jatropha's center of origin in Central America for establishing its climatic requirements and to develop the agro-climatic zoning for this crop for some Brazilian regions where, according to the literature, it would be suitable. For classifying the climatic conditions of the jatropha's center of origin, climate data from 123 weather stations located in Mexico (93) and in Guatemala (30) were used. These data were input for Thornthwaite and Mather's climatological water balance for determining the annual water deficiency (WD) and water surplus (WS) of each location, considering a soil water-holding capacity (SWHC) of 100 mm. Mean annual temperature (T m), WD, and WS data were organized in histograms for defining the limits of suitability for jatropha cultivation. The results showed that the suitable range of T m for jatropha cultivation is between 23 and 27 °C. T m between 15 and 22.9 °C and between 27.1 and 28 °C were classified as marginal by thermal deficiency and excess, respectively. T m below 15 °C and above 28 °C were considered as unsuitable for jatropha cultivation, respectively, by risk of frosts and physiological disturbs. For WD, suitability for rain-fed jatropha cultivation was considered when its value is below 360 mm, while between 361 and 720 mm is considered as marginal and over 720 mm unsuitable. The same order of suitability was also defined for WS, with the following limits: suitable for WS up to 1,200 mm; marginal for WS between 1,201 and 2,400 mm, and unsuitable for WS above 2,400 mm. For the crop zoning, the criteria previously defined were applied to 1,814 climate stations in the following Brazilian regions: Northeast (NE) region and the states of Goiás (GO), Tocantins (TO), and Minas Gerais (MG). The suitability maps were generated by crossing the crop climate requirements with the interpolated climate conditions of the selected regions. The maps showed that only 22.65% of the areas in the NE region are suitable for jatropha as a rain-fed crop. The other areas of the region are classified as marginal (62.61%) and unsuitable (14.74%). In the states of GO and TO, the majority of the areas (47.78%) is classified as suitable, and in the state of MG, 33.92% of the territory has suitability for the crop. These results prove that jatropha cannot be cultivated everywhere and will require, as any other crop, minimum climatic conditions to have sustainable performance and high yields.

Rules based process window OPC

NASA Astrophysics Data System (ADS)

O'Brien, Sean; Soper, Robert; Best, Shane; Mason, Mark

2008-03-01

As a preliminary step towards Model-Based Process Window OPC we have analyzed the impact of correcting post-OPC layouts using rules based methods. Image processing on the Brion Tachyon was used to identify sites where the OPC model/recipe failed to generate an acceptable solution. A set of rules for 65nm active and poly were generated by classifying these failure sites. The rules were based upon segment runlengths, figure spaces, and adjacent figure widths. 2.1 million sites for active were corrected in a small chip (comparing the pre and post rules based operations), and 59 million were found at poly. Tachyon analysis of the final reticle layout found weak margin sites distinct from those sites repaired by rules-based corrections. For the active layer more than 75% of the sites corrected by rules would have printed without a defect indicating that most rulesbased cleanups degrade the lithographic pattern. Some sites were missed by the rules based cleanups due to either bugs in the DRC software or gaps in the rules table. In the end dramatic changes to the reticle prevented catastrophic lithography errors, but this method is far too blunt. A more subtle model-based procedure is needed changing only those sites which have unsatisfactory lithographic margin.

Chinese Sentence Classification Based on Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Gu, Chengwei; Wu, Ming; Zhang, Chuang

2017-10-01

Sentence classification is one of the significant issues in Natural Language Processing (NLP). Feature extraction is often regarded as the key point for natural language processing. Traditional ways based on machine learning can not take high level features into consideration, such as Naive Bayesian Model. The neural network for sentence classification can make use of contextual information to achieve greater results in sentence classification tasks. In this paper, we focus on classifying Chinese sentences. And the most important is that we post a novel architecture of Convolutional Neural Network (CNN) to apply on Chinese sentence classification. In particular, most of the previous methods often use softmax classifier for prediction, we embed a linear support vector machine to substitute softmax in the deep neural network model, minimizing a margin-based loss to get a better result. And we use tanh as an activation function, instead of ReLU. The CNN model improve the result of Chinese sentence classification tasks. Experimental results on the Chinese news title database validate the effectiveness of our model.

Feature extraction based on semi-supervised kernel Marginal Fisher analysis and its application in bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Jiang, Li; Xuan, Jianping; Shi, Tielin

2013-12-01

Generally, the vibration signals of faulty machinery are non-stationary and nonlinear under complicated operating conditions. Therefore, it is a big challenge for machinery fault diagnosis to extract optimal features for improving classification accuracy. This paper proposes semi-supervised kernel Marginal Fisher analysis (SSKMFA) for feature extraction, which can discover the intrinsic manifold structure of dataset, and simultaneously consider the intra-class compactness and the inter-class separability. Based on SSKMFA, a novel approach to fault diagnosis is put forward and applied to fault recognition of rolling bearings. SSKMFA directly extracts the low-dimensional characteristics from the raw high-dimensional vibration signals, by exploiting the inherent manifold structure of both labeled and unlabeled samples. Subsequently, the optimal low-dimensional features are fed into the simplest K-nearest neighbor (KNN) classifier to recognize different fault categories and severities of bearings. The experimental results demonstrate that the proposed approach improves the fault recognition performance and outperforms the other four feature extraction methods.

A Raman spectroscopy bio-sensor for tissue discrimination in surgical robotics.

PubMed

Ashok, Praveen C; Giardini, Mario E; Dholakia, Kishan; Sibbett, Wilson

2014-01-01

We report the development of a fiber-based Raman sensor to be used in tumour margin identification during endoluminal robotic surgery. Although this is a generic platform, the sensor we describe was adapted for the ARAKNES (Array of Robots Augmenting the KiNematics of Endoluminal Surgery) robotic platform. On such a platform, the Raman sensor is intended to identify ambiguous tissue margins during robot-assisted surgeries. To maintain sterility of the probe during surgical intervention, a disposable sleeve was specially designed. A straightforward user-compatible interface was implemented where a supervised multivariate classification algorithm was used to classify different tissue types based on specific Raman fingerprints so that it could be used without prior knowledge of spectroscopic data analysis. The protocol avoids inter-patient variability in data and the sensor system is not restricted for use in the classification of a particular tissue type. Representative tissue classification assessments were performed using this system on excised tissue. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automatic classification of protein structures using physicochemical parameters.

PubMed

Mohan, Abhilash; Rao, M Divya; Sunderrajan, Shruthi; Pennathur, Gautam

2014-09-01

Protein classification is the first step to functional annotation; SCOP and Pfam databases are currently the most relevant protein classification schemes. However, the disproportion in the number of three dimensional (3D) protein structures generated versus their classification into relevant superfamilies/families emphasizes the need for automated classification schemes. Predicting function of novel proteins based on sequence information alone has proven to be a major challenge. The present study focuses on the use of physicochemical parameters in conjunction with machine learning algorithms (Naive Bayes, Decision Trees, Random Forest and Support Vector Machines) to classify proteins into their respective SCOP superfamily/Pfam family, using sequence derived information. Spectrophores™, a 1D descriptor of the 3D molecular field surrounding a structure was used as a benchmark to compare the performance of the physicochemical parameters. The machine learning algorithms were modified to select features based on information gain for each SCOP superfamily/Pfam family. The effect of combining physicochemical parameters and spectrophores on classification accuracy (CA) was studied. Machine learning algorithms trained with the physicochemical parameters consistently classified SCOP superfamilies and Pfam families with a classification accuracy above 90%, while spectrophores performed with a CA of around 85%. Feature selection improved classification accuracy for both physicochemical parameters and spectrophores based machine learning algorithms. Combining both attributes resulted in a marginal loss of performance. Physicochemical parameters were able to classify proteins from both schemes with classification accuracy ranging from 90-96%. These results suggest the usefulness of this method in classifying proteins from amino acid sequences.

Circumferential resection margin positivity after preoperative chemoradiotherapy based on magnetic resonance imaging for locally advanced rectal cancer: implication of boost radiotherapy to the involved mesorectal fascia.

PubMed

Kim, Kyung Hwan; Park, Min Jung; Lim, Joon Seok; Kim, Nam Kyu; Min, Byung Soh; Ahn, Joong Bae; Kim, Tae Il; Kim, Ho Geun; Koom, Woong Sub

2016-04-01

To identify patients who are at a higher risk of pathologic circumferential resection margin involvement using preoperative magnetic resonance imaging. Between October 2008 and November 2012, 165 patients with locally advanced rectal cancer (cT4 or cT3 with <2 mm distance from tumour to mesorectal fascia) who received preoperative chemoradiotherapy were analysed. The morphologic patterns on post-chemoradiotherapy magnetic resonance imaging were categorized into five patterns from Pattern A (most-likely negative pathologic circumferential resection margin) to Pattern E (most-likely positive pathologic circumferential resection margin). In addition, the location of mesorectal fascia involvement was classified as lateral, posterior and anterior. The diagnostic accuracy of the morphologic criteria was calculated using receiver operating characteristic curve analysis. Pathologic circumferential resection margin involvement was identified in 17 patients (10.3%). The diagnostic accuracy of predicting pathologic circumferential resection margin involvement was 0.73 using the five-scale magnetic resonance imaging pattern. The sensitivity, specificity, positive predictive value and negative predictive value for predicting pathologic circumferential resection margin involvement were 76.5, 65.5, 20.3 and 96.0%, respectively, when cut-off was set between Patterns C and D. On multivariate logistic regression, the magnetic resonance imaging patterns D and E (P= 0.005) and posterior or lateral mesorectal fascia involvement (P= 0.017) were independently associated with increased probability of pathologic circumferential resection margin involvement. The rate of pathologic circumferential resection margin involvement was 30.0% when the patient had Pattern D or E with posterior or lateral mesorectal fascia involvement. Patients who are at a higher risk of pathologic circumferential resection margin involvement can be identified using preoperative magnetic resonance imaging although the predictability is moderate. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effective diagnosis of Alzheimer’s disease by means of large margin-based methodology

PubMed Central

2012-01-01

Background Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer’s Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. Methods It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. Results Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. Conclusions All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET). PMID:22849649

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

PubMed

Chaves, Rosa; Ramírez, Javier; Górriz, Juan M; Illán, Ignacio A; Gómez-Río, Manuel; Carnero, Cristobal

2012-07-31

Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier.

PubMed

Zhang, Baochang; Yang, Yun; Chen, Chen; Yang, Linlin; Han, Jungong; Shao, Ling

2017-10-01

Human action recognition is an important yet challenging task. This paper presents a low-cost descriptor called 3D histograms of texture (3DHoTs) to extract discriminant features from a sequence of depth maps. 3DHoTs are derived from projecting depth frames onto three orthogonal Cartesian planes, i.e., the frontal, side, and top planes, and thus compactly characterize the salient information of a specific action, on which texture features are calculated to represent the action. Besides this fast feature descriptor, a new multi-class boosting classifier (MBC) is also proposed to efficiently exploit different kinds of features in a unified framework for action classification. Compared with the existing boosting frameworks, we add a new multi-class constraint into the objective function, which helps to maintain a better margin distribution by maximizing the mean of margin, whereas still minimizing the variance of margin. Experiments on the MSRAction3D, MSRGesture3D, MSRActivity3D, and UTD-MHAD data sets demonstrate that the proposed system combining 3DHoTs and MBC is superior to the state of the art.

Margined winner-take-all: New learning rule for pattern recognition.

PubMed

Fukushima, Kunihiko

2018-01-01

The neocognitron is a deep (multi-layered) convolutional neural network that can be trained to recognize visual patterns robustly. In the intermediate layers of the neocognitron, local features are extracted from input patterns. In the deepest layer, based on the features extracted in the intermediate layers, input patterns are classified into classes. A method called IntVec (interpolating-vector) is used for this purpose. This paper proposes a new learning rule called margined Winner-Take-All (mWTA) for training the deepest layer. Every time when a training pattern is presented during the learning, if the result of recognition by WTA (Winner-Take-All) is an error, a new cell is generated in the deepest layer. Here we put a certain amount of margin to the WTA. In other words, only during the learning, a certain amount of handicap is given to cells of classes other than that of the training vector, and the winner is chosen under this handicap. By introducing the margin to the WTA, we can generate a compact set of cells, with which a high recognition rate can be obtained with a small computational cost. The ability of this mWTA is demonstrated by computer simulation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sequential Monte Carlo tracking of the marginal artery by multiple cue fusion and random forest regression.

PubMed

Cherry, Kevin M; Peplinski, Brandon; Kim, Lauren; Wang, Shijun; Lu, Le; Zhang, Weidong; Liu, Jianfei; Wei, Zhuoshi; Summers, Ronald M

2015-01-01

Given the potential importance of marginal artery localization in automated registration in computed tomography colonography (CTC), we have devised a semi-automated method of marginal vessel detection employing sequential Monte Carlo tracking (also known as particle filtering tracking) by multiple cue fusion based on intensity, vesselness, organ detection, and minimum spanning tree information for poorly enhanced vessel segments. We then employed a random forest algorithm for intelligent cue fusion and decision making which achieved high sensitivity and robustness. After applying a vessel pruning procedure to the tracking results, we achieved statistically significantly improved precision compared to a baseline Hessian detection method (2.7% versus 75.2%, p<0.001). This method also showed statistically significantly improved recall rate compared to a 2-cue baseline method using fewer vessel cues (30.7% versus 67.7%, p<0.001). These results demonstrate that marginal artery localization on CTC is feasible by combining a discriminative classifier (i.e., random forest) with a sequential Monte Carlo tracking mechanism. In so doing, we present the effective application of an anatomical probability map to vessel pruning as well as a supplementary spatial coordinate system for colonic segmentation and registration when this task has been confounded by colon lumen collapse. Published by Elsevier B.V.

A comparison of the marginal adaptation of cathode-arc vapor-deposited titanium and cast base metal copings

PubMed Central

Wu, JC; Lai, LC; Sheets, CG; Earthman, J; Newcomb, R

2011-01-01

Statement of problem A new fabrication process has been developed where a titanium coping, which has a gold colored titanium nitride outer layer can be reliably fused to porcelain, but the marginal adaptation characteristics are still undetermined. Purpose The primary purpose of this study is to compare the rate of Clinically Acceptable Marginal Adaptation (CAMA-defined as a marginal gap mean ≤60 μm) of cathode-arc vapor-deposited titanium with the CAMA rate for the cast base metal copings. In addition, the study will evaluate the marginal gap scores themselves to assess their mean difference between the two study groups. Finally, the study will present two analyses of group differences in variability to support the contention that the titanium copings perform more consistently than their base metal counterparts. Material and methods Thirty-seven cathode-arc vapor-deposited titanium copings and 40 cast base metal copings were evaluated by computer-based image analysis using an optical microscope. The conventional lost wax technique was used to fabricate the 40 cast base metal copings that were 0.3 mm thick. The titanium copings were 0.3 mm thick and were formed by a collection of atomic titanium vapor onto a refractory die duplicate in a high vacuum chamber. Fifty vertical marginal gap measurements were collected from each of the 77 copings and the mean of these measurements was computed to form a gap score for each coping. Next, the gap score was compared to the 60 μm criterion to classify each coping as to whether it did or did not achieve Clinically Acceptable Marginal Adaption (CAMA). A comparison of the CAMA rates for each type of coping was used to address the primary purpose of this study. In addition, the gap scores themselves were used to test the (one-sided) hypothesis that the mean of the titanium gap scores is smaller than the mean of the base metal gap scores. Finally, the assertion that the titanium copings provide more consistency in their marginal gap performance was tested in two ways. First, the means of the titanium gap scores were compared to the means of the marginal gap scores for the base metal copings. Second, the standard deviations of the marginal gap scores for the titanium copings were compared with those for the base metal copings. Results Statistical comparison of the CAMA rates for each type of coping showed that the CAMA criterion was achieved by 24 of the 37 (64.86%) titanium copings, while 19 of the 40 (47.50%) base metal copings met this same standard. Noninferiority of the titanium copings was established by the 2-sided 90% Confidence Interval for the 17.36% difference in these rates (−0.95%, 35.68%) and noninferiority of titanium coping adaption was also demonstrated by the Wald Test rejection of the tentative hypothesis of inferiority (Z-score=1.9191, one-sided p=0.0275). The mean of the vertical marginal gap scores for the titanium copings (56.9025) was significantly less than the mean of the marginal gap scores for the base metal copings (71.9041) as shown by the Satterthwaite t-score=−2.29 (one-sided p=0.0126). To compare the adaption consistency of the titanium copings to the base metal counterparts the difference between the variance of the marginal gap scores for the titanium copings (594.843) and the variance of the marginal gap scores for the base metal copings (1510.901) was found to be statistically significant (Folded-F test score=2.63, p=0.0042). Our second method for showing that the titanium copings performed more consistently than the base metal comparisons was to use a one-sided test to show that the mean of the standard deviations of the vertical gap measurements for each titanium coping (29.9835) was significantly lower than the mean of the standard deviations of the vertical gap measurements for each base metal coping (36.1332). This test produced a Satterthwaite’s t-score of −2.24 (one-sided p=0.0141), indicating the titanium adaption was significantly more consistent. Conclusions Cathode-arc vapor deposited titanium copings exhibited a higher rate of Clinically Acceptable Marginal Adaption (CAMA) than the comparison base metal copings. Comparison of the coping marginal adaption score variances and direct assessment of the coping marginal adaption scores provided additional evidence that the titanium copings performed better and with more consistency than their base metal counterparts. PMID:21640242

Learning Structured Classifiers with Dual Coordinate Ascent

DTIC Science & Technology

2010-06-01

stochastic gradient descent (SGD) [LeCun et al., 1998], and the margin infused relaxed algorithm (MIRA) [ Crammer et al., 2006]. This paper presents a...evaluate these methods on the Prague Dependency Treebank us- ing online large-margin learning tech- niques ( Crammer et al., 2003; McDonald et al., 2005...between two kinds of factors: hard constraint factors, which are used to rule out forbidden par- tial assignments by mapping them to zero potential values

Distinct clinical outcomes of two CIMP-positive colorectal cancer subtypes based on a revised CIMP classification system.

PubMed

Bae, Jeong Mo; Kim, Jung Ho; Kwak, Yoonjin; Lee, Dae-Won; Cha, Yongjun; Wen, Xianyu; Lee, Tae Hun; Cho, Nam-Yun; Jeong, Seung-Yong; Park, Kyu Joo; Han, Sae Won; Lee, Hye Seung; Kim, Tae-You; Kang, Gyeong Hoon

2017-04-11

Colorectal cancer (CRC) is a heterogeneous disease in terms of molecular carcinogenic pathways. Based on recent findings regarding the multiple serrated neoplasia pathway, we revised an eight-marker panel for a new CIMP classification system. 1370 patients who received surgical resection for CRCs were classified into three CIMP subtypes (CIMP-N: 0-4 methylated markers, CIMP-P1: 5-6 methylated markers and CIMP-P2: 7-8 methylated markers). Our findings were validated in a separate set of high-risk stage II or stage III CRCs receiving adjuvant fluoropyrimidine plus oxaliplatin (n=950). A total of 1287/62/21 CRCs cases were classified as CIMP-N/CIMP-P1/CIMP-P2, respectively. CIMP-N showed male predominance, distal location, lower T, N category and devoid of BRAF mutation, microsatellite instability (MSI) and MLH1 methylation. CIMP-P1 showed female predominance, proximal location, advanced TNM stage, mild decrease of CK20 and CDX2 expression, mild increase of CK7 expression, BRAF mutation, MSI and MLH1 methylation. CIMP-P2 showed older age, female predominance, proximal location, advanced T category, markedly reduced CK20 and CDX2 expression, rare KRAS mutation, high frequency of CK7 expression, BRAF mutation, MSI and MLH1 methylation. CIMP-N showed better 5-year cancer-specific survival (CSS; HR=0.47; 95% CI: 0.28-0.78) in discovery set and better 5-year relapse-free survival (RFS; HR=0.50; 95% CI: 0.29-0.88) in validation set compared with CIMP-P1. CIMP-P2 showed marginally better 5-year CSS (HR=0.28, 95% CI: 0.07-1.22) in discovery set and marginally better 5-year RFS (HR=0.21, 95% CI: 0.05-0.92) in validation set compared with CIMP-P1. CIMP subtypes classified using our revised system showed different clinical outcomes, demonstrating the heterogeneity of multiple serrated precursors of CIMP-positive CRCs.

Gap-metric-based robustness analysis of nonlinear systems with full and partial feedback linearisation

NASA Astrophysics Data System (ADS)

Al-Gburi, A.; Freeman, C. T.; French, M. C.

2018-06-01

This paper uses gap metric analysis to derive robustness and performance margins for feedback linearising controllers. Distinct from previous robustness analysis, it incorporates the case of output unstructured uncertainties, and is shown to yield general stability conditions which can be applied to both stable and unstable plants. It then expands on existing feedback linearising control schemes by introducing a more general robust feedback linearising control design which classifies the system nonlinearity into stable and unstable components and cancels only the unstable plant nonlinearities. This is done in order to preserve the stabilising action of the inherently stabilising nonlinearities. Robustness and performance margins are derived for this control scheme, and are expressed in terms of bounds on the plant nonlinearities and the accuracy of the cancellation of the unstable plant nonlinearity by the controller. Case studies then confirm reduced conservatism compared with standard methods.

Submarine fans: Characteristics, models, classification, and reservoir potential

NASA Astrophysics Data System (ADS)

Shanmugam, G.; Moiola, R. J.

1988-02-01

Submarine-fan sequences are important hydrocarbon reservoirs throughout the world. Submarine-fan sequences may be interpreted from bed-thickness trends, turbidite facies associations, log motifs, and seismic-reflection profiles. Turbidites occurring predominantly in channels and lobes (or sheet sands) constitute the major portion of submarine-fan sequences. Thinning- and thickening-upward trends are suggestive of channel and lobe deposition, respectively. Mounded seismic reflections are commonly indicative of lower-fan depositional lobes. Fan models are discussed in terms of modern and ancient fans, attached and detached lobes, highly efficient and poorly efficient systems, and transverse and longitudinal fans. In general, depositional lobes are considered to be attached to feeder channels. Submarine fans can be classified into four types based on their tectonic settings: (1) immature passive-margin fans (North Sea type); (2) mature passive-margin fans (Atlantic type); (3) active-margin fans (Pacific type); and (4) mixed-setting fans. Immature passive-margin fans (e.g., Balder, North Sea), and active-margin fans (e.g., Navy, Pacific Ocean) are usually small, sand-rich, and possess well developed lobes. Mature passive-margin fans (e.g., Amazon, Atlantic Ocean) are large, mud-rich, and do not develop typical lobes. However, sheet sands are common in the lower-fan regions of mature passive-margin fans. Mixed-setting fans display characteristics of either Atlantic type (e.g., Bengal, Bay of Bengal), or Pacific type (Orinoco, Caribbean), or both. Conventional channel-lobe models may not be applicable to fans associated with mature passive margins. Submarine fans develop primarily during periods of low sea level on both active- and passive-margin settings. Consequently, hydrocarbon-bearing fan sequences are associated generally with global lowstands of sea level. Channel-fill sandstones in most tectonic settings are potential reservoirs. Lobes exhibit the most favorable reservoir quality in terms of sand content, lateral continuity, and porosity development. Lower-fan sheet sands may also make good reservoirs. Quartz-rich sandstones of mature passive-margin fans are most likely to preserve depositional porosity, whereas lithic sandstones of active-margin fans may not.

Hierarchical Marginal Land Assessment for Land Use Planning

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

Kang, Shujiang; Post, Wilfred M; Wang, Dali

2013-01-01

Marginal land provides an alternative potential for food and bioenergy production in the face of limited land resources; however, effective assessment of marginal lands is not well addressed. Concerns over environmental risks, ecosystem services and sustainability for marginal land have been widely raised. The objective of this study was to develop a hierarchical marginal land assessment framework for land use planning and management. We first identified major land functions linking production, environment, ecosystem services and economics, and then classified land resources into four categories of marginal land using suitability and limitations associated with major management goals, including physically marginal land,more » biologically marginal land, environmental-ecological marginal land, and economically marginal land. We tested this assessment framework in south-western Michigan, USA. Our results indicated that this marginal land assessment framework can be potentially feasible on land use planning for food and bioenergy production, and balancing multiple goals of land use management. We also compared our results with marginal land assessment from the Conservation Reserve Program (CRP) and land capability classes (LCC) that are used in the US. The hierarchical assessment framework has advantages of quantitatively reflecting land functions and multiple concerns. This provides a foundation upon which focused studies can be identified in order to improve the assessment framework by quantifying high-resolution land functions associated with environment and ecosystem services as well as their criteria are needed to improve the assessment framework.« less

Carcinogenic compounds in alcoholic beverages: an update.

PubMed

Pflaum, Tabea; Hausler, Thomas; Baumung, Claudia; Ackermann, Svenja; Kuballa, Thomas; Rehm, Jürgen; Lachenmeier, Dirk W

2016-10-01

The consumption of alcoholic beverages has been classified as carcinogenic to humans by the International Agency for Research on Cancer (IARC) since 1988. More recently, in 2010, ethanol as the major constituent of alcoholic beverages and its metabolite acetaldehyde were also classified as carcinogenic to humans. Alcoholic beverages as multi-component mixtures may additionally contain further known or suspected human carcinogens as constituent or contaminant. This review will discuss the occurrence and toxicology of eighteen carcinogenic compounds (acetaldehyde, acrylamide, aflatoxins, arsenic, benzene, cadmium, ethanol, ethyl carbamate, formaldehyde, furan, glyphosate, lead, 3-MCPD, 4-methylimidazole, N-nitrosodimethylamine, pulegone, ochratoxin A, safrole) occurring in alcoholic beverages as identified based on monograph reviews by the IARC. For most of the compounds of alcoholic beverages, quantitative risk assessment provided evidence for only a very low risk (such as margins of exposure above 10,000). The highest risk was found for ethanol, which may reach exposures in ranges known to increase the cancer risk even at moderate drinking (margin of exposure around 1). Other constituents that could pose a risk to the drinker were inorganic lead, arsenic, acetaldehyde, cadmium and ethyl carbamate, for most of which mitigation by good manufacturing practices is possible. Nevertheless, due to the major effect of ethanol, the cancer burden due to alcohol consumption can only be reduced by reducing alcohol consumption in general or by lowering the alcoholic strength of beverages.

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

NASA Astrophysics Data System (ADS)

Jiang, Li; Shi, Tielin; Xuan, Jianping

2012-05-01

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

Principles of treatment for soft tissue sarcoma.

PubMed

Dernell, W S; Withrow, S J; Kuntz, C A; Powers, B E

1998-02-01

Soft tissue sarcomas (STS) are mesenchymal tumors arising from connective tissue elements and are grouped together based on a common biologic behavior. The most common histologic types include malignant peripheral nerve sheath tumors (schwannoma and neurofibrosarcoma) "hemangiopericytoma," fibrosarcoma, and malignant fibrous histiocytoma. These tumors are relatively slow growing yet locally invasive with a high rate of recurrence following conservative management. Appropriate preoperative planning and aggressive surgical resection often result in long-term remission or cure. Identification and evaluation of resection margins are paramount in appropriate case management. The addition of radiotherapy after surgical resection can aid in remission for incompletely resected masses. Systemic chemotherapy for STS should be considered for high-grade tumors with a moderate metastatic potential. Potential prognostic factors include grade, resection margins, size, location, histologic type, and previous treatment, with grade and margins being the most important. Tumor types classified as STS that differ slightly in their presentation or treatment, including synovial cell sarcoma, rhabdomyosarcoma, liposarcoma, and vaccine-associated STS in cats, are discussed. Soft tissue sarcomas can be a frustrating disease to treat, but adherence to solid surgical oncology principles can greatly increase the odds of good disease control.

The tumour border on contrast-enhanced spectral mammography and its relation to histological characteristics of invasive breast cancer.

PubMed

Ambicka, Aleksandra; Luczynska, Elzbieta; Adamczyk, Agnieszka; Harazin-Lechowska, Agnieszka; Sas-Korczynska, Beata; Niemiec, Joanna

Contrast-enhanced spectral mammography (CESM) is one of the new diagnostic modalities implemented in clinical practice. In the case of these techniques, there are two major issues to be addressed: (1) their diagnostic usefulness, and (2) the relation between parameters assessed using these techniques and well-known diagnostic/prognostic/predictive markers (histological, clinical, and molecular). Therefore, we studied the relationship between the tumour margin assessed on CESM and (1) tumour borders defined on the basis of macroscopic and microscopic examination, (2) pT, (3) pN, and (4) tumour grade in a group of 82 breast cancer patients. Based on CESM, the tumour border was defined as sharp, indistinct or spiculated, whereas in the case of lesions showing weak or medium enhancement on CESM the borders were classified as unspecified. We found a statistically significant relationship between tumour margin on CESM and (1) macroscopic border (a spiculated margin on CESM was found only in carcinomas with an invasive border on histological examination; p = 0.004), (2) pT (p = 0.016), and (3) pN (nodal involvement was observed most frequently in carcinomas with a spiculated or indistinct margin on CESM; p = 0.045). Moreover, in cases with an undefined margin on CESM (cases showing weak or medium enhancement on CESM), both invasive and pushing borders were found on histological examination. The results of our preliminary study suggest that it is possible to assess macroscopic borders of examined lesions on the basis of CESM imaging. This might be useful in planning the extent of surgical excision. On the other hand, the assessment of the tumour margin on CESM might not be precise in cases showing weak enhancement.

MRI Evaluation of Resection Margins in Bone Tumour Surgery

PubMed Central

Traore, Sidi Yaya; Lecouvet, Frédéric; Galant, Christine

2014-01-01

In 12 patients operated on for bone sarcoma resection, a postoperative magnetic resonance imaging of the resection specimens was obtained in order to assess the surgical margins. Margins were classified according to MRI in R0, R1, and R2 by three independent observers: a radiologist and two orthopaedic surgeons. Final margin evaluation (R0, R1, and R2) was assessed by a confirmed pathologist. Agreement for margin evaluation between the pathologist and the radiologist was perfect (κ = 1). Agreement between the pathologist and an experienced orthopaedic surgeon was very good while it was fair between the pathologist and a junior orthopaedic surgeon. MRI should be considered as a tool to give quick information about the adequacy of margins and to help the pathologist to focus on doubtful areas and to spare time in specimen analysis. But it may not replace the pathological evaluation that gives additional information about tumor necrosis. This study shows that MRI extemporaneous analysis of a resection specimen may be efficient in bone tumor oncologic surgery, if made by an experienced radiologist with perfect agreement with the pathologist. PMID:24976785

Guidelines of the Brazilian Dermatology Society for diagnosis, treatment and follow up of primary cutaneous melanoma - Part I*

PubMed Central

Castro, Luiz Guilherme Martins; Messina, Maria Cristina; Loureiro, Walter; Macarenco, Ricardo Silvestre; Duprat Neto, João Pedreira; Giacomo, Thais Helena Bello Di; Bittencourt, Flávia Vasques; Bakos, Renato Marchiori; Serpa, Sérgio Schrader; Stolf, Hamilton Ometto; Gontijo, Gabriel

2015-01-01

The last Brazilian guidelines on melanoma were published in 2002. Development in diagnosis and treatment made updating necessary. The coordinators elaborated ten clinical questions, based on PICO system. A Medline search, according to specific MeSH terms for each of the 10 questions was performed and articles selected were classified from A to D according to level of scientific evidence. Based on the results, recommendations were defined and classified according to scientific strength. The present Guidelines were divided in two parts for editorial and publication reasons. In the first part, the following clinical questions were answered: 1) The use of dermoscopy for diagnosis of primary cutaneous melanoma brings benefits for patients when compared with clinical examination? 2) Does dermoscopy favor diagnosis of nail apparatus melanoma? 3) Is there a prognostic difference when incisional or excisional biopsies are used? 4) Does revision by a pathologist trained in melanoma contribute to diagnosis and treatment of primary cutaneous melanoma? What margins should be used to treat lentigo maligna melanoma and melanoma in situ? PMID:26734867

From hyperextended rift to convergent margin types: mapping the outer limit of the extended Continental Shelf of Spain in the Galicia area according UNCLOS Art. 76

NASA Astrophysics Data System (ADS)

Somoza, Luis; Medialdea, Teresa; Vázquez, Juan T.; González, Francisco J.; León, Ricardo; Palomino, Desiree; Fernández-Salas, Luis M.; Rengel, Juan

2017-04-01

Spain presented on 11 May 2009 a partial submission for delimiting the extended Continental Shelf in respect to the area of Galicia to the Commission on the Limits of the Continental Shelf (CLCS). The Galicia margin represents an example of the transition between two different types of continental margins (CM): a western hyperpextended margin and a northern convergent margin in the Bay of Biscay. The western Galicia Margin (wGM 41° to 43° N) corresponds to a hyper-extended rifted margin as result of the poly-phase development of the Iberian-Newfoundland conjugate margin during the Mesozoic. Otherwise, the north Galicia Margin (nGM) is the western end of the Cenozoic subduction of the Bay of Biscay along the north Iberian Margin (NIM) linked to the Pyrenean-Mediterranean collisional belt Following the procedure established by the CLCS Scientific and Technical Guidelines (CLCS/11), the points of the Foot of Slope (FoS) has to be determined as the points of maximum change in gradient in the region defined as the Base of the continental Slope (BoS). Moreover, the CLCS guidelines specify that the BoS should be contained within the continental margin (CM). In this way, a full-coverage multibeam bathymetry and an extensive dataset of up 4,736 km of multichannel seismic profiles were expressly obtained during two oceanographic surveys (Breogham-2005 and Espor-2008), aboard the Spanish research vessel Hespérides, to map the outer limit of the CM.In order to follow the criteria of the CLCS guidelines, two types of models reported in the CLCS Guidelines were applied to the Galicia Margin. In passive margins, the Commission's guidelines establish that the natural prolongation is based on that "the natural process by which a continent breaks up prior to the separation by seafloor spreading involves thinning, extension and rifting of the continental crust…" (para. 7.3, CLCS/11). The seaward extension of the wGM should include crustal continental blocks and the so-called Peridotite Ridge (PR), composed by serpentinized exhumed continental mantle. Thus, the PR should be regarded as a natural component of the continental margin since these seafloor highs were formed by hyperextension of the margin. Regarding convergent margins, the architecture of the nGM can be classified according the CLCS/11 as a "poor- or non-accretionary convergent continental margin" characterized by a poorly developed accretionary wedge, which is composed of: a large sedimentary apron mainly formed by large slumps and thrust wedges of igneous (ophiolitic/continental) body overlying subducting oceanic crust (Fig. 6.1B, CLCS/11). According to para. 6.3.6. (CLCS/11), the seaward extent of this type of continental convergent margins is defined by the seaward edge of the accretionary wedge. Applying this definition, the seaward extent of the margin is defined by the outer limit of the ophiolitic deformed body that marks the edge of the accretionary wedge. These geological criteria were strictly applied for mapping the BoS region, where the FoS were determinate by using the maximum change in gradient within this mapped region. Acknowledgments: Project for the Extension of the Spanish Continental according UNCLOS (CTM2010-09496-E) and Project CTM2016-75947-R

Comparison of histologic margin status in low-grade cutaneous and subcutaneous canine mast cell tumours examined by radial and tangential sections.

PubMed

Dores, C B; Milovancev, M; Russell, D S

2018-03-01

Radial sections are widely used to estimate adequacy of excision in canine cutaneous mast cell tumours (MCTs); however, this sectioning technique estimates only a small fraction of total margin circumference. This study aimed to compare histologic margin status in grade II/low grade MCTs sectioned using both radial and tangential sectioning techniques. A total of 43 circumferential margins were evaluated from 21 different tumours. Margins were first sectioned radially, followed by tangential sections. Tissues were examined by routine histopathology. Tangential margin status differed in 10 of 43 (23.3%) margins compared with their initial status on radial section. Of 39 margins, 9 (23.1%) categorized as histologic tumour-free margin (HTFM) >0 mm were positive on tangential sectioning. Tangential sections detected a significantly higher proportion of positive margins relative to radial sections (exact 2-tailed P-value = .0215). The HTFM was significantly longer in negative tangential margins than positive tangential margins (mean 10.1 vs 3.2 mm; P = .0008). A receiver operating characteristic curve comparing HTFM and tangentially negative margins found an area under the curve of 0.83 (95% confidence interval: 0.71-0.96). Although correct classification peaked at the sixth cut-point of HTFM ≥1 mm, radial sections still incorrectly classified 50% of margins as lacking tumour cells. Radial sections had 100% specificity for predicting negative tangential margins at a cut-point of 10.9 mm. These data indicate that for low grade MCTs, HTFMs >0 mm should not be considered completely excised, particularly when HTFM is <10.9 mm. This will inform future studies that use HTFM and overall excisional status as dependent variables in multivariable prognostic models. © 2017 John Wiley & Sons Ltd.

Modification of the Covered Areas Provision for Reformulated Gasoline - RE: Former Non-attainment Areas

EPA Pesticide Factsheets

This final rule will expand this provision to allow states to opt into the RFG program for areas which had been previously classified as marginal, moderate, serious, or severe for ozone, but were subsequently redesignated to attainment.

Rats classified as low or high cocaine locomotor responders: A unique model involving striatal dopamine transporters that predicts cocaine addiction-like behaviors

PubMed Central

Yamamoto, Dorothy J.; Nelson, Anna M.; Mandt, Bruce H.; Larson, Gaynor A.; Rorabaugh, Jacki M.; Ng, Christopher M.C.; Barcomb, Kelsey M.; Richards, Toni L.; Allen, Richard M.; Zahniser, Nancy R.

2013-01-01

Individual differences are a hallmark of drug addiction. Here, we describe a rat model based on differential initial responsiveness to low dose cocaine. Despite similar brain cocaine levels, individual outbred Sprague-Dawley rats exhibit markedly different magnitudes of acute cocaine-induced locomotor activity and, thereby, can be classified as low or high cocaine responders (LCRs or HCRs). LCRs and HCRs differ in drug-induced, but not novelty-associated, hyperactivity. LCRs have higher basal numbers of striatal dopamine transporters (DATs) than HCRs and exhibit marginal cocaine inhibition of in vivo DAT activity and cocaine-induced increases in extracellular DA. Importantly, lower initial cocaine response predicts greater locomotor sensitization, conditioned place preference and greater motivation to self-administer cocaine following low dose acquisition. Further, outbred Long-Evans rats classified as LCRs, versus HCRs, are more sensitive to cocaine’s discriminative stimulus effects. Overall, results to date with the LCR/HCR model underscore the contribution of striatal DATs to individual differences in initial cocaine responsiveness and the value of assessing the influence of initial drug response on subsequent expression of addiction-like behaviors. PMID:23850581

Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Halicek, Martin; Lu, Guolan; Little, James V.; Wang, Xu; Patel, Mihir; Griffith, Christopher C.; El-Deiry, Mark W.; Chen, Amy Y.; Fei, Baowei

2017-06-01

Surgical cancer resection requires an accurate and timely diagnosis of the cancer margins in order to achieve successful patient remission. Hyperspectral imaging (HSI) has emerged as a useful, noncontact technique for acquiring spectral and optical properties of tissue. A convolutional neural network (CNN) classifier is developed to classify excised, squamous-cell carcinoma, thyroid cancer, and normal head and neck tissue samples using HSI. The CNN classification was validated by the manual annotation of a pathologist specialized in head and neck cancer. The preliminary results of 50 patients indicate the potential of HSI and deep learning for automatic tissue-labeling of surgical specimens of head and neck patients.

Distinct clinical outcomes of two CIMP-positive colorectal cancer subtypes based on a revised CIMP classification system

PubMed Central

Bae, Jeong Mo; Kim, Jung Ho; Kwak, Yoonjin; Lee, Dae-Won; Cha, Yongjun; Wen, Xianyu; Lee, Tae Hun; Cho, Nam-Yun; Jeong, Seung-Yong; Park, Kyu Joo; Han, Sae Won; Lee, Hye Seung; Kim, Tae-You; Kang, Gyeong Hoon

2017-01-01

Background: Colorectal cancer (CRC) is a heterogeneous disease in terms of molecular carcinogenic pathways. Based on recent findings regarding the multiple serrated neoplasia pathway, we revised an eight-marker panel for a new CIMP classification system. Methods: 1370 patients who received surgical resection for CRCs were classified into three CIMP subtypes (CIMP-N: 0–4 methylated markers, CIMP-P1: 5–6 methylated markers and CIMP-P2: 7–8 methylated markers). Our findings were validated in a separate set of high-risk stage II or stage III CRCs receiving adjuvant fluoropyrimidine plus oxaliplatin (n=950). Results: A total of 1287/62/21 CRCs cases were classified as CIMP-N/CIMP-P1/CIMP-P2, respectively. CIMP-N showed male predominance, distal location, lower T, N category and devoid of BRAF mutation, microsatellite instability (MSI) and MLH1 methylation. CIMP-P1 showed female predominance, proximal location, advanced TNM stage, mild decrease of CK20 and CDX2 expression, mild increase of CK7 expression, BRAF mutation, MSI and MLH1 methylation. CIMP-P2 showed older age, female predominance, proximal location, advanced T category, markedly reduced CK20 and CDX2 expression, rare KRAS mutation, high frequency of CK7 expression, BRAF mutation, MSI and MLH1 methylation. CIMP-N showed better 5-year cancer-specific survival (CSS; HR=0.47; 95% CI: 0.28–0.78) in discovery set and better 5-year relapse-free survival (RFS; HR=0.50; 95% CI: 0.29–0.88) in validation set compared with CIMP-P1. CIMP-P2 showed marginally better 5-year CSS (HR=0.28, 95% CI: 0.07–1.22) in discovery set and marginally better 5-year RFS (HR=0.21, 95% CI: 0.05–0.92) in validation set compared with CIMP-P1. Conclusions: CIMP subtypes classified using our revised system showed different clinical outcomes, demonstrating the heterogeneity of multiple serrated precursors of CIMP-positive CRCs. PMID:28278514

Maximum margin semi-supervised learning with irrelevant data.

PubMed

Yang, Haiqin; Huang, Kaizhu; King, Irwin; Lyu, Michael R

2015-10-01

Semi-supervised learning (SSL) is a typical learning paradigms training a model from both labeled and unlabeled data. The traditional SSL models usually assume unlabeled data are relevant to the labeled data, i.e., following the same distributions of the targeted labeled data. In this paper, we address a different, yet formidable scenario in semi-supervised classification, where the unlabeled data may contain irrelevant data to the labeled data. To tackle this problem, we develop a maximum margin model, named tri-class support vector machine (3C-SVM), to utilize the available training data, while seeking a hyperplane for separating the targeted data well. Our 3C-SVM exhibits several characteristics and advantages. First, it does not need any prior knowledge and explicit assumption on the data relatedness. On the contrary, it can relieve the effect of irrelevant unlabeled data based on the logistic principle and maximum entropy principle. That is, 3C-SVM approaches an ideal classifier. This classifier relies heavily on labeled data and is confident on the relevant data lying far away from the decision hyperplane, while maximally ignoring the irrelevant data, which are hardly distinguished. Second, theoretical analysis is provided to prove that in what condition, the irrelevant data can help to seek the hyperplane. Third, 3C-SVM is a generalized model that unifies several popular maximum margin models, including standard SVMs, Semi-supervised SVMs (S(3)VMs), and SVMs learned from the universum (U-SVMs) as its special cases. More importantly, we deploy a concave-convex produce to solve the proposed 3C-SVM, transforming the original mixed integer programming, to a semi-definite programming relaxation, and finally to a sequence of quadratic programming subproblems, which yields the same worst case time complexity as that of S(3)VMs. Finally, we demonstrate the effectiveness and efficiency of our proposed 3C-SVM through systematical experimental comparisons. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cluster-based exposure variation analysis

PubMed Central

2013-01-01

Background Static posture, repetitive movements and lack of physical variation are known risk factors for work-related musculoskeletal disorders, and thus needs to be properly assessed in occupational studies. The aims of this study were (i) to investigate the effectiveness of a conventional exposure variation analysis (EVA) in discriminating exposure time lines and (ii) to compare it with a new cluster-based method for analysis of exposure variation. Methods For this purpose, we simulated a repeated cyclic exposure varying within each cycle between “low” and “high” exposure levels in a “near” or “far” range, and with “low” or “high” velocities (exposure change rates). The duration of each cycle was also manipulated by selecting a “small” or “large” standard deviation of the cycle time. Theses parameters reflected three dimensions of exposure variation, i.e. range, frequency and temporal similarity. Each simulation trace included two realizations of 100 concatenated cycles with either low (ρ = 0.1), medium (ρ = 0.5) or high (ρ = 0.9) correlation between the realizations. These traces were analyzed by conventional EVA, and a novel cluster-based EVA (C-EVA). Principal component analysis (PCA) was applied on the marginal distributions of 1) the EVA of each of the realizations (univariate approach), 2) a combination of the EVA of both realizations (multivariate approach) and 3) C-EVA. The least number of principal components describing more than 90% of variability in each case was selected and the projection of marginal distributions along the selected principal component was calculated. A linear classifier was then applied to these projections to discriminate between the simulated exposure patterns, and the accuracy of classified realizations was determined. Results C-EVA classified exposures more correctly than univariate and multivariate EVA approaches; classification accuracy was 49%, 47% and 52% for EVA (univariate and multivariate), and C-EVA, respectively (p < 0.001). All three methods performed poorly in discriminating exposure patterns differing with respect to the variability in cycle time duration. Conclusion While C-EVA had a higher accuracy than conventional EVA, both failed to detect differences in temporal similarity. The data-driven optimality of data reduction and the capability of handling multiple exposure time lines in a single analysis are the advantages of the C-EVA. PMID:23557439

Immunohistochemical analysis of the novel marginal zone B-cell marker IRTA1 in malignant lymphoma.

PubMed

Ikeda, Jun-Ichiro; Kohara, Masaharu; Tsuruta, Yoko; Nojima, Satoshi; Tahara, Shinichiro; Ohshima, Kenji; Kurashige, Masako; Wada, Naoki; Morii, Eiichi

2017-01-01

Marginal zone lymphoma (MZL) is a low-grade B-cell lymphoma derived from marginal zone B cells. Because of a lack of specific immunohistochemical markers, MZL is mainly diagnosed based on the cytological appearance and growth pattern of the tumor. Marginal zone B cells were recently shown to selectively express immunoglobulin superfamily receptor translocation-associated 1 (IRTA1), but the antibody used in that study is not commercially available. We therefore investigated the IRTA1 expression in nonneoplastic lymphoid tissues and 261 malignant lymphomas, examining the ability of a commercially available antibody to accurately diagnose MZL. Among 37 MZLs, 23 of 25 extranodal MZLs of mucosa-associated lymphoid tissue (MALT lymphomas), 3 of 6 splenic MZLs and 3 of 6 nodal MZLs were positive for IRTA1. Among the 98 diffuse large B-cell lymphomas, 33 were positive for IRTA1, including 1 of 38 follicular lymphomas, and all precursor B-lymphoblastic (2/2) and T-lymphoblastic (7/7) leukemia/lymphomas. Other mature B-cell and T-cell lymphomas, and Hodgkin lymphoma were negative for IRTA1. In MALT lymphoma, positive cells were detected mainly in intraepithelial and subepithelial marginal zone B cells. In 1 case of grade 3 follicular lymphoma, IRTA1 was also expressed in the area of large cell transformation. When tumors were classified as germinal center B cell-like (GCB) or non-GCB using the algorithm of Hans, positive expression of IRTA1 was correlated significantly with non-GCB diffuse large B-cell lymphomas (P < .05). These results demonstrated the ability of the commercially available IRTA1 antibody to distinguish MALT lymphoma from other low-grade B-cell lymphomas. Copyright © 2016 Elsevier Inc. All rights reserved.

The Prognostic Value of Varying Definitions of Positive Resection Margin in Patients with Colorectal Cancer Liver Metastases.

PubMed

Wang, Jane; Margonis, Georgios Antonios; Amini, Neda; Andreatos, Nikolaos; Yuan, Chunhui; Damaskos, Christos; Antoniou, Efstathios; Garmpis, Nikolaos; Buettner, Stefan; Barbon, Carlotta; Deshwar, Amar; He, Jin; Burkhart, Richard; Pawlik, Timothy M; Wolfgang, Christopher L; Weiss, Matthew J

2018-04-09

Varying definitions of resection margin clearance are currently employed among patients with colorectal cancer liver metastases (CRLM). Specifically, a microscopically positive margin (R1) has alternatively been equated with an involved margin (margin width = 0 mm) or a margin width < 1 mm. Consequently, patients with a margin width of 0-1 mm (sub-mm) are inconsistently classified in either the R0 or R1 categories, thus obscuring the prognostic implications of sub-mm margins. Six hundred thirty-three patients who underwent resection of CRLM were identified. Both R1 definitions were alternatively employed and multivariable analysis was used to determine the predictive power of each definition, as well as the prognostic implications of a sub-mm margin. Five hundred thirty-nine (85.2%) patients had a margin width ≥ 1 mm, 42 had a sub-mm margin width, and 52 had an involved margin (0 mm). A margin width ≥ 1 mm was associated with improved survival vs. a sub-mm margin (65 vs. 36 months; P = 0.03) or an involved margin (65 vs. 33 months; P < 0.001). No significant difference in survival was detected between patients with involved vs. sub-mm margins (P = 0.31). A sub-mm margin and an involved margin were both independent predictors of worse OS (HR 1.66, 1.04-2.67; P = 0.04, and HR 2.14, 1.46-3.16; P < 0.001, respectively) in multivariable analysis. Importantly, after combining the two definitions, patients with either an involved margin or a sub-mm margin were associated with worse OS in multivariable analysis (HR 1.94, 1.41-2.65; P < 0.001). Patients with involved or sub-mm margins demonstrated a similar inferior OS vs. patients with a margin width > 1 mm. Consequently, a uniform definition of R1 as a margin width < 1 mm should perhaps be employed by future studies.

Early graft dysfunction and mortality rate in marginal donor liver transplantation.

PubMed

Sarkut, Pmar; Gülcü, Bariş; Işçimen, Remzi; Kiyici, Murat; Türker, Gürkan; Topal, Naile Bolca; Ozen, Yilmaz; Kaya, Ekrem

2014-01-01

To determine the effect of marginal donor livers on mortality and graft survival in liver transplantation (LT) recipients. Donors with any 1 of following were considered marginal donors: age ≥65 years, sodium level ≥ 165 mmol/L and cold ischemia time ≥ 12 h. Donors were classified according to the donor risk index (DRI) < 1.7 and ≥ 1.7. The transplant recipients' model for end-stage liver disease (MELD) scores were considered low if < 20 and high if ≥ 20. Early graft dysfunction (EGD) and mortality rate were evaluated. During the study period 47 patients underwent cadaveric LT. The mean age of the donors and recipients was 45 years (range: 5-72 years) and 46 years (range: 4-66 years), respectively. In all, there were 15 marginal donors and 18 donors with a DRI > 1.7. In total, 4 LT patients that received livers from marginal donors and 5 that received livers from donors with a DRI ≥ 1.7 had EGD. Among the recipients of marginal livers, 5 died, versus 4 of the recipients of standard livers. There was no significant difference in EGD or mortality rate between the patients that received livers from marginal donors or those with a DRI ≥ 1.7 and patients that received standard donor livers. Marginal and DRI ≥ 1.7 donors negatively affected LT outcomes, but not significantly.

Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning.

PubMed

Alcaide-Leon, P; Dufort, P; Geraldo, A F; Alshafai, L; Maralani, P J; Spears, J; Bharatha, A

2017-06-01

Accurate preoperative differentiation of primary central nervous system lymphoma and enhancing glioma is essential to avoid unnecessary neurosurgical resection in patients with primary central nervous system lymphoma. The purpose of the study was to evaluate the diagnostic performance of a machine-learning algorithm by using texture analysis of contrast-enhanced T1-weighted images for differentiation of primary central nervous system lymphoma and enhancing glioma. Seventy-one adult patients with enhancing gliomas and 35 adult patients with primary central nervous system lymphomas were included. The tumors were manually contoured on contrast-enhanced T1WI, and the resulting volumes of interest were mined for textural features and subjected to a support vector machine-based machine-learning protocol. Three readers classified the tumors independently on contrast-enhanced T1WI. Areas under the receiver operating characteristic curves were estimated for each reader and for the support vector machine classifier. A noninferiority test for diagnostic accuracy based on paired areas under the receiver operating characteristic curve was performed with a noninferiority margin of 0.15. The mean areas under the receiver operating characteristic curve were 0.877 (95% CI, 0.798-0.955) for the support vector machine classifier; 0.878 (95% CI, 0.807-0.949) for reader 1; 0.899 (95% CI, 0.833-0.966) for reader 2; and 0.845 (95% CI, 0.757-0.933) for reader 3. The mean area under the receiver operating characteristic curve of the support vector machine classifier was significantly noninferior to the mean area under the curve of reader 1 ( P = .021), reader 2 ( P = .035), and reader 3 ( P = .007). Support vector machine classification based on textural features of contrast-enhanced T1WI is noninferior to expert human evaluation in the differentiation of primary central nervous system lymphoma and enhancing glioma. © 2017 by American Journal of Neuroradiology.

Acculturation and health-related quality of life: results from the German National Cohort migrant feasibility study.

PubMed

Brand, Tilman; Samkange-Zeeb, Florence; Ellert, Ute; Keil, Thomas; Krist, Lilian; Dragano, Nico; Jöckel, Karl-Heinz; Razum, Oliver; Reiss, Katharina; Greiser, Karin Halina; Zimmermann, Heiko; Becher, Heiko; Zeeb, Hajo

2017-06-01

We assessed the association between acculturation and health-related quality of life (HRQoL) among persons with a Turkish migrant background in Germany. 1226 adults of Turkish origin were recruited in four German cities. Acculturation was assessed using the Frankfurt Acculturation Scale resulting in four groups (integration, assimilation, separation and marginalization). Short Form-8 physical and mental components were used to assess the HRQoL. Associations were analysed with linear regression models. Of the respondents, 20% were classified as integrated, 29% assimilated, 29% separated and 19% as marginalized. Separation was associated with poorer physical and mental health (linear regression coefficient (RC) = -2.3, 95% CI -3.9 to -0.8 and RC = -2.4, 95% CI -4.4 to -0.5, respectively; reference: integration). Marginalization was associated with poorer mental health in descendants of migrants (RC = -6.4, 95% CI -12.0 to -0.8; reference: integration). Separation and marginalization are associated with a poorer HRQoL. Policies should support the integration of migrants, and health promotion interventions should target separated and marginalized migrants to improve their HRQoL.

Geomorphology of the Iberian Continental Margin

NASA Astrophysics Data System (ADS)

Maestro, Adolfo; López-Martínez, Jerónimo; Llave, Estefanía; Bohoyo, Fernando; Acosta, Juan; Hernández-Molina, F. Javier; Muñoz, Araceli; Jané, Gloria

2013-08-01

The submarine features and processes around the Iberian Peninsula are the result of a complex and diverse geological and oceanographical setting. This paper presents an overview of the seafloor geomorphology of the Iberian Continental Margin and the adjacent abyssal plains. The study covers an area of approximately 2.3 million km2, including a 50 to 400 km wide band adjacent to the coastline. The main morphological characteristics of the seafloor features on the Iberian continental shelf, continental slope, continental rise and the surrounding abyssal plains are described. Individual seafloor features existing on the Iberian Margin have been classified into three main groups according to their origin: tectonic and/or volcanic, depositional and erosional. Major depositional and erosional features around the Iberian Margin developed in late Pleistocene-Holocene times and have been controlled by tectonic movements and eustatic fluctuations. The distribution of the geomorphological features is discussed in relation to their genetic processes and the evolution of the margin. The prevalence of one or several specific processes in certain areas reflects the dominant morphotectonic and oceanographic controlling factors. Sedimentary processes and the resulting depositional products are dominant on the Valencia-Catalán Margin and in the northern part of the Balearic Promontory. Strong tectonic control is observed in the geomorphology of the Betic and the Gulf of Cádiz margins. The role of bottom currents is especially evident throughout the Iberian Margin. The Galicia, Portuguese and Cantabrian margins show a predominance of erosional features and tectonically-controlled linear features related to faults.

Enhancing Critical Infrastructure and Key Resources (CIKR) Level-0 Physical Process Security Using Field Device Distinct Native Attribute Features

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

Lopez, Juan; Liefer, Nathan C.; Busho, Colin R.

Here, the need for improved Critical Infrastructure and Key Resource (CIKR) security is unquestioned and there has been minimal emphasis on Level-0 (PHY Process) improvements. Wired Signal Distinct Native Attribute (WS-DNA) Fingerprinting is investigated here as a non-intrusive PHY-based security augmentation to support an envisioned layered security strategy. Results are based on experimental response collections from Highway Addressable Remote Transducer (HART) Differential Pressure Transmitter (DPT) devices from three manufacturers (Yokogawa, Honeywell, Endress+Hauer) installed in an automated process control system. Device discrimination is assessed using Time Domain (TD) and Slope-Based FSK (SB-FSK) fingerprints input to Multiple Discriminant Analysis, Maximum Likelihood (MDA/ML)more » and Random Forest (RndF) classifiers. For 12 different classes (two devices per manufacturer at two distinct set points), both classifiers performed reliably and achieved an arbitrary performance benchmark of average cross-class percent correct of %C > 90%. The least challenging cross-manufacturer results included near-perfect %C ≈ 100%, while the more challenging like-model (serial number) discrimination results included 90%< %C < 100%, with TD Fingerprinting marginally outperforming SB-FSK Fingerprinting; SB-FSK benefits from having less stringent response alignment and registration requirements. The RndF classifier was most beneficial and enabled reliable selection of dimensionally reduced fingerprint subsets that minimize data storage and computational requirements. The RndF selected feature sets contained 15% of the full-dimensional feature sets and only suffered a worst case %CΔ = 3% to 4% performance degradation.« less

Using Neural Networks to Predict MBA Student Success

ERIC Educational Resources Information Center

Naik, Bijayananda; Ragothaman, Srinivasan

2004-01-01

Predicting MBA student performance for admission decisions is crucial for educational institutions. This paper evaluates the ability of three different models--neural networks, logit, and probit to predict MBA student performance in graduate programs. The neural network technique was used to classify applicants into successful and marginal student…

Gigapixel surface imaging of radical prostatectomy specimens for comprehensive detection of cancer-positive surgical margins using structured illumination microscopy

PubMed Central

Wang, Mei; Tulman, David B.; Sholl, Andrew B.; Kimbrell, Hillary Z.; Mandava, Sree H.; Elfer, Katherine N.; Luethy, Samuel; Maddox, Michael M.; Lai, Weil; Lee, Benjamin R.; Brown, J. Quincy

2016-01-01

Achieving cancer-free surgical margins in oncologic surgery is critical to reduce the need for additional adjuvant treatments and minimize tumor recurrence; however, there is a delicate balance between completeness of tumor removal and preservation of adjacent tissues critical for normal post-operative function. We sought to establish the feasibility of video-rate structured illumination microscopy (VR-SIM) of the intact removed tumor surface as a practical and non-destructive alternative to intra-operative frozen section pathology, using prostate cancer as an initial target. We present the first images of the intact human prostate surface obtained with pathologically-relevant contrast and subcellular detail, obtained in 24 radical prostatectomy specimens immediately after excision. We demonstrate that it is feasible to routinely image the full prostate circumference, generating gigapixel panorama images of the surface that are readily interpreted by pathologists. VR-SIM confirmed detection of positive surgical margins in 3 out of 4 prostates with pathology-confirmed adenocarcinoma at the circumferential surgical margin, and furthermore detected extensive residual cancer at the circumferential margin in a case post-operatively classified by histopathology as having negative surgical margins. Our results suggest that the increased surface coverage of VR-SIM could also provide added value for detection and characterization of positive surgical margins over traditional histopathology. PMID:27257084

Satire, Surveillance, and the State: A Classified Primer

ERIC Educational Resources Information Center

Bogad, L. M.

2007-01-01

This article explores the use of ironic performance in education, particularly around issues of human rights. I examine my own efforts to engage audiences with the history of domestic espionage and sabotage by the intelligence agencies of the United States. This is a history well known to some marginalized counterpublics (see Fraser, 1997), but…

The crustal structure of the continental margin east of the Falkland Islands

NASA Astrophysics Data System (ADS)

Schimschal, Claudia Monika; Jokat, Wilfried

2018-01-01

The 1500 km long Falkland Plateau is the most prominent morphological structure in the southern South Atlantic Ocean, which crustal composition and development is mainly unknown. At the westernmost boundary of the plateau, the Falkland Islands' Precambrian geology provides the only insight into basement structure and age. The question of whether continental basement of a similar age and origin underlies the Falkland Plateau further east is strongly disputed. We present new high quality constraints on the crustal fabric of the plateau east of the Falkland Islands, based on wide-angle seismic and potential field data acquired in 2013. The P-wave velocity model, supported by amplitude and density modelling, shows that the Falkland Plateau Basin is filled with 8 km of sediments. Continental crust of 34 km thickness underlies the Falkland Islands. The eastern continental margin of the Falkland Islands can be classified as a volcanic rifted margin. The Falkland Plateau Basin is floored by up to 20 km thick oceanic crust. The exceptionally thick igneous crust and its high lower crustal velocities (up to 7.4 km/s) indicate the influence of a regional thermal mantle anomaly during its formation, which provided extra melt material. The wide-angle model revises published crustal models, which predicted thin oceanic or thick extended continental crust below the Falkland Plateau Basin. Our results provide a sound basis for future tectonic interpretations of the area.

Marginal Space Deep Learning: Efficient Architecture for Volumetric Image Parsing.

PubMed

Ghesu, Florin C; Krubasik, Edward; Georgescu, Bogdan; Singh, Vivek; Yefeng Zheng; Hornegger, Joachim; Comaniciu, Dorin

2016-05-01

Robust and fast solutions for anatomical object detection and segmentation support the entire clinical workflow from diagnosis, patient stratification, therapy planning, intervention and follow-up. Current state-of-the-art techniques for parsing volumetric medical image data are typically based on machine learning methods that exploit large annotated image databases. Two main challenges need to be addressed, these are the efficiency in scanning high-dimensional parametric spaces and the need for representative image features which require significant efforts of manual engineering. We propose a pipeline for object detection and segmentation in the context of volumetric image parsing, solving a two-step learning problem: anatomical pose estimation and boundary delineation. For this task we introduce Marginal Space Deep Learning (MSDL), a novel framework exploiting both the strengths of efficient object parametrization in hierarchical marginal spaces and the automated feature design of Deep Learning (DL) network architectures. In the 3D context, the application of deep learning systems is limited by the very high complexity of the parametrization. More specifically 9 parameters are necessary to describe a restricted affine transformation in 3D, resulting in a prohibitive amount of billions of scanning hypotheses. The mechanism of marginal space learning provides excellent run-time performance by learning classifiers in clustered, high-probability regions in spaces of gradually increasing dimensionality. To further increase computational efficiency and robustness, in our system we learn sparse adaptive data sampling patterns that automatically capture the structure of the input. Given the object localization, we propose a DL-based active shape model to estimate the non-rigid object boundary. Experimental results are presented on the aortic valve in ultrasound using an extensive dataset of 2891 volumes from 869 patients, showing significant improvements of up to 45.2% over the state-of-the-art. To our knowledge, this is the first successful demonstration of the DL potential to detection and segmentation in full 3D data with parametrized representations.

Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a practical and convenient non-linear classifier.

PubMed

Steyrl, David; Scherer, Reinhold; Faller, Josef; Müller-Putz, Gernot R

2016-02-01

There is general agreement in the brain-computer interface (BCI) community that although non-linear classifiers can provide better results in some cases, linear classifiers are preferable. Particularly, as non-linear classifiers often involve a number of parameters that must be carefully chosen. However, new non-linear classifiers were developed over the last decade. One of them is the random forest (RF) classifier. Although popular in other fields of science, RFs are not common in BCI research. In this work, we address three open questions regarding RFs in sensorimotor rhythm (SMR) BCIs: parametrization, online applicability, and performance compared to regularized linear discriminant analysis (LDA). We found that the performance of RF is constant over a large range of parameter values. We demonstrate - for the first time - that RFs are applicable online in SMR-BCIs. Further, we show in an offline BCI simulation that RFs statistically significantly outperform regularized LDA by about 3%. These results confirm that RFs are practical and convenient non-linear classifiers for SMR-BCIs. Taking into account further properties of RFs, such as independence from feature distributions, maximum margin behavior, multiclass and advanced data mining capabilities, we argue that RFs should be taken into consideration for future BCIs.

Soil Carbon Change and Net Energy Associated with Biofuel Production on Marginal Lands: A Regional Modeling Perspective

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

Bandaru, Varaprasad; Izaurralde, Roberto C.; Manowitz, David H.

2013-12-01

The use of marginal lands (MLs) for biofuel production has been contemplated as a promising solution for meeting biofuel demands. However, there have been concerns with spatial location of MLs, their inherent biofuel potential, and possible environmental consequences with the cultivation of energy crops. Here, we developed a new quantitative approach that integrates high-resolution land cover and land productivity maps and uses conditional probability density functions for analyzing land use patterns as a function of land productivity to classify the agricultural lands. We subsequently applied this method to determine available productive croplands (P-CLs) and non-crop marginal lands (NC-MLs) in amore » nine-county Southern Michigan. Furthermore, Spatially Explicit Integrated Modeling Framework (SEIMF) using EPIC (Environmental Policy Integrated Climate) was used to understand the net energy (NE) and soil organic carbon (SOC) implications of cultivating different annual and perennial production systems.« less

Data mining framework for identification of myocardial infarction stages in ultrasound: A hybrid feature extraction paradigm (PART 2).

PubMed

Sudarshan, Vidya K; Acharya, U Rajendra; Ng, E Y K; Tan, Ru San; Chou, Siaw Meng; Ghista, Dhanjoo N

2016-04-01

Early expansion of infarcted zone after Acute Myocardial Infarction (AMI) has serious short and long-term consequences and contributes to increased mortality. Thus, identification of moderate and severe phases of AMI before leading to other catastrophic post-MI medical condition is most important for aggressive treatment and management. Advanced image processing techniques together with robust classifier using two-dimensional (2D) echocardiograms may aid for automated classification of the extent of infarcted myocardium. Therefore, this paper proposes novel algorithms namely Curvelet Transform (CT) and Local Configuration Pattern (LCP) for an automated detection of normal, moderately infarcted and severely infarcted myocardium using 2D echocardiograms. The methodology extracts the LCP features from CT coefficients of echocardiograms. The obtained features are subjected to Marginal Fisher Analysis (MFA) dimensionality reduction technique followed by fuzzy entropy based ranking method. Different classifiers are used to differentiate ranked features into three classes normal, moderate and severely infarcted based on the extent of damage to myocardium. The developed algorithm has achieved an accuracy of 98.99%, sensitivity of 98.48% and specificity of 100% for Support Vector Machine (SVM) classifier using only six features. Furthermore, we have developed an integrated index called Myocardial Infarction Risk Index (MIRI) to detect the normal, moderately and severely infarcted myocardium using a single number. The proposed system may aid the clinicians in faster identification and quantification of the extent of infarcted myocardium using 2D echocardiogram. This system may also aid in identifying the person at risk of developing heart failure based on the extent of infarcted myocardium. Copyright © 2016 Elsevier Ltd. All rights reserved.

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation.

PubMed

Mansoor, Awais; Cerrolaza, Juan J; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-11

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM 1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

Marginal shape deep learning: applications to pediatric lung field segmentation

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Cerrolaza, Juan J.; Perez, Geovany; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-01

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, local- ization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0:927 using only the four highest modes of variation (compared to 0:888 with classical ASM1 (p-value=0:01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation

PubMed Central

Mansoor, Awais; Cerrolaza, Juan J.; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-01-01

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects. PMID:28592911

Descriptive epidemiology of joint injuries in Thoroughbred racehorses in training.

PubMed

Reed, S R; Jackson, B F; Mc Ilwraith, C W; Wright, I M; Pilsworth, R; Knapp, S; Wood, J L N; Price, J S; Verheyen, K L P

2012-01-01

No large scale epidemiological studies have previously quantified the occurrence of carpal, metacarpo- and metatarsophalangeal (MCP/MTP) joint injuries in Thoroughbred racehorses. To develop an objective classification system for carpal and MCP/MTP joint injuries and estimate the incidence of these injuries in young Thoroughbreds in flat race training. In a prospective cohort study, data on daily exercise and veterinary-diagnosed carpal and MCP/MTP joint injuries were collected from Thoroughbreds monitored since starting training as yearlings, for up to 2 years. Cases were classified in one of 4 categories: 1) localised to a carpal or MCP/MTP joint based on clinical examination and/or diagnostic analgesia; no diagnostic imaging performed; 2) localised to a carpal or MCP/MTP joint based on clinical examination and/or diagnostic analgesia; radiographs taken but no abnormalities detected; 3) evidence of abnormality of subchondral bone and/or articular margin(s) on diagnostic imaging and 4) evidence of discontinuity of the articular surface on diagnostic imaging. Incidence rates and rate ratios were estimated using Poisson regression, adjusting for trainer-level clustering. A total of 647 horses from 13 trainers throughout England contributed 7785 months at risk of joint injury. One-hundred-and-eighty-four cases of carpal (n = 82) or MCP/MTP (n = 102) joint injury were reported in 165 horses and classified in Category 1 (n = 21), Category 2 (n = 21), Category 3 (n = 72) or Category 4 (n = 70). The overall joint injury rate was 1.8 per 100 horse months (95% CI = 1.2, 2.8); rates did not differ significantly between 2- and 3-year-olds but females sustained Category 1 injuries at triple the rate of males (P = 0.03). Joint injury rates differed significantly between trainers (P<0.001) and there was trainer variation in anatomical site and severity of injury. Carpal and MCP/MTP joint injuries are an important cause of morbidity in Thoroughbred racehorses. Identification of modifiable risk factors for these injuries may reduce their incidence. © 2011 EVJ Ltd.

DFM flow by using combination between design based metrology system and model based verification at sub-50nm memory device

NASA Astrophysics Data System (ADS)

Kim, Cheol-kyun; Kim, Jungchan; Choi, Jaeseung; Yang, Hyunjo; Yim, Donggyu; Kim, Jinwoong

2007-03-01

As the minimum transistor length is getting smaller, the variation and uniformity of transistor length seriously effect device performance. So, the importance of optical proximity effects correction (OPC) and resolution enhancement technology (RET) cannot be overemphasized. However, OPC process is regarded by some as a necessary evil in device performance. In fact, every group which includes process and design, are interested in whole chip CD variation trend and CD uniformity, which represent real wafer. Recently, design based metrology systems are capable of detecting difference between data base to wafer SEM image. Design based metrology systems are able to extract information of whole chip CD variation. According to the results, OPC abnormality was identified and design feedback items are also disclosed. The other approaches are accomplished on EDA companies, like model based OPC verifications. Model based verification will be done for full chip area by using well-calibrated model. The object of model based verification is the prediction of potential weak point on wafer and fast feed back to OPC and design before reticle fabrication. In order to achieve robust design and sufficient device margin, appropriate combination between design based metrology system and model based verification tools is very important. Therefore, we evaluated design based metrology system and matched model based verification system for optimum combination between two systems. In our study, huge amount of data from wafer results are classified and analyzed by statistical method and classified by OPC feedback and design feedback items. Additionally, novel DFM flow would be proposed by using combination of design based metrology and model based verification tools.

Aptitude Level and Performance on Intramodal and Intermodal Form Discrimination Tasks. Technical Report.

ERIC Educational Resources Information Center

Kress, Gary

The increased number of marginal aptitude trainees inducted into the Army has created the need for adequately and efficiently training these men. This report presents the finding of research that compared high and low aptitude men--classified on the basis of scores from the Armed Forces Qualification Test (AFQT)--on two form discrimination tasks…

Disadvantaged Young People Accessing the New Urban Economies of the Post-Industrial City

ERIC Educational Resources Information Center

Raffo, Carlo

2006-01-01

The aim of the paper is to examine current and evolving supply side transition policy initiatives in the light of (a) particular demand side needs of urban young people classified as those most disadvantaged and potentially marginalized; and (b) the emerging realities of accessing and operating within particular examples of high value-added…

Soft tissue recurrence of giant cell tumor of the bone: Prevalence and radiographic features.

PubMed

Xu, Leilei; Jin, Jing; Hu, Annan; Xiong, Jin; Wang, Dongmei; Sun, Qi; Wang, Shoufeng

2017-11-01

Recurrence of giant cell tumor of bone (GCTB) in the soft tissue is rarely seen in the clinical practice. This study aims to determine the prevalence of soft tissue recurrence of GCTB, and to characterize its radiographic features. A total of 291 patients treated by intralesional curettage for histologically diagnosed GCTB were reviewed. 6 patients were identified to have the recurrence of GCTB in the soft tissue, all of whom had undergone marginal resection of the lesion. Based on the x-ray, CT and MRI imaging, the radiographic features of soft tissue recurrence were classified into 3 types. Type I was defined as soft tissue recurrence with peripheral ossification, type II was defined as soft tissue recurrence with central ossification, and type III was defined as pure soft tissue recurrence without ossification. Demographic data including period of recurrence and follow-up duration after the second surgery were recorded for these 6 patients. Musculoskeletal Tumor Society (MSTS) scoring system was used to evaluate functional outcomes. The overall recurrence rate was 2.1% (6/291). The mean interval between initial surgery and recurrence was 11.3 ± 4.1 months (range, 5-17). The recurrence lesions were located in the thigh of 2 patients, in the forearm of 2 patients and in the leg of the other 2 patients. According to the classification system mentioned above, 2 patients were classified with type I, 1 as type II and 3 as type III. After the marginal excision surgery, all patients were consistently followed up for a mean period of 13.4 ± 5.3 months (range, 6-19), with no recurrence observed at the final visit. All the patients were satisfied with the surgical outcome. According to the MSTS scale, the mean postoperative functional score was 28.0 ± 1.2 (range, 26-29). The classification of soft tissue recurrence of GCTB may be helpful for the surgeon to select the appropriate imaging procedure to detect the recurrence. In addition, the marginal resection can produce a favorable outcome for the patients.

Areas Participating in the Reformulated Gasoline Program (Short-Term Energy Outlook Supplement June 1999)

EIA Publications

1999-01-01

Section 107(d) of the Clean Air Act, as amended in 1990 (the Act), required states to identify all areas that do not meet the national ambient air quality standards (NAAQS) for ozone, and directed the Environmental Protection Agency (EPA) to designate these areas as ozone nonattainment areas. Section 181 of the Act required EPA to classify each area as a marginal, moderate, serious, severe or extreme ozone nonattainment area. EPA classified all areas that were designated as in nonattainment for ozone at the time of the enactment of the 1990 Amendments, except for certain "nonclassifiable" areas (56 FR 56694, November 6, 1991).

Frozen Section Evaluation of Margin Status in Primary Squamous Cell Carcinomas of the Head and Neck: A Correlation Study of Frozen Section and Final Diagnoses.

PubMed

Layfield, Eleanor M; Schmidt, Robert L; Esebua, Magda; Layfield, Lester J

2018-06-01

Frozen section is routinely used for intraoperative margin evaluation in carcinomas of the head and neck. We studied a series of frozen sections performed for margin status of head and neck tumors to determine diagnostic accuracy. All frozen sections for margin control of squamous carcinomas of the head and neck were studied from a 66 month period. Frozen and permanent section diagnoses were classified as negative or malignant. Correlation of diagnoses was performed to determine accuracy. One thousand seven hundred and ninety-six pairs of frozen section and corresponding permanent section diagnoses were obtained. Discordances were found in 55 (3.1%) pairs. In 35 pairs (1.9%), frozen section was reported as benign, but permanent sections disclosed carcinoma. In 21 cases, the discrepancy was due to sampling and in the remaining cases it was an interpretive error. In 20 cases (1.1%), frozen section was malignant, but the permanent section was interpreted as negative. Frozen section is an accurate method for evaluation of operative margins for head and neck carcinomas with concordance between frozen and permanent results of 97%. Most errors are false negative results with the majority of these being due to sampling issues.

Asymmetric rifting, breakup and magmatism across conjugate margin pairs: insights from Newfoundland to Ireland

NASA Astrophysics Data System (ADS)

Peace, Alexander L.; Welford, J. Kim; Foulger, Gillian R.; McCaffrey, Ken J. W.

2017-04-01

Continental extension, subsequent rifting and eventual breakup result in the development of passive margins with transitional crust between extended continental crust and newly created oceanic crust. Globally, passive margins are typically classified as either magma-rich or magma-poor. Despite this simple classification, magma-poor margins like the West Orphan Basin, offshore Newfoundland, do exhibit some evidence of localized magmatism, as magmatism to some extent invariably accompanies all continental breakup. For example, on the Newfoundland margin, a small volcanic province has been interpreted near the termination of the Charlie Gibbs Fracture Zone, whereas on the conjugate Irish margin within the Rockall Basin, magmatism appears to be more widespread and has been documented both in the north and in the south. The broader region over which volcanism has been identified on the Irish margin is suggestive of magmatic asymmetry across this conjugate margin pair and this may have direct implications for the mechanisms governing the nature of rifting and breakup. Possible causes of the magmatic asymmetry include asymmetric rifting (simple shear), post-breakup thermal anomalies in the mantle, or pre-existing compositional zones in the crust that predispose one of the margins to more melting than its conjugate. A greater understanding of the mechanisms leading to conjugate margin asymmetry will enhance our fundamental understanding of rifting processes and will also reduce hydrocarbon exploration risk by better characterizing the structural and thermal evolution of hydrocarbon bearing basins on magma-poor margins where evidence of localized magmatism exists. Here, the latest results of a conjugate margin study of the Newfoundland-Ireland pair utilizing seismic interpretation integrated with other geological and geophysical datasets are presented. Our analysis has begun to reveal the nature and timing of rift-related magmatism and the degree to which magmatic asymmetry exists between these conjugate margins. The main implications from this work are that different processes may have operated during and after rifting on these conjugate margins. This concept should be carried forward when conducting conjugate margin studies elsewhere, particularly when exploring for hydrocarbons as prospectivity on one margin may not be predictive for its conjugate as different thermal and structural regimes may have been in operation during conjugate basin evolution.

A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification

PubMed Central

Khorshidtalab, Aida; Mesbah, Mostefa; Salami, Momoh J. E.

2015-01-01

In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain–computer interface (BCI). This method uses a signal-dependent orthogonal transform, referred to as linear prediction singular value decomposition (LP-SVD), for feature extraction. The transform defines the mapping as the left singular vectors of the LP coefficient filter impulse response matrix. Using a logistic tree-based model classifier; the extracted features are classified into one of four motor imagery movements. The proposed approach was first benchmarked against two related state-of-the-art feature extraction approaches, namely, discrete cosine transform (DCT) and adaptive autoregressive (AAR)-based methods. By achieving an accuracy of 67.35%, the LP-SVD approach outperformed the other approaches by large margins (25% compared with DCT and 6 % compared with AAR-based methods). To further improve the discriminatory capability of the extracted features and reduce the computational complexity, we enlarged the extracted feature subset by incorporating two extra features, namely, Q- and the Hotelling’s \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$T^{2}$ \\end{document} statistics of the transformed EEG and introduced a new EEG channel selection method. The performance of the EEG classification based on the expanded feature set and channel selection method was compared with that of a number of the state-of-the-art classification methods previously reported with the BCI IIIa competition data set. Our method came second with an average accuracy of 81.38%. PMID:27170898

Bioenergy crop productivity and potential climate change mitigation from marginal lands in the United States: An ecosystem modeling perspective

DOE PAGES

Qin, Zhangcai; Zhuang, Qianlai; Cai, Ximing

2014-06-16

Growing biomass feedstocks from marginal lands is becoming an increasingly attractive choice for producing biofuel as an alternative energy to fossil fuels. Here, we used a biogeochemical model at ecosystem scale to estimate crop productivity and greenhouse gas (GHG) emissions from bioenergy crops grown on marginal lands in the United States. Two broadly tested cellulosic crops, switchgrass, and Miscanthus, were assumed to be grown on the abandoned land and mixed crop–vegetation land with marginal productivity. Production of biomass and biofuel as well as net carbon exchange and nitrous oxide emissions were estimated in a spatially explicit manner. We found that,more » cellulosic crops, especially Miscanthus could produce a considerable amount of biomass, and the effective ethanol yield is high on these marginal lands. For every hectare of marginal land, switchgrass and Miscanthus could produce 1.0–2.3 kl and 2.9–6.9 kl ethanol, respectively, depending on nitrogen fertilization rate and biofuel conversion efficiency. Nationally, both crop systems act as net GHG sources. Switchgrass has high global warming intensity (100–390 g CO 2eq l –1 ethanol), in terms of GHG emissions per unit ethanol produced. Miscanthus, however, emits only 21–36 g CO 2eq to produce every liter of ethanol. To reach the mandated cellulosic ethanol target in the United States, growing Miscanthus on the marginal lands could potentially save land and reduce GHG emissions in comparison to growing switchgrass. Furthermore, the ecosystem modeling is still limited by data availability and model deficiencies, further efforts should be made to classify crop–specific marginal land availability, improve model structure, and better integrate ecosystem modeling into life cycle assessment.« less

Are food insecurity's health impacts underestimated in the U.S. population? Marginal food security also predicts adverse health outcomes in young U.S. children and mothers.

PubMed

Cook, John T; Black, Maureen; Chilton, Mariana; Cutts, Diana; Ettinger de Cuba, Stephanie; Heeren, Timothy C; Rose-Jacobs, Ruth; Sandel, Megan; Casey, Patrick H; Coleman, Sharon; Weiss, Ingrid; Frank, Deborah A

2013-01-01

This review addresses epidemiological, public health, and social policy implications of categorizing young children and their adult female caregivers in the United States as food secure when they live in households with "marginal food security," as indicated by the U.S. Household Food Security Survey Module. Existing literature shows that households in the US with marginal food security are more like food-insecure households than food-secure households. Similarities include socio-demographic characteristics, psychosocial profiles, and patterns of disease and health risk. Building on existing knowledge, we present new research on associations of marginal food security with health and developmental risks in young children (<48 mo) and health in their female caregivers. Marginal food security is positively associated with adverse health outcomes compared with food security, but the strength of the associations is weaker than that for food insecurity as usually defined in the US. Nonoverlapping CIs, when comparing odds of marginally food-secure children's fair/poor health and developmental risk and caregivers' depressive symptoms and fair/poor health with those in food-secure and -insecure families, indicate associations of marginal food security significantly and distinctly intermediate between those of food security and food insecurity. Evidence from reviewed research and the new research presented indicates that households with marginal food security should not be classified as food secure, as is the current practice, but should be reported in a separate discrete category. These findings highlight the potential underestimation of the prevalence of adverse health outcomes associated with exposure to lack of enough food for an active, healthy life in the US and indicate an even greater need for preventive action and policies to limit and reduce exposure among children and mothers.

Clinical usefulness of extending the proximal margin in total gastrectomies for gastric adenocarcinoma.

PubMed

Clemente-Gutiérrez, U; Sánchez-Morales, G; Santes, O; Medina-Franco, H

2018-05-09

Surgical resection with negative margins is part of the curative treatment of gastric adenocarcinoma. Positive surgical margins are associated with worse outcome. The aim of the present study was to determine the clinical usefulness of extending the proximal surgical margin in patients undergoing total gastrectomy for gastric adenocarcinoma. A retrospective analysis of patients that underwent total gastrectomy within the time frame of 2002 and 2017 was conducted. Patients diagnosed with adenocarcinoma that underwent curative surgery were included. Patients were divided into three groups, depending on proximal surgical margin status: negative margin (R0), positive margin with additional resection to achieve negative margin (R1-R0), and positive margin (R1). Demographic and clinical variables were analyzed. The outcome measures to evaluate were recurrence, disease-free survival, and overall survival. Forty-eight patients were included in the study. Thirty-seven were classified as R0, 9 as R1-R0, and 2 as R1. Fifty-two percent of the patients had clinical stage III disease. The overall surgical mortality rate was 2% and the morbidity rate was higher than 29%. The local recurrence rate was 0% in the R1-R0 group vs. 50% in the R1 group (p = 0.02). Disease-free survival was 49 months in the R1-R0 group vs. 32 months in the R1 group (p = 0.6). Overall survival was 51 months for the R1-R0 group vs. 35 months for the R1 group (p = 0.5). Intraoperative extension of the positive surgical margin improved the local recurrence rate but was not associated with improvement in overall survival or disease-free survival and could possibly increase postoperative morbidity. Copyright © 2018 Asociación Mexicana de Gastroenterología. Publicado por Masson Doyma México S.A. All rights reserved.

Bayes classification of terrain cover using normalized polarimetric data

NASA Technical Reports Server (NTRS)

Yueh, H. A.; Swartz, A. A.; Kong, J. A.; Shin, R. T.; Novak, L. M.

1988-01-01

The normalized polarimetric classifier (NPC) which uses only the relative magnitudes and phases of the polarimetric data is proposed for discrimination of terrain elements. The probability density functions (PDFs) of polarimetric data are assumed to have a complex Gaussian distribution, and the marginal PDF of the normalized polarimetric data is derived by adopting the Euclidean norm as the normalization function. The general form of the distance measure for the NPC is also obtained. It is demonstrated that for polarimetric data with an arbitrary PDF, the distance measure of NPC will be independent of the normalization function selected even when the classifier is mistrained. A complex Gaussian distribution is assumed for the polarimetric data consisting of grass and tree regions. The probability of error for the NPC is compared with those of several other single-feature classifiers. The classification error of NPCs is shown to be independent of the normalization function.

Deepwater Fold-and-Thrust Belt Along New Caledonia's Western Margin: Relation to Post-obduction Vertical Motions

NASA Astrophysics Data System (ADS)

Collot, J.; Patriat, M.; Etienne, S.; Rouillard, P.; Soetaert, F.; Juan, C.; Marcaillou, B.; Palazzin, G.; Clerc, C.; Maurizot, P.; Pattier, F.; Tournadour, E.; Sevin, B.; Privat, A.

2017-10-01

Classically, deepwater fold-and-thrust belts are classified in two main types, depending if they result from near- or far-field stresses and the understanding of their driving and triggering mechanism is poorly known. We present a geophysical data set off the western margin of New Caledonia (SW Pacific) that reveals deformed structures of a deepwater fold-and-thrust belt that we interpret as a near-field gravity-driven system, which is not located at a rifted passive margin. The main factor triggering deformation is inferred to be oversteepening of the margin slope by postobduction isostatic rebound. Onshore erosion of abnormally dense obducted material, combined with sediment loading in the adjacent basin, has induced vertical motions that have caused oversteepening of the margin. Detailed morphobathymetric, seismic stratigraphic, and structural analysis reveals that the fold-and-thrust belt extends 200 km along the margin, and 50 km into the New Caledonia Trough. Deformation is rooted at depths greater than 5 km beneath the seafloor, affects an area of 3,500 km2, and involves a sediment volume of approximately 13,000 km3. This deformed belt is organized into an imbricate fan system of faults, and one out-of-sequence thrust fault affects the seabed. The thrust faults are deeply rooted in the basin along a low-angle floor thrust and connected to New Caledonia Island along a major detachment. This study not only provides a better knowledge of the New Caledonia margin but also provides new insight into the mechanisms that trigger deepwater fold-and-thrust belts.

Intraoperative Raman Spectroscopy of Soft Tissue Sarcomas

PubMed Central

Nguyen, John Q.; Gowani, Zain S.; O’Connor, Maggie; Pence, Isaac J.; Nguyen, The-Quyen; Holt, Ginger E.; Schwartz, Herbert S.; Halpern, Jennifer L.; Mahadevan-Jansen, Anita

2017-01-01

Background and Objective Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated through surgical resection. Current intraoperative margin assessment methods are limited and highlight the need for an improved approach with respect to time and specificity. Here we investigate the potential of near-infrared Raman spectroscopy for the intraoperative differentiation of STS from surrounding normal tissue. Materials and Methods In vivo Raman measurements at 785 nm excitation were intraoperatively acquired from subjects undergoing STS resection using a probe based spectroscopy system. A multivariate classification algorithm was developed in order to automatically identify spectral features that can be used to differentiate STS from the surrounding normal muscle and fat. The classification algorithm was subsequently tested using leave-one-subject-out cross-validation. Results With the exclusion of well-differentiated liposarcomas, the algorithm was able to classify STS from the surrounding normal muscle and fat with a sensitivity and specificity of 89.5% and 96.4%, respectively. Conclusion These results suggest that single point near-infrared Raman spectroscopy could be utilized as a rapid and non-destructive surgical guidance tool for identifying abnormal tissue margins in need of further excision. PMID:27454580

Intraoperative Raman spectroscopy of soft tissue sarcomas.

PubMed

Nguyen, John Q; Gowani, Zain S; O'Connor, Maggie; Pence, Isaac J; Nguyen, The-Quyen; Holt, Ginger E; Schwartz, Herbert S; Halpern, Jennifer L; Mahadevan-Jansen, Anita

2016-10-01

Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated through surgical resection. Current intraoperative margin assessment methods are limited and highlight the need for an improved approach with respect to time and specificity. Here we investigate the potential of near-infrared Raman spectroscopy for the intraoperative differentiation of STS from surrounding normal tissue. In vivo Raman measurements at 785 nm excitation were intraoperatively acquired from subjects undergoing STS resection using a probe based spectroscopy system. A multivariate classification algorithm was developed in order to automatically identify spectral features that can be used to differentiate STS from the surrounding normal muscle and fat. The classification algorithm was subsequently tested using leave-one-subject-out cross-validation. With the exclusion of well-differentiated liposarcomas, the algorithm was able to classify STS from the surrounding normal muscle and fat with a sensitivity and specificity of 89.5% and 96.4%, respectively. These results suggest that single point near-infrared Raman spectroscopy could be utilized as a rapid and non-destructive surgical guidance tool for identifying abnormal tissue margins in need of further excision. Lasers Surg. Med. 48:774-781, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Low Prevalence of Iron and Vitamin A Deficiency among Cambodian Women of Reproductive Age

PubMed Central

Wieringa, Frank T.; Sophonneary, Prak; Whitney, Sophie; Mao, Bunsoth; Berger, Jacques; Conkle, Joel; Dijkhuizen, Marjoleine A.; Laillou, Arnaud

2016-01-01

Nearly half of women of reproductive age (WRA) in Cambodia are anemic. To guide interventions, national data on nutritional causes of anemia, including iron deficiency and vitamin A deficiency, are needed. In 2012, a national household survey in WRA on antibodies to routine vaccine-preventable disease immunity was performed. We used serum samples from this survey to estimate the prevalence of iron and vitamin A deficiency in 2112 Cambodian WRA, aged 15 to 39 years. Iron deficiency was classified as low or marginal iron stores (ferritin concentrations corrected for inflammation <15 μg/L and <50 μg/L respectively; Fer), iron deficient erythropoiesis (soluble transferrin receptor concentrations >8.3 mg/L; sTfR), or low total body iron (TBI) derived from Fer and sTfR concentrations (<0 mg/kg). Vitamin A status was classified using retinol binding protein (RBP) concentrations corrected for inflammation as deficient (<0.70 μmol/L) or marginal (<1.05 μmol/L. Overall, the prevalence of low iron stores, low TBI and iron deficient erythropoiesis was 8.1%, 5.0% and 9.3% respectively. Almost 40% of the women had marginal iron stores. Iron status was better in women living in urban areas compared to rural areas (p < 0.05 for TBI and sTfR). The prevalence of vitamin A deficiency was <1%. These findings suggest that the contribution of iron and vitamin A deficiency to the high prevalence of anemia in Cambodian WRA may be limited. The etiology of anemia in Cambodia needs to be elucidated further to guide current policies on anemia. PMID:27043624

Association Between Years of Experience and Ankle Joint Disorder in Male Student Basketball Players Based on Ultrasonography.

PubMed

Fukushima, Yaeko

2017-04-01

The goal of the study was to survey ankle joint disorder in male senior high school and college student basketball players based on the results of an ultrasonographic medical check-up of the ankle joint. The subjects were 17 senior high school student and 19 college student basketball players. Ultrasonography, evaluation of ATFL injury, and examination of the talocrural joint region were performed. The subjects were grouped based on the presence or absence of old ATFL injury, and subjects with ATFL injury were classified by the injured region: fibular insertion site, parenchyma, and talar insertion site. The talocrural joint region was evaluated based on the areas of the lateral margin, central region, and medial margin, and sites with an irregular bone contour and osteophyte were counted individually. The questionnaire asked about the patients' history of ankle injuries. A questionnaire survey revealed that 70-79% of all subjects had experienced a sprain at least once and 21-29% had frequently sprained the left or right foot 10 or more times in the past. On ultrasonography, there was no significant difference in ligament injury or injured site between the senior high school and college students, but the number of osteochondral findings in the talocrural joint region was significantly higher in the college students. In addition, the number of injured sites significantly increased in those with 10 or more years of playing experience. These results suggest that disorder of the talocrural joint region progresses with an increase in years of experience in student basketball players who do not take specific preventive measures against this injury.

Intraoperative Near-Infrared Fluorescence Imaging using indocyanine green in colorectal carcinomatosis surgery: Proof of concept.

PubMed

Barabino, G; Klein, J P; Porcheron, J; Grichine, A; Coll, J-L; Cottier, M

2016-12-01

This study assesses the value of using Intraoperative Near Infrared Fluorescence Imaging and Indocyanine green to detect colorectal carcinomatosis during oncological surgery. In colorectal carcinomatosis cancer, two of the most important prognostic factors are completeness of staging and completeness of cytoreductive surgery. Presently, intraoperative assessment of tumoral margins relies on palpation and visual inspection. The recent introduction of Near Infrared fluorescence image guidance provides new opportunities for surgical roles, particularly in cancer surgery. The study was a non-randomized, monocentric, pilot "ex vivo" blinded clinical trial validated by the ethical committee of University Hospital of Saint Etienne. Ten patients with colorectal carcinomatosis cancer scheduled for cytoreductive surgery were included. Patients received 0.25 mg/kg of Indocyanine green intravenously 24 h before surgery. A Near Infrared camera was used to detect "ex-vivo" fluorescent lesions. There was no surgical mortality. Each analysis was done blindly. In a total of 88 lesions analyzed, 58 were classified by a pathologist as cancerous and 30 as non-cancerous. Among the 58 cancerous lesions, 42 were correctly classified by the Intraoperative Near-Infrared camera (sensitivity of 72.4%). Among the 30 non-cancerous lesions, 18 were correctly classified by the Intraoperative Near-Infrared camera (specificity of 60.0%). Near Infrared fluorescence imaging is a promising technique for intraoperative tumor identification. It could help the surgeon to determine resection margins and reduce the risk of locoregional recurrence. Copyright © 2016 Elsevier Ltd, BASO ~ the Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Canine ocular gliomas: a retrospective study.

PubMed

Naranjo, Carolina; Schobert, Charles; Dubielzig, Richard

2008-01-01

The purpose of this paper is to classify glial tumors observed in the canine retina and optic nerve, describe the histopathological features and provide prognostic information on these neoplasms. The database of the Comparative Ocular Pathology Laboratory of Wisconsin (COPLOW) was searched to collect canine glioma cases. Clinical and follow-up information was gathered from submission forms and an extensive follow-up survey. Slides were reviewed to describe the histopathological characteristics of the neoplasm and classify them. Immunohistochemistry for Glial Fibrillary Acidic Protein (GFAP) was performed in all cases. 18 canine glioma cases were found in the COPLOW database. There was no breed or gender predilection. The mean age was 9.33 +/- 3.67 years. Follow-up information was available for 12 dogs, 8 of which were dead at the time of most recent contact, with a survival time ranging from 0 days (globes received after euthanasia) up to 20 months post-enucleation. In 6 of the 8 dogs that had died during this stud), tumor extended to the margin where the optic nerve had been sectioned. Light microscopic examination of the optic nerve of the affected eyes of four dogs that were still alive during this study revealed no tumor at this surgical margin. One neoplasm was classified as low-grade astrocytoma, 5 tumors as medium-grade astrocytoma, 11 tumors as high grade-astrocytoma and 1 tumor as oligodendroglioma. GFAP was positive in all but two tumors. Retinal and optic nerve gliomas may be considered as differential diagnoses of intraocular and orbital masses. The metastatic potential appears to be low, but ascending invasion into the ventral aspect of the brain is possible.

Tensor-product kernel-based representation encoding joint MRI view similarity.

PubMed

Alvarez-Meza, A; Cardenas-Pena, D; Castro-Ospina, A E; Alvarez, M; Castellanos-Dominguez, G

2014-01-01

To support 3D magnetic resonance image (MRI) analysis, a marginal image similarity (MIS) matrix holding MR inter-slice relationship along every axis view (Axial, Coronal, and Sagittal) can be estimated. However, mutual inference from MIS view information poses a difficult task since relationships between axes are nonlinear. To overcome this issue, we introduce a Tensor-Product Kernel-based Representation (TKR) that allows encoding brain structure patterns due to patient differences, gathering all MIS matrices into a single joint image similarity framework. The TKR training strategy is carried out into a low dimensional projected space to get less influence of voxel-derived noise. Obtained results for classifying the considered patient categories (gender and age) on real MRI database shows that the proposed TKR training approach outperforms the conventional voxel-wise sum of squared differences. The proposed approach may be useful to support MRI clustering and similarity inference tasks, which are required on template-based image segmentation and atlas construction.

Adapting Local Features for Face Detection in Thermal Image.

PubMed

Ma, Chao; Trung, Ngo Thanh; Uchiyama, Hideaki; Nagahara, Hajime; Shimada, Atsushi; Taniguchi, Rin-Ichiro

2017-11-27

A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses). We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.

A Clinical Decision Support System Using Ultrasound Textures and Radiologic Features to Distinguish Metastasis From Tumor-Free Cervical Lymph Nodes in Patients With Papillary Thyroid Carcinoma.

PubMed

Abbasian Ardakani, Ali; Reiazi, Reza; Mohammadi, Afshin

2018-03-30

This study investigated the potential of a clinical decision support approach for the classification of metastatic and tumor-free cervical lymph nodes (LNs) in papillary thyroid carcinoma on the basis of radiologic and textural analysis through ultrasound (US) imaging. In this research, 170 metastatic and 170 tumor-free LNs were examined by the proposed clinical decision support method. To discover the difference between the groups, US imaging was used for the extraction of radiologic and textural features. The radiologic features in the B-mode scans included the echogenicity, margin, shape, and presence of microcalcification. To extract the textural features, a wavelet transform was applied. A support vector machine classifier was used to classify the LNs. In the training set data, a combination of radiologic and textural features represented the best performance with sensitivity, specificity, accuracy, and area under the curve (AUC) values of 97.14%, 98.57%, 97.86%, and 0.994, respectively, whereas the classification based on radiologic and textural features alone yielded lower performance, with AUCs of 0.964 and 0.922. On testing the data set, the proposed model could classify the tumor-free and metastatic LNs with an AUC of 0.952, which corresponded to sensitivity, specificity, and accuracy of 93.33%, 96.66%, and 95.00%. The clinical decision support method based on textural and radiologic features has the potential to characterize LNs via 2-dimensional US. Therefore, it can be used as a supplementary technique in daily clinical practice to improve radiologists' understanding of conventional US imaging for characterizing LNs. © 2018 by the American Institute of Ultrasound in Medicine.

78 FR 4365 - Capital, Margin, and Segregation Requirements for Security-Based Swap Dealers and Major Security...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-22

... 3235-AL12 Capital, Margin, and Segregation Requirements for Security-Based Swap Dealers and Major... public comment to establish capital, margin, and segregation requirements for security-based swap dealers... soliciting comment on proposed rules and rule amendments establishing capital, margin, and segregation...

Evaluation of a low density DNA microarray for small B-cell non-Hodgkin lymphoma differential diagnosis.

PubMed

Gillet, Jean-Pierre; Molina, Thierry Jo; Jamart, Jacques; Gaulard, Philippe; Leroy, Karen; Briere, Josette; Theate, Ivan; Thieblemont, Catherine; Bosly, Andre; Herin, Michel; Hamels, Jacques; Remacle, Jose

2009-03-01

Lymphomas are classified according to the World Health Organisation (WHO) classification which defines subtypes on the basis of clinical, morphological, immunophenotypic, molecular and cytogenetic criteria. Differential diagnosis of the subtypes is sometimes difficult, especially for small B-cell lymphoma (SBCL). Standardisation of molecular genetic assays using multiple gene expression analysis by microarrays could be a useful complement to the current diagnosis. The aim of the present study was to develop a low density DNA microarray for the analysis of 107 genes associated with B-cell non-Hodgkin lymphoma and to evaluate its performance in the diagnosis of SBCL. A predictive tool based on Fisher discriminant analysis using a training set of 40 patients including four different subtypes (follicular lymphoma n = 15, mantle cell lymphoma n = 7, B-cell chronic lymphocytic leukemia n = 6 and splenic marginal zone lymphoma n = 12) was designed. A short additional preliminary analysis to gauge the accuracy of this signature was then performed on an external set of nine patients. Using this model, eight of nine of those samples were classified successfully. This pilot study demonstrates that such a microarray tool may be a promising diagnostic approach for small B-cell non-Hodgkin lymphoma.

S-CNN: Subcategory-aware convolutional networks for object detection.

PubMed

Chen, Tao; Lu, Shijian; Fan, Jiayuan

2017-09-26

The marriage between the deep convolutional neural network (CNN) and region proposals has made breakthroughs for object detection in recent years. While the discriminative object features are learned via a deep CNN for classification, the large intra-class variation and deformation still limit the performance of the CNN based object detection. We propose a subcategory-aware CNN (S-CNN) to solve the object intra-class variation problem. In the proposed technique, the training samples are first grouped into multiple subcategories automatically through a novel instance sharing maximum margin clustering process. A multi-component Aggregated Channel Feature (ACF) detector is then trained to produce more latent training samples, where each ACF component corresponds to one clustered subcategory. The produced latent samples together with their subcategory labels are further fed into a CNN classifier to filter out false proposals for object detection. An iterative learning algorithm is designed for the joint optimization of image subcategorization, multi-component ACF detector, and subcategory-aware CNN classifier. Experiments on INRIA Person dataset, Pascal VOC 2007 dataset and MS COCO dataset show that the proposed technique clearly outperforms the state-of-the-art methods for generic object detection.

75 FR 13610 - Office of New Reactors; Interim Staff Guidance on Implementation of a Seismic Margin Analysis for...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-22

... Staff Guidance on Implementation of a Seismic Margin Analysis for New Reactors Based on Probabilistic... Seismic Margin Analysis for New Reactors Based on Probabilistic Risk Assessment,'' (Agencywide Documents.../COL-ISG-020 ``Implementation of a Seismic Margin Analysis for New Reactors Based on Probabilistic Risk...

Measuring Cosmological Parameters with Photometrically Classified Pan-STARRS Supernovae

NASA Astrophysics Data System (ADS)

Jones, David; Scolnic, Daniel; Riess, Adam; Rest, Armin; Kirshner, Robert; Berger, Edo; Kessler, Rick; Pan, Yen-Chen; Foley, Ryan; Chornock, Ryan; Ortega, Carolyn; Challis, Peter; Burgett, William; Chambers, Kenneth; Draper, Peter; Flewelling, Heather; Huber, Mark; Kaiser, Nick; Kudritzki, Rolf; Metcalfe, Nigel; Tonry, John; Wainscoat, Richard J.; Waters, Chris; Gall, E. E. E.; Kotak, Rubina; McCrum, Matt; Smartt, Stephen; Smith, Ken

2018-01-01

We use nearly 1,200 supernovae (SNe) from Pan-STARRS and ~200 low-z (z < 0.1) SNe Ia to measure cosmological parameters. Though most of these SNe lack spectroscopic classifications, in a previous paper we demonstrated that photometrically classified SNe can still be used to infer unbiased cosmological parameters by using a Bayesian methodology that marginalizes over core-collapse (CC) SN contamination. Our sample contains nearly twice as many SNe as the largest previous compilation of SNe Ia. Combining SNe with Cosmic Microwave Background (CMB) constraints from the Planck satellite, we measure the dark energy equation of state parameter w to be -0.986±0.058 (stat+sys). If we allow w to evolve with redshift as w(a) = w0 + wa(1-a), we find w0 = -0.923±0.148 and wa = -0.404±0.797. These results are consistent with measurements of cosmological parameters from the JLA and from a new analysis of 1049 spectroscopically confirmed SNe Ia (Scolnic et al. 2017). We try four different photometric classification priors for Pan-STARRS SNe and two alternate ways of modeling the CC SN contamination, finding that none of these variants gives a w that differs by more than 1% from the baseline measurement. The systematic uncertainty on w due to marginalizing over the CC SN contamination, σwCC = 0.019, is approximately equal to the photometric calibration uncertainty and is lower than the systematic uncertainty in the SN\\,Ia dispersion model (σwdisp = 0.024). Our data provide one of the best current constraints on w, demonstrating that samples with ~5% CC SN contamination can give competitive cosmological constraints when the contaminating distribution is marginalized over in a Bayesian framework.

Measuring Dark Energy Properties with Photometrically Classified Pan-STARRS Supernovae. II. Cosmological Parameters

NASA Astrophysics Data System (ADS)

Jones, D. O.; Scolnic, D. M.; Riess, A. G.; Rest, A.; Kirshner, R. P.; Berger, E.; Kessler, R.; Pan, Y.-C.; Foley, R. J.; Chornock, R.; Ortega, C. A.; Challis, P. J.; Burgett, W. S.; Chambers, K. C.; Draper, P. W.; Flewelling, H.; Huber, M. E.; Kaiser, N.; Kudritzki, R.-P.; Metcalfe, N.; Tonry, J.; Wainscoat, R. J.; Waters, C.; Gall, E. E. E.; Kotak, R.; McCrum, M.; Smartt, S. J.; Smith, K. W.

2018-04-01

We use 1169 Pan-STARRS supernovae (SNe) and 195 low-z (z < 0.1) SNe Ia to measure cosmological parameters. Though most Pan-STARRS SNe lack spectroscopic classifications, in a previous paper we demonstrated that photometrically classified SNe can be used to infer unbiased cosmological parameters by using a Bayesian methodology that marginalizes over core-collapse (CC) SN contamination. Our sample contains nearly twice as many SNe as the largest previous SN Ia compilation. Combining SNe with cosmic microwave background (CMB) constraints from Planck, we measure the dark energy equation-of-state parameter w to be ‑0.989 ± 0.057 (stat+sys). If w evolves with redshift as w(a) = w 0 + w a (1 ‑ a), we find w 0 = ‑0.912 ± 0.149 and w a = ‑0.513 ± 0.826. These results are consistent with cosmological parameters from the Joint Light-curve Analysis and the Pantheon sample. We try four different photometric classification priors for Pan-STARRS SNe and two alternate ways of modeling CC SN contamination, finding that no variant gives a w differing by more than 2% from the baseline measurement. The systematic uncertainty on w due to marginalizing over CC SN contamination, {σ }wCC}=0.012, is the third-smallest source of systematic uncertainty in this work. We find limited (1.6σ) evidence for evolution of the SN color-luminosity relation with redshift, a possible systematic that could constitute a significant uncertainty in future high-z analyses. Our data provide one of the best current constraints on w, demonstrating that samples with ∼5% CC SN contamination can give competitive cosmological constraints when the contaminating distribution is marginalized over in a Bayesian framework.

Comparison of external and internal implant-abutment connections for implant supported prostheses. A systematic review and meta-analysis.

PubMed

Lemos, Cleidiel Aparecido Araujo; Verri, Fellippo Ramos; Bonfante, Estevam Augusto; Santiago Júnior, Joel Ferreira; Pellizzer, Eduardo Piza

2018-03-01

The systematic review and meta-analysis aimed to answer the PICO question: "Do patients that received external connection implants show similar marginal bone loss, implant survival and complication rates as internal connection implants?". Meta-analyses of marginal bone loss, survival rates of implants and complications rates were performed for the included studies. Study eligibility criteria included (1) randomized controlled trials (RCTs) and/or prospective, (2) studies with at least 10 patients, (3) direct comparison between connection types and (4) publications in English language. The Cochrane risk of bias tool was used to assess the quality and risk of bias in RCTs, while Newcastle-Ottawa scale was used for non-RCTs. A comprehensive search strategy was designed to identify published studies on PubMed/MEDLINE, Scopus, and The Cochrane Library databases up to October 2017. The search identified 661 references. Eleven studies (seven RCTs and four prospective studies) were included, with a total of 530 patients (mean age, 53.93 years), who had received a total of 1089 implants (461 external-connection and 628 internal-connection implants). The internal-connection implants exhibited lower marginal bone loss than external-connection implants (P<0.00001; Mean Difference (MD): 0.44mm; 95% Confidence interval (CI): 0.26-0.63mm). No significant difference was observed in implant survival (P=0.65; Risk Ratio (RR): 0.83; 95% CI: 0.38-1.84), and complication rates (P=0.43; RR: 1.15; 95% CI: 0.81-1.65). Internal connections had lower marginal bone loss when compared to external connections. However, the implant-abutment connection had no influence on the implant's survival and complication rates. Based on the GRADE approach the evidence was classified as very low to moderate due to the study design, inconsistency, and publication bias. Thus, future research is highly encouraged. Internal connection implants should be preferred over external connection implants, especially when different risk factors that may contribute to increased marginal bone loss are present. Copyright © 2017 Elsevier Ltd. All rights reserved.

Supervised learning with decision margins in pools of spiking neurons.

PubMed

Le Mouel, Charlotte; Harris, Kenneth D; Yger, Pierre

2014-10-01

Learning to categorise sensory inputs by generalising from a few examples whose category is precisely known is a crucial step for the brain to produce appropriate behavioural responses. At the neuronal level, this may be performed by adaptation of synaptic weights under the influence of a training signal, in order to group spiking patterns impinging on the neuron. Here we describe a framework that allows spiking neurons to perform such "supervised learning", using principles similar to the Support Vector Machine, a well-established and robust classifier. Using a hinge-loss error function, we show that requesting a margin similar to that of the SVM improves performance on linearly non-separable problems. Moreover, we show that using pools of neurons to discriminate categories can also increase the performance by sharing the load among neurons.

Are Food Insecurity’s Health Impacts Underestimated in the U.S. Population? Marginal Food Security Also Predicts Adverse Health Outcomes in Young U.S. Children and Mothers123

PubMed Central

Cook, John T.; Black, Maureen; Chilton, Mariana; Cutts, Diana; Ettinger de Cuba, Stephanie; Heeren, Timothy C.; Rose-Jacobs, Ruth; Sandel, Megan; Casey, Patrick H.; Coleman, Sharon; Weiss, Ingrid; Frank, Deborah A.

2013-01-01

This review addresses epidemiological, public health, and social policy implications of categorizing young children and their adult female caregivers in the United States as food secure when they live in households with “marginal food security,” as indicated by the U.S. Household Food Security Survey Module. Existing literature shows that households in the US with marginal food security are more like food-insecure households than food-secure households. Similarities include socio-demographic characteristics, psychosocial profiles, and patterns of disease and health risk. Building on existing knowledge, we present new research on associations of marginal food security with health and developmental risks in young children (<48 mo) and health in their female caregivers. Marginal food security is positively associated with adverse health outcomes compared with food security, but the strength of the associations is weaker than that for food insecurity as usually defined in the US. Nonoverlapping CIs, when comparing odds of marginally food-secure children’s fair/poor health and developmental risk and caregivers’ depressive symptoms and fair/poor health with those in food-secure and -insecure families, indicate associations of marginal food security significantly and distinctly intermediate between those of food security and food insecurity. Evidence from reviewed research and the new research presented indicates that households with marginal food security should not be classified as food secure, as is the current practice, but should be reported in a separate discrete category. These findings highlight the potential underestimation of the prevalence of adverse health outcomes associated with exposure to lack of enough food for an active, healthy life in the US and indicate an even greater need for preventive action and policies to limit and reduce exposure among children and mothers. PMID:23319123

Repair of dimethacrylate-based composite restorations by a silorane-based composite: a one-year randomized clinical trial.

PubMed

Popoff, D A V; Santa Rosa, T T A; Ferreira, R C; Magalhães, C S; Moreira, A N; Mjör, I A

2012-01-01

To investigate clinical performance of a low-shrinkage silorane-based composite resin when used for repairing conventional dimethacrylate-based composite restorations. Despite the continued development of resin-based materials, polymerization shrinkage and shrinkage stress still require improvement. A silorane-based monomer system was recently made available for dental restorations. This report refers to the use of this material for making repairs and evaluates the clinical performance of this alternative treatment. One operator repaired the defective dimethacrylate-based composite resin restorations that were randomly assigned to one of two treatment groups: control (n=50) repair with Adper SE Plus (3M/ESPE) and Filtek P60 Posterior Restorative (3M/ESPE), and test (n=50) repair with P90 System Adhesive Self-Etch Primer and Bond (3M/ESPE) and Filtek P90 Low Shrink Posterior Restorative (3M/ESPE). After one week, restorations were finished and polished. Two calibrated examiners (Kw≥0.78) evaluated all repaired restorations, blindly and independently, at baseline and one year. The parameters examined were marginal adaptation, anatomic form, surface roughness, marginal discoloration, postoperative sensitivity, and secondary caries. The restorations were classified as Alpha, Bravo, or Charlie, according to modified US Public Health Service criteria. Mann-Whitney and Wilcoxon tests were used to compare the groups. Of the 100 restorations repaired in this study, 93 were reexamined at baseline. Dropout from baseline to one-year recall was 11%. No statistically significant differences were found between the materials for all clinical criteria, at baseline or at one-year recall (p>0.05). No statistically significant differences were registered (p>0.05) for each material when compared for all clinical criteria at baseline and at one-year recall. The hypothesis tested in this randomized controlled clinical trial was accepted. After the one-year evaluations, the silorane-based composite exhibited a similar performance compared with dimethacrylate-based composite when used to make repairs.

Coccolithophorid blooms in the global ocean

NASA Technical Reports Server (NTRS)

Brown, Christopher W.; Yoder, James A.

1994-01-01

The global distribution pattern of coccolithophrid blooms was mapped in order to ascertain the prevalence of these blooms in the world's oceans and to estimate their worldwide production of CaCO3 and dimethyl sulfide (DMS). Mapping was accomplished by classifying pixels of 5-day global composites of coastal zone color scanner imagery into bloom and nonbloom classes using a supervised, multispectral classification scheme. Surface waters with the spectral signature of coccolithophorid blooms annually covered an average of 1.4 x 10(exp 6) sq km in the world oceans from 1979 to 1985, with the subpolar latitudes accounting for 71% of this surface area. Classified blooms were most extensive in the Subartic North Atlantic. Large expanses of the bloom signal were also detected in the North Pacific, on the Argentine shelf and slope, and in numerous lower latitude marginal seas and shelf regions. The greatest spatial extent of classified blooms in subpolar oceanic regions occurred in the months from summer to early autumn, while those in lower latitude marginal seas occurred in midwinter to early spring. Though the classification scheme was effcient in separating bloom and nonbloom classes during test simulations, and biogeographical literature generally confirms the resulting distribution pattern of blooms in the subpolar regions, the cause of the bloom signal is equivocal in some geographic areas, particularly on shelf regions at lower latitudes. Standing stock estimates suggest that the presumed Emiliania huxleyi blooms act as a significant source of calcite carbon and DMS sulfur on a regional scale. On a global scale, however, the satellite-detected coccolithophorid blooms are estimated to play only a minor role in the annual production of these two compounds and their flux from the surface mixed layer.

Magnetic resonance imaging-guided navigation with a thermoplastic shell for breast-conserving surgery.

PubMed

Abe, M; Kiryu, T; Sonoda, K; Kashiki, Y

2011-11-01

The aim of this study was to evaluate the accuracy of a magnetic resonance imaging (MRI) marking technique with a drape-type thermoplastic shell for planning breast-conserving surgery (BCS). A prospective review was performed on 35 consecutive patients who underwent MRI in the supine position and used the specified MRI marking technique. Eleven cases underwent pre-operative chemotherapy and 24 cases did not. After immobilizing the breast mound with a drape-type thermoplastic shell, patients underwent MRI, and the location of the lesion was marked on the shell. Resection lines were dyed blue by indigo carmine, which was pushed through the pores of the shell. Specimens obtained during BCS were sliced into 5-mm contiguous sections, and the margin was assessed for each specimen. Cancer foci less than 5 mm from the margin were classified as positive. Of 35 patients, 33 were included in the analysis; 2 were excluded due to a lack of effect of pre-operative chemotherapy. Of these 33 patients, 25 (75.8%) had negative margins and 7 (21.2%) had positive margins. Our MRI marking technique may be useful for evaluating the extent of tumors that were determined by MRI alone. Long-term outcomes of this technique should be evaluated further. Copyright © 2011 Elsevier Ltd. All rights reserved.

Association Between Years of Experience and Ankle Joint Disorder in Male Student Basketball Players Based on Ultrasonography

PubMed Central

Fukushima, Yaeko

2017-01-01

Purpose The goal of the study was to survey ankle joint disorder in male senior high school and college student basketball players based on the results of an ultrasonographic medical check-up of the ankle joint. Materials and Methods The subjects were 17 senior high school student and 19 college student basketball players. Ultrasonography, evaluation of ATFL injury, and examination of the talocrural joint region were performed. The subjects were grouped based on the presence or absence of old ATFL injury, and subjects with ATFL injury were classified by the injured region: fibular insertion site, parenchyma, and talar insertion site. The talocrural joint region was evaluated based on the areas of the lateral margin, central region, and medial margin, and sites with an irregular bone contour and osteophyte were counted individually. The questionnaire asked about the patients’ history of ankle injuries. Results A questionnaire survey revealed that 70–79% of all subjects had experienced a sprain at least once and 21–29% had frequently sprained the left or right foot 10 or more times in the past. On ultrasonography, there was no significant difference in ligament injury or injured site between the senior high school and college students, but the number of osteochondral findings in the talocrural joint region was significantly higher in the college students. In addition, the number of injured sites significantly increased in those with 10 or more years of playing experience. Conclusion These results suggest that disorder of the talocrural joint region progresses with an increase in years of experience in student basketball players who do not take specific preventive measures against this injury. PMID:28603784

Morphological and micromorphological characteristics of Desmodium fruits (Leguminosae: Papilionoideae).

PubMed

Freitas, Daiane M; Reis, Ademir; Bortoluzzi, Roseli L da Costa; Santos, Marisa

2014-12-01

The genus Desmodium is represented in Santa Catarina State, Brazil, by 13 species, all with lomen- taceous fruits. Shape, size and isthmus margin of loments vary, while the surface is glabrous, or covered by trichomes of different types. Morphological diversity of trichomes becomes particularly relevant to taxonomic description. The trichome types present on the surface of Desmodium fruits provide data for the identification and classification of species in the State. To assess this, three fruits of each species were collected and deposited at two herbaria, HBR and FLOR, in Santa Catarina, Brazil. Some rehydrated samples were examined using light microscopy (LM); and some sections were exposed to the following histochemical reagents: Sudan III for oils and Thionine for mucilage. The structural aspects of trichomes can be classified into uni- or multicellular and may still be simple, i.e., nonglandular or glandular. Using scanning electron microscopy (SEM), five types of trichomes were identified and analyzed among the Desmodium species studied: uncinate, uniseriate, globose multicellular, globose unicellular and subulate. Characteristics, such as loment margin and article form, glabrescent or pillous indument, trichome type, with or without papillous epidermal cells and epicuticular striations, showed relevant diagnostic value. An identification key was developed for Desmodium species from Santa Catarina State, Brazil, based on macro and micromorphological characters of the fruit.

Petrography and geochemistry of clastic rocks within the Inthanon zone, northern Thailand: Implications for Paleo-Tethys subduction and convergence

NASA Astrophysics Data System (ADS)

Hara, Hidetoshi; Kunii, Miyuki; Hisada, Ken-ichiro; Ueno, Katsumi; Kamata, Yoshihito; Srichan, Weerapan; Charusiri, Punya; Charoentitirat, Thasinee; Watarai, Megumi; Adachi, Yoshiko; Kurihara, Toshiyuki

2012-11-01

The provenance, source rock compositions, and sediment supply system for a convergence zone of the Paleo-Tethys were reconstructed based on the petrography and geochemistry of clastic rocks of the Inthanon Zone, northern Thailand. The clastic rocks are classified into two types based on field and microscopic observations, the modal composition of sandstone, and mineral compositions: (1) lithic sandstone and shale within mélange in a Permo-Triassic accretionary complex; and (2) Carboniferous quartzose sandstone and mudstone within the Sibumasu Block. Geochemical data indicate that the clastic rocks of the mélange were derived from continental island arc and continental margin settings, which correspond to felsic volcanic rocks within the Sukhothai Zone and quartz-rich fragments within the Indochina Block, respectively. The results of a mixing model indicate the source rocks were approximately 35% volcanic rocks of the Sukhothai Zone and 65% craton sandstone and upper continental crust of the Indochina Block. In contrast, Carboniferous quartzose sedimentary rocks within the Sibumasu Block originated from a continental margin, without a contribution from volcanic rocks. In terms of Paleo-Tethys subduction, a continental island arc in the Sukhothai Zone evolved in tandem with Late Permian-Triassic forearc basins and volcanic activity during the Middle-early Late Triassic. The accretionary complex formed contemporaneously with the evolution of continental island arc during the Permo-Triassic, supplied with sediment from the Sukhothai Zone and the Indochina Block.

Atraumatic restorative treatment with resin-modified glass ionomer material: short-term results of a pilot study.

PubMed

Dülgergil, Coruh Türksel; Soyman, Mübin; Civelek, Arzu

2005-01-01

The aim of this study was to assess the feasibility of the resin-modified glass ionomer (RMGI) material in atraumatic restorative treatment (ART) approach and compare RMGI with the high-strength traditional glass ionomer cement (GIC) in permanent teeth with one or more surface-carious cavities. This study was conducted in a village school in rural southeastern Anatolia, Turkey. The RMGI and GIC restorations with the ART technique were placed randomly employing a split mouth design. In addition, the ART approach was used when necessary for both primary and/or permanent teeth with no pulpal involvement and no perceived pain before treatment. Ninety-one fillings were placed on contralateral molar pairs of 37 children. Baseline and 6-month evaluation of the fillings were made with the classic ART, modified Ryge and USPHS criteria. Based on the ART criteria, 100% of RMGI and 92.4% of GIC restorations were classified as successful after 6 months, and the difference between the 2 groups was statistically significant (p=0.009). While marginal discoloration was the commonest failure in the RMGI group according to both the modified Ryge and USPHS criteria, unsatisfactory surface texture and low anatomic form were the commonly seen failures in the ART technique. Generally, for each rating system, RMGI exhibited better clinical performance than GIC in all categories, except for marginal discoloration. Results based on the 6-month evaluation show that RMGI can be an alternative material to the GIC. Copyright (c) 2005 S. Karger AG, Basel.

Influence of Different Implant Geometry in Clinical Longevity and Maintenance of Marginal Bone: A Systematic Review.

PubMed

Lovatto, Sabrina Telles; Bassani, Rafaela; Sarkis-Onofre, Rafael; Dos Santos, Mateus Bertolini Fernandes

2018-03-26

To assess, through a systematic review, the influence of different implant geometries on clinical longevity and maintenance of marginal bone tissue. An electronic search was conducted in MEDLINE, Scopus, and Web of Science databases, limited to studies written in English from 1996 to 2017 using specific search strategies. Only randomized controlled trials (RCTs) that compared dental implants and their geometries were included. Two reviewers independently selected studies, extracted data, and assessed the risk of bias of included studies. From the 4006 references identified by the search, 24 were considered eligible for full-text analysis, after which 10 studies were included in this review. A similar behavior of marginal bone loss between tapered and cylindrical geometries was observed; however, implants that had micro-threads in the neck presented a slight decrease of marginal bone loss compared to implants with straight or smooth neck. Success and survival rates were high, with cylindrical implants presenting higher success and survival rates than tapered ones. Implant geometry seems to have little influence on marginal bone loss (MBL) and survival and success rates after 1 year of implant placement; however, the evidence in this systematic review was classified as very low due to limitations such as study design, sample size, and publication bias. Thus, more well-designed RCTs should be conducted to provide evidence regarding the influence of implant geometry on MBL and survival and success rates after 1 year of implant placement. © 2018 by the American College of Prosthodontists.

Analysis of surgical margins in oral cancer using in situ fluorescence spectroscopy.

PubMed

Francisco, Ana Lucia Noronha; Correr, Wagner Rafael; Pinto, Clóvis Antônio Lopes; Gonçalves Filho, João; Chulam, Thiago Celestino; Kurachi, Cristina; Kowalski, Luiz Paulo

2014-06-01

Oral cancer is a public health problem with high prevalence in the population. Local tumor control is best achieved by complete surgical resection with adequate margins. A disease-free surgical margin correlates with a lower rate of local recurrence and a higher rate of disease-free survival. Fluorescence spectroscopy is a noninvasive diagnostic tool that can aid in real-time cancer detection. The technique, which evaluates the biochemical composition and structure of tissue fluorescence, is relatively simple, fast and, accurate. This study aimed to compare oral squamous cell carcinoma lesions to surgical margins and the mucosa of healthy volunteers by fluorescence spectroscopy. The sample consisted of 56 individuals, 28 with oral squamous cell carcinoma and 28 healthy volunteers with normal oral mucosa. Thirty six cases (64.3%) were male and the mean age was 60.9 years old. The spectra were classified and compared to histopathology to determine fluorescence efficiency for diagnostic discrimination of tumors. In the analysis of the other cases we observed discrimination between normal mucosa, injury and margins. At two-year follow up, three individuals had local recurrence, and in two cases investigation fluorescence in the corresponding area showed qualitative differences in spectra between the recurrence area and the area without recurrence at the same anatomical site in the same patient. In situ analysis of oral mucosa showed the potential of fluorescence spectroscopy as a diagnostic tool that can aid in discrimination of altered mucosa and normal mucosa. Copyright © 2014 Elsevier Ltd. All rights reserved.

Accuracy of digital images in the detection of marginal microleakage: an in vitro study.

PubMed

Alvarenga, Fábio Augusto; Andrade, Marcelo Ferrarezi; Pinelli, Camila; Rastelli, Alessanda Nara; Victorino, Keli Regina; Loffredo, Leonor de

2012-08-01

To evaluate the accuracy of Image Tool Software 3.0 (ITS 3.0) to detect marginal microleakage using the stereomicroscope as the validation criterion and ITS 3.0 as the tool under study. Class V cavities were prepared at the cementoenamel junction of 61 bovine incisors, and 53 halves of them were used. Using the stereomicroscope, microleakage was classified dichotomously: presence or absence. Next, ITS 3.0 was used to obtain measurements of the microleakage, so that 0.75 was taken as the cut-off point, and values equal to or greater than 0.75 indicated its presence, while values between 0.00 and 0.75 indicated its absence. Sensitivity and specificity were calculated by point and given as 95% confidence interval (95% CI). The accuracy of the ITS 3.0 was verified with a sensitivity of 0.95 (95% CI: 0.89 to 1.00) and a specificity of 0.92 (95% CI: 0.84 to 0.99). Digital diagnosis of marginal microleakage using ITS 3.0 was sensitive and specific.

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition

PubMed Central

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-01-01

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition. PMID:28467371

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-05-03

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition.

Real-time image annotation by manifold-based biased Fisher discriminant analysis

NASA Astrophysics Data System (ADS)

Ji, Rongrong; Yao, Hongxun; Wang, Jicheng; Sun, Xiaoshuai; Liu, Xianming

2008-01-01

Automatic Linguistic Annotation is a promising solution to bridge the semantic gap in content-based image retrieval. However, two crucial issues are not well addressed in state-of-art annotation algorithms: 1. The Small Sample Size (3S) problem in keyword classifier/model learning; 2. Most of annotation algorithms can not extend to real-time online usage due to their low computational efficiencies. This paper presents a novel Manifold-based Biased Fisher Discriminant Analysis (MBFDA) algorithm to address these two issues by transductive semantic learning and keyword filtering. To address the 3S problem, Co-Training based Manifold learning is adopted for keyword model construction. To achieve real-time annotation, a Bias Fisher Discriminant Analysis (BFDA) based semantic feature reduction algorithm is presented for keyword confidence discrimination and semantic feature reduction. Different from all existing annotation methods, MBFDA views image annotation from a novel Eigen semantic feature (which corresponds to keywords) selection aspect. As demonstrated in experiments, our manifold-based biased Fisher discriminant analysis annotation algorithm outperforms classical and state-of-art annotation methods (1.K-NN Expansion; 2.One-to-All SVM; 3.PWC-SVM) in both computational time and annotation accuracy with a large margin.

A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels.

PubMed

Xu, Ming; Jiao, Yan; Li, Xiaoming; Cao, Qingfeng; Wang, Xiaoyang

2015-01-01

This paper presents a multi-period optimization model for high margin and zero salvage products in online distribution channels with classifying customers based on number of products required. Taking hotel customers as an example, one is regular customers who reserve rooms for one day, and the other is long term stay (LTS) customers who reserve rooms for a number of days. LTS may guarantee a specific amount of demand and generate opportunity income for a certain number of periods, meanwhile with risk of punishment incurred by overselling. By developing an operational optimization model and exploring the effects of parameters on optimal decisions, we suggest that service providers should make decisions based on the types of customers, number of products required, and duration of multi-period to reduce the loss of reputation and obtain more profit; at the same time, multi-period buying customers should buy products early. Finally, the paper conducts a numerical experiment, and the results are consistent with prevailing situations.

A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels

PubMed Central

Xu, Ming; Jiao, Yan; Li, Xiaoming; Cao, Qingfeng; Wang, Xiaoyang

2015-01-01

This paper presents a multi-period optimization model for high margin and zero salvage products in online distribution channels with classifying customers based on number of products required. Taking hotel customers as an example, one is regular customers who reserve rooms for one day, and the other is long term stay (LTS) customers who reserve rooms for a number of days. LTS may guarantee a specific amount of demand and generate opportunity income for a certain number of periods, meanwhile with risk of punishment incurred by overselling. By developing an operational optimization model and exploring the effects of parameters on optimal decisions, we suggest that service providers should make decisions based on the types of customers, number of products required, and duration of multi-period to reduce the loss of reputation and obtain more profit; at the same time, multi-period buying customers should buy products early. Finally, the paper conducts a numerical experiment, and the results are consistent with prevailing situations. PMID:26147663

Optimizing area under the ROC curve using semi-supervised learning

PubMed Central

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M.

2014-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.1 PMID:25395692

Optimizing area under the ROC curve using semi-supervised learning.

PubMed

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M

2015-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.

Fusion of spatial gray level dependency and fractal texture features for the characterization of thyroid lesions.

PubMed

Raghavendra, U; Rajendra Acharya, U; Gudigar, Anjan; Hong Tan, Jen; Fujita, Hamido; Hagiwara, Yuki; Molinari, Filippo; Kongmebhol, Pailin; Hoong Ng, Kwan

2017-05-01

Thyroid is a small gland situated at the anterior side of the neck and one of the largest glands of the endocrine system. The abrupt cell growth or malignancy in the thyroid gland may cause thyroid cancer. Ultrasound images distinctly represent benign and malignant lesions, but accuracy may be poor due to subjective interpretation. Computer Aided Diagnosis (CAD) can minimize the errors created due to subjective interpretation and assists to make fast accurate diagnosis. In this work, fusion of Spatial Gray Level Dependence Features (SGLDF) and fractal textures are used to decipher the intrinsic structure of benign and malignant thyroid lesions. These features are subjected to graph based Marginal Fisher Analysis (MFA) to reduce the number of features. The reduced features are subjected to various ranking methods and classifiers. We have achieved an average accuracy, sensitivity and specificity of 97.52%, 90.32% and 98.57% respectively using Support Vector Machine (SVM) classifier. The achieved maximum Area Under Curve (AUC) is 0.9445. Finally, Thyroid Clinical Risk Index (TCRI) a single number is developed using two MFA features to discriminate the two classes. This prototype system is ready to be tested with huge diverse database. Copyright © 2017 Elsevier B.V. All rights reserved.

Re-Evaluation of Open Partial Horizontal Laryngectomies at Our Institution According to the New Classification Recommended by the European Laryngological Society.

PubMed

Bozkurt, Gülpembe; Ünsal, Özlem; Coşkun, Berna Uslu

2016-06-01

The aim of this study was to re-evaluate the open partial horizontal laryngectomies (OPHLs) performed at our institution in terms of the new classification of the European Laryngological Society and compare the differences with the new classification system. A retrospective analysis of 45 patients diagnosed with T1b, T2, and T3 laryngeal carcinoma who were treated with OPHLs in our department between 2010 and 2016 were conducted. All supraglottic laryngectomies (31 operations) were classified as OPHL Type 1. Among these, 11 operations required a resection of an additional structure including arytenoid (ARY) in five operations, piriform sinus (PIR) in four operations, the base of tongue (BOT) in one surgery, and ARY + PIR in one patient. Five supracricoid laryngectomies with cricohyoidoepiglottopexy (CHEP), five supracricoid laryngectomies with cricohyoidopexy (CHP), and four near-total laryngectomy operations constituted Type 2 OPHL (7 operations) and Type 3 OPHL (7 operations). Among these operations, two were classified into Type 2b OPHL and four into Type 3b OPHL as the superior margin of incision included epiglottis. We consider that, this new classification, because it allows understanding the content of the surgery from the related title, will be useful in comparing different series and techniques.

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing

NASA Astrophysics Data System (ADS)

O'Connell, Jerome; Bradter, Ute; Benton, Tim G.

2015-11-01

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ˜22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability.

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing.

PubMed

O'Connell, Jerome; Bradter, Ute; Benton, Tim G

2015-11-01

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer ( Emberiza citronella ), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m 2 . The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability.

Multilevel en bloc spondylectomy for tumors of the thoracic and lumbar spine is challenging but rewarding.

PubMed

Luzzati, Alessandro Davide; Shah, Sambhav; Gagliano, Fabio; Perrucchini, Giuseppe; Scotto, Gennaro; Alloisio, Marco

2015-03-01

Over the years, en bloc spondylectomy has proven its efficacy in controlling spinal tumors and improving survival rates. However, there are few reports of large series that critically evaluate the results of multilevel en bloc spondylectomies for spinal neoplasms. Using data from a large spine tumor center, we answered the following questions: (1) Does multilevel total en bloc spondylectomy result in acceptable function, survival rates, and local control in spinal neoplasms? (2) Is reconstruction after this procedure feasible? (3) What complications are associated with this procedure? (4) is it possible to achieve adequate surgical margins with this procedure? We retrospectively investigated 38 patients undergoing multilevel total en bloc spondylectomy by a single surgeon (AL) from 1994 to 2011. Indications for this procedure were primary spinal sarcomas, solitary metastases, and aggressive primary benign tumors involving multiple segments of the thoracic or lumbar spine. Patients had to be medically fit and have no visceral metastases. Analysis was by chart and radiographic review. Margin quality was classified into intralesional, marginal, and wide. Radiographs, MR images, and CT scans were studied for local recurrence. Graft healing and instrumentation failures at subsequent followup were assessed. Complications were divided into major or minor and further classified as intraoperative and early and late postoperative. We evaluated the oncologic status using cumulative disease-specific and metastases-free survival analysis. Minimum followup was 24 months (mean, 39 months; range, 24-124 months). Of the 38 patients, 34 (89%) were alive and walking without support at final followup. Thirty-one (81%) had no evidence of disease. Two patients died postoperatively and another two died of systemic disease (without local recurrence). Only three patients (8%) had a local recurrence. There were 14 major complications and 22 minor complications in 25 patients (65%). Only one patient required revision of implants secondary to mechanical failure. Two cases of cage subsidence were noted but had no clinical significance. Wide margins were achieved in nine patients (23%), marginal in 25 (66%), and intralesional in four (11%). In patients with multisegmental spinal tumors, oncologic resections were achieved by multilevel en bloc spondylectomy and led to an acceptable survival rate with reasonable local control. Multilevel en bloc surgery was associated with a high complication rate; however, most patients recovered from their complications. Although the surgical procedure is challenging, our encouraging mid-term results clearly favor and validate this technique. Level IV, therapeutic study. See Instructions for Authors for a complete description of levels of evidence.

Supervised linear dimensionality reduction with robust margins for object recognition

NASA Astrophysics Data System (ADS)

Dornaika, F.; Assoum, A.

2013-01-01

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.

Realistic respiratory motion margins for external beam partial breast irradiation

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

Conroy, Leigh; Quirk, Sarah; Department of Physics and Astronomy, University of Calgary, Calgary, Alberta T2N 1N4

Purpose: Respiratory margins for partial breast irradiation (PBI) have been largely based on geometric observations, which may overestimate the margin required for dosimetric coverage. In this study, dosimetric population-based respiratory margins and margin formulas for external beam partial breast irradiation are determined. Methods: Volunteer respiratory data and anterior–posterior (AP) dose profiles from clinical treatment plans of 28 3D conformal radiotherapy (3DCRT) PBI patient plans were used to determine population-based respiratory margins. The peak-to-peak amplitudes (A) of realistic respiratory motion data from healthy volunteers were scaled from A = 1 to 10 mm to create respiratory motion probability density functions. Dosemore » profiles were convolved with the respiratory probability density functions to produce blurred dose profiles accounting for respiratory motion. The required margins were found by measuring the distance between the simulated treatment and original dose profiles at the 95% isodose level. Results: The symmetric dosimetric respiratory margins to cover 90%, 95%, and 100% of the simulated treatment population were 1.5, 2, and 4 mm, respectively. With patient set up at end exhale, the required margins were larger in the anterior direction than the posterior. For respiratory amplitudes less than 5 mm, the population-based margins can be expressed as a fraction of the extent of respiratory motion. The derived formulas in the anterior/posterior directions for 90%, 95%, and 100% simulated population coverage were 0.45A/0.25A, 0.50A/0.30A, and 0.70A/0.40A. The differences in formulas for different population coverage criteria demonstrate that respiratory trace shape and baseline drift characteristics affect individual respiratory margins even for the same average peak-to-peak amplitude. Conclusions: A methodology for determining population-based respiratory margins using real respiratory motion patterns and dose profiles in the AP direction was described. It was found that the currently used respiratory margin of 5 mm in partial breast irradiation may be overly conservative for many 3DCRT PBI patients. Amplitude alone was found to be insufficient to determine patient-specific margins: individual respiratory trace shape and baseline drift both contributed to the dosimetric target coverage. With respiratory coaching, individualized respiratory margins smaller than the full extent of motion could reduce planning target volumes while ensuring adequate coverage under respiratory motion.« less

Pharmacological targeting of exercise adaptations in skeletal muscle: Benefits and pitfalls.

PubMed

Weihrauch, Martin; Handschin, Christoph

2018-01-01

Exercise exerts significant effects on the prevention and treatment of many diseases. However, even though some of the key regulators of training adaptation in skeletal muscle have been identified, this biological program is still poorly understood. Accordingly, exercise-based pharmacological interventions for many muscle wasting diseases and also for pathologies that are triggered by a sedentary lifestyle remain scarce. The most efficacious compounds that induce muscle hypertrophy or endurance are hampered by severe side effects and are classified as doping. In contrast, dietary supplements with a higher safety margin exert milder outcomes. In recent years, the design of pharmacological agents that activate the training program, so-called "exercise mimetics", has been proposed, although the feasibility of such an approach is highly debated. In this review, the most recent insights into key regulatory factors and therapeutic approaches aimed at leveraging exercise adaptations are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Probabilistic margin evaluation on accidental transients for the ASTRID reactor project

NASA Astrophysics Data System (ADS)

Marquès, Michel

2014-06-01

ASTRID is a technological demonstrator of Sodium cooled Fast Reactor (SFR) under development. The conceptual design studies are being conducted in accordance with the Generation IV reactor objectives, particularly in terms of improving safety. For the hypothetical events, belonging to the accidental category "severe accident prevention situations" having a very low frequency of occurrence, the safety demonstration is no more based on a deterministic demonstration with conservative assumptions on models and parameters but on a "Best-Estimate Plus Uncertainty" (BEPU) approach. This BEPU approach ispresented in this paper for an Unprotected Loss-of-Flow (ULOF) event. The Best-Estimate (BE) analysis of this ULOFt ransient is performed with the CATHARE2 code, which is the French reference system code for SFR applications. The objective of the BEPU analysis is twofold: first evaluate the safety margin to sodium boiling in taking into account the uncertainties on the input parameters of the CATHARE2 code (twenty-two uncertain input parameters have been identified, which can be classified into five groups: reactor power, accident management, pumps characteristics, reactivity coefficients, thermal parameters and head losses); secondly quantify the contribution of each input uncertainty to the overall uncertainty of the safety margins, in order to refocusing R&D efforts on the most influential factors. This paper focuses on the methodological aspects of the evaluation of the safety margin. At least for the preliminary phase of the project (conceptual design), a probabilistic criterion has been fixed in the context of this BEPU analysis; this criterion is the value of the margin to sodium boiling, which has a probability 95% to be exceeded, obtained with a confidence level of 95% (i.e. the M5,95percentile of the margin distribution). This paper presents two methods used to assess this percentile: the Wilks method and the Bootstrap method ; the effectiveness of the two methods is compared on the basis of 500 simulations performed with theCATHARE2 code. We conclude that, with only 100 simulations performed with the CATHARE2 code, which is a number of simulations workable in the conceptual design phase of the ASTRID project where the models and the hypothesis are often modified, it is best in order to evaluate the percentile M5,95 of the margin to sodium boiling to use the bootstrap method, which will provide a slightly conservative result. On the other hand, in order to obtain an accurate estimation of the percentileM5,95, for the safety report for example, it will be necessary to perform at least 300 simulations with the CATHARE2 code. In this case, both methods (Wilks and Bootstrap) would give equivalent results.

The Effect of Water or Wax-based Binders on the Chemical and Morphological Characteristics of the Margin Ceramic-Framework Interface.

PubMed

Güler, Umut; de Queiroz, José Renato Cavalcanti; de Oliveira, Luiz Fernando Cappa; Canay, Senay; Ozcan, Mutlu

2015-09-01

This study evaluated the effect of binder choice in mixing ceramic powder on the chemical and morphological features between the margin ceramic-framework interfaces. Titanium and zirconia frameworks (15 x 5 x 0.5 mm3) were veneered with margin ceramics prepared with two different binders, namely a) water/conventional or b) wax-based. For each zirconia framework material, four different margin ceramics were used: a- Creation Zi (Creation Willi Geller International); b- GC Initial Zr (GC America); Triceram (Dentaurum); and d- IPS emax (voclar Vivadent). For the titanium framework, three different margin ceramics were used: a- Creation Ti (Creation Willi Geller International); b- Triceram (Dentaurum); and c- VITA Titaniumkeramik (Vita Zahnfabrik). The chemical composition of the framework-margin ceramic interface was analyzed using Energy Dispersive X-ray Spectroscopy (EDS) and porosity level was quantified within the margin ceramic using an image program (ImageJ) from four random areas (100 x 100 pixels) on each SEM image. EDS analysis showed the presence of Carbon at the margin ceramic-framework interface in the groups where wax-based binder technique was used with the concentration being the highest for the IPS emax ZirCAD group. While IPS system (IPS ZirCAD and IPS Emax) presented higher porosity concentration using wax binder, in the other groups wax-based binder reduced the porosity of margin ceramic, except for Titanium - Triceram combination.

Background parenchymal enhancement in preoperative breast MRI.

PubMed

Kohara, Satoko; Ishigaki, Satoko; Satake, Hiroko; Kawamura, Akiko; Kawai, Hisashi; Kikumori, Toyone; Naganawa, Shinji

2015-08-01

We aimed to assess the influence of background parenchymal enhancement (BPE) on surgical planning performed using preoperative MRI for breast cancer evaluation. Between January 2009 and December 2010, 91 newly diagnosed breast cancer patients (mean age, 55.5 years; range, 30-88 years) who underwent preoperative bilateral breast MRI followed by planned breast conservation therapy were retrospectively enrolled. MRI was performed to assess the tumor extent in addition to mammography and breast ultrasonography. BPE in the contralateral normal breast MRI at the early dynamic phase was visually classified as follows: minimal (n=49), mild (n=27), moderate (n=7), and marked (n=8). The correlations between the BPE grade and age, menopausal status, index tumor size, changes in surgical management based on MRI results, positive predictive value (PPV) of MRI, and surgical margins were assessed. Patients in the strong BPE groups were significantly younger (p=0.002) and generally premenopausal (p<0.001). Surgical treatment was not changed in 67 cases (73.6%), while extended excision and mastectomy were performed in 12 cases (13.2%), each based on additional lesions on MRI. Six of 79 (7.6%) patients who underwent breast conservation therapy had tumor-positive resection margins. In cases where surgical management was changed, the PPV for MRI-detected foci was high in the minimal (91.7%) and mild groups (66.7%), and 0% in the moderate and marked groups (p=0.002). Strong BPE causes false-positive MRI findings and may lead to overly extensive surgery, whereas MRI may be beneficial in select patients with weak BPE.

12 CFR 502.15 - How does OTS determine my size component?

Code of Federal Regulations, 2010 CFR

2010-01-01

... size component is: This amount—Base assessment amount Column C Plus—Marginal rate Column D Of assets... across in that same row, find your base assessment amount in Column C, your marginal rate in Column D... floor. Multiply this number by your Column D marginal rate. Add this number to your Column C base...

Near-infrared autofluorescence spectroscopy of in vivo soft tissue sarcomas

PubMed Central

Nguyen, John Quan; Gowani, Zain; O'Connor, Maggie; Pence, Isaac; Nguyen, The-Quyen; Holt, Ginger; Mahadevan-Jansen, Anita

2016-01-01

Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated via surgical resection. Inadequate resection can lead to local recurrence and decreased survival rates. In this study, we investigate the hypothesis that near-infrared (NIR) autofluorescence can be utilized for tumor margin analysis by differentiating STS from the surrounding normal tissue. Intraoperative in vivo measurements were acquired from 30 patients undergoing STS resection and were characterized to differentiate between normal tissue and STS. Overall, normal muscle and fat were observed to have the highest and lowest autofluorescence intensities, respectively, with STS falling in between. With the exclusion of well-differentiated liposarcomas, the algorithm's accuracy for classifying muscle, fat, and STS was 93%, 92%, and 88%, respectively. These findings suggest that NIR autofluorescence spectroscopy has potential as a rapid and nondestructive surgical guidance tool that can inform surgeons of suspicious margins in need of immediate re-excision. PMID:26625035

Deformations of superconformal theories

DOE PAGES

Córdova, Clay; Dumitrescu, Thomas T.; Intriligator, Kenneth

2016-11-22

Here, we classify possible supersymmetry-preserving relevant, marginal, and irrelevant deformations of unitary superconformal theories in d ≥ 3 dimensions. Our method only relies on symmetries and unitarity. Hence, the results are model independent and do not require a Lagrangian description. Two unifying themes emerge: first, many theories admit deformations that reside in multiplets together with conserved currents. Such deformations can lead to modifications of the supersymmetry algebra by central and noncentral charges. Second, many theories with a sufficient amount of supersymmetry do not admit relevant or marginal deformations, and some admit neither. The classification is complicated by the fact thatmore » short superconformal multiplets display a rich variety of sporadic phenomena, including supersymmetric deformations that reside in the middle of a multiplet. We illustrate our results with examples in diverse dimensions. In particular, we explain how the classification of irrelevant supersymmetric deformations can be used to derive known and new constraints on moduli-space effective actions.« less

Sparse Substring Pattern Set Discovery Using Linear Programming Boosting

NASA Astrophysics Data System (ADS)

Kashihara, Kazuaki; Hatano, Kohei; Bannai, Hideo; Takeda, Masayuki

In this paper, we consider finding a small set of substring patterns which classifies the given documents well. We formulate the problem as 1 norm soft margin optimization problem where each dimension corresponds to a substring pattern. Then we solve this problem by using LPBoost and an optimal substring discovery algorithm. Since the problem is a linear program, the resulting solution is likely to be sparse, which is useful for feature selection. We evaluate the proposed method for real data such as movie reviews.

Burial of Undersea Pipes and Cables State-of-the Art Assessment,

DTIC Science & Technology

1976-01-01

rippable rocks." The biggest rippers can penetrate to a depth of over 6 ft, but working to this kind of depth in a single...34-’ " ....... ......................... •". . "-.’...........".-’-.. ... .--. ’’""’"..- % . . . ... ,.. types of rippers and tractors classify various rock types as " rippable ," "marginal," or "non- rippable " depending on seismic...highest velocity for consistently rippable conditions, and in some types of rock the same limit would occur at less

[Revenue and losses with vertebral augmentation under the G-DRG system 2012 - a comparison of supply costs in the context of vertebroplasty and kyphoplasty].

PubMed

Krüger, A; Wollny, M; Oberkircher, L; Bornemann, R; Pflugmacher, R

2012-10-01

If clearly indicated and implemented, augmentations of vertebral bodies with cement are standardized, safe and low-risk procedures. However, the multiplicity of providers and systems are today more varied than ever. At present, the systems differ starkly from one another not only in specifications, possible applications and extensions of indications, but they are also extremely variable in price. Publications have shown that in times of medical-economic change, vertebral augmentations make sense not only medically, but also in terms of economics and the national economy. Our analysis targets the question of how insurance costs with vertebroplasty and kyphoplasty affect profit margins per G-DRG (German Diagnosis Related Groups) in consideration of the different system approaches of the providers. After reviewing the literature, extremely varied, minimally invasive augmentation methods and techniques for treating vertebral body fractures were identified and classified. These were grouped based also [sic: on] OPS and possibly further subdivisions. Material costs were gathered based on average price quotations of different providers and techniques and aligned with those from the literature. The inpatient costs per day were estimated as a lump sum according to published information, since our analysis was interested in less detailed process costs as these are difficult to transfer to other clinics due to parameters being unique to each facility. The G-DRGs concerned were likewise determined according to the case-based lump sum catalogue from 2012. Based on this, the material costs as well as the daily costs per day of inpatient stay according to the average length of stay per G-DRG were subtracted. Vertebral augmentation methods are classified into vertebroplasty and kyphoplasty according to OPS. In addition, according to current literature, a further subdivision of kyphoplasty into substance-conserving or direct cement injection techniques and substance-destroying or indirect cement injection techniques took place. The procedures involve material costs between 10-40 % of G-DRG revenue. The profit margin of vertebral augmentation ranges from approx. 4100 € to approx. 11 400 €. The calculative costs of the inpatient care per day amount to 488.86 €. Based on the average lengths of stay per G-DRG (7.8-12.6 days) for 2012 determined by the InEK (Institut für das Entgeltsystem im Krankenhaus [Institute for the Hospital Remuneration System]), the financial costs of inpatient care were calculated between 3813.11 € and 6159.65 €. A shortfall of -197.53 € for the treatment of a vertebral body resulted for the vertebroplasty. This shortfall increases with the treatment of three vertebral bodies and a PCCL = 4 to -466.30 €. The indirect cement injection techniques accounted for a positive profit margin of 196.03 € for the treatment of a vertebra. Due to high material costs, however, this dips into the negative in the amount of -1227.70 € for two vertebrae and increases to -2522.50 € for the treatment of three vertebral bodies. In contrast, the multilevel care in substance-preserving kyphoplasty techniques show a positive profit margin of 72.30 € for the treatment of two vertebrae and 577.50 € for the treatment of three vertebrae. Against the background of the increasing economization of the health care system, it should be emphasized once more that the decision for a therapy or a system based on medical reasons should only be made by the treating physician. The vertebroplasty could not be performed at a profit in our analysis, despite comparatively low material costs. A shortfall between -197.53 € and -466.30 € was determined. The comparatively higher material costs of the kyphoplasty make comparisons important. The results of our investigation also show that supposedly inexpensive purchases of materials are not automatically a favorable alternative. In addition, the kyphoplasty techniques currently available on the market are not necessarily comparable. According to our investigation, profits of between 196.03 € and 577.50 € are to be realized in the selection of vertebral augmentation systems based on purely economic considerations. The results of our analysis show that the pure comparison of figures of the average material costs of a G-DRG and the material price distort the picture. A calculation of the profit margin on the basis of costs of care per vertebral body is more definitive. Georg Thieme Verlag KG Stuttgart · New York.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

NASA Astrophysics Data System (ADS)

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

PubMed Central

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods. PMID:28120883

Monitoring of surface-fatigue crack propagation in a welded steel angle structure using guided waves and principal component analysis

NASA Astrophysics Data System (ADS)

Lu, Mingyu; Qu, Yongwei; Lu, Ye; Ye, Lin; Zhou, Limin; Su, Zhongqing

2012-04-01

An experimental study is reported in this paper demonstrating monitoring of surface-fatigue crack propagation in a welded steel angle structure using Lamb waves generated by an active piezoceramic transducer (PZT) network which was freely surface-mounted for each PZT transducer to serve as either actuator or sensor. The fatigue crack was initiated and propagated in welding zone of a steel angle structure by three-point bending fatigue tests. Instead of directly comparing changes between a series of specific signal segments such as S0 and A0 wave modes scattered from fatigue crack tips, a variety of signal statistical parameters representing five different structural status obtained from marginal spectrum in Hilbert-huang transform (HHT), indicating energy progressive distribution along time period in the frequency domain including all wave modes of one wave signal were employed to classify and distinguish different structural conditions due to fatigue crack initiation and propagation with the combination of using principal component analysis (PCA). Results show that PCA based on marginal spectrum is effective and sensitive for monitoring the growth of fatigue crack although the received signals are extremely complicated due to wave scattered from weld, multi-boundaries, notch and fatigue crack. More importantly, this method indicates good potential for identification of integrity status of complicated structures which cause uncertain wave patterns and ambiguous sensor network arrangement.

Effects of environmental amenities and locational disamenities on home values in the Santa Cruz watershed: a hedonic analysis using census data

USGS Publications Warehouse

Arora, Gaurav; Frisvold, George; Norman, Laura

2014-01-01

For this study, we used the hedonic pricing method to measure the effects of natural amenities on home prices in the U.S-side of the Santa Cruz Watershed. We employed multivariate spatial regression techniques to estimate how difference factors affect median home values in 613 census block groups of the 2000 Census, accounting for spatial autocorrelation, spatial lags, and/or spatial heterogeneity in the data. Diagnostic tests suggest that failure to account for the hedonic model can be classified as (1) physical features of the housing stock, (2) neighborhood characteristics, and (3) environmental attributes. Census data was combined with GIS data for vegetation and land cover, land administration, measures of species richness and open space, and proximity to amenities and disamenities. Census block groups close to the US-Mexico border of airports/air bases were negative. Results suggest that policies to maintain biodiversity and open space provide economic benefits to homeowners, reflected in higher home values. Future research will quantify the marginal effects of regression explanatory variables on home values to assess their economic and policy significant. These marginal effects will be used as input indicators to discern potential economic impacts of various scenarios in the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM). Future research will also expand this effort into the Mexican-portion of the watershed.

Novel layered clustering-based approach for generating ensemble of classifiers.

PubMed

Rahman, Ashfaqur; Verma, Brijesh

2011-05-01

This paper introduces a novel concept for creating an ensemble of classifiers. The concept is based on generating an ensemble of classifiers through clustering of data at multiple layers. The ensemble classifier model generates a set of alternative clustering of a dataset at different layers by randomly initializing the clustering parameters and trains a set of base classifiers on the patterns at different clusters in different layers. A test pattern is classified by first finding the appropriate cluster at each layer and then using the corresponding base classifier. The decisions obtained at different layers are fused into a final verdict using majority voting. As the base classifiers are trained on overlapping patterns at different layers, the proposed approach achieves diversity among the individual classifiers. Identification of difficult-to-classify patterns through clustering as well as achievement of diversity through layering leads to better classification results as evidenced from the experimental results.

Buried Mesozoic rift basins of Moroccan Atlantic continental margin

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

Mohamed, N.; Jabour, H.; El Mostaine, M.

1995-08-01

The Atlantic continental margin is the largest frontier area for oil and gas exploration in Morocco. Most of the activity has been concentrated where Upper Jurassic carbonate rocks have been the drilling objectives, with only one significant but non commercial oil discovery. Recent exploration activities have focused on early Mesozoic Rift basins buried beneath the post-rift sediments of the Middle Atlantic coastal plain. Many of these basins are of interest because they contain fine-grained lacustrine rocks that have sufficient organic richness to be classified as efficient oil prone source rock. Location of inferred rift basins beneath the Atlantic coastal plainmore » were determined by analysis of drilled-hole data in combination with gravity anomaly and aeromagnetic maps. These rift basins are characterized by several half graben filled by synrift sediments of Triassic age probably deposited in lacustrine environment. Coeval rift basins are known to be present in the U.S. Atlantic continental margin. Basin modeling suggested that many of the less deeply bored rift basins beneath the coastal plain are still within the oil window and present the most attractive exploration targets in the area.« less

NRC Continental Margins Workshop

NASA Astrophysics Data System (ADS)

Katsouros, Mary Hope

The Ocean Studies Board of the National Research Council is organizing a workshop, “Continental Margins: Evolution of Passive Continental Margins and Active Marginal Processes,” to stimulate discussion and longterm planning in the scientific community about the evolution of all types of continental margins. We want to coordinate academic, industry, and government agency efforts in this field, and to enhance communication between sea-based and land-based research programs.The continental margins constitute the only available record of the long-term dynamic interaction of oceanic and continental lithosphere. Of great interest are the unique structures and thick sedimentary sequences associated with this interaction. A major focus of the workshop will be to define strategies for exploring and understanding the continental margins in three dimensions and through geologic time. The workshop will be divided into 7 working groups, each concentrating on a major issue in continental margins research. A background document is being prepared summarizing recent research in specific continental margin fields and identifying key scientific and technical issues.

Estimation of marginal abatement costs of CO2 in Chinese provinces under 2020 carbon emission rights allocation: 2005-2020.

PubMed

Duan, Fumei; Wang, Yong; Wang, Ying; Zhao, Han

2018-06-16

The calculation of marginal abatement costs of CO 2 plays a vital role in meeting China's 2020 emission reduction targets by providing reference for determining carbon tax and carbon trading pricing. However, most existing researches only used one method to discuss regional and industrial marginal abatement costs, and almost no studies predicted future marginal abatement costs from the perspective of CO 2 emission efficiency. To make up for the gaps, this paper first estimates marginal abatement costs of CO 2 in three major industries of 30 provinces in China from 2005 to 2015 based on three assumptions. Second, based on the principle of fairness and efficiency, China's 2020 emission reduction targets are decomposed by province. Based on the ZSG-C-DDF model, the marginal abatement costs of CO 2 in all provinces in China in 2020 are estimated and compared with the marginal abatement costs of 2005 to 2015. The results show that (1) from 2005 to 2015, marginal abatement costs of CO 2 in all provinces show a fluctuating upward trend; (2) compared with the marginal abatement costs of primary industry or tertiary industry, most provinces have lower marginal abatement costs for secondary industry; and (3) the average marginal abatement costs of CO 2 for China in 2020 are 2766.882 Yuan/tonne for the 40% carbon intensity reduction target and 3334.836 Yuan/tonne for the 45% target, showing that the higher the emission reduction target, the higher the marginal abatement costs of CO 2 . (4) Overall, the average marginal abatement costs of CO 2 in China by 2020 are higher than those in 2005-2015. The empirical analysis in this paper can provide multiple references for environmental policy makers.

Computerized margin and texture analyses for differentiating bacterial pneumonia and invasive mucinous adenocarcinoma presenting as consolidation.

PubMed

Koo, Hyun Jung; Kim, Mi Young; Koo, Ja Hwan; Sung, Yu Sub; Jung, Jiwon; Kim, Sung-Han; Choi, Chang-Min; Kim, Hwa Jung

2017-01-01

Radiologists have used margin characteristics based on routine visual analysis; however, the attenuation changes at the margin of the lesion on CT images have not been quantitatively assessed. We established a CT-based margin analysis method by comparing a target lesion with normal lung attenuation, drawing a slope to represent the attenuation changes. This approach was applied to patients with invasive mucinous adenocarcinoma (n = 40) or bacterial pneumonia (n = 30). Correlations among multiple regions of interest (ROIs) were obtained using intraclass correlation coefficient (ICC) values. CT visual assessment, margin and texture parameters were compared for differentiating the two disease entities. The attenuation and margin parameters in multiple ROIs showed excellent ICC values. Attenuation slopes obtained at the margins revealed a difference between invasive mucinous adenocarcinoma and pneumonia (P<0.001), and mucinous adenocarcinoma produced a sharply declining attenuation slope. On multivariable logistic regression analysis, pneumonia had an ill-defined margin (odds ratio (OR), 4.84; 95% confidence interval (CI), 1.26-18.52; P = 0.02), ground-glass opacity (OR, 8.55; 95% CI, 2.09-34.95; P = 0.003), and gradually declining attenuation at the margin (OR, 12.63; 95% CI, 2.77-57.51, P = 0.001). CT-based margin analysis method has a potential to act as an imaging parameter for differentiating invasive mucinous adenocarcinoma and bacterial pneumonia.

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity

PubMed Central

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B.; Bringas-Vega, Maria L.; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A.

2018-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented. PMID:29379411

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity.

PubMed

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B; Bringas-Vega, Maria L; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A

2017-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

IODP drilling in the South China Sea in 2017 will address the mechanism of continental breakup

NASA Astrophysics Data System (ADS)

Sun, Z.; Larsen, H. C.; Lin, J.; Pang, X.; McIntosh, K. D.; Stock, J. M.; Jian, Z.; Wang, P.; Li, C.

2016-12-01

Geophysical exploration and scientific drilling along the North Atlantic rifted continental margins suggested that passive continental margins can be classified into two end members: magma-rich and magma-poor. Bearing seaward-dipping reflector sequences (SDRS) and highly mafic underplated high velocity lower crust (HVLC), the magma-rich margin is thought to be related to large igneous provinces (LIP) or mantle plume activity. Magma-poor margins have been drilled offshore Iberia and Newfoundland, where brittle faults cut through the whole crust and reach the upper mantle. Following seawater infiltration, the mantle was serpentinized and exhumed in the continent-ocean transition zone (COT). Later geophysical exploration and modeling suggested that in magma-poor margins lithosphere may break up in different styles, including uniform breakup, lower crust exhumation, or upper mantle exhumed at the COT, etc. The northern continental margin of the South China Sea (SCS) between longitude 114.5º and 116.5º hosts features that might be similar to both of the two end-members defined in the North Atlantic. Wide-angle seismic studies suggest that below the inner margin, crustal underplating of high velocity material is present, while syn-rift as well as post-rift intrusive features are visible and have in places been verified by industry drilling. However, the profound volcanism and associated SDRS formation are entirely lacking, and thus classification as a volcanic rifted margin can be ruled out. Instead, the COT exhibits a profound thinning of the continental crust towards the ocean crust of the SCS, showing some similarity to the Iberia type margin. The crustal thinning is caused by low-angle faults that have stretched the upper continental crust. There are indications of lower crustal flow toward the SCS. Alternatively, these extensional faults may have reached the lithospheric mantle and generated serpentinized material in a similar fashion as seen off Iberia. It will require deep drilling and sampling of characteristic basement units within the COT to distinguish. Four months of drilling by IODP to address this question is scheduled for February to June in 2017. The IODP drilling has the potential to support a third breakup mechanism theorized by modelling in addition to the two types drilled.

Validation of self-reported health literacy questions among diverse English and Spanish-speaking populations.

PubMed

Sarkar, Urmimala; Schillinger, Dean; López, Andrea; Sudore, Rebecca

2011-03-01

Limited health literacy (HL) contributes to poor health outcomes and disparities, and direct measurement is often time-intensive. Self-reported HL questions have not been validated among Spanish-speaking and diverse English-speaking populations. To evaluate three self-reported questions: 1 "How confident are you filling out medical forms?"; 2 "How often do you have problems learning about your medical condition because of difficulty understanding written information?"; and 3 "How often do you have someone help you read hospital materials?" Answers were based on a 5-point Likert scale. This was a validation study nested within a trial of diabetes self-management support in the San Francisco Department of Public Health. English and Spanish-speaking adults with type 2 diabetes receiving primary care. Using the Test of Functional Health Literacy in Adults (s-TOFHLA) in English and Spanish as the reference, we classified HL as inadequate, marginal, or adequate. We calculated the C-index and test characteristics of the three questions and summative scale compared to the s-TOFHLA and assessed variations in performance by language, race/ethnicity, age, and education. Of 296 participants, 48% were Spanish-speaking; 9% were White, non-Hispanic; 47% had inadequate HL and 12% had marginal HL. Overall, 57% reported being confident with forms "somewhat" or less. The "confident with forms" question performed best for detecting inadequate (C-index = 0.82, (0.77-0.87)) and inadequate plus marginal HL (C index = 0.81, (0.76-0.86); p<0.01 for differences from other questions), and performed comparably to the summative scale. The "confident with forms" question and scale also performed best across language, race/ethnicity, educational attainment, and age. A single self-reported HL question about confidence with forms and a summative scale of three questions discriminated between Spanish and English speakers with adequate HL and those with inadequate and/or inadequate plus marginal HL. The "confident with forms" question or the summative scale may be useful for estimating HL in clinical research involving Spanish-speaking and English-speaking, chronically-ill, diverse populations.

A clinical analysis of two indolent lymphoma entities: mantle cell lymphoma and marginal zone lymphoma (including the mucosa-associated lymphoid tissue and monocytoid B-cell subcategories): a Southwest Oncology Group study.

PubMed

Fisher, R I; Dahlberg, S; Nathwani, B N; Banks, P M; Miller, T P; Grogan, T M

1995-02-15

The objectives of this study were (1) to determine the clinical presentation and natural history associated with two newly recognized pathologic entities termed mantle cell lymphoma (MCL) and marginal zone lymphoma (MZL), including the mucosa-associated lymphoid tissue (MALT) and monocytoid B-cell subcategories, and (2) to determine whether these entities differ clinically from the other relatively indolent non-Hodgkin's lymphomas with which they have been previously classified. We reviewed the conventional pathology and clinical course of 376 patients who had no prior therapy; had stage III/IV disease; were classified as Working Formulation categories A, B, C, D, or E; and received cyclophosphamide, doxorubicin, vincristine, prednisone (CHOP) on Southwest Oncology Group (SWOG) studies no. 7204, 7426, or 7713. All slides were reviewed by the three pathologists who reached a consensus diagnosis. Age, sex, performance status, bone marrow and/or gastrointestinal involvement, failure-free survival, and overall survival were compared among all the categories. We found that (1) MCL and MZL each represent approximately 10% of stage III or IV patients previously classified as Working Formulation categories A through E and treated with CHOP on SWOG clinical trials; (2) the failure-free survival and overall survival of patients with MZL is the same as that of patients with Working Formulation categories A through E, but the failure-free survival and overall survival of the monocytoid B-cell patients were higher than that of the MALT lymphoma patients (P = .009 and .007, respectively); and (3) the failure-free survival and overall survival of patients with MCL is significantly worse than that of patients with Working Formulation categories A through E (P = .0002 and .0001, respectively). In conclusion, patients with advanced stage MALT lymphomas may have a more aggressive course than previously recognized. Patients with MCL do not have an indolent lymphoma and are candidates for innovative therapy.

Cysts of the Iris Pigment Epithelium. What Is New and Interesting? The 2016 Jose Rizal International Medal Lecture.

PubMed

Shields, Jerry A; Shields, Carol L

2017-01-01

Cysts of the iris pigment epithelium (IPE) can involve the pupillary margin, midzone, or peripheral location or can be free-floating in the aqueous or vitreous or lodged in the anterior chamber angle. Avariant of IPE cyst, known as iris flocculi, can be a marker for systemic thoracic aneurysm. Review of IPE cysts and description of new observations of the lesions. Review of IPE cysts. Lesions in 672 eyes were classified as of the pupillary margin (n = 49; 7%), midzone (n = 188; 28%), peripheral (n = 424; 63%), or dislodged/free-floating (n = 11; 2%). Cysts of the IPE occurred most often in young adults (21-40 years) (n = 229; 34%) manifesting with peripheral or midzonal cysts. The characteristic clinical features of pupillary margin cyst were teardrop configuration at the pupillary margin, midzonal cyst with fusiform brown appearance, peripheral cyst as iris stromal bulge, dislodged cyst as a brown lesion in the angle, and free-floating cyst with round mass moving by gravitational forces in the aqueous or vitreous. Ultrasound biomicroscopy and anterior segment optical coherence tomography demonstrated the lesions. Surgical intervention for drainage/resection was rarely necessary (<1%). Some (<1%) cysts were associated with iris nevus, iris melanoma, or ciliary body melanoma. Pupillary margin cysts (flocculi) can be found with dissecting thoracic aortic aneurysm, related to genetic mutation in smooth muscle of the iris and aorta. Cysts of the IPE most often affect the peripheral region (iridociliary) and rarely require intervention. These cysts can be associated with underlying iris or ciliary body nevus or melanoma. Patients with iris flocculi should be monitored for dissecting thoracic aneurysm. Copyright© 2017 Asia-Pacific Academy of Ophthalmology.

4D-Listmode-PET-CT and 4D-CT for optimizing PTV margins in gastric lymphoma : Determination of intra- and interfractional gastric motion.

PubMed

Reinartz, Gabriele; Haverkamp, Uwe; Wullenkord, Ramona; Lehrich, Philipp; Kriz, Jan; Büther, Florian; Schäfers, Klaus; Schäfers, Michael; Eich, Hans Theodor

2016-05-01

New imaging protocols for radiotherapy in localized gastric lymphoma were evaluated to optimize planning target volume (PTV) margin and determine intra-/interfractional variation of the stomach. Imaging of 6 patients was explored prospectively. Intensity-modulated radiotherapy (IMRT) planning was based on 4D/3D imaging of computed tomography (CT) and positron-emission tomography (PET)-CT. Static and motion gross tumor volume (sGTV and mGTV, respectively) were distinguished by defining GTV (empty stomach), clinical target volume (CTV = GTV + 5 mm margin), PTV (GTV + 10/15/20/25 mm margins)  plus paraaortic lymph nodes and proximal duodenum. Overlap of 4D-Listmode-PET-based mCTV with 3D-CT-based PTV (increasing margins) and V95/D95 of mCTV were evaluated. Gastric shifts were determined using online cone-beam CT. Dose contribution to organs at risk was assessed. The 4D data demonstrate considerable intra-/interfractional variation of the stomach, especially along the vertical axis. Conventional 3D-CT planning utilizing advancing PTV margins of 10/15/20/25 mm resulted in rising dose coverage of mCTV (4D-Listmode-PET-Summation-CT) and rising D95 and V95 of mCTV. A PTV margin of 15 mm was adequate in 3 of 6 patients, a PTV margin of 20 mm was adequate in 4 of 6 patients, and a PTV margin of 25 mm was adequate in 5 of 6 patients. IMRT planning based on 4D-PET-CT/4D-CT together with online cone-beam CT is advisable to individualize the PTV margin and optimize target coverage in gastric lymphoma.

Biofuel crops with CAM photosynthesis: Economic potential on moisture-limited lands

NASA Astrophysics Data System (ADS)

Bartlett, Mark; Hartzell, Samantha; Porporato, Amilcare

2017-04-01

As the demand for food and renewable energy increases, the intelligent utilization of marginal lands is becoming increasingly critical. In marginal lands classified by limited rainfall or soil salinity, the cultivation of traditional C3 and C4 photosynthesis crops often is economically infeasible. However, in such lands, nontraditional crops with crassulacean acid metabolism (CAM) photosynthesis show great economic potential for cultivation. CAM crops including Opuntia (prickly pear) and Ananas (pineapple) achieve a water use efficiency which is three fold higher than C4 crops such as corn and 6-fold higher than C3 crops such as wheat, leading to a comparable annual productivity with only 20% of the water demand. This feature, combined with a shallow rooting depth and a high water storage capacity, allows CAM plants to take advantage of small, infrequent rainfall amounts in shallow, quickly draining soils. Furthermore, CAM plants typically have properties (e.g., high content of non-structural carbohydrates) that are favorable for biofuel production. Here, for marginal lands characterized by low soil moisture availability and/or high salinity, we assess the potential productivity and economic benefits of CAM plants. CAM productivity is estimated using a recently developed model which simulates CAM photosynthesis under a range of soil and climate conditions. From these results, we compare the energy and water resource inputs required by CAM plants to those required by more traditional C3 and C4 crops (corn, wheat, sorghum), and we evaluate the economic potential of CAM crops as sources of food, fodder, or biofuel in marginal soils. As precipitation events become more intense and infrequent, we show that even though marginal land area may increase, CAM crop cultivation shows great promise for maintaining high productivity with minimal water inputs. Our analysis indicates that on marginal lands, widespread cultivation of CAM crops as biofuel feedstock may help alleviate existing tensions between food and fuel production.

Comparative evaluation of different periods of enamel microabrasion on the microleakage of class V resin-modified glass ionomer and compomer restorations: An In vitro study.

PubMed

Bansal, Disha; Mahajan, Mrinalini

2017-01-01

The design of the class V cavity presents a clinical challenge in the field of adhesive dentistry as the margin placement is partially in enamel and partly in dentin, and the trouble associated with this design is the microleakage at the dentinal margin. When these restorations undergo microabrasion due to cosmetic reasons, this trouble aggravates to the significant levels. The aim of this study was the measurement of microleakage of class V glass ionomer restorations over two different periods of enamel microabrasion. This in vitro experimental study was conducted on 120 class V cavities which had been prepared on the buccal and lingual surfaces of 60 sound human premolars. One-half of the cavities were restored with the resin-modified glass ionomer cement (GIC) (60 cavities) and another half with the compomer (60 cavities). Finishing and polishing were performed. Then, the teeth were classified into six groups (n = 20). Microabrasion treatment was performed with Opaluster (Ultradent Product Inc., South Jordan, UT, USA) for 0 (control no treatment), 60 and 120 s. Then, teeth were thermocycled between 5°C and 55°C, immersed in rhodamine B solution (24 h), and sectioned longitudinally in buccolingual direction. Dye penetration was examined with stereomicroscope (×10). Microleakage scores were statistically analyzed. The mean occlusal margin scores and gingival margin scores were compared between all the groups using the Kruskal-Wallis test, Mann-Whitney U-test, Wilcoxon signed-rank test, and post hoc comparison. There was a significant difference between Group 1a, Group 2a, Group 1b, Group 2b, Group 1c, and Group 2c. Statistical analysis used in this study was Kruskal-Wallis test, Mann-Whitney U-test, Wilcoxon signed-rank test, and post hoc comparison. The least microleakage scores were observed in occlusal margins of control groups (without microabrasion). Moreover, in both restorations, the microleakage scores in occlusal margins were higher than gingival margins, and compoglass had less microleakage in occlusal and occlusal plus axial walls of class V cavities compared with resin-modified GIC. Whereas, the light-cured glass ionomer had less microleakage in the gingival and gingival plus axial walls of class V cavities when compared with compoglass. The least microleakage scores were observed in occlusal margins of control groups (without microabrasion). Moreover, in both restorations, the microleakage scores in occlusal margins were higher than gingival margins.

Histopathological Validation of the Surface-Intermediate-Base Margin Score for Standardized Reporting of Resection Technique during Nephron Sparing Surgery.

PubMed

Minervini, Andrea; Campi, Riccardo; Kutikov, Alexander; Montagnani, Ilaria; Sessa, Francesco; Serni, Sergio; Raspollini, Maria Rosaria; Carini, Marco

2015-10-01

The surface-intermediate-base margin score is a novel standardized reporting system of resection techniques during nephron sparing surgery. We validated the surgeon assessed surface-intermediate-base score with microscopic histopathological assessment of partial nephrectomy specimens. Between June and August 2014 data were prospectively collected from 40 consecutive patients undergoing nephron sparing surgery. The surface-intermediate-base score was assigned to all cases. The score specific areas were color coded with tissue margin ink and sectioned for histological evaluation of healthy renal margin thickness. Maximum, minimum and mean thickness of healthy renal margin for each score specific area grade (surface [S] = 0, S = 1 ; intermediate [I] or base [B] = 0, I or B = 1, I or B = 2) was reported. The Mann-Whitney U and Kruskal-Wallis tests were used to compare the thickness of healthy renal margin in S = 0 vs 1 and I or B = 0 vs 1 vs 2 grades, respectively. Maximum, minimum and mean thickness of healthy renal margin was significantly different among score specific area grades S = 0 vs 1, and I or B = 0 vs 1, 0 vs 2 and 1 vs 2 (p <0.001). The main limitations of the study are the low number of the I or B = 1 and I or B = 2 samples and the assumption that each microscopic slide reflects the entire score specific area for histological analysis. The surface-intermediate-base scoring method can be readily harnessed in real-world clinical practice and accurately mirrors histopathological analysis for quantification and reporting of healthy renal margin thickness removed during tumor excision. Copyright © 2015 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Shift in disparities in hepatitis C treatment from interferon to DAA era: A population-based cohort study.

PubMed

Janjua, N Z; Islam, N; Wong, J; Yoshida, E M; Ramji, A; Samji, H; Butt, Z A; Chong, M; Cook, D; Alvarez, M; Darvishian, M; Tyndall, M; Krajden, M

2017-08-01

We evaluated the shift in the characteristics of people who received interferon-based hepatitis C virus (HCV) treatments and those who received recently introduced direct-acting antivirals (DAAs) in British Columbia (BC), Canada. The BC Hepatitis Testers Cohort includes 1.5 million individuals tested for HCV or HIV, or reported cases of hepatitis B and active tuberculosis in BC from 1990 to 2013 linked to medical visits, hospitalization, cancer, prescription drugs and mortality data. This analysis included all patients who filled at least one prescription for HCV treatment until 31 July 2015. HCV treatments were classified as older interferon-based treatments including pegylated interferon/ribavirin (PegIFN/RBV) with/without boceprevir or telaprevir, DAAs with RBV or PegIFN/RBV, and newer interferon-free DAAs. Of 11 886 people treated for HCV between 2000 and 2015, 1164 (9.8%) received interferon-free DAAs (ledipasvir/sofosbuvir: n=1075; 92.4%), while 452 (3.8%) received a combination of DAAs and RBV or PegIFN/RBV. Compared to those receiving interferon-based treatment, people with HIV co-infection (adjusted odds ratio [aOR]: 2.96, 95% CI: 2.31-3.81), cirrhosis (aOR: 1.77, 95% CI: 1.45-2.15), decompensated cirrhosis (aOR: 1.72, 95% CI: 1.31-2.28), diabetes (aOR: 1.30, 95% CI: 1.10-1.54), a history of injection drug use (aOR: 1.34, 95% CI: 1.09-1.65) and opioid substitution therapy (aOR: 1.30, 95% CI: 1.01-1.67) were more likely to receive interferon-free DAAs. Socio-economically marginalized individuals were significantly less likely (most deprived vs most privileged: aOR: 0.71, 95% CI: 0.58-0.87) to receive DAAs. In conclusion, there is a shift in prescription of new HCV treatments to previously excluded groups (eg HIV-co-infected), although gaps remain for the socio-economically marginalized populations. © 2017 John Wiley & Sons Ltd.

Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

PubMed

Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

2016-05-15

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

Fusion and Gaussian mixture based classifiers for SONAR data

NASA Astrophysics Data System (ADS)

Kotari, Vikas; Chang, KC

2011-06-01

Underwater mines are inexpensive and highly effective weapons. They are difficult to detect and classify. Hence detection and classification of underwater mines is essential for the safety of naval vessels. This necessitates a formulation of highly efficient classifiers and detection techniques. Current techniques primarily focus on signals from one source. Data fusion is known to increase the accuracy of detection and classification. In this paper, we formulated a fusion-based classifier and a Gaussian mixture model (GMM) based classifier for classification of underwater mines. The emphasis has been on sound navigation and ranging (SONAR) signals due to their extensive use in current naval operations. The classifiers have been tested on real SONAR data obtained from University of California Irvine (UCI) repository. The performance of both GMM based classifier and fusion based classifier clearly demonstrate their superior classification accuracy over conventional single source cases and validate our approach.

Discovering Fine-grained Sentiment in Suicide Notes

PubMed Central

Wang, Wenbo; Chen, Lu; Tan, Ming; Wang, Shaojun; Sheth, Amit P.

2012-01-01

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system gains a better trade-off between precision and recall, and yields the highest micro-averaged F-measure (0.5038), which is better than the mean (0.4875) and median (0.5027) micro-average F-measures among all participating teams. PMID:22879770

Impact of organ shape variations on margin concepts for cervix cancer ART.

PubMed

Seppenwoolde, Yvette; Stock, Markus; Buschmann, Martin; Georg, Dietmar; Bauer-Novotny, Kwei-Yuang; Pötter, Richard; Georg, Petra

2016-09-01

Target and organ movement motivate adaptive radiotherapy for cervix cancer patients. We investigated the dosimetric impact of margin concepts with different levels of complexity on both organ at risk (OAR) sparing and PTV coverage. Weekly CT and daily CBCT scans were delineated for 10 patients. The dosimetric impact of organ shape variations were evaluated for four (isotropic) margin concepts: two static PTVs (PTV 6mm and PTV 15mm ), a PTV based on ITV of the planning CT and CBCTs of the first treatment week (PTV ART ITV ) and an adaptive PTV based on a library approach (PTV ART Library ). Using static concepts, OAR doses increased with large margins, while smaller margins compromised target coverage. ART PTVs resulted in comparable target coverage and better sparing of bladder (V40Gy: 15% and 7% less), rectum (V40Gy: 18 and 6cc less) and bowel (V40Gy: 106 and 15cc less) compared to PTV 15mm . Target coverage evaluation showed that for elective fields a static 5mm margin sufficed. PTV ART Library achieved the best dosimetric results. However when weighing clinical benefit against workload, ITV margins based on repetitive movement evaluation during the first week also provide improvements over static margin concepts. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Comparative assessment of marginal accuracy of grade II titanium and Ni–Cr alloy before and after ceramic firing: An in vitro study

PubMed Central

Patil, Abhijit; Singh, Kishan; Sahoo, Sukant; Suvarna, Suraj; Kumar, Prince; Singh, Anupam

2013-01-01

Objective: The aims of the study are to assess the marginal accuracy of base metal and titanium alloy casting and to evaluate the effect of repeated ceramic firing on the marginal accuracy of base metal and titanium alloy castings. Materials and Methods: Twenty metal copings were fabricated with each casting material. Specimens were divided into 4 groups of 10 each representing base metal alloys castings without (Group A) and with metal shoulder margin (Group B), titanium castings without (Group C) and with metal shoulder margin (Group D). The measurement of fit of the metal copings was carried out before the ceramic firing at four different points and the same was followed after porcelain build-up. Results: Significant difference was found when Ni–Cr alloy samples were compared with Grade II titanium samples both before and after ceramic firings. The titanium castings with metal shoulder margin showed highest microgap among all the materials tested. Conclusions: Based on the results that were found and within the limitations of the study design, it can be concluded that there is marginal discrepancy in the copings made from Ni–Cr and Grade II titanium. This marginal discrepancy increased after ceramic firing cycles for both Ni–Cr and Grade II titanium. The comparative statistical analysis for copings with metal-collar showed maximum discrepancy for Group D. The comparative statistical analysis for copings without metal-collar showed maximum discrepancy for Group C. PMID:24926205

Diffuse reflectance spectroscopy as a tool for real-time tissue assessment during colorectal cancer surgery

NASA Astrophysics Data System (ADS)

Baltussen, Elisabeth J. M.; Snaebjornsson, Petur; de Koning, Susan G. Brouwer; Sterenborg, Henricus J. C. M.; Aalbers, Arend G. J.; Kok, Niels; Beets, Geerard L.; Hendriks, Benno H. W.; Kuhlmann, Koert F. D.; Ruers, Theo J. M.

2017-10-01

Colorectal surgery is the standard treatment for patients with colorectal cancer. To overcome two of the main challenges, the circumferential resection margin and postoperative complications, real-time tissue assessment could be of great benefit during surgery. In this ex vivo study, diffuse reflectance spectroscopy (DRS) was used to differentiate tumor tissue from healthy surrounding tissues in patients with colorectal neoplasia. DRS spectra were obtained from tumor tissue, healthy colon, or rectal wall and fat tissue, for every patient. Data were randomly divided into training (80%) and test (20%) sets. After spectral band selection, the spectra were classified using a quadratic classifier and a linear support vector machine. Of the 38 included patients, 36 had colorectal cancer and 2 had an adenoma. When the classifiers were applied to the test set, colorectal cancer could be discriminated from healthy tissue with an overall accuracy of 0.95 (±0.03). This study demonstrates the possibility to separate colorectal cancer from healthy surrounding tissue by applying DRS. High classification accuracies were obtained both in homogeneous and inhomogeneous tissues. This is a fundamental step toward the development of a tool for real-time in vivo tissue assessment during colorectal surgery.

Margins Associated with Loss of Assured Safety for Systems with Multiple Time-Dependent Failure Modes.

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

Helton, Jon C.; Brooks, Dusty Marie; Sallaberry, Cedric Jean-Marie.

Representations for margins associated with loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems involving multiple time-dependent failure modes are developed. The following topics are described: (i) defining properties for WLs and SLs, (ii) background on cumulative distribution functions (CDFs) for link failure time, link property value at link failure, and time at which LOAS occurs, (iii) CDFs for failure time margins defined by (time at which SL system fails) – (time at which WL system fails), (iv) CDFs for SL system property values at LOAS, (v) CDFs for WL/SL property value margins defined by (property valuemore » at which SL system fails) – (property value at which WL system fails), and (vi) CDFs for SL property value margins defined by (property value of failing SL at time of SL system failure) – (property value of this SL at time of WL system failure). Included in this presentation is a demonstration of a verification strategy based on defining and approximating the indicated margin results with (i) procedures based on formal integral representations and associated quadrature approximations and (ii) procedures based on algorithms for sampling-based approximations.« less

Quantitative calculation and numerical modeling of the conjugate margins of the South China Sea

NASA Astrophysics Data System (ADS)

Dong, D.; Pérez-Gussinyé, M.; Wang, W.; Bai, Y.

2017-12-01

South China margin rifted on the tectonic setting of the early active continental margin since Cenozoic. The present South China Sea (SCS) opened at 32 Ma and showed propagation from east to west, with different crustal and sedimentary structures at the conjugate continental margins. Based on the latest high-quality multi-channel seismic data, bathymetric data, and other obtained seismic profiles, the asymmetric characteristics between the conjugate margins of the SCS are revealed. Spatial variation of morphology, basement structure and marginal faults are discovered among the SCS margin profiles. We calculate the lithospheric stretching factors and analyze the anomalous post-rift subsidence from two typical seismic profiles in the conjugate margins of the SCS, with integrated method of 2D forward and inversion based on flexural-cantilever model. We propose a differential extension model to explain the spatial differences in the SCS margins and emphasize the role of detachment fault in evolutionary process. Numerical modeling has a great advantage in studying the rifted margin formation mechanism. Dynamic modeling for the formation of asymmetric conjugate margins of the SCS is carried out by solving the thermal-mechanical equation, based on the viscoelastic-plastic model. The results show that the width and symmetry of the margin are controlled by the crustal rheological structure and sedimentation rate. Crust with lower strength is prone to distributed and persistent faulting instead of strain localization, which results in the wider margin. On the contrary, the stronger crust would generate large faults and lead to strain localization in a small amount of them, easier to form narrow continental margin. Large sediment loading is favorable for the development of large faults, meanwhile, the subsequent thermal effect reduces the crustal viscosity. A sudden transition zone of sedimentation rate is prone to strain localization and accelerates the crust rift, which may affect the future break-up. The numerical modeling with full dynamics in SCS needs a further investigation. Acknowledge: This study was supported by the National Natural Science Foundation of China (No. 41476042, 41506055 )

Updated evidence-based clinical practice guidelines for the diagnosis and management of melanoma: definitive excision margins for primary cutaneous melanoma.

PubMed

Sladden, Michael J; Nieweg, Omgo E; Howle, Julie; Coventry, Brendon J; Thompson, John F

2018-02-19

Definitive management of primary cutaneous melanoma consists of surgical excision of the melanoma with the aim of curing the patient. The melanoma is widely excised together with a safety margin of surrounding skin and subcutaneous tissue, after the diagnosis and Breslow thickness have been established by histological assessment of the initial excision biopsy specimen. Sentinel lymph node biopsy should be discussed for melanomas ≥ 1 mm thickness (≥ 0.8 mm if other high risk features) in which case lymphoscintigraphy must be performed before wider excision of the primary melanoma site. The 2008 evidence-based clinical practice guidelines for the management of melanoma (http://www.cancer.org.au/content/pdf/HealthProfessionals/ClinicalGuidelines/ClinicalPracticeGuidelines-ManagementofMelanoma.pdf) are currently being revised and updated in a staged process by a multidisciplinary working party established by Cancer Council Australia. The guidelines for definitive excision margins for primary melanomas have been revised as part of this process. Main recommendations: The recommendations for definitive wide local excision of primary cutaneous melanoma are: melanoma in situ: 5-10 mm margins invasive melanoma (pT1) ≤ 1.0 mm thick: 1 cm margins invasive melanoma (pT2) 1.01-2.00 mm thick: 1-2 cm margins invasive melanoma (pT3) 2.01-4.00 mm thick: 1-2 cm margins invasive melanoma (pT4) > 4.0 mm thick: 2 cm margins Changes in management as a result of the guideline: Based on currently available evidence, excision margins for invasive melanoma have been left unchanged compared with the 2008 guidelines. However, melanoma in situ should be excised with 5-10 mm margins, with the aim of achieving complete histological clearance. Minimum clearances from all margins should be assessed and stated. Consideration should be given to further excision if necessary; positive or close histological margins are unacceptable.

Centre-based restricted nearest feature plane with angle classifier for face recognition

NASA Astrophysics Data System (ADS)

Tang, Linlin; Lu, Huifen; Zhao, Liang; Li, Zuohua

2017-10-01

An improved classifier based on the nearest feature plane (NFP), called the centre-based restricted nearest feature plane with the angle (RNFPA) classifier, is proposed for the face recognition problems here. The famous NFP uses the geometrical information of samples to increase the number of training samples, but it increases the computation complexity and it also has an inaccuracy problem coursed by the extended feature plane. To solve the above problems, RNFPA exploits a centre-based feature plane and utilizes a threshold of angle to restrict extended feature space. By choosing the appropriate angle threshold, RNFPA can improve the performance and decrease computation complexity. Experiments in the AT&T face database, AR face database and FERET face database are used to evaluate the proposed classifier. Compared with the original NFP classifier, the nearest feature line (NFL) classifier, the nearest neighbour (NN) classifier and some other improved NFP classifiers, the proposed one achieves competitive performance.

Segmentation of Coronary Angiograms Using Gabor Filters and Boltzmann Univariate Marginal Distribution Algorithm

PubMed Central

Cervantes-Sanchez, Fernando; Hernandez-Aguirre, Arturo; Solorio-Meza, Sergio; Ornelas-Rodriguez, Manuel; Torres-Cisneros, Miguel

2016-01-01

This paper presents a novel method for improving the training step of the single-scale Gabor filters by using the Boltzmann univariate marginal distribution algorithm (BUMDA) in X-ray angiograms. Since the single-scale Gabor filters (SSG) are governed by three parameters, the optimal selection of the SSG parameters is highly desirable in order to maximize the detection performance of coronary arteries while reducing the computational time. To obtain the best set of parameters for the SSG, the area (A z) under the receiver operating characteristic curve is used as fitness function. Moreover, to classify vessel and nonvessel pixels from the Gabor filter response, the interclass variance thresholding method has been adopted. The experimental results using the proposed method obtained the highest detection rate with A z = 0.9502 over a training set of 40 images and A z = 0.9583 with a test set of 40 images. In addition, the experimental results of vessel segmentation provided an accuracy of 0.944 with the test set of angiograms. PMID:27738422

Prospect for the development of salted egg agro industry: an analysis on marketing distribution aspect

NASA Astrophysics Data System (ADS)

Sumekar, W.; Al-Baarri, A. N.; Kurnianto, E.

2018-01-01

Marketing distribution is an important of the strategy in business development in agroindustries. The aim of the research was to introduce marketing (distribution pattern, margin and marketing efficiency) at the salted egg agro industries in Brebes Regency. Survey method had been conducted on 52 salted egg agro industries which had active PIRT certificate. The data collection was conducted by means of interview and observation. Descriptive analysis was used to determine the marketing distribution of salted eggs. Marketing efficiency was obtained by calculating marketing margin and farmer share. The results show that the salted egg agro industries implemented two marketing distribution patterns; direct marketing pattern (consumer→producers) and indirect marketing pattern (producer→retailer→consumer). The number of the salted egg agro industries which apply indirect marketing pattern is 57.69%. The implementation of direct and indirect marketing patterns was classified as efficient according to the farmer’s share values of 87.13% and 78.21%. It can be recommended the direct marketing.

Gingival Retraction Methods for Fabrication of Fixed Partial Denture: Literature Review

PubMed Central

S, Safari; Ma, Vossoghi Sheshkalani; Mi, Vossoghi Sheshkalani; F, Hoseini Ghavam; M, Hamedi

2016-01-01

Fixed dental prosthesis success requires appropriate impression taking of the prepared finish line. This is critical in either tooth supported fixed prosthesis (crown and bridge) or implant supported fixed prosthesis (solid abutment). If the prepared finish line is adjacent to the gingival sulcus, gingival retraction techniques should be used to decrease the marginal discrepancy among the restoration and the prepared abutment. Accurate marginal positioning of the restoration in the prepared finish line of the abutment is required for therapeutic, preventive and aesthetic purposes. In this article, conventional and modern methods of gingival retraction in the fixed tooth supported prosthesis and fixed implant supported prosthesis are expressed. PubMed and Google Scholar databases were searched manually for studies on gingival tissue managements prior to impression making in fixed dental prosthesis since 1975. Conclusions were extracted and summarized. Keywords were impression making, gingival retraction, cordless retraction, and implant. Gingival retraction techniques can be classified as mechanical, chemical or surgical. In this article, different gingival management techniques are discussed. PMID:28959744

Gingival Retraction Methods for Fabrication of Fixed Partial Denture: Literature Review.

PubMed

S, Safari; Ma, Vossoghi Sheshkalani; Mi, Vossoghi Sheshkalani; F, Hoseini Ghavam; M, Hamedi

2016-06-01

Fixed dental prosthesis success requires appropriate impression taking of the prepared finish line. This is critical in either tooth supported fixed prosthesis (crown and bridge) or implant supported fixed prosthesis (solid abutment). If the prepared finish line is adjacent to the gingival sulcus, gingival retraction techniques should be used to decrease the marginal discrepancy among the restoration and the prepared abutment. Accurate marginal positioning of the restoration in the prepared finish line of the abutment is required for therapeutic, preventive and aesthetic purposes. In this article, conventional and modern methods of gingival retraction in the fixed tooth supported prosthesis and fixed implant supported prosthesis are expressed. PubMed and Google Scholar databases were searched manually for studies on gingival tissue managements prior to impression making in fixed dental prosthesis since 1975. Conclusions were extracted and summarized. Keywords were impression making, gingival retraction, cordless retraction, and implant. Gingival retraction techniques can be classified as mechanical, chemical or surgical. In this article, different gingival management techniques are discussed.

Volcanism in the Bransfield Strait, Antarctica

NASA Astrophysics Data System (ADS)

Fisk, M. R.

Back-arc and marginal basins make up a significant portion of the earth's crust and they can represent the transition from continental to oceanic crust. The Bransfield Strait is a young marginal basin of the arc-trench system that lies off the northwestern edge of the Antarctic Peninsula. The strait is about 65 km wide and has a maximum water depth of 2000 m. "Active" volcanoes in the Bransfield Strait include two seamounts, which are south of the eastern end of King George Island, and three island volcanoes — Penguin, Deception, and Bridgeman Islands. Alkaline and calc-alkaline suites occur on these islands, and the seamounts are composed of tholeiites and basaltic andesites. This diversity is similar to that found in some back-arc basins, but the Bransfield Strait basalts as a group cannot be classified as back-arc basin or island-arc basalts. The diverse rock types and the chemical similarity of some of the Bransfield Strait basalts to ophiolite basalts suggests that some ophiolites were generated in back-arc basins.

Development and validation of a new instrument for testing functional health literacy in Japanese adults.

PubMed

Nakagami, Katsuyuki; Yamauchi, Toyoaki; Noguchi, Hiroyuki; Maeda, Tohru; Nakagami, Tomoko

2014-06-01

This study aimed to develop a reliable and valid measure of functional health literacy in a Japanese clinical setting. Test development consisted of three phases: generation of an item pool, consultation with experts to assess content validity, and comparison with external criteria (the Japanese Health Knowledge Test) to assess criterion validity. A trial version of the test was administered to 535 Japanese outpatients. Internal consistency reliability, calculated by Cronbach's alpha, was 0.81, and concurrent validity was moderate. Receiver Operating Characteristics and Item Response Theory were used to classify patients as having adequate, marginal, or inadequate functional health literacy. Both inadequate and marginal functional health literacy were associated with older age, lower income, lower educational attainment, and poor health knowledge. The time required to complete the test was 10-15 min. This test should enable health workers to better identify patients with inadequate health literacy. © 2013 Wiley Publishing Asia Pty Ltd.

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing

PubMed Central

O’Connell, Jerome; Bradter, Ute; Benton, Tim G.

2015-01-01

Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability. PMID:26664131

Aggressive resection at the infiltrative margins of glioblastoma facilitated by intraoperative fluorescein guidance.

PubMed

Neira, Justin A; Ung, Timothy H; Sims, Jennifer S; Malone, Hani R; Chow, Daniel S; Samanamud, Jorge L; Zanazzi, George J; Guo, Xiaotao; Bowden, Stephen G; Zhao, Binsheng; Sheth, Sameer A; McKhann, Guy M; Sisti, Michael B; Canoll, Peter; D'Amico, Randy S; Bruce, Jeffrey N

2017-07-01

OBJECTIVE Extent of resection is an important prognostic factor in patients undergoing surgery for glioblastoma (GBM). Recent evidence suggests that intravenously administered fluorescein sodium associates with tumor tissue, facilitating safe maximal resection of GBM. In this study, the authors evaluate the safety and utility of intraoperative fluorescein guidance for the prediction of histopathological alteration both in the contrast-enhancing (CE) regions, where this relationship has been established, and into the non-CE (NCE), diffusely infiltrated margins. METHODS Thirty-two patients received fluorescein sodium (3 mg/kg) intravenously prior to resection. Fluorescence was intraoperatively visualized using a Zeiss Pentero surgical microscope equipped with a YELLOW 560 filter. Stereotactically localized biopsy specimens were acquired from CE and NCE regions based on preoperative MRI in conjunction with neuronavigation. The fluorescence intensity of these specimens was subjectively classified in real time with subsequent quantitative image analysis, histopathological evaluation of localized biopsy specimens, and radiological volumetric assessment of the extent of resection. RESULTS Bright fluorescence was observed in all GBMs and localized to the CE regions and portions of the NCE margins of the tumors, thus serving as a visual guide during resection. Gross-total resection (GTR) was achieved in 84% of the patients with an average resected volume of 95%, and this rate was higher among patients for whom GTR was the surgical goal (GTR achieved in 93.1% of patients, average resected volume of 99.7%). Intraoperative fluorescein staining correlated with histopathological alteration in both CE and NCE regions, with positive predictive values by subjective fluorescence evaluation greater than 96% in NCE regions. CONCLUSIONS Intraoperative administration of fluorescein provides an easily visualized marker for glioma pathology in both CE and NCE regions of GBM. These findings support the use of fluorescein as a microsurgical adjunct for guiding GBM resection to facilitate safe maximal removal.

Impact of Gas Hydrate and Related Fluid Seepage on Submarine Slope Failures along the Margins of the Ulleung Basin, East Sea (Japan Sea)

NASA Astrophysics Data System (ADS)

Horozal, S.; Bahk, J. J.; Urgeles, R.; Kim, G. Y.; Cukur, D.; Lee, G. H.; Lee, S. H.; Kim, S. P.; Ryu, B. J.; Kim, J. H.

2016-12-01

The Ulleung Basin is a back-arc basin that is known to retain gas hydrate reservoirs in the East (Japan) Sea. The basin contains large volumes of mass-transport deposits (MTDs) due to submarine slope failures along its margins since the Neogene. In this study, seismic indicators of gas hydrate and associated gas and fluid flow were re-compiled on a regional multi-channel seismic reflection data. The gas hydrate occurrence zone (GHOZ) is defined by the BSR (bottom-simulating reflector) distribution. It is more pronounced along the southwestern slope with a minimum depth of 100 mbsf (meters below seafloor) at 295 mbsl (meter below sea level) on the southern, while its thickness is the greatest (250 mbsf) at the southwestern margin. Flow and seepage structures reflected on the seismic data as columnar acoustic-blanking zones varying in width and height (up to hundreds of meters) were classified into: (a) buried seismic chimneys (BSC), (b) chimneys with a mound (SCM), and (c) chimneys with a depression (SCD) on the seafloor. Pockmarks which are not associated with seismic chimneys, reflection anomalies (i.e., enhanced reflections below the BSR and hyperbolic reflections), and SCD are predominant features in the western margin, while the BSR, BSC and SCM are densely distributed in the south-southwestern margin. Present-day gas hydrate stability zone (GHSZ) is calculated using in-situ bottom-water temperature and geothermal gradient measurements (ranging between 0-17.5 oC and 25-200 oC/km, respectively) and multibeam bathymetry data. The GHSZ thickness exceeds 190 m, and the upslope limit of GHSZ ranges between about 180 and 260 mbsl. This depth range is in the proximity of the uppermost depths of landslide scars ( 190 mbsl) which are common features on the slopes along with glide planes, slides/slumps and MTDs. Overall, the base of GHSZ (BGHSZ) and the BSR depths are well-correlated in the basin. However, the BSR depths are typically greater (up to 50 m) than the BGHSZ depths on the slopes suggesting that the GHOZ is not stable. A close correlation exists between the spatial distributions of the landslides, and indicators of gas hydrate and gas/fluid flow and the GHSZ. This may imply that excess pore-pressure caused by dissociation/dissolution of gas hydrates could have played a role on slope failures.

Mass wasting on the Orange Cone of the Atlantic Margin, South Africa

NASA Astrophysics Data System (ADS)

Fielies, Anthony; Murphy, Alain; Johnson, Sean; Thovhogi, Tshifhiwa

2017-04-01

The South African Atlantic Margin represents the rift-drift passive volcanic margin sequence which records the break-up of Gondwana around 155 Ma and the subsequent opening of the South Atlantic Ocean. The Orange Cone - the morphological expression of the sediment buildout and modification of the continental margin along the southwest African continental margin - has undergone extensive mass failure and slope modification over a protracted period. This failure extends all the way to the present-day toe of the Orange Cone. This paper outlines the data and analysis by South Arica in support of its Submission to the Commission on the Limits of the Continental Shelf. South Africa has, in its submission, identified and mapped a considerable number of gravity-driven failure features and deposits as evidence of the Orange Cone being classified as a slope in the sense of Article 76 of UNCLOS. Sediment mass failure, which includes slumping, sliding, mass transport deposits, etc., are known to be continental slope phenomena because they are gravity-driven and thus require a free slope upon which gravitational forces can cause kinetic action. Upper slope failure is ubiquitous on the Orange Cone and has been well documented. The most striking example of slope modification and downslope movement in the upper slope of the Orange Cone/Basin is the paired, gravity-driven deformation system, over 100 km across, with extension high on the submarine slope and contraction toward the toe of slope. The lower slope of the Orange Cone has experienced multiple episodes of failure in the form of glides, slides and debris flows. Failure on the lower slope is highly relevant for the purposes of delineating the foot of the continental slope as the deposition location represents the terminus of the slope processes. These gravity-driven failures are inherently linked to upper slope failure processes although their expression is markedly different. The change in gradients between the upper and lower slope corresponds to a change in the style of mass wasting where the failure regime changes from one of faulting and mass wasting to one of detachment and debris flows. Much of the material that is redeposited at the base of the upper slope is in turn remobilised and transported downslope on the lower slope. Some MTDs are likely disaggregated extensions of more coherent slides that have their origin in the upper slope. The lower slope is characterised by bathymetric scarps and translation of material along distinct glide planes. Seismic interpretation suggests that these relatively coherent units disaggregate further downslope resulting in debrites.

An assessment of PTV margin based on actual accumulated dose for prostate cancer radiotherapy

NASA Astrophysics Data System (ADS)

Wen, Ning; Kumarasiri, Akila; Nurushev, Teamour; Burmeister, Jay; Xing, Lei; Liu, Dezhi; Glide-Hurst, Carri; Kim, Jinkoo; Zhong, Hualiang; Movsas, Benjamin; Chetty, Indrin J.

2013-11-01

The purpose of this work is to present the results of a margin reduction study involving dosimetric and radiobiologic assessment of cumulative dose distributions, computed using an image guided adaptive radiotherapy based framework. Eight prostate cancer patients, treated with 7-9, 6 MV, intensity modulated radiation therapy (IMRT) fields, were included in this study. The workflow consists of cone beam CT (CBCT) based localization, deformable image registration of the CBCT to simulation CT image datasets (SIM-CT), dose reconstruction and dose accumulation on the SIM-CT, and plan evaluation using radiobiological models. For each patient, three IMRT plans were generated with different margins applied to the CTV. The PTV margin for the original plan was 10 mm and 6 mm at the prostate/anterior rectal wall interface (10/6 mm) and was reduced to: (a) 5/3 mm, and (b) 3 mm uniformly. The average percent reductions in predicted tumor control probability (TCP) in the accumulated (actual) plans in comparison to the original plans over eight patients were 0.4%, 0.7% and 11.0% with 10/6 mm, 5/3 mm and 3 mm uniform margin respectively. The mean increase in predicted normal tissue complication probability (NTCP) for grades 2/3 rectal bleeding for the actual plans in comparison to the static plans with margins of 10/6, 5/3 and 3 mm uniformly was 3.5%, 2.8% and 2.4% respectively. For the actual dose distributions, predicted NTCP for late rectal bleeding was reduced by 3.6% on average when the margin was reduced from 10/6 mm to 5/3 mm, and further reduced by 1.0% on average when the margin was reduced to 3 mm. The average reduction in complication free tumor control probability (P+) in the actual plans in comparison to the original plans with margins of 10/6, 5/3 and 3 mm was 3.7%, 2.4% and 13.6% correspondingly. The significant reduction of TCP and P+ in the actual plan with 3 mm margin came from one outlier, where individualizing patient treatment plans through margin adaptation based on biological models, might yield higher quality treatments.

Case base classification on digital mammograms: improving the performance of case base classifier

NASA Astrophysics Data System (ADS)

Raman, Valliappan; Then, H. H.; Sumari, Putra; Venkatesa Mohan, N.

2011-10-01

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. The aim of the research presented here is in twofold. First stage of research involves machine learning techniques, which segments and extracts features from the mass of digital mammograms. Second level is on problem solving approach which includes classification of mass by performance based case base classifier. In this paper we build a case-based Classifier in order to diagnose mammographic images. We explain different methods and behaviors that have been added to the classifier to improve the performance of the classifier. Currently the initial Performance base Classifier with Bagging is proposed in the paper and it's been implemented and it shows an improvement in specificity and sensitivity.

Discrimination of benign and neoplastic mucosa with a high-resolution microendoscope (HRME) in head and neck cancer.

PubMed

Vila, Peter M; Park, Chan W; Pierce, Mark C; Goldstein, Gregg H; Levy, Lauren; Gurudutt, Vivek V; Polydorides, Alexandros D; Godbold, James H; Teng, Marita S; Genden, Eric M; Miles, Brett A; Anandasabapathy, Sharmila; Gillenwater, Ann M; Richards-Kortum, Rebecca; Sikora, Andrew G

2012-10-01

The efficacy of ablative surgery for head and neck squamous cell carcinoma (HNSCC) depends critically on obtaining negative margins. Although intraoperative "frozen section" analysis of margins is a valuable adjunct, it is expensive, time-consuming, and highly dependent on pathologist expertise. Optical imaging has potential to improve the accuracy of margins by identifying cancerous tissue in real time. Our goal was to determine the accuracy and inter-rater reliability of head and neck cancer specialists using high-resolution microendoscopic (HRME) images to discriminate between cancerous and benign mucosa. Thirty-eight patients diagnosed with head and neck squamous cell carcinoma (HNSCC) were enrolled in this single-center study. HRME was used to image each specimen after application of proflavine, with concurrent standard histopathologic analysis. Images were evaluated for quality control, and a training set containing representative images of benign and neoplastic tissue was assembled. After viewing training images, seven head and neck cancer specialists with no previous HRME experience reviewed 36 test images and were asked to classify each. The mean accuracy of all reviewers in correctly diagnosing neoplastic mucosa was 97% (95% confidence interval (CI), 94-99%). The mean sensitivity and specificity were 98% (97-100%) and 92% (87-98%), respectively. The Fleiss kappa statistic for inter-rater reliability was 0.84 (0.77-0.91). Medical professionals can be quickly trained to use HRME to discriminate between benign and neoplastic mucosa in the head and neck. With further development, the HRME shows promise as a method of real-time margin determination at the point of care.

Discrimination of Benign and Neoplastic Mucosa with a High-Resolution Microendoscope (HRME) in Head and Neck Cancer

PubMed Central

Vila, Peter M.; Park, Chan W.; Pierce, Mark C.; Goldstein, Gregg H.; Levy, Lauren; Gurudutt, Vivek V.; Polydorides, Alexandras D.; Godbold, James H.; Teng, Marita S.; Genden, Eric M.; Miles, Brett A.; Anandasabapathy, Sharmila; Gillenwater, Ann M.; Richards-Kortum, Rebecca; Sikora, Andrew G.

2012-01-01

Background The efficacy of ablative surgery for head and neck squamous cell carcinoma (HNSCC) depends critically on obtaining negative margins. While intraoperative "frozen section" analysis of margins is a valuable adjunct, it is expensive, time-consuming, and highly dependent on pathologist expertise. Optical imaging has potential to improve the accuracy of margins by identifying cancerous tissue in real time. Our aim was to determine the accuracy and inter-rater reliability of head and neck cancer specialists using high-resolution microendoscopic (HRME) images to discriminate between cancerous and benign mucosa. Methods Thirty-eight patients diagnosed with HNSCC were enrolled in this single-center study. HRME was used to image each specimen after application of proflavine, with concurrent standard histopathologic analysis. Images were evaluated for quality control, and a training set containing representative images of benign and neoplastic tissue was assembled. After viewing training images, seven head and neck cancer specialists with no prior HRME experience reviewed 37 test images and were asked to classify each. Results The mean accuracy of all reviewers in correctly diagnosing neoplastic mucosa was 97 percent (95% Cl = 94–99%). The mean sensitivity and specificity were 98 percent (97–100%) and 92 percent (87–98%), respectively. The Fleiss kappa statistic for inter-rater reliability was 0.84 (0.77–0.91). Conclusions Medical professionals can be quickly trained to use HRME to discriminate between benign and neoplastic mucosa in the head and neck. With further development, the HRME shows promise as a method of real-time margin determination at the point of care. PMID:22492225

Seismicity During Continental Breakup in the Red Sea Rift of Northern Afar

NASA Astrophysics Data System (ADS)

Illsley-Kemp, Finnigan; Keir, Derek; Bull, Jonathan M.; Gernon, Thomas M.; Ebinger, Cynthia; Ayele, Atalay; Hammond, James O. S.; Kendall, J.-Michael; Goitom, Berhe; Belachew, Manahloh

2018-03-01

Continental rifting is a fundamental component of plate tectonics. Recent studies have highlighted the importance of magmatic activity in accommodating extension during late-stage rifting, yet the mechanisms by which crustal thinning occurs are less clear. The Red Sea rift in Northern Afar presents an opportunity to study the final stages of continental rifting as these active processes are exposed subaerially. Between February 2011 and February 2013 two seismic networks were installed in Ethiopia and Eritrea. We locate 4,951 earthquakes, classify them by frequency content, and calculate 31 focal mechanisms. Results show that seismicity is focused at the rift axis and the western marginal graben. Rift axis seismicity accounts for ˜64% of the seismic moment release and exhibits a swarm-like behavior. In contrast, seismicity at the marginal graben is characterized by high-frequency earthquakes that occur at a constant rate. Results suggest that the rift axis remains the primary locus of seismicity. Low-frequency earthquakes, indicative of magmatic activity, highlight the presence of a magma complex ˜12 km beneath Alu-Dalafilla at the rift axis. Seismicity at the marginal graben predominantly occurs on westward dipping, antithetic faults. Focal mechanisms show that this seismicity is accommodating E-W extension. We suggest that the seismic activity at the marginal graben is either caused by upper crustal faulting accommodating enhanced crustal thinning beneath Northern Afar or as a result of flexural faulting between the rift and plateau. This seismicity is occurring in conjunction with magmatic extension at the rift axis, which accommodates the majority of long-term extension.

A unifying framework for marginalized random intercept models of correlated binary outcomes

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian M.

2013-01-01

We demonstrate that many current approaches for marginal modeling of correlated binary outcomes produce likelihoods that are equivalent to the copula-based models herein. These general copula models of underlying latent threshold random variables yield likelihood-based models for marginal fixed effects estimation and interpretation in the analysis of correlated binary data with exchangeable correlation structures. Moreover, we propose a nomenclature and set of model relationships that substantially elucidates the complex area of marginalized random intercept models for binary data. A diverse collection of didactic mathematical and numerical examples are given to illustrate concepts. PMID:25342871

Exploring the Margin Recipe for Online Adaptive Radiation Therapy for Intermediate-Risk Prostate Cancer: An Intrafractional Seminal Vesicles Motion Analysis

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

Sheng, Yang, E-mail: Yang.Sheng@duke.edu; Medical Physics Graduate Program, Duke University, Durham, North Carolina; Li, Taoran

Purpose: To provide a benchmark for seminal vesicle (SV) margin selection to account for intrafractional motion and to investigate the effectiveness of 2 motion surrogates in predicting intrafractional SV coverage. Methods and Materials: Fifteen prostate patients were studied. Each patient had 5 pairs (1 patient had 4 pairs) of pretreatment and posttreatment cone beam CTs (CBCTs). Each pair of CBCTs was registered on the basis of prostate fiducial markers. All pretreatment SVs were expanded with 1-, 2-, 3-, 4-, 5-, and 8-mm isotropic margins to form a series of planning target volumes, and their intrafractional coverage to the posttreatment SVmore » determined the “ground truth” for exact coverage. Two motion surrogates, the center of mass (COM) and the border of contour, were evaluated by the use of Pearson product-moment correlation coefficient and exponential fitting for predicting SV underdosage. Action threshold of each surrogate was calculated. The margin for each surrogate was calculated according to a traditional margin recipe. Results: Ninety-five percent posttreatment SV coverage was achieved in 9%, 53%, 73%, 86%, 95%, and 97% of fractions with 1-, 2-, 3-, 4-, 5-, and 8-mm margins, respectively. The 5-mm margins provided 95% intrafractional SV coverage in over 90% of fractions. The correlation between the COM and border was weak, moderate, and strong in the left-right (L-R), anterior-posterior (A-P), and superior-inferior (S-I) directions, respectively. Exponential fitting gave the underdosage threshold of 4.5 and 7.0 mm for the COM and border. The Van Herk margin recipe recommended 0-, 0.5-, and 0.8-mm margins in the L-R, A-P, and S-I directions based on the COM, and 1.2-, 3.9-, and 2.5-mm margins based on the border. Conclusions: Five-millimeter isotropic margins for the SV constitute the minimum required to mitigate the intrafractional motion. Both the COM and the border are acceptable predictors for SV underdosage with 4.5- and 7.0-mm action threshold. Traditional margin based on the COM or border underestimates the margin.« less

Endovascular abdominal aortic aneurysm repair is more profitable than open repair based on contribution margin per day.

PubMed

Rosenberg, Barry L; Comstock, Matthew C; Butz, David A; Taheri, Paul A; Williams, David M; Upchurch, Gilbert R

2005-03-01

Earlier studies have reported that endovascular abdominal aortic aneurysm (EAAA) repair yields lower total profit margins than open AAA (OAAA) repair. This study compared EAAA versus OAAA based on contribution margin per day, which may better measure profitability of new clinical technologies. Contribution margin equals revenue less variable direct costs (VDCs). VDCs capture incremental resources tied directly to individual patients' activity (eg, invoice price of endograft device, nursing labor). Overhead costs factor into total margin, but not contribution margin. The University of Michigan Health System's cost accounting system was used to extract fiscal year 2002-2003 information on revenue, total margin, contribution margin, and duration of stay for Medicare patients with principal diagnosis of AAA (ICD-9 code 441.4). OAAA had revenues of $37,137 per case versus $28,960 for EAAA, similar VDCs per case, and thus higher contribution margin per case ($24,404 for OAAA vs $13,911 for EAAA, P < .001). However, OAAA had significantly longer mean duration of stay per case (10.2 days vs 2.2 days, P < .001). Therefore, mean contribution margin per day was $2948 for OAAA, but $8569 for EAAA ( P < .001). On the basis of contribution margin per day, EAAA repair dominates OAAA repair. The shorter duration of stay with EAAA allows higher throughput, fuller overhead amortization, better use of scarce inpatient beds, and higher health system profits. Surgeons must understand overhead allocation to devices, especially when new technologies cut duration of stay markedly.

Marginal adaptation of newer root canal sealers to dentin: A SEM study.

PubMed

Polineni, Swapnika; Bolla, Nagesh; Mandava, Pragna; Vemuri, Sayesh; Mallela, Madhusudana; Gandham, Vijaya Madhuri

2016-01-01

This in vitro study evaluated and compared the marginal adaptation of three newer root canal sealers to root dentin. Thirty freshly extracted human single-rooted teeth with completely formed apices were taken. Teeth were decoronated, and root canals were instrumented. The specimens were randomly divided into three groups (n = 10) based upon the sealer used. Group 1 - teeth were obturated with epoxy resin sealer (MM-Seal). Group 2 - teeth were obturated with mineral trioxide aggregate (MTA) based sealer (MTA Fillapex), Group 3 - teeth were obturated with bioceramic sealer (EndoSequence BC sealer). Later samples were vertically sectioned using hard tissue microtome and marginal adaptation of sealers to root dentin was evaluated under coronal and apical halves using scanning electron microscopy (SEM) and marginal gap values were recorded. The data were statistically analyzed by two-way ANOVA and Tukey's multiple post hoc test. The highest marginal gap was seen in Group 2 (apical-16680.00 nm, coronal-10796 nm) and the lowest marginal gap was observed in Group 1 (apical-599.42 nm, coronal-522.72 nm). Coronal halves showed superior adaptation compared to apical halves in all the groups under SEM. Within the limitations of this study epoxy resin-based MM-Seal showed good marginal adaptation than other materials tested.

Intelligent query by humming system based on score level fusion of multiple classifiers

NASA Astrophysics Data System (ADS)

Pyo Nam, Gi; Thu Trang Luong, Thi; Ha Nam, Hyun; Ryoung Park, Kang; Park, Sung-Joo

2011-12-01

Recently, the necessity for content-based music retrieval that can return results even if a user does not know information such as the title or singer has increased. Query-by-humming (QBH) systems have been introduced to address this need, as they allow the user to simply hum snatches of the tune to find the right song. Even though there have been many studies on QBH, few have combined multiple classifiers based on various fusion methods. Here we propose a new QBH system based on the score level fusion of multiple classifiers. This research is novel in the following three respects: three local classifiers [quantized binary (QB) code-based linear scaling (LS), pitch-based dynamic time warping (DTW), and LS] are employed; local maximum and minimum point-based LS and pitch distribution feature-based LS are used as global classifiers; and the combination of local and global classifiers based on the score level fusion by the PRODUCT rule is used to achieve enhanced matching accuracy. Experimental results with the 2006 MIREX QBSH and 2009 MIR-QBSH corpus databases show that the performance of the proposed method is better than that of single classifier and other fusion methods.

Discriminative Learning of Receptive Fields from Responses to Non-Gaussian Stimulus Ensembles

PubMed Central

Meyer, Arne F.; Diepenbrock, Jan-Philipp; Happel, Max F. K.; Ohl, Frank W.; Anemüller, Jörn

2014-01-01

Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design. PMID:24699631

Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.

PubMed

Meyer, Arne F; Diepenbrock, Jan-Philipp; Happel, Max F K; Ohl, Frank W; Anemüller, Jörn

2014-01-01

Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design.

Diet quality and physical activity in relation to childhood obesity.

PubMed

An, Ruopeng

2017-04-01

Healthy lifestyles such as being physically active and eating a healthy diet help reduce the childhood obesity risk. However, population-level studies on the relationship between lifestyles and childhood obesity typically focus on either physical activity or diet but seldom both. This study examined physical activity and diet quality in relation to obesity in a nationally representative sample of U.S. children and adolescents. The study sample of 2818 children 6-17 years old came from the National Health and Nutrition Examination Survey 2003-2006 waves. A healthy eating index (HEI)-2010 was constructed based on two nonconsecutive 24-h dietary recalls. Participants at or above the 60th percentile of the HEI-2010 score were classified as consuming a healthy diet. Participants engaging in at least 60 min of moderate-vigorous physical activity daily measured by accelerometer were classified as being physically active. Adjusted average marginal effect of diet quality and physical activity on obesity was calculated based on estimates from logistic regressions. Compared with those consuming a healthy diet who are physically active, the estimated probabilities for overweight and obesity were 19.03 (95% confidence interval: 11.31, 26.74) and 15.84 (10.48, 21.21) percentage points higher among children consuming an unhealthy diet and who are physically inactive, 16.53 (7.58, 25.48) and 13.48 (5.68, 21.29) percentage points higher among children consuming a healthy diet but who are physically inactive and 3.22 (-3.43, 9.88) and 3.10 (-3.08, 9.29) percentage points higher among children consuming an unhealthy diet but physically active, respectively. Healthy habit formation at an early age is essential in obesity prevention.

Electricity Prices in a Competitive Environment: Marginal Cost Pricing

EIA Publications

1997-01-01

Presents the results of an analysis that focuses on two questions: (1) How are prices for competitive generation services likely to differ from regulated prices if competitive prices are based on marginal costs rather than regulated cost-of-service pricing? (2) What impacts will the competitive pricing of generation services (based on marginal costs) have on electricity consumption patterns, production costs, and the financial integrity of electricity suppliers?

Comparing vaccines: a systematic review of the use of the non-inferiority margin in vaccine trials.

PubMed

Donken, R; de Melker, H E; Rots, N Y; Berbers, G; Knol, M J

2015-03-17

Non-inferiority (NI) randomized controlled trials (RCTs) aim to demonstrate that a new treatment is no worse than a comparator that has already shown its efficacy over placebo within a pre-specified margin. However, clear guidelines on how the NI margin should be determined are lacking for vaccine trials. A difference (seroprevalence/risk) of 10% or a geometric mean titre/concentration (GMT) ratio of 1.5 or 2.0 in antibody levels is implicitly recommended for vaccine trials. We aimed to explore which NI margins were used in vaccine RCTs and how they were determined. A systematic search for NI vaccine RCTs yielded 177 eligible articles. Data were extracted from these articles using a standardized form and included general characteristics and characteristics specific for NI trials. Relations between the study characteristics and the NI margin used were explored. Among the 143 studies using an NI margin based on difference (n=136 on immunogenicity, n=2 on efficacy and n=5 on safety), 66% used a margin of 10%, 23% used margins lower than 10% (range 1-7.5%) and 11% used margins larger than 10% (range 11.5-25%). Of the 103 studies using a NI margin based on the GMT ratio, 50% used a margin of 0.67/1.5 and 49% used 0.5/2.0. As observed, 85% of the studies did not discuss the method of margin determination; and 19% of the studies lacked a confidence interval or p-value for non-inferiority. Most NI vaccine RCTs used an NI margin of 10% for difference or a GMT ratio of 1.5 or 2.0 without a clear rationale. Most articles presented enough information for the reader to make a judgement about the NI margin used and the conclusions. The reporting on the design, margins used and results of NI vaccine trials could be improved; more explicit guidelines may help to achieve this end. Copyright © 2015 Elsevier Ltd. All rights reserved.

SU-E-T-573: The Robustness of a Combined Margin Recipe for Uncertainties During Radiotherapy

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

Stroom, J; Vieira, S; Greco, C

2014-06-01

Purpose: To investigate the variability of a safety margin recipe that combines CTV and PTV margins quadratically, with several tumor, treatment, and user related factors. Methods: Margin recipes were calculated by monte-carlo simulations in 5 steps. 1. A spherical tumor with or without isotropic microscopic was irradiated with a 5 field dose plan2. PTV: Geometric uncertainties were introduced using systematic (Sgeo) and random (sgeo) standard deviations. CTV: Microscopic disease distribution was modelled by semi-gaussian (Smicro) with varying number of islets (Ni)3. For a specific uncertainty set (Sgeo, sgeo, Smicro(Ni)), margins were varied until pre-defined decrease in TCP or dose coveragemore » was fulfilled. 4. First, margin recipes were calculated for each of the three uncertainties separately. CTV and PTV recipes were then combined quadratically to yield a final recipe M(Sgeo, sgeo, Smicro(Ni)).5. The final M was verified by simultaneous simulations of the uncertainties.Now, M has been calculated for various changing parameters like margin criteria, penumbra steepness, islet radio-sensitivity, dose conformity, and number of fractions. We subsequently investigated A: whether the combined recipe still holds in all these situations, and B: what the margin variation was in all these cases. Results: We found that the accuracy of the combined margin recipes remains on average within 1mm for all situations, confirming the correctness of the quadratic addition. Depending on the specific parameter, margin factors could change such that margins change over 50%. Especially margin recipes based on TCP-criteria are more sensitive to more parameters than those based on purely geometric Dmin-criteria. Interestingly, measures taken to minimize treatment field sizes (by e.g. optimizing dose conformity) are counteracted by the requirement of larger margins to get the same tumor coverage. Conclusion: Margin recipes combining geometric and microscopic uncertainties quadratically are accurate under varying circumstances. However margins can change up to 50% for different situations.« less

An ensemble of SVM classifiers based on gene pairs.

PubMed

Tong, Muchenxuan; Liu, Kun-Hong; Xu, Chungui; Ju, Wenbin

2013-07-01

In this paper, a genetic algorithm (GA) based ensemble support vector machine (SVM) classifier built on gene pairs (GA-ESP) is proposed. The SVMs (base classifiers of the ensemble system) are trained on different informative gene pairs. These gene pairs are selected by the top scoring pair (TSP) criterion. Each of these pairs projects the original microarray expression onto a 2-D space. Extensive permutation of gene pairs may reveal more useful information and potentially lead to an ensemble classifier with satisfactory accuracy and interpretability. GA is further applied to select an optimized combination of base classifiers. The effectiveness of the GA-ESP classifier is evaluated on both binary-class and multi-class datasets. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mass Properties for Space Systems Standards Development

NASA Technical Reports Server (NTRS)

Beech, Geoffrey

2013-01-01

Current Verbiage in S-120 Applies to Dry Mass. Mass Margin is difference between Required Mass and Predicted Mass. Performance Margin is difference between Predicted Performance and Required Performance. Performance estimates and corresponding margin should be based on Predicted Mass (and other inputs). Contractor Mass Margin reserved from Performance Margin. Remaining performance margin allocated according to mass partials. Compliance can be evaluated effectively by comparison of three areas (preferably on a single sheet). Basic and Predicted Mass (including historical trend). Aggregate potential changes (threats and opportunities) which gives Mass Forecast. Mass Maturity by category (Estimated/Calculated/Actual).

Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI.

PubMed

Shiradkar, Rakesh; Podder, Tarun K; Algohary, Ahmad; Viswanath, Satish; Ellis, Rodney J; Madabhushi, Anant

2016-11-10

Radiomics or computer - extracted texture features have been shown to achieve superior performance than multiparametric MRI (mpMRI) signal intensities alone in targeting prostate cancer (PCa) lesions. Radiomics along with deformable co-registration tools can be used to develop a framework to generate targeted focal radiotherapy treatment plans. The Rad-TRaP framework comprises three distinct modules. Firstly, a module for radiomics based detection of PCa lesions on mpMRI via a feature enabled machine learning classifier. The second module comprises a multi-modal deformable co-registration scheme to map tissue, organ, and delineated target volumes from MRI onto CT. Finally, the third module involves generation of a radiomics based dose plan on MRI for brachytherapy and on CT for EBRT using the target delineations transferred from the MRI to the CT. Rad-TRaP framework was evaluated using a retrospective cohort of 23 patient studies from two different institutions. 11 patients from the first institution were used to train a radiomics classifier, which was used to detect tumor regions in 12 patients from the second institution. The ground truth cancer delineations for training the machine learning classifier were made by an experienced radiation oncologist using mpMRI, knowledge of biopsy location and radiology reports. The detected tumor regions were used to generate treatment plans for brachytherapy using mpMRI, and tumor regions mapped from MRI to CT to generate corresponding treatment plans for EBRT. For each of EBRT and brachytherapy, 3 dose plans were generated - whole gland homogeneous ([Formula: see text]) which is the current clinical standard, radiomics based focal ([Formula: see text]), and whole gland with a radiomics based focal boost ([Formula: see text]). Comparison of [Formula: see text] against conventional [Formula: see text] revealed that targeted focal brachytherapy would result in a marked reduction in dosage to the OARs while ensuring that the prescribed dose is delivered to the lesions. [Formula: see text] resulted in only a marginal increase in dosage to the OARs compared to [Formula: see text]. A similar trend was observed in case of EBRT with [Formula: see text] and [Formula: see text] compared to [Formula: see text]. A radiotherapy planning framework to generate targeted focal treatment plans has been presented. The focal treatment plans generated using the framework showed reduction in dosage to the organs at risk and a boosted dose delivered to the cancerous lesions.

Soft computing-based terrain visual sensing and data fusion for unmanned ground robotic systems

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir

2006-05-01

In this paper, we have primarily discussed technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain visual clues. The Kalman Filtering technique is applied for aggregative fusion of sub-terrain assessment results. The last two terrain classifiers are shown to have remarkable capability for terrain traversability assessment of natural terrains. We have conducted a comparative performance evaluation of all three terrain classifiers and presented the results in this paper.

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.

Self-supervised online metric learning with low rank constraint for scene categorization.

PubMed

Cong, Yang; Liu, Ji; Yuan, Junsong; Luo, Jiebo

2013-08-01

Conventional visual recognition systems usually train an image classifier in a bath mode with all training data provided in advance. However, in many practical applications, only a small amount of training samples are available in the beginning and many more would come sequentially during online recognition. Because the image data characteristics could change over time, it is important for the classifier to adapt to the new data incrementally. In this paper, we present an online metric learning method to address the online scene recognition problem via adaptive similarity measurement. Given a number of labeled data followed by a sequential input of unseen testing samples, the similarity metric is learned to maximize the margin of the distance among different classes of samples. By considering the low rank constraint, our online metric learning model not only can provide competitive performance compared with the state-of-the-art methods, but also guarantees convergence. A bi-linear graph is also defined to model the pair-wise similarity, and an unseen sample is labeled depending on the graph-based label propagation, while the model can also self-update using the more confident new samples. With the ability of online learning, our methodology can well handle the large-scale streaming video data with the ability of incremental self-updating. We evaluate our model to online scene categorization and experiments on various benchmark datasets and comparisons with state-of-the-art methods demonstrate the effectiveness and efficiency of our algorithm.

Relationship between occurrence of surgical complications and hospital finances.

PubMed

Eappen, Sunil; Lane, Bennett H; Rosenberg, Barry; Lipsitz, Stuart A; Sadoff, David; Matheson, Dave; Berry, William R; Lester, Mark; Gawande, Atul A

2013-04-17

The effect of surgical complications on hospital finances is unclear. To determine the relationship between major surgical complications and per-encounter hospital costs and revenues by payer type. Retrospective analysis of administrative data for all inpatient surgical discharges during 2010 from a nonprofit 12-hospital system in the southern United States. Discharges were categorized by principal procedure and occurrence of 1 or more postsurgical complications, using International Classification of Diseases, Ninth Revision, diagnosis and procedure codes. Nine common surgical procedures and 10 major complications across 4 payer types were analyzed. Hospital costs and revenue at discharge were obtained from hospital accounting systems and classified by payer type. Hospital costs, revenues, and contribution margin (defined as revenue minus variable expenses) were compared for patients with and without surgical complications according to payer type. Of 34,256 surgical discharges, 1820 patients (5.3%; 95% CI, 4.4%-6.4%) experienced 1 or more postsurgical complications. Compared with absence of complications, complications were associated with a $39,017 (95% CI, $20,069-$50,394; P < .001) higher contribution margin per patient with private insurance ($55,953 vs $16,936) and a $1749 (95% CI, $976-$3287; P < .001) higher contribution margin per patient with Medicare ($3629 vs $1880). For this hospital system in which private insurers covered 40% of patients (13,544), Medicare covered 45% (15,406), Medicaid covered 4% (1336), and self-payment covered 6% (2202), occurrence of complications was associated with an $8084 (95% CI, $4903-$9740; P < .001) higher contribution margin per patient ($15,726 vs $7642) and with a $7435 lower per-patient total margin (95% CI, $5103-$10,507; P < .001) ($1013 vs -$6422). In this hospital system, the occurrence of postsurgical complications was associated with a higher per-encounter hospital contribution margin for patients covered by Medicare and private insurance but a lower one for patients covered by Medicaid and who self-paid. Depending on payer mix, many hospitals have the potential for adverse near-term financial consequences for decreasing postsurgical complications.

Morphometric analysis of Eocene nummulitids in Western and Central Cuba - inferences on taxonomy, biostratigaphy and evolutionary trends

NASA Astrophysics Data System (ADS)

Ives Torres-Silva, Ana; Eder, Wolfgang; Hohenegger, Johann; Briguglio, Antonino

2017-04-01

None other larger benthic foraminifera (LBF) group in the Caribbean realm has led to such diverse opinions and controversy about their classification than the nummulitids. Unlike the Tethys species, where delimitation and details of evolutionary changes within species are well known, intraspecific evolution in the Caribbean remains understudied and generic nomenclature has not reached consensus yet. Morphometric studies appear to be the most appropriate methods in solving this unsatisfactory taxonomical situation. For every proposed species, morphological variations correlating with paleoecological factors and precise stratigraphic occurrence and range has to be studied in detail. Thus, the morphology in equatorial sections of nummulitids without chamber partitions was quantified at seven localities from Western and Central Cuba and interpreted by eleven growth-independent and/or growth-invariant characters and attributes. 102 isolated megalospheric individuals originating from Cuban localities, spanning the time interval from lower Middle Eocene to lower Oligocene, were classified by nonmetric multidimensional scaling and cluster analysis. Thirteen Caribbean specimens, which are considered as type material, were included. Two clearly differentiated morphogroups could be differentiated according to cluster and ordination analysis into the genera Nummulites and Palaeonummulites. Main differences in morphological characters between the morphogroups were confirmed by discriminant analysis. Nummulites differs from Palaeonummulites in a weak increase of the marginal radius and weak backbend angles. All specimens of Nummulites s.stricto from different localities were regarded as Nummulites striatoreticulatus. Based on discriminant analysis, N. striatoreticulatus specimens with similar depositional environments, but of different stratigraphic occurrence, are strongly separated. The older forms have a smaller backbend angle, perimeter ratio and proloculus nominal diameter, thus documenting stratigraphic and evolutionary trends. The species Nummulites striatoreticulatus in the Cuban sections ranges from lower middle Eocene to lower Priabonian. Within the Palaeonummulites group, the exceptional range of morphological variation tends to obscure the fact that there are several well-defined morphological species. Based on discriminant analysis the species P. willcoxi, P. trinitatensis, P. floridensis, P. ocalanus and P. soldadensis were classified ranging from tightly coiled individuals that are very similar to Nummulites to loosely coiled moprhotypes. Major separators between the species are the marginal radius, proloculus nominal diameter, spiral chamber height increase and the length of the first chamber. Stratigraphic trends within species were not clearly detectable, but paleogeographic differences and the morphological overlap between morphogroups in certain species are obvious. Paleonummulites species have long stratigraphic ranges from late Middle Eocene to probably lower Oligocene.

A new discriminative kernel from probabilistic models.

PubMed

Tsuda, Koji; Kawanabe, Motoaki; Rätsch, Gunnar; Sonnenburg, Sören; Müller, Klaus-Robert

2002-10-01

Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully in, for example, DNA and protein analysis. Whereas the Fisher kernel is calculated from the marginal log-likelihood, we propose the TOP kernel derived; from tangent vectors of posterior log-odds. Furthermore, we develop a theoretical framework on feature extractors from probabilistic models and use it for analyzing the TOP kernel. In experiments, our new discriminative TOP kernel compares favorably to the Fisher kernel.

Comparing ensemble learning methods based on decision tree classifiers for protein fold recognition.

PubMed

Bardsiri, Mahshid Khatibi; Eftekhari, Mahdi

2014-01-01

In this paper, some methods for ensemble learning of protein fold recognition based on a decision tree (DT) are compared and contrasted against each other over three datasets taken from the literature. According to previously reported studies, the features of the datasets are divided into some groups. Then, for each of these groups, three ensemble classifiers, namely, random forest, rotation forest and AdaBoost.M1 are employed. Also, some fusion methods are introduced for combining the ensemble classifiers obtained in the previous step. After this step, three classifiers are produced based on the combination of classifiers of types random forest, rotation forest and AdaBoost.M1. Finally, the three different classifiers achieved are combined to make an overall classifier. Experimental results show that the overall classifier obtained by the genetic algorithm (GA) weighting fusion method, is the best one in comparison to previously applied methods in terms of classification accuracy.

A non-stationary cost-benefit based bivariate extreme flood estimation approach

NASA Astrophysics Data System (ADS)

Qi, Wei; Liu, Junguo

2018-02-01

Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.

Automatic Classification of Time-variable X-Ray Sources

NASA Astrophysics Data System (ADS)

Lo, Kitty K.; Farrell, Sean; Murphy, Tara; Gaensler, B. M.

2014-05-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ~97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7-500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.

An ensemble of dissimilarity based classifiers for Mackerel gender determination

NASA Astrophysics Data System (ADS)

Blanco, A.; Rodriguez, R.; Martinez-Maranon, I.

2014-03-01

Mackerel is an infravalored fish captured by European fishing vessels. A manner to add value to this specie can be achieved by trying to classify it attending to its sex. Colour measurements were performed on Mackerel females and males (fresh and defrozen) extracted gonads to obtain differences between sexes. Several linear and non linear classifiers such as Support Vector Machines (SVM), k Nearest Neighbors (k-NN) or Diagonal Linear Discriminant Analysis (DLDA) can been applied to this problem. However, theyare usually based on Euclidean distances that fail to reflect accurately the sample proximities. Classifiers based on non-Euclidean dissimilarities misclassify a different set of patterns. We combine different kind of dissimilarity based classifiers. The diversity is induced considering a set of complementary dissimilarities for each model. The experimental results suggest that our algorithm helps to improve classifiers based on a single dissimilarity.

A fuzzy classifier system for process control

NASA Technical Reports Server (NTRS)

Karr, C. L.; Phillips, J. C.

1994-01-01

A fuzzy classifier system that discovers rules for controlling a mathematical model of a pH titration system was developed by researchers at the U.S. Bureau of Mines (USBM). Fuzzy classifier systems successfully combine the strengths of learning classifier systems and fuzzy logic controllers. Learning classifier systems resemble familiar production rule-based systems, but they represent their IF-THEN rules by strings of characters rather than in the traditional linguistic terms. Fuzzy logic is a tool that allows for the incorporation of abstract concepts into rule based-systems, thereby allowing the rules to resemble the familiar 'rules-of-thumb' commonly used by humans when solving difficult process control and reasoning problems. Like learning classifier systems, fuzzy classifier systems employ a genetic algorithm to explore and sample new rules for manipulating the problem environment. Like fuzzy logic controllers, fuzzy classifier systems encapsulate knowledge in the form of production rules. The results presented in this paper demonstrate the ability of fuzzy classifier systems to generate a fuzzy logic-based process control system.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Rank preserving sparse learning for Kinect based scene classification.

PubMed

Tao, Dapeng; Jin, Lianwen; Yang, Zhao; Li, Xuelong

2013-10-01

With the rapid development of the RGB-D sensors and the promptly growing population of the low-cost Microsoft Kinect sensor, scene classification, which is a hard, yet important, problem in computer vision, has gained a resurgence of interest recently. That is because the depth of information provided by the Kinect sensor opens an effective and innovative way for scene classification. In this paper, we propose a new scheme for scene classification, which applies locality-constrained linear coding (LLC) to local SIFT features for representing the RGB-D samples and classifies scenes through the cooperation between a new rank preserving sparse learning (RPSL) based dimension reduction and a simple classification method. RPSL considers four aspects: 1) it preserves the rank order information of the within-class samples in a local patch; 2) it maximizes the margin between the between-class samples on the local patch; 3) the L1-norm penalty is introduced to obtain the parsimony property; and 4) it models the classification error minimization by utilizing the least-squares error minimization. Experiments are conducted on the NYU Depth V1 dataset and demonstrate the robustness and effectiveness of RPSL for scene classification.

IgV(H) and bcl6 somatic mutation analysis reveals the heterogeneity of cutaneous B-cell lymphoma, and indicates the presence of undisclosed local antigens.

PubMed

Franco, Renato; Camacho, Francisca I; Fernández-Vázquez, Amalia; Algara, Patrocinio; Rodríguez-Peralto, José L; De Rosa, Gaetano; Piris, Miguel A

2004-06-01

Our understanding of the ontology of B-cell lymphomas (BCL) has been improved by the study of mutational status of IgV(H) and bcl6 genes, but only a few cases of cutaneous BCL have been examined for this status. We analyzed IgV(H) and bcl6 somatic mutations in 10 cutaneous BCL, classified as follicular (three primary and one secondary), primary marginal zone (two cases), and diffuse large BCL (three primary and one secondary). We observed a lower rate (<2%) of IgV(H) mutation in all marginal zone lymphomas, and a preferential usage of V(H)2-70 (one primary follicular and two primary diffuse large BCL). Fewer than expected replacement mutations in framework regions (FR) were observed in three primary follicular lymphomas (FLs) and in all diffuse large BCL, indicating a negative antigen selection pressure. Ongoing mutations were observed in eight of 10 cases. Only two primary FLs and two diffuse large BCL showed bcl6 somatic mutation. These data support the heterogeneous nature of the different cutaneous BCL, and specifically the distinction between cutaneous follicular and marginal zone lymphomas. The biased usage of V(H)2-70, the low rate of replacement mutation in the FR, and the presence of ongoing mutation imply that local antigens could modulate the growth of primary cutaneous BCL.

In-TFT-array-process micro defect inspection using nonlinear principal component analysis.

PubMed

Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang

2009-11-20

Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image.

DVH- and NTCP-based dosimetric comparison of different longitudinal margins for VMAT-IMRT of esophageal cancer.

PubMed

Münch, S; Oechsner, M; Combs, S E; Habermehl, D

2017-08-15

To cover the microscopic tumor spread in squamous cell carcinoma of the esophagus (SCC), longitudinal margins of 3-4 cm are used for radiotherapy (RT) protocols. However, smaller margins of 2-3 cm might be reasonable when advanced diagnostic imaging is integrated into target volume delineation. Purpose of this study was to compare the dose distribution and deposition to the organs at risk (OAR) for different longitudinal margins using a DVH- and NTCP-based approach. Ten patients with SCC of the middle or lower third were retrospectively selected. Three planning target volumes (PTV) with longitudinal margins of 4 cm, 3 cm and 2 cm and an axial margin of 1.5 cm to the gross target volume (GTV) were defined for each patient. For each PTV two treatment plans with total doses of 41.4 Gy (neoadjuvant treatment) and 50.4 Gy (definite treatment) were calculated. Dose to the lungs, heart, myelon and liver were then evaluated and compared between different PTVs. When using a longitudinal margin of 3 cm instead of 4 cm, all dose parameters (Dmin, Dmean, Dmedian and V5-V35), except Dmax could be significantly reduced for the lungs. Regarding the heart, a significant reduction was seen for Dmean and V5, but not for Dmin, Dmax, Dmedian and V10-V35. When comparing a longitudinal margin of 4 cm to a longitudinal margin of 2 cm, a significant difference was calculated for Dmin, Dmean, Dmedian and V5-V35 of the lungs and for Dmax, Dmean and V5-V35 of the heart. Nevertheless, no difference was seen for median heart dose. An additional dose reduction for V10 of the heart was achieved for definite treatment plans when using a longitudinal margin of 3 cm. The NTCP-based risk of pneumonitis was significantly reduced by a margin reduction to 2 cm for neoadjuvant and definite treatment plans. Reduction of longitudinal margins from 4 cm to 3 cm can significantly reduce the dose to lungs and Dmean of the heart. Despite clinical benefit and oncologic outcome remain unclear, reduction of the longitudinal margins might provide the opportunity to reduce side effects of chemoradiation (CRT) for SCC in upcoming studies.

The continent-ocean transition at the mid-northern margin of the South China Sea

NASA Astrophysics Data System (ADS)

Gao, Jinwei; Wu, Shiguo; McIntosh, Kirk; Mi, Lijun; Yao, Bochu; Chen, Zeman; Jia, Liankai

2015-07-01

The northern margin of the South China Sea (SCS) has particular structural and stratigraphic characteristics that are somewhat different from those described in typical passive margin models. The differences are attributable to poly-phase tectonic movements and magmatic activity resulting from the interaction among the Eurasian, Philippine Sea and Indo-Australian plates. Based on several crustal-scale multi-channel seismic reflection profiles and satellite gravity data across the northern SCS margin, this paper analyzes the structures, volcanoes and deep crust of the continent-ocean transition zone (COT) at the mid-northern margin of the SCS to study the patterns and model of extension there. The results indicate that the COT is limited landward by basin-bounding faults near Baiyun sag and is bounded by seaward-dipping normal faults near the oceanic basin in our seismic lines. The shallow anatomy of the COT is characterized by rift depression, structural highs with igneous rock and/or a volcanic zone or a zone of tilted fault blocks at the distal edge. Gravity modeling revealed that a high velocity layer (HVL) with a 0.8-6-km thickness is frequently present in the slope below the lower crust. Our study shows that the HVL is only located in the eastern portion of the northern SCS margin based on the available geophysical data. We infer from this that the presence of an HVL is not required in the COT at the northern SCS margin. The magmatic intrusions and HVL may be related to partial melting caused by the decompression of a passive, upwelling asthenosphere, which resulted primarily in post-rifting underplating and magmatic emplacement or modification of the crust. Based on this study, we propose that an intermediate mode of rifting was active in the mid-northern margin of the SCS with characteristics that are closer to those of the magma-poor margins than those of volcanic margins.

Primary cutaneous marginal zone B-cell lymphoma: response to treatment and disease-free survival in a series of 137 patients.

PubMed

Servitje, Octavio; Muniesa, Cristina; Benavente, Yolanda; Monsálvez, Verónica; Garcia-Muret, M Pilar; Gallardo, Fernando; Domingo-Domenech, Eva; Lucas, Anna; Climent, Fina; Rodriguez-Peralto, Jose L; Ortiz-Romero, Pablo L; Sandoval, Juan; Pujol, Ramon M; Estrach, M Teresa

2013-09-01

Primary cutaneous marginal zone B-cell lymphomas are low-grade lymphomas running an indolent course. Skin relapses have been frequently reported but little information about disease-free survival (DFS) is available. We sought to evaluate relapse rate and DFS in patients with primary cutaneous marginal zone B-cell lymphomas. Clinical features, European Organization for Research and Treatment of Cancer/International Society for Cutaneous Lymphomas stage, light chain restriction, clonality, treatments, skin relapses, DFS, stage progression, extracutaneous disease, and outcome are analyzed in a series of 137 patients. Patients were classified as solitary lesion (T1) (n = 70; 51%), regional skin involvement (T2) (n = 40; 29%), and generalized skin lesions (T3) (n = 27; 20%). Surgical excision, local radiotherapy, or a combination were the initial treatment in 118 patients (86%). In 121 of 137 patients (88%) a complete remission was observed after initial treatment, including 99 of 106 patients (93%) with solitary or localized disease and 22 of 31 patients (71%) with multifocal lesions. Cutaneous relapses were observed in 53 patients (44%). Median DFS was 47 months. Patients with multifocal lesions or T3 disease showed higher relapse rate and shorter DFS. No significant differences were observed between surgery and radiotherapy, but surgery alone was associated with more recurrences at initial site. Overall survival at 5 and 10 years was 93%. Six patients (4%) developed extracutaneous disease during follow-up. This was a case series retrospective study. Our results support long-term follow-up in patients with primary cutaneous marginal zone B-cell lymphomas. Disseminated skin lesions have higher relapse rate and shorter DFS suggesting further investigation on systemic therapies in such a group of patients. Copyright © 2013 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Evaluation of local toxic effects and outcomes for dogs undergoing marginal tumor excision with intralesional cisplatin-impregnated bead placement for treatment of soft tissue sarcomas: 62 cases (2009-2012).

PubMed

Bergman, Noelle S; Urie, Bridget K; Pardo, Anthony D; Newman, Rebecca G

2016-05-15

OBJECTIVE To evaluate outcomes for dogs following marginal tumor excision and intralesional placement of cisplatin-impregnated beads for the treatment of cutaneous or subcutaneous soft tissue sarcomas (STSs) and assess local toxic effects of cisplatin-impregnated beads in these patients. DESIGN Retrospective case series. ANIMALS 62 client-owned dogs. PROCEDURES Medical records were reviewed to identify dogs with STSs treated with marginal excision and intralesional placement of cisplatin-impregnated beads. Patient signalment; tumor location, type, and grade; dates of tumor resection and bead placement; number of beads placed; and concurrent treatments were recorded. Data regarding toxicosis at the bead site (up to the time of suture removal) and tumor recurrence were collected; variables of interest were evaluated for associations with these outcomes, and systemic adverse effects (if any) were recorded. RESULTS 24 of 51 (47%) evaluated dogs had toxicosis at bead placement sites (classified as mild [n = 12] or moderate [10] in most). Fifteen of 51 (29%) tumors recurred. Median disease-free interval was not reached for dogs with grade 1 and 2 STSs, whereas that for dogs with grade 3 STSs was 148 days. Disease-free survival rates of dogs with grade 1 and 2 tumors at 1, 2, and 3 years were 88%, 75%, and 64%, respectively. One dog was treated for presumptive systemic toxicosis but recovered with medical treatment. CONCLUSIONS AND CLINICAL RELEVANCE Cisplatin-impregnated beads were generally well tolerated; good results were achieved for dogs with grade 1 or 2 STSs. Prospective, controlled studies are needed to determine efficacy of this treatment for preventing recurrence of marginally excised STSs in dogs.

Margin based ontology sparse vector learning algorithm and applied in biology science.

PubMed

Gao, Wei; Qudair Baig, Abdul; Ali, Haidar; Sajjad, Wasim; Reza Farahani, Mohammad

2017-01-01

In biology field, the ontology application relates to a large amount of genetic information and chemical information of molecular structure, which makes knowledge of ontology concepts convey much information. Therefore, in mathematical notation, the dimension of vector which corresponds to the ontology concept is often very large, and thus improves the higher requirements of ontology algorithm. Under this background, we consider the designing of ontology sparse vector algorithm and application in biology. In this paper, using knowledge of marginal likelihood and marginal distribution, the optimized strategy of marginal based ontology sparse vector learning algorithm is presented. Finally, the new algorithm is applied to gene ontology and plant ontology to verify its efficiency.

Visual terrain mapping for traversable path planning of mobile robots

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Amrani, Rachida; Tunstel, Edward W.

2004-10-01

In this paper, we have primarily discussed technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain visual clues. The Kalman Filtering technique is applied for aggregative fusion of sub-terrain assessment results. The last two terrain classifiers are shown to have remarkable capability for terrain traversability assessment of natural terrains. We have conducted a comparative performance evaluation of all three terrain classifiers and presented the results in this paper.

Accurate determination of imaging modality using an ensemble of text- and image-based classifiers.

PubMed

Kahn, Charles E; Kalpathy-Cramer, Jayashree; Lam, Cesar A; Eldredge, Christina E

2012-02-01

Imaging modality can aid retrieval of medical images for clinical practice, research, and education. We evaluated whether an ensemble classifier could outperform its constituent individual classifiers in determining the modality of figures from radiology journals. Seventeen automated classifiers analyzed 77,495 images from two radiology journals. Each classifier assigned one of eight imaging modalities--computed tomography, graphic, magnetic resonance imaging, nuclear medicine, positron emission tomography, photograph, ultrasound, or radiograph-to each image based on visual and/or textual information. Three physicians determined the modality of 5,000 randomly selected images as a reference standard. A "Simple Vote" ensemble classifier assigned each image to the modality that received the greatest number of individual classifiers' votes. A "Weighted Vote" classifier weighted each individual classifier's vote based on performance over a training set. For each image, this classifier's output was the imaging modality that received the greatest weighted vote score. We measured precision, recall, and F score (the harmonic mean of precision and recall) for each classifier. Individual classifiers' F scores ranged from 0.184 to 0.892. The simple vote and weighted vote classifiers correctly assigned 4,565 images (F score, 0.913; 95% confidence interval, 0.905-0.921) and 4,672 images (F score, 0.934; 95% confidence interval, 0.927-0.941), respectively. The weighted vote classifier performed significantly better than all individual classifiers. An ensemble classifier correctly determined the imaging modality of 93% of figures in our sample. The imaging modality of figures published in radiology journals can be determined with high accuracy, which will improve systems for image retrieval.

SU-F-J-17: Patient Localization Using MRI-Guided Soft Tissue for Head-And-Neck Radiotherapy: Indication for Margin Reduction and Its Feasibility

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

Qi, X; Yang, Y; Jack, N

Purpose: On-board MRI provides superior soft-tissue contrast, allowing patient alignment using tumor or nearby critical structures. This study aims to study H&N MRI-guided IGRT to analyze inter-fraction patient setup variations using soft-tissue targets and design appropriate CTV-to-PTV margin and clinical implication. Methods: 282 MR images for 10 H&N IMRT patients treated on a ViewRay system were retrospectively analyzed. Patients were immobilized using a thermoplastic mask on a customized headrest fitted in a radiofrequency coil and positioned to soft-tissue targets. The inter-fraction patient displacements were recorded to compute the PTV margins using the recipe: 2.5∑+0.7σ. New IMRT plans optimized on themore » revised PTVs were generated to evaluate the delivered dose distributions. An in-house dose deformation registration tool was used to assess the resulting dosimetric consequences when margin adaption is performed based on weekly MR images. The cumulative doses were compared to the reduced margin plans for targets and critical structures. Results: The inter-fraction displacements (and standard deviations), ∑ and σ were tabulated for MRI and compared to kVCBCT. The computed CTV-to-PTV margin was 3.5mm for soft-tissue based registration. There were minimal differences between the planned and delivered doses when comparing clinical and the PTV reduced margin plans: the paired t-tests yielded p=0.38 and 0.66 between the planned and delivered doses for the adapted margin plans for the maximum cord and mean parotid dose, respectively. Target V95 received comparable doses as planned for the reduced margin plans. Conclusion: The 0.35T MRI offers acceptable soft-tissue contrast and good spatial resolution for patient alignment and target visualization. Better tumor conspicuity from MRI allows soft-tissue based alignments with potentially improved accuracy, suggesting a benefit of margin reduction for H&N radiotherapy. The reduced margin plans (i.e., 2 mm) resulted in improved normal structure sparing and accurate dose delivery to achieve intended treatment goal under MR guidance.« less

Utilizing ToxCast Data and Lifestage Physiologically-Based Pharmacokinetic (PBPK) models to Drive Adverse Outcome Pathways (AOPs)-Based Margin of Exposures (ABME) to Chemicals.

EPA Science Inventory

Utilizing ToxCast Data and Lifestage Physiologically-Based Pharmacokinetic (PBPK) models to Drive Adverse Outcome Pathways (AOPs)-Based Margin of Exposures (ABME) to Chemicals. Hisham A. El-Masri1, Nicole C. Klienstreur2, Linda Adams1, Tamara Tal1, Stephanie Padilla1, Kristin I...

Comparative risk assessment of carcinogens in alcoholic beverages using the margin of exposure approach.

PubMed

Lachenmeier, Dirk W; Przybylski, Maria C; Rehm, Jürgen

2012-09-15

Alcoholic beverages have been classified as carcinogenic to humans. As alcoholic beverages are multicomponent mixtures containing several carcinogenic compounds, a quantitative approach is necessary to compare the risks. Fifteen known and suspected human carcinogens (acetaldehyde, acrylamide, aflatoxins, arsenic, benzene, cadmium, ethanol, ethyl carbamate, formaldehyde, furan, lead, 4-methylimidazole, N-nitrosodimethylamine, ochratoxin A and safrole) occurring in alcoholic beverages were identified based on monograph reviews by the International Agency for Research on Cancer. The margin of exposure (MOE) approach was used for comparative risk assessment. MOE compares a toxicological threshold with the exposure. MOEs above 10,000 are judged as low priority for risk management action. MOEs were calculated for different drinking scenarios (low risk and heavy drinking) and different levels of contamination for four beverage groups (beer, wine, spirits and unrecorded alcohol). The lowest MOEs were found for ethanol (3.1 for low risk and 0.8 for heavy drinking). Inorganic lead and arsenic have average MOEs between 10 and 300, followed by acetaldehyde, cadmium and ethyl carbamate between 1,000 and 10,000. All other compounds had average MOEs above 10,000 independent of beverage type. Ethanol was identified as the most important carcinogen in alcoholic beverages, with clear dose response. Some other compounds (lead, arsenic, ethyl carbamate, acetaldehyde) may pose risks below thresholds normally tolerated for food contaminants, but from a cost-effectiveness point of view, the focus should be on reducing alcohol consumption in general rather than on mitigative measures for some contaminants that contribute only to a limited extent (if at all) to the total health risk. Copyright © 2012 UICC.

Residual lower esophageal sphincter pressure as a prognostic factor in the pneumatic balloon treatment of achalasia.

PubMed

Park, Jung Ho; Lee, Yong Chan; Lee, Hyuk; Park, Hyojin; Youn, Young Hoon; Park, Hyung Seok; Lee, Tae Hee; Hong, Kyoung Sup

2015-01-01

Pneumatic balloon dilatation (PD) is a mainstay in achalasia treatment. The aim of this study was to identify predictive factors for successful treatment. We retrospectively reviewed 76 patients with a diagnosis of achalasia who underwent PD from June 2010 to May 2013. Clinical symptoms were assessed using Eckardt score and manometry data were analyzed using resting and relaxation pressure (4sIRP) of lower esophageal sphincter (LES) and the distal contractile integral (DCI), which was calculated for 10 s from the start of deglutition between the upper margin of the LES and lower margin of upper esophageal contraction. Patients with achalasia were classified into three groups based on the Chicago classification. Among 76 patients, 52 patients received PD, and the treatment was unsuccessful in 9 patients (6 in class I and 3 in class III). When comparing prognostic factors between successful and unsuccessful treatment groups, the mean value for 4sIRP in the unsuccessful treatment group was significantly lower than that in the successful treatment group (P < 0.05). However, no difference was noticed in resting LES pressure, DCI, age, and sex. Furthermore, a lower mean value of 4sIRP was significantly related to unsuccessful treatment of achalasia (odds ratio, 1.092; 95% confidence interval, 1.001-1.191) even after adjustment for a series of confounding factors. Lower 4sIRP may be a prognostic indicator for poor treatment outcome after PD. © 2014 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

Detection of early osteoarthritis in the centrodistal joints of Icelandic horses: Evaluation of radiography and low-field magnetic resonance imaging.

PubMed

Ley, C J; Björnsdóttir, S; Ekman, S; Boyde, A; Hansson, K

2016-01-01

Validated noninvasive detection methods for early osteoarthritis (OA) are required for OA prevention and early intervention treatment strategies. To evaluate radiography and low-field magnetic resonance imaging (MRI) for the detection of early stage OA osteochondral lesions in equine centrodistal joints using microscopy as the reference standard. Prospective imaging of live horses and imaging and microscopy of cadaver tarsal joints. Centrodistal (distal intertarsal) joints of 38 Icelandic research horses aged 27-29 months were radiographed. Horses were subjected to euthanasia approximately 2 months later and cadaver joints examined with low-field MRI. Osteochondral joint specimens were classified as negative or positive for OA using light microscopy histology or scanning electron microscopy. Radiographs and MRIs were evaluated for osteochondral lesions and results compared with microscopy. Forty-two joints were classified OA positive with microscopy. Associations were detected between microscopic OA and the radiography lesion categories; mineralisation front defect (P<0.0001), joint margin lesion (P<0.0001), central osteophyte (P = 0.03) and the low-field MRI lesion categories; mineralisation front defect (P = 0.01), joint margin lesion (P = 0.02) and articular cartilage lesion (P = 0.0003). The most frequent lesion category detected in microscopic OA positive joints was the mineralisation front defect in radiographs (28/42 OA positive joints, specificity 97%, sensitivity 67%). No significant differences were detected between the sensitivity and specificity of radiography and low-field MRI pooled lesion categories, but radiography was often superior when individual lesion categories were compared. Early stage centrodistal joint OA changes may be detected with radiography and low-field MRI. Detection of mineralisation front defects in radiographs may be a useful screening method for detection of early OA in centrodistal joints of young Icelandic horses. © 2015 EVJ Ltd.

Selection of Properties as References for Ecological Restoration in Brazilian Semiarid

NASA Astrophysics Data System (ADS)

Alvarez, I. A.; Oliveira, A. R.; Rennó, C. D.; Pereira, L. A.; Vicente, L. E.; Andrade, R. G.; Santos, S. M.; Taura, T. A.

2011-12-01

The São Francisco River has suffered over many years with the deterioration of its margins. Degradation is more intense when it removes native vegetation for logging, for livestock or expansion of arable land. It is remarkable the loss of biodiversity in degraded areas, increased erosion, siltation of the river, among other negative aspects. In the Lower Middle São Francisco River Valley this degradation is very worrying, especially because this semiarid region is the most populated in the world and has an uncontrolled growth of urban areas along the river margins. When compared to other regions along the river, there is more irrigated agriculture area. The application of ecological restoration models faces the process of selection of properties. The universe of analysis is very large because there are several areas with different degrees of degradation. In addition most farmers do not accept the environmental police and management. This study aimed to select 2 properties per city for pilot implementation restoration ecology in two ways. Firstly, it was defined a series criteria for choosing areas through GIS techniques. After, questionnaires were applied for selecting the properties in the cities. The study involved the Integrated Network of Economic Development (RIDE) composed by 4 cities in the state of Pernambuco and 4 in Bahia. Land use and land cover type were diagnosed in the counties from the images processing, which served as basis for defining a cutout of 3 km (1:50.000) band Riverside. The use land and land cover was classified into six main categories (shrubs, forest, grassland, water, urban area and desert) based on IBGE and the interpretation key which was established previously for PROBIO/MMA. Then, 759 units were processed and degradation degree was evaluated using the vegetation cover index. This index was used as orientation to preselect the areas to be checked in field. After field checking, 68 farms were selected in eight counties of the RIDE for the application of the questionnaires. The criteria were established and took into account qualitative and quantitative aspects, such as total area, conservation area, length margin, location, land ownership, conservation actions, the owner's interest in preserving, the neighbors' interests in participating of the plan, awareness actions for conservation, availability of human resources, recognition of the landscape, perception of interactions between humans and other coastal and river subjective factors. Based on these criteria, 16 properties were selected.

Development of the Canadian Marginalization Index: a new tool for the study of inequality.

PubMed

Matheson, Flora I; Dunn, James R; Smith, Katherine L W; Moineddin, Rahim; Glazier, Richard H

2012-04-30

Area-based measures of socio-economic status are increasingly used in population health research. Based on previous research and theory, the Canadian Marginalization Index (CAN-Marg) was created to reflect four dimensions of marginalization: residential instability, material deprivation, dependency and ethnic concentration. The objective of this paper was threefold: to describe CAN-Marg; to illustrate its stability across geographic area and time; and to describe its association with health and behavioural problems. CAN-Marg was created at the dissemination area (DA) and census tract level for census years 2001 and 2006, using factor analysis. Descriptions of 18 health and behavioural problems were selected using individual-level data from the Canadian Community Health Survey (CCHS) 3.1 and 2007/08. CAN-Marg quintiles created at the DA level (2006) were assigned to individual CCHS records. Multilevel logistic regression modeling was conducted to examine associations between marginalization and CCHS health and behavioural problems. The index demonstrated marked stability across time and geographic area. Each of the four dimensions showed strong and significant associations with the selected health and behavioural problems, and these associations differed depending on which of the dimensions of marginalization was examined. CAN-Marg is a census-based, empirically derived and theoretically informed tool designed to reflect a broader conceptualization of Canadian marginalization.

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

PubMed

Bokulich, Nicholas A; Kaehler, Benjamin D; Rideout, Jai Ram; Dillon, Matthew; Bolyen, Evan; Knight, Rob; Huttley, Gavin A; Gregory Caporaso, J

2018-05-17

Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

Evaluation of marginal failures of dental composite restorations by acoustic emission analysis.

PubMed

Gu, Ja-Uk; Choi, Nak-Sam

2013-01-01

In this study, a nondestructive method based on acoustic emission (AE) analysis was developed to evaluate the marginal failure states of dental composite restorations. Three types of ring-shaped substrates, which were modeled after a Class I cavity, were prepared from polymethyl methacrylate, stainless steel, and human molar teeth. A bonding agent and a composite resin were applied to the ring-shaped substrates and cured by light exposure. At each time-interval measurement, the tooth substrate presented a higher number of AE hits than polymethyl methacrylate and steel substrates. Marginal disintegration estimations derived from cumulative AE hits and cumulative AE energy parameters showed that a signification portion of marginal gap formation was already realized within 1 min at the initial light-curing stage. Estimation based on cumulative AE energy gave a higher level of marginal failure than that based on AE hits. It was concluded that the AE analysis method developed in this study was a viable approach in predicting the clinical survival of dental composite restorations efficiently within a short test period.

Chaotic particle swarm optimization with mutation for classification.

PubMed

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms.

Pairwise diversity ranking of polychotomous features for ensemble physiological signal classifiers.

PubMed

Gupta, Lalit; Kota, Srinivas; Molfese, Dennis L; Vaidyanathan, Ravi

2013-06-01

It is well known that fusion classifiers for physiological signal classification with diverse components (classifiers or data sets) outperform those with less diverse components. Determining component diversity, therefore, is of the utmost importance in the design of fusion classifiers that are often employed in clinical diagnostic and numerous other pattern recognition problems. In this article, a new pairwise diversity-based ranking strategy is introduced to select a subset of ensemble components, which when combined will be more diverse than any other component subset of the same size. The strategy is unified in the sense that the components can be classifiers or data sets. Moreover, the classifiers and data sets can be polychotomous. Classifier-fusion and data-fusion systems are formulated based on the diversity-based selection strategy, and the application of the two fusion strategies are demonstrated through the classification of multichannel event-related potentials. It is observed that for both classifier and data fusion, the classification accuracy tends to increase/decrease when the diversity of the component ensemble increases/decreases. For the four sets of 14-channel event-related potentials considered, it is shown that data fusion outperforms classifier fusion. Furthermore, it is demonstrated that the combination of data components that yield the best performance, in a relative sense, can be determined through the diversity-based selection strategy.

TU-AB-303-06: Does Online Adaptive Radiation Therapy Mean Zero Margin for Intermediate-Risk Prostate Cancer? An Intra-Fractional Seminal Vesicles Motion Analysis

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

Sheng, Y; Li, T; Lee, W

Purpose: To provide benchmark for seminal vesicles (SVs) margin selection to account for intra-fractional motion; and to investigate the effectiveness of two motion surrogates in predicting intra-fractional SV underdosage. Methods: 9 prostate SBRT patients were studied; each has five pairs of pre-treatment and post-treatment cone-beam CTs (CBCTs). Each pair of CBCTs was registered based on fiducial markers in the prostate. To provide “ground truth” for coverage evaluation, all pre-treatment SVs were expanded with isotropic margin of 1,2,3,5 and 8mm, and their overlap with post-treatment SVs were used to quantify intra-fractional coverage. Two commonly used motion surrogates, the center-of-mass (COM) andmore » the border of contour (the most distal points in SI/AP/LR directions) were evaluated using Receiver-Operating Characteristic (ROC) analyses for predicting SV underdosage due to intra-fractional motion. Action threshold of determining underdosage for each surrogate was calculated by selecting the optimal balancing between sensitivity and specificity. For comparison, margin for each surrogate was also calculated based on traditional margin recipe. Results: 90% post-treatment SV coverage can be achieved in 47%, 82%, 91%, 98% and 98% fractions for 1,2,3,5 and 8mm margins. 3mm margin ensured the 90% intra-fractional SV coverage in 90% fractions when prostate was aligned. The ROC analysis indicated the AUC for COM and border were 0.88 and 0.72. The underdosage threshold was 2.9mm for COM and 4.1mm for border. The Van Herk’s margin recipe recommended 0.5, 0 and 1.8mm margin in LR, AP and SI direction based on COM and for border, the corresponding margin was 2.1, 4.5 and 3mm. Conclusion: 3mm isotropic margin is the minimum required to mitigate the intra-fractional SV motion when prostate is aligned. ROC analysis reveals that both COM and border are acceptable predictors for SV underdosage with 2.9mm and 4.1mm action threshold. Traditional margin calculation is less reliable for this application. This work is partially supported a master research grant from Varian Medical Systems.« less

Habitat Distribution on the Inner Continental Shelf of Northern South Carolina Based on Sidescan Sonar and Submarine Video Data

NASA Astrophysics Data System (ADS)

Ojeda, G. Y.; Gayes, P. T.; van Dolah, R. F.; Schwab, W. C.

2002-12-01

Assessment of the extent and variability of benthic habitats is an important mission of biologists and marine scientists, and has supreme relevance in monitoring and maintaining the offshore resources of coastal nations. Mapping `hard bottoms', in particular, is of critical importance because these are the areas that support sessile benthic habitats and associated fisheries. To quantify the extent and distribution of habitats offshore northern South Carolina, we used a spatially quantitative approach that involved textural analysis of side scan sonar images and training of an artificial neural network classifier. This approach was applied to a 2 m-pixel image mosaic of sonar data collected by the USGS in 1999 and 2000. The entire mosaic covered some 686 km2 and extended between the ~6 m and ~10+ m isobaths off the Grand Strand region of South Carolina. Bottom video transects across selected sites provided 2,119 point observations which were used for image-to-ground control as well as training of the neural network classifier. A sensitivity study of 52 space-domain textural features indicated that 12 of them provided reasonable discriminating power between two end-member bottom types: hard bottom and sand. The selected features were calculated over 5 by 5 pixel windows of the image where video point observations existed. These feature vectors were then fed to a 3-layer neural network classifier, trained with a Levenberg-Marquardt backpropagation algorithm. Registration and display of the output habitat map were performed in GIS. Results of our classification indicate that outcropping Tertiary and Cretaceous strata are exposed over a significant portion of northern South Carolina's inner shelf, consistent with a sediment-starved margin type. The combined surface extent classified as hard bottom was 405 km2 -or 59 % of the imaged area-, while only 281 km2 -or 41 % of the area were classified as sand. In addition, our results provided constraints on the spatial continuity of nearshore benthic habitats. The median surface area of the regions classified as hard bottom (n= 190,521) and sand (n= 234,946) were both equal to the output cell size (100 m2), confirming the `patchy' nature of these habitats and suggesting that these medians probably represent upper bounds rather than estimates of the typical extent of individual patches. Furthermore, comparison of the interpretive habitat map with available swath bathymetry data suggests positive correlation between bathymetry `highs' and the major sandy-bottom areas interpreted with our routine. In contrast, the location of hard bottom areas does not appear to be significantly correlated with major bathymetric features. Our findings are in agreement with published qualitative estimates of hard bottom areas on neighboring North Carolina's inner shelf.

Planning Target Margin Calculations for Prostate Radiotherapy Based on Intrafraction and Interfraction Motion Using Four Localization Methods

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

Beltran, Chris; Herman, Michael G.; Davis, Brian J.

2008-01-01

Purpose: To determine planning target volume (PTV) margins for prostate radiotherapy based on the internal margin (IM) (intrafractional motion) and the setup margin (SM) (interfractional motion) for four daily localization methods: skin marks (tattoo), pelvic bony anatomy (bone), intraprostatic gold seeds using a 5-mm action threshold, and using no threshold. Methods and Materials: Forty prostate cancer patients were treated with external radiotherapy according to an online localization protocol using four intraprostatic gold seeds and electronic portal images (EPIs). Daily localization and treatment EPIs were obtained. These data allowed inter- and intrafractional analysis of prostate motion. The SM for the fourmore » daily localization methods and the IM were determined. Results: A total of 1532 fractions were analyzed. Tattoo localization requires a SM of 6.8 mm left-right (LR), 7.2 mm inferior-superior (IS), and 9.8 mm anterior-posterior (AP). Bone localization requires 3.1, 8.9, and 10.7 mm, respectively. The 5-mm threshold localization requires 4.0, 3.9, and 3.7 mm. No threshold localization requires 3.4, 3.2, and 3.2 mm. The intrafractional prostate motion requires an IM of 2.4 mm LR, 3.4 mm IS and AP. The PTV margin using the 5-mm threshold, including interobserver uncertainty, IM, and SM, is 4.8 mm LR, 5.4 mm IS, and 5.2 mm AP. Conclusions: Localization based on EPI with implanted gold seeds allows a large PTV margin reduction when compared with tattoo localization. Except for the LR direction, bony anatomy localization does not decrease the margins compared with tattoo localization. Intrafractional prostate motion is a limiting factor on margin reduction.« less

77 FR 71369 - Capital, Margin, and Segregation Requirements for Security-Based Swap Dealers and Major Security...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-30

... SECURITIES AND EXCHANGE COMMISSION 17 CFR Part 240 [Release No. 34-68071; File No. S7-08-12] RIN 3235-AL12 Capital, Margin, and Segregation Requirements for Security-Based Swap Dealers and Major Security-Based Swap Participants and Capital Requirements for Broker-Dealers Correction In proposed rule...

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

PubMed

Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification

PubMed Central

Feng, Yang; Jiang, Jiancheng; Tong, Xin

2015-01-01

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing. PMID:27185970

Large margin nearest neighbor classifiers.

PubMed

Domeniconi, Carlotta; Gunopulos, Dimitrios; Peng, Jing

2005-07-01

The nearest neighbor technique is a simple and appealing approach to addressing classification problems. It relies on the assumption of locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with a finite number of examples due to the curse of dimensionality. Severe bias can be introduced under these conditions when using the nearest neighbor rule. The employment of a locally adaptive metric becomes crucial in order to keep class conditional probabilities close to uniform, thereby minimizing the bias of estimates. We propose a technique that computes a locally flexible metric by means of support vector machines (SVMs). The decision function constructed by SVMs is used to determine the most discriminant direction in a neighborhood around the query. Such a direction provides a local feature weighting scheme. We formally show that our method increases the margin in the weighted space where classification takes place. Moreover, our method has the important advantage of online computational efficiency over competing locally adaptive techniques for nearest neighbor classification. We demonstrate the efficacy of our method using both real and simulated data.

An Automatic Diagnosis Method of Facial Acne Vulgaris Based on Convolutional Neural Network.

PubMed

Shen, Xiaolei; Zhang, Jiachi; Yan, Chenjun; Zhou, Hong

2018-04-11

In this paper, we present a new automatic diagnosis method for facial acne vulgaris which is based on convolutional neural networks (CNNs). To overcome the shortcomings of previous methods which were the inability to classify enough types of acne vulgaris. The core of our method is to extract features of images based on CNNs and achieve classification by classifier. A binary-classifier of skin-and-non-skin is used to detect skin area and a seven-classifier is used to achieve the classification task of facial acne vulgaris and healthy skin. In the experiments, we compare the effectiveness of our CNN and the VGG16 neural network which is pre-trained on the ImageNet data set. We use a ROC curve to evaluate the performance of binary-classifier and use a normalized confusion matrix to evaluate the performance of seven-classifier. The results of our experiments show that the pre-trained VGG16 neural network is effective in extracting features from facial acne vulgaris images. And the features are very useful for the follow-up classifiers. Finally, we try applying the classifiers both based on the pre-trained VGG16 neural network to assist doctors in facial acne vulgaris diagnosis.

Managing Marginal School Employees: Applying Standards-Based Performance Measures

ERIC Educational Resources Information Center

Fields, Lynette; Reck, Brianne; Egley, Robert

2006-01-01

This book contains a collection of case studies that provide a variety of situations in managing or working with marginal employees in a school system. Managing Marginal School Employees will serve as a primary or companion text for administrator candidates or current administrators that include dilemmas for the student to think about, discuss,…

30 CFR 204.209 - What if a property ceases to qualify for relief obtained under this subpart?

Code of Federal Regulations, 2010 CFR

2010-07-01

..., DEPARTMENT OF THE INTERIOR MINERALS REVENUE MANAGEMENT ALTERNATIVES FOR MARGINAL PROPERTIES Accounting and...) A marginal property must qualify for relief under this subpart for each calendar year based on... of your interest in a marginal property during the calendar year, your relief terminates as of the...

Lower crustal strength controls on melting and type of oceanization at magma-poor margins

NASA Astrophysics Data System (ADS)

Ros, E.; Perez-Gussinye, M.; Araujo, M. N.; Thoaldo Romeiro, M.; Andres-Martinez, M.; Morgan, J. P.

2017-12-01

Geodynamical models have been widely used to explain the variability in the architectonical style of conjugate rifted margins as a combination of lithospheric deformation modes, which are strongly influenced by lower crustal strength. We use 2D numerical models to show that the lower crustal strength also plays a key role on the onset and amount of melting and serpentinization during continental rifting. The relative timing between melting and serpentinization onsets controls whether the continent-ocean transition (COT) of margins will be predominantly magmatic or will mainly consist of exhumed and serpentinized mantle. Based on our results for magma-poor continental rifting, we propose a genetic link between margin architecture and COT styles that can be used as an additional tool to help interpret and understand the processes leading to margin formation. Our results show that strong lower crusts and very slow extension velocities (<5 mm/yr) lead to either symmetric or asymmetric margins with large oceanward dipping faults, strong syn-rift subsidence and abrupt crustal tapering beneath the continental shelf. These margins are characterized by a COT consisting of exhumed and serpentinized mantle and some magmatic products. Weak lower crusts at ultra-slow velocities lead also to either symmetric or asymmetric margins with small faults dipping both ocean- and landward, small syn-rift subsidence and gentle crustal tapering, and present a predominantly magmatic COT, perhaps underlain by some serpentinized mantle. When conjugate margins are asymmetric, if the rheology is relatively strong, serpentinite predominantly underlays the wide margin, whereas if the lower crustal strength is weak, melt preferentially migrates towards the wide margin. Based on the onshore lithospheric structure, extension velocity and margin architecture of the magma-poor section of the South Atlantic, we suggest that the COT of the northern sector, Camamu-Gabon basins, is more likely to consist of exhumed mantle with intruded magmatism, while to the South, the Camamu-Kwanza and North Santos-South Kwanza conjugates, may be better characterized by a predominantly magmatic COT.

Improving ensemble decision tree performance using Adaboost and Bagging

NASA Astrophysics Data System (ADS)

Hasan, Md. Rajib; Siraj, Fadzilah; Sainin, Mohd Shamrie

2015-12-01

Ensemble classifier systems are considered as one of the most promising in medical data classification and the performance of deceision tree classifier can be increased by the ensemble method as it is proven to be better than single classifiers. However, in a ensemble settings the performance depends on the selection of suitable base classifier. This research employed two prominent esemble s namely Adaboost and Bagging with base classifiers such as Random Forest, Random Tree, j48, j48grafts and Logistic Model Regression (LMT) that have been selected independently. The empirical study shows that the performance varries when different base classifiers are selected and even some places overfitting issue also been noted. The evidence shows that ensemble decision tree classfiers using Adaboost and Bagging improves the performance of selected medical data sets.

An updated global earthquake catalogue for stable continental regions: Reassessing the correlation with ancient rifts

USGS Publications Warehouse

Schulte, S.M.; Mooney, W.D.

2005-01-01

We present an updated global earthquake catalogue for stable continental regions (SCRs; i.e. intraplate earthquakes) that is available on the Internet. Our database contains information on location, magnitude, seismic moment and focal mechanisms for over 1300 M (moment magnitude) ??? 4.5 historic and instrumentally recorded crustal events. Using this updated earthquake database in combination with a recently published global catalogue of rifts, we assess the correlation of intraplate seismicity with ancient rifts on a global scale. Each tectonic event is put into one of five categories based on location: (i) interior rifts/taphrogens, (ii) rifted continental margins, (iii) non-rifted crust, (iv) possible interior rifts and (v) possible rifted margins. We find that approximately 27 per cent of all events are classified as interior rifts (i), 25 per cent are rifted continental margins (ii), 36 per cent are within non-rifted crust (iii) and 12 per cent (iv and v) remain uncertain. Thus, over half (52 per cent) of all events are associated with rifted crust, although within the continental interiors (i.e. away from continental margins), non-rifted crust has experienced more earthquakes than interior rifts. No major change in distribution is found if only large (M ??? 6.0) earthquakes are considered. The largest events (M ??? 7.0) however, have occurred predominantly within rifts (50 per cent) and continental margins (43 per cent). Intraplate seismicity is not distributed evenly. Instead several zones of concentrated seismicity seem to exist. This is especially true for interior rifts/taphrogens, where a total of only 12 regions are responsible for 74 per cent of all events and as much as 98 per cent of all seismic moment released in that category. Of the four rifts/taphrogens that have experienced the largest earthquakes, seismicity within the Kutch rift, India, and the East China rift system, may be controlled by diffuse plate boundary deformation more than by the presence of the ancient rifts themselves. The St. Lawrence depression, Canada, besides being an ancient rift, is also the site of a major collisional suture. Thus only at the Reelfoot rift (New Madrid seismic zone, NMSZ, USA), is the presence of features associated with rifting itself the sole candidate for causing seismicity. Our results suggest that on a global scale, the correlation of seismicity within SCRs and ancient rifts has been overestimated in the past. Because the majority of models used to explain intraplate seismicity have focused on seismicity within rifts, we conclude that a shift in attention more towards non-rifted as well as rifted crust is in order. ?? 2005 RAS.

Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors.

PubMed

Kim, Seongjung; Kim, Jongman; Ahn, Soonjae; Kim, Youngho

2018-04-18

Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restrictions. In this study, we developed a finger language recognition algorithm based on an ensemble artificial neural network (E-ANN) using an armband system with 8-channel electromyography (EMG) sensors. The developed algorithm was composed of signal acquisition, filtering, segmentation, feature extraction and an E-ANN based classifier that was evaluated with the Korean finger language (14 consonants, 17 vowels and 7 numbers) in 17 subjects. E-ANN was categorized according to the number of classifiers (1 to 10) and size of training data (50 to 1500). The accuracy of the E-ANN-based classifier was obtained by 5-fold cross validation and compared with an artificial neural network (ANN)-based classifier. As the number of classifiers (1 to 8) and size of training data (50 to 300) increased, the average accuracy of the E-ANN-based classifier increased and the standard deviation decreased. The optimal E-ANN was composed with eight classifiers and 300 size of training data, and the accuracy of the E-ANN was significantly higher than that of the general ANN.

Systematic Review of Studies Reporting Positive Surgical Margins After Bladder Neck Sparing Radical Prostatectomy.

PubMed

Bellangino, Mariangela; Verrill, Clare; Leslie, Tom; Bell, Richard W; Hamdy, Freddie C; Lamb, Alastair D

2017-11-07

Bladder neck preservation (BNP) during radical prostatectomy (RP) has been proposed as a method to improve early recovery of urinary continence after radical prostatectomy. However, there is concern over a possible increase in the risk of positive surgical margins and prostate cancer recurrence rate. A recent systematic review and meta-analysis reported improved early recovery and overall long-term urinary continence without compromising oncologic control. The aim of our study was to perform a critical review of the literature to assess the impact on bladder neck and base margins after bladder neck sparing radical prostatectomy. We carried out a systematic review of the literature using Pubmed, Scopus and Cochrane library databases in May 2017 using medical subject headings and free-text protocol according to PRISMA guidelines. We used the following search terms: bladder neck preservation, prostate cancer, radical prostatectomy and surgical margins. Studies focusing on positive surgical margins (PSM) in bladder neck sparing RP pertinent to the objective of this review were included. Overall, we found 15 relevant studies reporting overall and site-specific positive surgical margins rate after bladder neck sparing radical prostatectomy. This included two RCTs, seven prospective comparative studies, two retrospective comparative studies and four case series. All studies were published between 1993 and 2015 with sample sizes ranging between 50 and 1067. Surgical approaches included open, laparoscopic and robot-assisted radical prostatectomy. The overall and base-specific PSM rates ranged between 7-36% and 0-16.3%, respectively. Mean base PSM was 4.9% in those patients where bladder neck sparing was performed, but only 1.85% in those without sparing. Bladder neck preservation during radical prostatectomy may increase base-positive margins. Further studies are needed to better investigate the impact of this technique on oncological outcomes. A future paradigm could include modification of intended approach to bladder neck dissection when anterior base lesions are identified on pre-operative MRI.

Cervical and Incisal Marginal Discrepancy in Ceramic Laminate Veneering Materials: A SEM Analysis

PubMed Central

Ranganathan, Hemalatha; Ganapathy, Dhanraj M.; Jain, Ashish R.

2017-01-01

Context: Marginal discrepancy influenced by the choice of processing material used for the ceramic laminate veneers needs to be explored further for better clinical application. Aims: This study aimed to evaluate the amount of cervical and incisal marginal discrepancy associated with different ceramic laminate veneering materials. Settings and Design: This was an experimental, single-blinded, in vitro trial. Subjects and Methods: Ten central incisors were prepared for laminate veneers with 2 mm uniform reduction and heavy chamfer finish line. Ceramic laminate veneers fabricated over the prepared teeth using four different processing materials were categorized into four groups as Group I - aluminous porcelain veneers, Group II - lithium disilicate ceramic veneers, Group III - lithium disilicate-leucite-based veneers, Group IV - zirconia-based ceramic veneers. The cervical and incisal marginal discrepancy was measured using a scanning electron microscope. Statistical Analysis Used: ANOVA and post hoc Tukey honest significant difference (HSD) tests were used for statistical analysis. Results: The cervical and incisal marginal discrepancy for four groups was Group I - 114.6 ± 4.3 μm, 132.5 ± 6.5 μm, Group II - 86.1 ± 6.3 μm, 105.4 ± 5.3 μm, Group III - 71.4 ± 4.4 μm, 91.3 ± 4.7 μm, and Group IV - 123.1 ± 4.1 μm, 142.0 ± 5.4 μm. ANOVA and post hoc Tukey HSD tests observed a statistically significant difference between the four test specimens with regard to cervical marginal discrepancy. The cervical and incisal marginal discrepancy scored F = 243.408, P < 0.001 and F = 180.844, P < 0.001, respectively. Conclusion: This study concluded veneers fabricated using leucite reinforced lithium disilicate exhibited the least marginal discrepancy followed by lithium disilicate ceramic, aluminous porcelain, and zirconia-based ceramics. The marginal discrepancy was more in the incisal region than in the cervical region in all the groups. PMID:28839415

Cervical and Incisal Marginal Discrepancy in Ceramic Laminate Veneering Materials: A SEM Analysis.

PubMed

Ranganathan, Hemalatha; Ganapathy, Dhanraj M; Jain, Ashish R

2017-01-01

Marginal discrepancy influenced by the choice of processing material used for the ceramic laminate veneers needs to be explored further for better clinical application. This study aimed to evaluate the amount of cervical and incisal marginal discrepancy associated with different ceramic laminate veneering materials. This was an experimental, single-blinded, in vitro trial. Ten central incisors were prepared for laminate veneers with 2 mm uniform reduction and heavy chamfer finish line. Ceramic laminate veneers fabricated over the prepared teeth using four different processing materials were categorized into four groups as Group I - aluminous porcelain veneers, Group II - lithium disilicate ceramic veneers, Group III - lithium disilicate-leucite-based veneers, Group IV - zirconia-based ceramic veneers. The cervical and incisal marginal discrepancy was measured using a scanning electron microscope. ANOVA and post hoc Tukey honest significant difference (HSD) tests were used for statistical analysis. The cervical and incisal marginal discrepancy for four groups was Group I - 114.6 ± 4.3 μm, 132.5 ± 6.5 μm, Group II - 86.1 ± 6.3 μm, 105.4 ± 5.3 μm, Group III - 71.4 ± 4.4 μm, 91.3 ± 4.7 μm, and Group IV - 123.1 ± 4.1 μm, 142.0 ± 5.4 μm. ANOVA and post hoc Tukey HSD tests observed a statistically significant difference between the four test specimens with regard to cervical marginal discrepancy. The cervical and incisal marginal discrepancy scored F = 243.408, P < 0.001 and F = 180.844, P < 0.001, respectively. This study concluded veneers fabricated using leucite reinforced lithium disilicate exhibited the least marginal discrepancy followed by lithium disilicate ceramic, aluminous porcelain, and zirconia-based ceramics. The marginal discrepancy was more in the incisal region than in the cervical region in all the groups.

Future coral reef habitat marginality: Temporal and spatial effects of climate change in the Pacific basin

USGS Publications Warehouse

Guinotte, J.M.; Buddemeier, R.W.; Kleypas, J.A.

2003-01-01

Marginal reef habitats are regarded as regions where coral reefs and coral communities reflect the effects of steady-state or long-term average environmental limitations. We used classifications based on this concept with predicted time-variant conditions of future climate to develop a scenario for the evolution of future marginality. Model results based on a conservative scenario of atmospheric CO2 increase were used to examine changes in sea surface temperature and aragonite saturation state over the Pacific Ocean basin until 2069. Results of the projections indicated that essentially all reef locations are likely to become marginal with respect to aragonite saturation state. Significant areas, including some with the highest biodiversity, are expected to experience high-temperature regimes that may be marginal, and additional areas will enter the borderline high temperature range that have experienced significant ENSO-related bleaching in the recent past. The positive effects of warming in areas that are presently marginal in terms of low temperature were limited. Conditions of the late 21st century do not lie outside the ranges in which present-day marginal reef systems occur. Adaptive and acclimative capabilities of organisms and communities will be critical in determining the future of coral reef ecosystems.

GEOLOGIC ASPECTS OF TIGHT GAS RESERVOIRS IN THE ROCKY MOUNTAIN REGION.

USGS Publications Warehouse

Spencer, Charles W.

1985-01-01

The authors describe some geologic characteristics of tight gas reservoirs in the Rocky Mountain region. These reservoirs usually have an in-situ permeability to gas of 0. 1 md or less and can be classified into four general geologic and engineering categories: (1) marginal marine blanket, (2) lenticular, (3) chalk, and (4) marine blanket shallow. Microscopic study of pore/permeability relationships indicates the existence of two varieties of tight reservoirs. One variety is tight because of the fine grain size of the rock. The second variety is tight because the rock is relatively tightly cemented and the pores are poorly connected by small pore throats and capillaries.

Disease Control After Reduced Volume Conformal and Intensity Modulated Radiation Therapy for Childhood Craniopharyngioma

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

Merchant, Thomas E., E-mail: thomas.merchant@stjude.org; Kun, Larry E.; Hua, Chia-Ho

2013-03-15

Purpose: To estimate the rate of disease control after conformal radiation therapy using reduced clinical target volume (CTV) margins and to determine factors that predict for tumor progression. Methods and Materials: Eighty-eight children (median age, 8.5 years; range, 3.2-17.6 years) received conformal or intensity modulated radiation therapy between 1998 and 2009. The study group included those prospectively treated from 1998 to 2003, using a 10-mm CTV, defined as the margin surrounding the solid and cystic tumor targeted to receive the prescription dose of 54 Gy. The CTV margin was subsequently reduced after 2003, yielding 2 groups of patients: those treatedmore » with a CTV margin greater than 5 mm (n=26) and those treated with a CTV margin less than or equal to 5 mm (n=62). Disease progression was estimated on the basis of additional variables including sex, race, extent of resection, tumor interventions, target volume margins, and frequency of weekly surveillance magnetic resonance (MR) imaging during radiation therapy. Median follow-up was 5 years. Results: There was no difference between progression-free survival rates based on CTV margins (>5 mm vs ≤5 mm) at 5 years (88.1% ± 6.3% vs 96.2% ± 4.4% [P=.6386]). There were no differences based on planning target volume (PTV) margins (or combined CTV plus PTV margins). The PTV was systematically reduced from 5 to 3 mm during the time period of the study. Factors predictive of superior progression-free survival included Caucasian race (P=.0175), no requirement for cerebrospinal fluid shunting (P=.0066), and number of surveillance imaging studies during treatment (P=.0216). Patients whose treatment protocol included a higher number of weekly surveillance MR imaging evaluations had a lower rate of tumor progression. Conclusions: These results suggest that targeted volume reductions for radiation therapy using smaller margins are feasible and safe but require careful monitoring. We are currently investigating the differences in outcome based on host factors to explain the results.« less

Chaotic Particle Swarm Optimization with Mutation for Classification

PubMed Central

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms. PMID:25709937

Evaluating pixel and object based image classification techniques for mapping plant invasions from UAV derived aerial imagery: Harrisia pomanensis as a case study

NASA Astrophysics Data System (ADS)

Mafanya, Madodomzi; Tsele, Philemon; Botai, Joel; Manyama, Phetole; Swart, Barend; Monate, Thabang

2017-07-01

Invasive alien plants (IAPs) not only pose a serious threat to biodiversity and water resources but also have impacts on human and animal wellbeing. To support decision making in IAPs monitoring, semi-automated image classifiers which are capable of extracting valuable information in remotely sensed data are vital. This study evaluated the mapping accuracies of supervised and unsupervised image classifiers for mapping Harrisia pomanensis (a cactus plant commonly known as the Midnight Lady) using two interlinked evaluation strategies i.e. point and area based accuracy assessment. Results of the point-based accuracy assessment show that with reference to 219 ground control points, the supervised image classifiers (i.e. Maxver and Bhattacharya) mapped H. pomanensis better than the unsupervised image classifiers (i.e. K-mediuns, Euclidian Length and Isoseg). In this regard, user and producer accuracies were 82.4% and 84% respectively for the Maxver classifier. The user and producer accuracies for the Bhattacharya classifier were 90% and 95.7%, respectively. Though the Maxver produced a higher overall accuracy and Kappa estimate than the Bhattacharya classifier, the Maxver Kappa estimate of 0.8305 is not significantly (statistically) greater than the Bhattacharya Kappa estimate of 0.8088 at a 95% confidence interval. The area based accuracy assessment results show that the Bhattacharya classifier estimated the spatial extent of H. pomanensis with an average mapping accuracy of 86.1% whereas the Maxver classifier only gave an average mapping accuracy of 65.2%. Based on these results, the Bhattacharya classifier is therefore recommended for mapping H. pomanensis. These findings will aid in the algorithm choice making for the development of a semi-automated image classification system for mapping IAPs.

A Systematic Review of Training Interventions Addressing Sexual Violence against Marginalized At-Risk Groups of Women

ERIC Educational Resources Information Center

Kouta, Christiana; Pithara, Christalla; Zobnina, Anna; Apostolidou, Zoe; Christodoulou, Josie; Papadakaki, Maria; Chliaoutakis, Joannes

2015-01-01

Women from marginalized groups working in occupations such as domestic work are at increased risk for sexual violence. Scarce evidence exists about training interventions targeting such groups. The article aims to identify community and workplace-based training interventions aiming to increase capacity among marginalized at-risk women to deal with…

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.

Comparison of microleakage of three acid-base luting cements versus one resin-bonded cement for Class V direct composite inlays.

PubMed

Piemjai, Morakot; Miyasaka, Kumiko; Iwasaki, Yasuhiko; Nakabayashi, Nobuo

2002-12-01

Demineralized dentin beneath set cement may adversely affect microleakage under fixed restorations. Microleakage of direct composite inlays cemented with acid-base cements and a methyl methacrylate resin cement were evaluated to determine their effect on the integrity of the underlying hybridized dentin. Sixty Class V box preparations (3 mm x 3 mm x 1.5 mm) were precisely prepared in previously frozen bovine teeth with one margin in enamel and another margin in dentin. Direct composite inlays (EPIC-TMPT) for each preparation were divided into 4 groups of 15 specimens each and cemented with 3 acid-base cements (control group): Elite, Ketac-Cem, Hy-Bond Carbo-Cem, and 1 adhesive resin cement: C&B Metabond. All specimens were stored in distilled water for 24 hours at 37 degrees C before immersion in 0.5% basic fuchsin for 24 hours. The dye penetration was measured on the sectioned specimens at the tooth-cement interface of enamel and cementum margins and recorded with graded criteria under light microscopy (Olympus Vanox-T) at original magnification x 50, 100, and 200. A Kruskal-Wallis and the Mann-Whitney test at P<.05 were used to analyze leakage score. All cementum margins of the 3 acid-base cements tested demonstrated significantly higher leakage scores than cementum margins for inlays cemented with the resin cement tested(P<.01). No leakage along the tooth-cement interface was found for inlays retained with the adhesive resin cement. Within the limitations of this study, the 3 acid-base cements tested exhibited greater microleakage at the cementum margins than did the adhesive resin cement that was tested.

Recognition of medication information from discharge summaries using ensembles of classifiers.

PubMed

Doan, Son; Collier, Nigel; Xu, Hua; Pham, Hoang Duy; Tu, Minh Phuong

2012-05-07

Extraction of clinical information such as medications or problems from clinical text is an important task of clinical natural language processing (NLP). Rule-based methods are often used in clinical NLP systems because they are easy to adapt and customize. Recently, supervised machine learning methods have proven to be effective in clinical NLP as well. However, combining different classifiers to further improve the performance of clinical entity recognition systems has not been investigated extensively. Combining classifiers into an ensemble classifier presents both challenges and opportunities to improve performance in such NLP tasks. We investigated ensemble classifiers that used different voting strategies to combine outputs from three individual classifiers: a rule-based system, a support vector machine (SVM) based system, and a conditional random field (CRF) based system. Three voting methods were proposed and evaluated using the annotated data sets from the 2009 i2b2 NLP challenge: simple majority, local SVM-based voting, and local CRF-based voting. Evaluation on 268 manually annotated discharge summaries from the i2b2 challenge showed that the local CRF-based voting method achieved the best F-score of 90.84% (94.11% Precision, 87.81% Recall) for 10-fold cross-validation. We then compared our systems with the first-ranked system in the challenge by using the same training and test sets. Our system based on majority voting achieved a better F-score of 89.65% (93.91% Precision, 85.76% Recall) than the previously reported F-score of 89.19% (93.78% Precision, 85.03% Recall) by the first-ranked system in the challenge. Our experimental results using the 2009 i2b2 challenge datasets showed that ensemble classifiers that combine individual classifiers into a voting system could achieve better performance than a single classifier in recognizing medication information from clinical text. It suggests that simple strategies that can be easily implemented such as majority voting could have the potential to significantly improve clinical entity recognition.

Optimal moment determination in POME-copula based hydrometeorological dependence modelling

NASA Astrophysics Data System (ADS)

Liu, Dengfeng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi

2017-07-01

Copula has been commonly applied in multivariate modelling in various fields where marginal distribution inference is a key element. To develop a flexible, unbiased mathematical inference framework in hydrometeorological multivariate applications, the principle of maximum entropy (POME) is being increasingly coupled with copula. However, in previous POME-based studies, determination of optimal moment constraints has generally not been considered. The main contribution of this study is the determination of optimal moments for POME for developing a coupled optimal moment-POME-copula framework to model hydrometeorological multivariate events. In this framework, margins (marginals, or marginal distributions) are derived with the use of POME, subject to optimal moment constraints. Then, various candidate copulas are constructed according to the derived margins, and finally the most probable one is determined, based on goodness-of-fit statistics. This optimal moment-POME-copula framework is applied to model the dependence patterns of three types of hydrometeorological events: (i) single-site streamflow-water level; (ii) multi-site streamflow; and (iii) multi-site precipitation, with data collected from Yichang and Hankou in the Yangtze River basin, China. Results indicate that the optimal-moment POME is more accurate in margin fitting and the corresponding copulas reflect a good statistical performance in correlation simulation. Also, the derived copulas, capturing more patterns which traditional correlation coefficients cannot reflect, provide an efficient way in other applied scenarios concerning hydrometeorological multivariate modelling.

Silica-gold nanoshells as potential intraoperative molecular probes for HER2-overexpression in ex vivo breast tissue using near-infrared reflectance confocal microscopy.

PubMed

Bickford, Lissett R; Agollah, Germaine; Drezek, Rebekah; Yu, Tse-Kuan

2010-04-01

Obtaining negative margins is critical for breast cancer patients undergoing conservation therapy in order to reduce the reemergence of the original cancer. Currently, breast cancer tumor margins are examined in a pathology lab either while the patient is anesthetized or after the surgical procedure has been terminated. These current methods often result in cancer cells present at the surgical resection margin due to inadequate margin assessment at the point of care. Due to such limitations evident in current diagnoses, tools for increasing the accuracy and speed of tumor margin detection directly in the operating room are still needed. We are exploring the potential of using a nano-biophotonics system to facilitate intraoperative tumor margin assessment ex vivo at the cellular level. By combining bioconjugated silica-based gold nanoshells, which scatter light in the near-infrared, with a portable FDA-approved reflectance confocal microscope, we first validate the use of gold nanoshells as effective reflectance-based imaging probes by evaluating the contrast enhancement of three different HER2-overexpressing cell lines. Additionally, we demonstrate the ability to detect HER2-overexpressing cells in human tissue sections within 5 min of incubation time. This work supports the use of targeted silica-based gold nanoshells as potential real-time molecular probes for HER2-overexpression in human tissue.

EUS-guided biopsy for the diagnosis and classification of lymphoma.

PubMed

Ribeiro, Afonso; Pereira, Denise; Escalón, Maricer P; Goodman, Mark; Byrne, Gerald E

2010-04-01

EUS-guided FNA and Tru-cut biopsy (TCB) is highly accurate in the diagnosis of lymphoma. Subclassification, however, may be difficult in low-grade non-Hodgkin lymphoma and Hodgkin lymphoma. To determine the yield of EUS-guided biopsy to classify lymphoma based on the World Health Organization classification of tumors of hematopoietic lymphoid tissues. Retrospective study. Tertiary referral center. A total of 24 patients referred for EUS-guided biopsy who had a final diagnosis of lymphoma or "highly suspicious for lymphoma." EUS-guided FNA and TCB combined with flow cytometry (FC) analysis. MAIN OUTCOMES MEASUREMENT: Lymphoma subclassification accuracy of EUS guided biopsy. Twenty-four patients were included in this study. Twenty-three patients underwent EUS-FNA, and 1 patient had only TCB. Twenty-two underwent EUS-TCB combined with FNA. EUS correctly diagnosed lymphoma in 19 out of 24 patients (79%), and subclassification was determined in 16 patients (66.6%). Flow cytometry correctly identified B-cell monoclonality in 95% (18 out of 19). In 1 patient diagnosed as having marginal-zone lymphoma by EUS-FNA/FC only, the diagnosis was changed to hairy cell leukemia after a bone marrow biopsy was obtained. EUS had a lower yield in nonlarge B-cell lymphoma (only 9 out of 15 cases [60%]) compared with large B-cell lymphoma (78%; P = .3 [Fisher exact test]). Retrospective, small number of patients. EUS-guided biopsy has a lower yield to correctly classify Hodgkin lymphoma and low-grade lymphoma compared with high-grade diffuse large B-cell lymphoma. Copyright 2010 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

Water-quality characteristics of Montana streams in a statewide monitoring network, 1999-2003

USGS Publications Warehouse

Lambing, John H.; Cleasby, Thomas E.

2006-01-01

A statewide monitoring network of 38 sites was operated during 1999-2003 in cooperation with the Montana Department of Environmental Quality to provide a broad geographic base of water-quality information on Montana streams. The purpose of this report is to summarize and describe the water-quality characteristics for those sites. Samples were collected at U.S. Geological Survey streamflow-gaging stations in the Missouri, Yellowstone, and Columbia River basins for stream properties, nutrients, suspended sediment, major ions, and selected trace elements. Mean annual streamflows were below normal during the period, which likely influenced water quality. Continuous water-temperature monitors were operated at 26 sites. The median of daily mean water temperatures for the June-August summer period ranged from 12.5 degC at Kootenai River below Libby Dam to 23.0 degC at Poplar River near Poplar and Tongue River at Miles City. In general, sites in the Missouri River basin commonly had the highest water temperatures. Median daily mean summer water temperatures at four sites (Jefferson River near Three Forks, Missouri River at Toston, Judith River near Winifred, and Poplar River near Poplar) classified as supporting or marginally supporting cold-water biota exceeded the general guideline of 19.4 degC for cold-water biota. Median daily mean temperatures at sites in the network classified as supporting warm-water biota did not exceed the guideline of 26.7 degC for warm-water biota, although several sites exceeded the warm-water guideline on several days during the summer. More...

Verb-raising and Numeral Classifiers in Japanese: Incompatible Bedfellows.

ERIC Educational Resources Information Center

Fukushima, Kazuhiko

2003-01-01

Examines verb raising in Japanese and looks at Koizumi's (2000) evidence for verb-raising based on data involving, among other things, numeral classifiers. Demonstrates that Koizumi's evidence based on numeral classifiers does not support his claim that verb-raising occurs in Japanese. (Author/VWL)

Class-specific Error Bounds for Ensemble Classifiers

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

Prenger, R; Lemmond, T; Varshney, K

2009-10-06

The generalization error, or probability of misclassification, of ensemble classifiers has been shown to be bounded above by a function of the mean correlation between the constituent (i.e., base) classifiers and their average strength. This bound suggests that increasing the strength and/or decreasing the correlation of an ensemble's base classifiers may yield improved performance under the assumption of equal error costs. However, this and other existing bounds do not directly address application spaces in which error costs are inherently unequal. For applications involving binary classification, Receiver Operating Characteristic (ROC) curves, performance curves that explicitly trade off false alarms and missedmore » detections, are often utilized to support decision making. To address performance optimization in this context, we have developed a lower bound for the entire ROC curve that can be expressed in terms of the class-specific strength and correlation of the base classifiers. We present empirical analyses demonstrating the efficacy of these bounds in predicting relative classifier performance. In addition, we specify performance regions of the ROC curve that are naturally delineated by the class-specific strengths of the base classifiers and show that each of these regions can be associated with a unique set of guidelines for performance optimization of binary classifiers within unequal error cost regimes.« less

Automated identification of Monogeneans using digital image processing and K-nearest neighbour approaches.

PubMed

Yousef Kalafi, Elham; Tan, Wooi Boon; Town, Christopher; Dhillon, Sarinder Kaur

2016-12-22

Monogeneans are flatworms (Platyhelminthes) that are primarily found on gills and skin of fishes. Monogenean parasites have attachment appendages at their haptoral regions that help them to move about the body surface and feed on skin and gill debris. Haptoral attachment organs consist of sclerotized hard parts such as hooks, anchors and marginal hooks. Monogenean species are differentiated based on their haptoral bars, anchors, marginal hooks, reproductive parts' (male and female copulatory organs) morphological characters and soft anatomical parts. The complex structure of these diagnostic organs and also their overlapping in microscopic digital images are impediments for developing fully automated identification system for monogeneans (LNCS 7666:256-263, 2012), (ISDA; 457-462, 2011), (J Zoolog Syst Evol Res 52(2): 95-99. 2013;). In this study images of hard parts of the haptoral organs such as bars and anchors are used to develop a fully automated identification technique for monogenean species identification by implementing image processing techniques and machine learning methods. Images of four monogenean species namely Sinodiplectanotrema malayanus, Trianchoratus pahangensis, Metahaliotrema mizellei and Metahaliotrema sp. (undescribed) were used to develop an automated technique for identification. K-nearest neighbour (KNN) was applied to classify the monogenean specimens based on the extracted features. 50% of the dataset was used for training and the other 50% was used as testing for system evaluation. Our approach demonstrated overall classification accuracy of 90%. In this study Leave One Out (LOO) cross validation is used for validation of our system and the accuracy is 91.25%. The methods presented in this study facilitate fast and accurate fully automated classification of monogeneans at the species level. In future studies more classes will be included in the model, the time to capture the monogenean images will be reduced and improvements in extraction and selection of features will be implemented.

Hybrid ANN optimized artificial fish swarm algorithm based classifier for classification of suspicious lesions in breast DCE-MRI

NASA Astrophysics Data System (ADS)

Janaki Sathya, D.; Geetha, K.

2017-12-01

Automatic mass or lesion classification systems are developed to aid in distinguishing between malignant and benign lesions present in the breast DCE-MR images, the systems need to improve both the sensitivity and specificity of DCE-MR image interpretation in order to be successful for clinical use. A new classifier (a set of features together with a classification method) based on artificial neural networks trained using artificial fish swarm optimization (AFSO) algorithm is proposed in this paper. The basic idea behind the proposed classifier is to use AFSO algorithm for searching the best combination of synaptic weights for the neural network. An optimal set of features based on the statistical textural features is presented. The investigational outcomes of the proposed suspicious lesion classifier algorithm therefore confirm that the resulting classifier performs better than other such classifiers reported in the literature. Therefore this classifier demonstrates that the improvement in both the sensitivity and specificity are possible through automated image analysis.

Automatic classification of time-variable X-ray sources

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

Lo, Kitty K.; Farrell, Sean; Murphy, Tara

2014-05-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, andmore » other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ∼97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7–500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.« less

Analysis of dual tree M-band wavelet transform based features for brain image classification.

PubMed

Ayalapogu, Ratna Raju; Pabboju, Suresh; Ramisetty, Rajeswara Rao

2018-04-29

The most complex organ in the human body is the brain. The unrestrained growth of cells in the brain is called a brain tumor. The cause of a brain tumor is still unknown and the survival rate is lower than other types of cancers. Hence, early detection is very important for proper treatment. In this study, an efficient computer-aided diagnosis (CAD) system is presented for brain image classification by analyzing MRI of the brain. At first, the MRI brain images of normal and abnormal categories are modeled by using the statistical features of dual tree m-band wavelet transform (DTMBWT). A maximum margin classifier, support vector machine (SVM) is then used for the classification and validated with k-fold approach. Results show that the system provides promising results on a repository of molecular brain neoplasia data (REMBRANDT) with 97.5% accuracy using 4 th level statistical features of DTMBWT. Viewing the experimental results, we conclude that the system gives a satisfactory performance for the brain image classification. © 2018 International Society for Magnetic Resonance in Medicine.

Sociocultural influences on science and on science identities

NASA Astrophysics Data System (ADS)

Guerra, Andreia; Rezende, Flavia

2017-06-01

Angela Chapman and Allan Feldman (2016) conducted a study that aimed to exam how a group of diverse urban high school students were affected by the participation in a contextually based authentic science experience. The analysis of all data led the authors to conclude that the experience of authentic science positively influenced the science identity of students and promoted a shift in perceptions from stereotypical to more diverse views of scientists. For the purpose of this forum paper, we concentrated on the unexpected results of Hispanic students in the IAS instrument. In the authors' interpretation, Hispanic students were classified as non science identities because they do not feel recognized as a particular kind of student in that school, being possibly more marginalized than other students. We tried to expand the discussion bringing the contribution of a sociocultural approach of science construction and of science identity to enrich some of the issues involved. Our concise analysis does not allow conclusions about the Hispanic students' results, but we believe it helped to understand sociocultural problems involved in their science identity and to reveal the inequality in science production as one of these problems.

Energy minimization in medical image analysis: Methodologies and applications.

PubMed

Zhao, Feng; Xie, Xianghua

2016-02-01

Energy minimization is of particular interest in medical image analysis. In the past two decades, a variety of optimization schemes have been developed. In this paper, we present a comprehensive survey of the state-of-the-art optimization approaches. These algorithms are mainly classified into two categories: continuous method and discrete method. The former includes Newton-Raphson method, gradient descent method, conjugate gradient method, proximal gradient method, coordinate descent method, and genetic algorithm-based method, while the latter covers graph cuts method, belief propagation method, tree-reweighted message passing method, linear programming method, maximum margin learning method, simulated annealing method, and iterated conditional modes method. We also discuss the minimal surface method, primal-dual method, and the multi-objective optimization method. In addition, we review several comparative studies that evaluate the performance of different minimization techniques in terms of accuracy, efficiency, or complexity. These optimization techniques are widely used in many medical applications, for example, image segmentation, registration, reconstruction, motion tracking, and compressed sensing. We thus give an overview on those applications as well. Copyright © 2015 John Wiley & Sons, Ltd.

Research of facial feature extraction based on MMC

NASA Astrophysics Data System (ADS)

Xue, Donglin; Zhao, Jiufen; Tang, Qinhong; Shi, Shaokun

2017-07-01

Based on the maximum margin criterion (MMC), a new algorithm of statistically uncorrelated optimal discriminant vectors and a new algorithm of orthogonal optimal discriminant vectors for feature extraction were proposed. The purpose of the maximum margin criterion is to maximize the inter-class scatter while simultaneously minimizing the intra-class scatter after the projection. Compared with original MMC method and principal component analysis (PCA) method, the proposed methods are better in terms of reducing or eliminating the statistically correlation between features and improving recognition rate. The experiment results on Olivetti Research Laboratory (ORL) face database shows that the new feature extraction method of statistically uncorrelated maximum margin criterion (SUMMC) are better in terms of recognition rate and stability. Besides, the relations between maximum margin criterion and Fisher criterion for feature extraction were revealed.

Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

A method for identifying EMI critical circuits during development of a large C3

NASA Astrophysics Data System (ADS)

Barr, Douglas H.

The circuit analysis methods and process Boeing Aerospace used on a large, ground-based military command, control, and communications (C3) system are described. This analysis was designed to help identify electromagnetic interference (EMI) critical circuits. The methodology used the MIL-E-6051 equipment criticality categories as the basis for defining critical circuits, relational database technology to help sort through and account for all of the approximately 5000 system signal cables, and Macintosh Plus personal computers to predict critical circuits based on safety margin analysis. The EMI circuit analysis process systematically examined all system circuits to identify which ones were likely to be EMI critical. The process used two separate, sequential safety margin analyses to identify critical circuits (conservative safety margin analysis, and detailed safety margin analysis). These analyses used field-to-wire and wire-to-wire coupling models using both worst-case and detailed circuit parameters (physical and electrical) to predict circuit safety margins. This process identified the predicted critical circuits that could then be verified by test.

The composition and structure of volcanic rifted continental margins in the North Atlantic: Further insight from shear waves

NASA Astrophysics Data System (ADS)

Eccles, Jennifer D.; White, Robert S.; Christie, Philip A. F.

2011-07-01

Imaging challenges caused by highly attenuative flood basalt sequences have resulted in the understanding of volcanic rifted continental margins lagging behind that of non-volcanic rifted and convergent margins. Massive volcanism occurred during break-up at 70% of the passive margins bordering the Atlantic Ocean, the causes and dynamics of which are still debated. This paper shows results from traveltime tomography of compressional and converted shear wave arrivals recorded on 170 four-component ocean bottom seismometers along two North Atlantic continental margin profiles. This traveltime tomography was performed using two different approaches. The first, a flexible layer-based parameterisation, enables the quality control of traveltime picks and investigation of the crustal structure. The second, with a regularised grid-based parameterisation, requires correction of converted shear wave traveltimes to effective symmetric raypaths and allows exploration of the model space via Monte Carlo analyses. The velocity models indicate high lower-crustal velocities and sharp transitions in both velocity and Vp/Vs ratios across the continent-ocean transition. The velocities are consistent with established mixing trends between felsic continental crust and high magnesium mafic rock on both margins. Interpretation of the high quality seismic reflection profile on the Faroes margin confirms that this mixing is through crustal intrusion. Converted shear wave data also provide constraints on the sub-basalt lithology on the Faroes margin, which is interpreted as a pre-break-up Mesozoic to Paleocene sedimentary system intruded by sills.

[Retroperitoneal liposarcoma as etiology of abdominal pain. Case report and literature review].

PubMed

Pérez-Ponce, Yisvanth; Castellanos-Alejandre, Raúl; Guerrero-Romero, J Francisco; Estrada-León, Felipe; Torres-Lobatón, Alfonso

2008-01-01

Soft tissue sarcomas are very uncommon types of tumors, with their embryological origin in the mesoderm and in nerve structures of the neuroectodermic layer. They represent only 1.5% of cases in the National Registry of Malignant Tumors in Mexico. They can be encountered anywhere connective soft tissue is found. Because of their specialized localization, retroperitoneal soft tissue sarcomas have a propensity to remain asymptomatic for long periods of time and reach a large size before being diagnosed. The only accepted treatment is wide surgical excision with clear margins, without a clear benefit for adjuvant treatment. The very uncommon nature of these tumors and their varied histopathology, site and behavior classify them as a difficult entity in terms of treatment. We present here the case of a 66-year-old female with a left-side retroperitoneal tumor, complaining only of vague abdominal pain as the presenting symptom. A CT-guided needle biopsy reported a sarcoma and the patient was subjected to laparatomy with complete resection of the tumor (30 x 13 x 10 cm). Histopathological report demonstrated a low-grade retroperitoneal sarcoma and free macroscopic and microscopic borders, without obvious invasion except for left kidney and ureter. The patient refused adjuvant treatment, and she is disease-free 7 years after treatment. Retroperitoneal sarcomas can cause pain and reach very large sizes. The best treatment available is wide surgical resection with clear margins. The most important prognostic factors are free margins, type of resection, age of patient and tumor histology.

Liver Transplantation Using Grafts From Donors After Circulatory Death: A Propensity Score-Matched Study From a Single Center.

PubMed

Laing, R W; Scalera, I; Isaac, J; Mergental, H; Mirza, D F; Hodson, J; Wilkin, R J W; Perera, M T P R; Muiesan, P

2016-06-01

The use of livers from donation after circulatory death (DCD) is increasing, but concerns exist regarding outcomes following use of grafts from "marginal" donors. To compare outcomes in transplants using DCD and donation after brain death (DBD), propensity score matching was performed for 973 patients with chronic liver disease and/or malignancy who underwent primary whole-liver transplant between 2004 and 2014 at University Hospitals Birmingham NHS Foundation Trust. Primary end points were overall graft and patient survival. Secondary end points included postoperative, biliary and vascular complications. Over 10 years, 234 transplants were carried out using DCD grafts. Of the 187 matched DCDs, 82.9% were classified as marginal per British Transplantation Society guidelines. Kaplan-Meier analysis of graft and patient survival found no significant differences for either outcome between the paired DCD and DBD patients (p = 0.162 and p = 0.519, respectively). Aspartate aminotransferase was significantly higher in DCD recipients until 48 h after transplant (p < 0.001). The incidences of acute kidney injury and ischemic cholangiopathy were greater in DCD recipients (32.6% vs. 15% [p < 0.001] and 9.1% vs. 1.1% [p < 0.001], respectively). With appropriate recipient selection, the use of DCDs, including those deemed marginal, can be safe and can produce outcomes comparable to those seen using DBD grafts in similar recipients. © Copyright 2016 The American Society of Transplantation and the American Society of Transplant Surgeons.

Resistor-logic demultiplexers for nanoelectronics based on constant-weight codes.

PubMed

Kuekes, Philip J; Robinett, Warren; Roth, Ron M; Seroussi, Gadiel; Snider, Gregory S; Stanley Williams, R

2006-02-28

The voltage margin of a resistor-logic demultiplexer can be improved significantly by basing its connection pattern on a constant-weight code. Each distinct code determines a unique demultiplexer, and therefore a large family of circuits is defined. We consider using these demultiplexers for building nanoscale crossbar memories, and determine the voltage margin of the memory system based on a particular code. We determine a purely code-theoretic criterion for selecting codes that will yield memories with large voltage margins, which is to minimize the ratio of the maximum to the minimum Hamming distance between distinct codewords. For the specific example of a 64 × 64 crossbar, we discuss what codes provide optimal performance for a memory.

Modeling ocean wave propagation under sea ice covers

NASA Astrophysics Data System (ADS)

Zhao, Xin; Shen, Hayley H.; Cheng, Sukun

2015-02-01

Operational ocean wave models need to work globally, yet current ocean wave models can only treat ice-covered regions crudely. The purpose of this paper is to provide a brief overview of ice effects on wave propagation and different research methodology used in studying these effects. Based on its proximity to land or sea, sea ice can be classified as: landfast ice zone, shear zone, and the marginal ice zone. All ice covers attenuate wave energy. Only long swells can penetrate deep into an ice cover. Being closest to open water, wave propagation in the marginal ice zone is the most complex to model. The physical appearance of sea ice in the marginal ice zone varies. Grease ice, pancake ice, brash ice, floe aggregates, and continuous ice sheet may be found in this zone at different times and locations. These types of ice are formed under different thermal-mechanical forcing. There are three classic models that describe wave propagation through an idealized ice cover: mass loading, thin elastic plate, and viscous layer models. From physical arguments we may conjecture that mass loading model is suitable for disjoint aggregates of ice floes much smaller than the wavelength, thin elastic plate model is suitable for a continuous ice sheet, and the viscous layer model is suitable for grease ice. For different sea ice types we may need different wave ice interaction models. A recently proposed viscoelastic model is able to synthesize all three classic models into one. Under suitable limiting conditions it converges to the three previous models. The complete theoretical framework for evaluating wave propagation through various ice covers need to be implemented in the operational ocean wave models. In this review, we introduce the sea ice types, previous wave ice interaction models, wave attenuation mechanisms, the methods to calculate wave reflection and transmission between different ice covers, and the effect of ice floe breaking on shaping the sea ice morphology. Laboratory experiments, field measurements and numerical simulations supporting the fundamental research in wave-ice interaction models are discussed. We conclude with some outlook of future research needs in this field.

Investigation of Tectonic Boundaries in Taiwan Obtained with a Hierarchical Clustering of Dense GNSS Data

NASA Astrophysics Data System (ADS)

Takahashi, A.; Hashimoto, M.; Hu, J. C.; Fukahata, Y.

2017-12-01

Taiwan Island is composed of many geological structures. The main tectonic feature is the collision of the Luzon volcanic arc with the Eurasian continent, which propagates westward and generates complicated crustal deformation. One way to model crustal deformation is to divide Taiwan island into man rigid blocks that moves relatively each other along the boundaries (deformation zones) of the blocks. Since earthquakes tend to occur in the deformation zones, identification of such tectonic boundaries is important. So far, many tectonic boundaries have been proposed on the basis of geology, geomorphology, seismology and geodesy. However, which is the most significant boundary depends on disciplines and there is no way to objectively classify them. Here, we introduce an objective method to identify significant tectonic boundaries with a hierarchical representation proposed by Simpson et al. [2012].We apply a hierarchical agglomerative clustering algorithm to dense GNSS horizontal velocity data in Taiwan. One of the significant merits of the hierarchical representation of the clustering results is that we can consistently explore crustal structures from larger to smaller scales. This is because a higher hierarchy corresponds to a larger crustal structure, and a lower hierarchy corresponds to a smaller crustal structure. Relative motion between clusters can be obtained from this analysis.The first major boundary is identified along the eastern margin of the Longitudinal Valley, which corresponds to the separation of the Philippine Sea plate and the Eurasian continental margin. The second major boundary appears along the Chaochou fault and the Chishan fault in southwestern Taiwan. The third major boundary appears along the eastern margin of the coastal plane. The identified major clusters can be divided into several smaller blocks without losing consistency with geological boundaries. For example, the Fengshun fault, concealed beneath thick sediment layers, is identified. Furthermore, obtained relative motion between clusters demands a reverse fault or a left lateral fault in the off shore of the coastal range.Our clustering based block modeling is consistent with tectonics of Taiwan, implying that observed crustal deformation in Taiwan can be attributed to motion or deformation of shallow structures.

Nanowire NMOS Logic Inverter Characterization.

PubMed

Hashim, Yasir

2016-06-01

This study is the first to demonstrate characteristics optimization of nanowire N-Channel Metal Oxide Semiconductor (NW-MOS) logic inverter. Noise margins and inflection voltage of transfer characteristics are used as limiting factors in this optimization. A computer-based model used to produce static characteristics of NW-NMOS logic inverter. In this research two circuit configuration of NW-NMOS inverter was studied, in first NW-NMOS circuit, the noise margin for (low input-high output) condition was very low. For second NMOS circuit gives excellent noise margins, and results indicate that optimization depends on applied voltage to the inverter. Increasing gate to source voltage with (2/1) nanowires ratio results better noise margins. Increasing of applied DC load transistor voltage tends to increasing in decreasing noise margins; decreasing this voltage will improve noise margins significantly.

Close Margins Less Than 2 mm Are Not Associated With Higher Risks of 10-Year Local Recurrence and Breast Cancer Mortality Compared With Negative Margins in Women Treated With Breast-Conserving Therapy.

PubMed

Tyler, Susan; Truong, Pauline T; Lesperance, Mary; Nichol, Alan; Baliski, Chris; Warburton, Rebecca; Tyldesley, Scott

2018-03-13

The 2014 Society of Surgical Oncology-American Society for Radiation Oncology consensus suggested "no ink on tumor" is a sufficient surgical margin for invasive breast cancer treated with breast-conserving surgery (BCS). Whether close margins <2 mm are associated with inferior outcomes remains controversial. This study evaluated 10-year outcomes by margin status in a population-based cohort treated with BCS and adjuvant radiation therapy (RT). The subjects were 10,863 women with invasive cancer categorized as pT1 to T3, any N, and M0 referred from 2001 to 2011, an era in which the institutional policy was to re-excise close or positive margins, except in select cases. All women underwent BCS and whole-breast RT with or without boost RT. Local recurrence (LR) and breast cancer-specific survival (BCSS) were examined using competing-risk analysis in cohorts with negative (≥2 mm; n = 9241, 85%), close (<2 mm; n = 1310, 12%), or positive (tumor touching ink; n = 312, 3%) margins. Multivariable analysis and matched-pair analysis were performed. The median follow-up period was 8 years. Systemic therapy was used in 87% of patients. Boost RT was used in 34.1%, 76.9%, and 79.5% of patients with negative, close, and positive margins, respectively. In the negative, close, and positive margin cohorts, the 10-year cumulative incidence of LR was 1.8%, 2.0%, and 1.1%, respectively (P = .759). Corresponding BCSS estimates were 93.9%, 91.8%, and 87.9%, respectively (P < .001). On multivariable analysis, close margins were not associated with increased LR (hazard ratio, 1.25; 95% confidence interval 0.79-1.97; P = .350) or reduced BCSS (hazard ratio, 1.25; 95% confidence interval 0.98-1.58, P = .071) relative to negative margins. On matched-pair analysis, close margin cases had similar LR (P = .114) and BCSS (P = .100) to negative margin controls. Select cases with close or positive margins in this population-based analysis had similar LR and BCSS to cases with negative margins. While these findings do not endorse omitting re-excision for all cases, the data support a policy of accepting carefully selected cases with close margins for adjuvant RT without re-excision. Copyright © 2018 Elsevier Inc. All rights reserved.

Boosting Contextual Information for Deep Neural Network Based Voice Activity Detection

DTIC Science & Technology

2015-02-01

multi-resolution stacking (MRS), which is a stack of ensemble classifiers. Each classifier in a building block inputs the concatenation of the predictions ...a base classifier in MRS, named boosted deep neural network (bDNN). bDNN first generates multiple base predictions from different contexts of a single...frame by only one DNN and then aggregates the base predictions for a better prediction of the frame, and it is different from computationally

Optimal classification for the diagnosis of duchenne muscular dystrophy images using support vector machines.

PubMed

Zhang, Ming-Huan; Ma, Jun-Shan; Shen, Ying; Chen, Ying

2016-09-01

This study aimed to investigate the optimal support vector machines (SVM)-based classifier of duchenne muscular dystrophy (DMD) magnetic resonance imaging (MRI) images. T1-weighted (T1W) and T2-weighted (T2W) images of the 15 boys with DMD and 15 normal controls were obtained. Textural features of the images were extracted and wavelet decomposed, and then, principal features were selected. Scale transform was then performed for MRI images. Afterward, SVM-based classifiers of MRI images were analyzed based on the radical basis function and decomposition levels. The cost (C) parameter and kernel parameter [Formula: see text] were used for classification. Then, the optimal SVM-based classifier, expressed as [Formula: see text]), was identified by performance evaluation (sensitivity, specificity and accuracy). Eight of 12 textural features were selected as principal features (eigenvalues [Formula: see text]). The 16 SVM-based classifiers were obtained using combination of (C, [Formula: see text]), and those with lower C and [Formula: see text] values showed higher performances, especially classifier of [Formula: see text]). The SVM-based classifiers of T1W images showed higher performance than T1W images at the same decomposition level. The T1W images in classifier of [Formula: see text]) at level 2 decomposition showed the highest performance of all, and its overall correct sensitivity, specificity, and accuracy reached 96.9, 97.3, and 97.1 %, respectively. The T1W images in SVM-based classifier [Formula: see text] at level 2 decomposition showed the highest performance of all, demonstrating that it was the optimal classification for the diagnosis of DMD.

Input Decimated Ensembles

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Oza, Nikunj C.; Clancy, Daniel (Technical Monitor)

2001-01-01

Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers' performance levels high is an important area of research. In this article, we explore input decimation (ID), a method which selects feature subsets for their ability to discriminate among the classes and uses them to decouple the base classifiers. We provide a summary of the theoretical benefits of correlation reduction, along with results of our method on two underwater sonar data sets, three benchmarks from the Probenl/UCI repositories, and two synthetic data sets. The results indicate that input decimated ensembles (IDEs) outperform ensembles whose base classifiers use all the input features; randomly selected subsets of features; and features created using principal components analysis, on a wide range of domains.

Impact of Resection Margin Distance on Survival of Pancreatic Cancer: A Systematic Review and Meta-Analysis

PubMed Central

Kim, Kyung Su; Kwon, Jeanny; Kim, Kyubo; Chie, Eui Kyu

2017-01-01

Purpose While curative resection is the only chance of cure in pancreatic cancer, controversies exist about the impact of surgical margin status on survival. Non-standardized pathologic report and different criteria on the R1 status made it difficult to implicate adjuvant therapy after resection based on the margin status. We evaluated the influence of resection margins on survival by meta-analysis. Materials and Methods We thoroughly searched electronic databases of PubMed, EMBASE, and Cochrane Library. We included studies reporting survival outcomes with different margin status: involved margin (R0 mm), margin clearance with ≤ 1 mm (R0-1 mm), and margin with > 1 mm (R>1 mm). Hazard ratio (HR) for overall survival was extracted, and a random-effects model was used for pooled analysis. Results A total of eight retrospective studies involving 1,932 patients were included. Pooled HR for overall survival showed that patients with R>1 mm had reduced risk of death than those with R0-1 mm (HR, 0.74; 95% confidence interval [CI], 0.61 to 0.88; p=0.001). In addition, patients with R0-1 mm had reduced risk of death than those with R0 mm (HR, 0.81; 95% CI, 0.72 to 0.91; p < 0.001). There was no heterogeneity between the included studies (I2 index, 42% and 0%; p=0.10 and p=0.82, respectively). Conclusion Our results suggest that stratification of the patients based on margin status is warranted in the clinical trials assessing the role of adjuvant treatment for pancreatic cancer. PMID:27561314

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

PubMed

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

2011-07-01

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

Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors

NASA Astrophysics Data System (ADS)

Herschtal, A.; te Marvelde, L.; Mengersen, K.; Hosseinifard, Z.; Foroudi, F.; Devereux, T.; Pham, D.; Ball, D.; Greer, P. B.; Pichler, P.; Eade, T.; Kneebone, A.; Bell, L.; Caine, H.; Hindson, B.; Kron, T.

2015-02-01

Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement (‘random error’) than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts -19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements.

Marginal Emissions Factors for Electricity Generation in the Midcontinent ISO.

PubMed

Thind, Maninder P S; Wilson, Elizabeth J; Azevedo, Inês L; Marshall, Julian D

2017-12-19

Environmental consequences of electricity generation are often determined using average emission factors. However, as different interventions are incrementally pursued in electricity systems, the resulting marginal change in emissions may differ from what one would predict based on system-average conditions. Here, we estimate average emission factors and marginal emission factors for CO 2 , SO 2 , and NO x from fossil and nonfossil generators in the Midcontinent Independent System Operator (MISO) region during years 2007-2016. We analyze multiple spatial scales (all MISO; each of the 11 MISO states; each utility; each generator) and use MISO data to characterize differences between the two emission factors (average; marginal). We also explore temporal trends in emissions factors by hour, day, month, and year, as well as the differences that arise from including only fossil generators versus total generation. We find, for example, that marginal emission factors are generally higher during late-night and early morning compared to afternoons. Overall, in MISO, average emission factors are generally higher than marginal estimates (typical difference: ∼20%). This means that the true environmental benefit of an energy efficiency program may be ∼20% smaller than anticipated if one were to use average emissions factors. Our analysis can usefully be extended to other regions to support effective near-term technical, policy and investment decisions based on marginal rather than only average emission factors.

Influence of CAD/CAM systems and cement selection on marginal discrepancy of zirconia-based ceramic crowns.

PubMed

Martínez-Rus, Francisco; Suárez, María J; Rivera, Begoña; Pradíes, Guillermo

2012-04-01

To analyze the effect of ceramic manufacturing technique and luting cement selection on the marginal adaptation of zirconium oxide-based all-ceramic crowns. An extracted mandibular first premolar was prepared for a complete coverage restoration and subsequently duplicated 40 times in a liquid crystal polymer (LCP). All-ceramic crowns (n = 10) were fabricated on LCP models using the following systems: glass-infiltrated zirconia-toughened alumina (In-Ceram Zirconia) and yttrium cation-doped tetragonal zirconia polycrystals (In-Ceram YZ, Cercon, and Procera Zirconia). The restorations (n = 5) were cemented on their respective dies with glass-ionomer cement (Ketac Cem Aplicap) and resin cement (Panavia 21). The absolute marginal discrepancy of the crowns was measured before and after cementation by scanning electronic microscopy at 160 points along the circumferential margin. The data were analyzed using one-way ANOVA for repeated measures and for independent samples, Scheffé's multiple range post hoc test, and Student's t-test (alpha = 0.05). There were statistical differences in the mean marginal openings among the four all-ceramic systems before and after luting (P < 0.0001). The Procera restorations had the lowest pre- and post-cementation values (P < 0.0001). A significant increase in the marginal gap size caused by luting media occurred in all tested groups (P < 0.0001). Resin cement resulted in larger marginal discrepancies than glass-ionomer cement (P < 0.0001).

In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis

PubMed Central

Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang

2009-01-01

Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image. PMID:20057957

Risk strata-based therapy and outcome in stage Ib-IIa carcinoma cervix: single-centre ten-year experience.

PubMed

Kundargi, Rajshekar S; Guruprasad, B; Rathod, Praveen Shankar; Shakuntala, Pn; Shobha, K; Pallavi, Vr; Uma Devi, K; Bafna, Ud

2013-01-01

To review the outcome of stage (Ib, IIa), cervical cancer patients were primarily treated with radical hysterectomy and risk-based postoperative therapy. Between January 2001 and December 2011, 601 cases underwent surgery followed by tailored therapy. Patients were classified into low risk (pelvic lymph node negative, tumour less than 4 cm, no evidence of lympho-vascular invasion, less than one-third of thickness of surgical stoma involved), intermediate risk (positive lympho-vascular space invasion, tumour size more than 4 cm, and deep invasion of cervical stroma), and high risk (pelvic lymph node involved, positive parametrial, or vaginal margins) groups. Postoperative adju-vant therapy in the form of radiotherapy alone to those with intermediate risk and chemo-radiotherapy to those with high risk was given to patients. The median follow-up was 60 months. The majority of patients had intermediate risk. The overall event-free survival (EFS) at five years was 74.37%, with EFS of 86.5% in those from the low-risk group, 73% in those from the intermediate-risk group, and 64% in those from the high-risk group. In conclusion, risk strata-based adjuvant postoperative therapy is able to provide a favourable outcome in patients with stage Ib-IIa cervical cancer with a nearly 11% improvement in survival compared with historical control.

Independent Predictors of Prognosis Based on Oral Cavity Squamous Cell Carcinoma Surgical Margins.

PubMed

Buchakjian, Marisa R; Ginader, Timothy; Tasche, Kendall K; Pagedar, Nitin A; Smith, Brian J; Sperry, Steven M

2018-05-01

Objective To conduct a multivariate analysis of a large cohort of oral cavity squamous cell carcinoma (OCSCC) cases for independent predictors of local recurrence (LR) and overall survival (OS), with emphasis on the relationship between (1) prognosis and (2) main specimen permanent margins and intraoperative tumor bed frozen margins. Study Design Retrospective cohort study. Setting Tertiary academic head and neck cancer program. Subjects and Methods This study included 426 patients treated with OCSCC resection between 2005 and 2014 at University of Iowa Hospitals and Clinics. Patients underwent excision of OCSCC with intraoperative tumor bed frozen margin sampling and main specimen permanent margin assessment. Multivariate analysis of the data set to predict LR and OS was performed. Results Independent predictors of LR included nodal involvement, histologic grade, and main specimen permanent margin status. Specifically, the presence of a positive margin (odds ratio, 6.21; 95% CI, 3.3-11.9) or <1-mm/carcinoma in situ margin (odds ratio, 2.41; 95% CI, 1.19-4.87) on the main specimen was an independent predictor of LR, whereas intraoperative tumor bed margins were not predictive of LR on multivariate analysis. Similarly, independent predictors of OS on multivariate analysis included nodal involvement, extracapsular extension, and a positive main specimen margin. Tumor bed margins did not independently predict OS. Conclusion The main specimen margin is a strong independent predictor of LR and OS on multivariate analysis. Intraoperative tumor bed frozen margins do not independently predict prognosis. We conclude that emphasis should be placed on evaluating the main specimen margins when estimating prognosis after OCSCC resection.

Classification of Multiple Chinese Liquors by Means of a QCM-based E-Nose and MDS-SVM Classifier.

PubMed

Li, Qiang; Gu, Yu; Jia, Jing

2017-01-30

Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method to identify multiple Chinese liquors is of positive significance. This paper presents a pattern recognition system for classifying ten brands of Chinese liquors based on multidimensional scaling (MDS) and support vector machine (SVM) algorithms in a quartz crystal microbalance (QCM)-based electronic nose (e-nose) we designed. We evaluated the comprehensive performance of the MDS-SVM classifier that predicted all ten brands of Chinese liquors individually. The prediction accuracy (98.3%) showed superior performance of the MDS-SVM classifier over the back-propagation artificial neural network (BP-ANN) classifier (93.3%) and moving average-linear discriminant analysis (MA-LDA) classifier (87.6%). The MDS-SVM classifier has reasonable reliability, good fitting and prediction (generalization) performance in classification of the Chinese liquors. Taking both application of the e-nose and validation of the MDS-SVM classifier into account, we have thus created a useful method for the classification of multiple Chinese liquors.

Effect of metal selection and porcelain firing on the marginal accuracy of titanium-based metal ceramic restorations.

PubMed

Shokry, Tamer E; Attia, Mazen; Mosleh, Ihab; Elhosary, Mohamed; Hamza, Tamer; Shen, Chiayi

2010-01-01

Titanium is the most biocompatible metal used for dental casting; however, there is concern about its marginal accuracy after porcelain application since this aspect has direct influence on marginal fit. The purpose of this study was to determine the effect that metal selection and the porcelain firing procedure have on the marginal accuracy of metal ceramic prostheses. Cast CP Ti, milled CP Ti, cast Ti-6Al-7Nb, and cast Ni-Cr copings (n=5) were fired with compatible porcelains (Triceram for titanium-based metals and VITA VMK 95 for Ni-Cr alloy). The Ni-Cr alloy fired with its porcelain served as the control. Photographs of metal copings placed on a master die were made. Marginal discrepancy was determined on the photographs using an image processing program at 8 predetermined locations before airborne-particle abrasion for porcelain application, after firing of the opaque layer, and after firing of the dentin layer. Repeated-measures 2-way ANOVA was used to investigate the effect of metal selection and firing stage, and paired t tests were used to determine the effect of each firing stage within each material group (alpha=.05). ANOVA showed that both metal selection and firing stage significantly influenced the measured marginal discrepancy (P<.001), and there was interaction between the 2 variables (P<.001). Student-Newman-Keuls multiple comparison tests showed that there were significant differences between any 2 metals compared, at each stage of measurement. Paired t tests showed that significant changes in marginal discrepancy occurred with opaque firing on milled CP Ti (P=.017) and cast Ti-6Al-7Nb alloy (P=.003). Titanium copings fabricated by CAD/CAM demonstrated the least marginal discrepancy among all groups, while the base metal (Ni-Cr) groups exhibited the most discrepancy of all groups tested. Copyright 2010 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

An ANN-based HRV classifier for cardiac health prognosis.

PubMed

Sunkaria, Ramesh Kumar; Kumar, Vinod; Saxena, Suresh Chandra; Singhal, Achala M

2014-01-01

A multi-layer artificial neural network (ANN)-based heart rate variability (HRV) classifier has been proposed, which gives the cardiac health status as the output based on HRV of the patients independently of the cardiologists' view. The electrocardiogram (ECG) data of 46 patients were recorded in the out-patient department (OPD) of a hospital and HRV was evaluated using self-designed autoregressive-model-based technique. These patients suspected to be suffering from cardiac abnormalities were thoroughly examined by experienced cardiologists. On the basis of symptoms and other investigations, the attending cardiologists advised them to be classified into four categories as per the severity of cardiac health. Out of 46, the HRV data of 28 patients were used for training and data of 18 patients were used for testing of the proposed classifier. The cardiac health classification of each tested patient with the proposed classifier matches with the medical opinion of the cardiologists.

Robust Combining of Disparate Classifiers Through Order Statistics

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Ghosh, Joydeep

2001-01-01

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

Performance comparison of classifiers for differentiation among obstructive lung diseases based on features of texture analysis at HRCT

NASA Astrophysics Data System (ADS)

Lee, Youngjoo; Seo, Joon Beom; Kang, Bokyoung; Kim, Dongil; Lee, June Goo; Kim, Song Soo; Kim, Namkug; Kang, Suk Ho

2007-03-01

The performance of classification algorithms for differentiating among obstructive lung diseases based on features from texture analysis using HRCT (High Resolution Computerized Tomography) images was compared. HRCT can provide accurate information for the detection of various obstructive lung diseases, including centrilobular emphysema, panlobular emphysema and bronchiolitis obliterans. Features on HRCT images can be subtle, however, particularly in the early stages of disease, and image-based diagnosis is subject to inter-observer variation. To automate the diagnosis and improve the accuracy, we compared three types of automated classification systems, naÃve Bayesian classifier, ANN (Artificial Neural Net) and SVM (Support Vector Machine), based on their ability to differentiate among normal lung and three types of obstructive lung diseases. To assess the performance and cross-validation of these three classifiers, 5 folding methods with 5 randomly chosen groups were used. For a more robust result, each validation was repeated 100 times. SVM showed the best performance, with 86.5% overall sensitivity, significantly different from the other classifiers (one way ANOVA, p<0.01). We address the characteristics of each classifier affecting performance and the issue of which classifier is the most suitable for clinical applications, and propose an appropriate method to choose the best classifier and determine its optimal parameters for optimal disease discrimination. These results can be applied to classifiers for differentiation of other diseases.

Classifier ensemble construction with rotation forest to improve medical diagnosis performance of machine learning algorithms.

PubMed

Ozcift, Akin; Gulten, Arif

2011-12-01

Improving accuracies of machine learning algorithms is vital in designing high performance computer-aided diagnosis (CADx) systems. Researches have shown that a base classifier performance might be enhanced by ensemble classification strategies. In this study, we construct rotation forest (RF) ensemble classifiers of 30 machine learning algorithms to evaluate their classification performances using Parkinson's, diabetes and heart diseases from literature. While making experiments, first the feature dimension of three datasets is reduced using correlation based feature selection (CFS) algorithm. Second, classification performances of 30 machine learning algorithms are calculated for three datasets. Third, 30 classifier ensembles are constructed based on RF algorithm to assess performances of respective classifiers with the same disease data. All the experiments are carried out with leave-one-out validation strategy and the performances of the 60 algorithms are evaluated using three metrics; classification accuracy (ACC), kappa error (KE) and area under the receiver operating characteristic (ROC) curve (AUC). Base classifiers succeeded 72.15%, 77.52% and 84.43% average accuracies for diabetes, heart and Parkinson's datasets, respectively. As for RF classifier ensembles, they produced average accuracies of 74.47%, 80.49% and 87.13% for respective diseases. RF, a newly proposed classifier ensemble algorithm, might be used to improve accuracy of miscellaneous machine learning algorithms to design advanced CADx systems. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes.

PubMed

Kireeva, Natalia V; Ovchinnikova, Svetlana I; Kuznetsov, Sergey L; Kazennov, Andrey M; Tsivadze, Aslan Yu

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

PubMed

Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Alvarez, Jose Luis; Skrovseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert

2016-09-01

The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, little effort has been invested toward feature selection and the features' corresponding medical interpretation. In this study, we focus on the task of early detection of anastomosis leakage (AL), a severe complication after elective surgery for colorectal cancer (CRC) surgery, using free text extracted from EHRs. We use a bag-of-words model to investigate the potential for feature selection strategies. The purpose is earlier detection of AL and prediction of AL with data generated in the EHR before the actual complication occur. Due to the high dimensionality of the data, we derive feature selection strategies using the robust support vector machine linear maximum margin classifier, by investigating: 1) a simple statistical criterion (leave-one-out-based test); 2) an intensive-computation statistical criterion (Bootstrap resampling); and 3) an advanced statistical criterion (kernel entropy). Results reveal a discriminatory power for early detection of complications after CRC (sensitivity 100%; specificity 72%). These results can be used to develop prediction models, based on EHR data, that can support surgeons and patients in the preoperative decision making phase.

Mass-transport deposits controlling fault propagation, reactivation and structural decoupling on continental margins (Espírito Santo Basin, SE Brazil)

NASA Astrophysics Data System (ADS)

Omosanya, Kamal'deen O.; Alves, Tiago M.

2014-07-01

This work uses high-quality 3D seismic data to assess the importance of mass-transport deposits (MTDs) as markers of fault propagation. We mapped three distinct MTDs and several fault families on the continental slope of Espírito Santo, SE Brazil. Fault mapping was based on seismic attributes such as seismic coherence and structural smoothing, and was further completed using ant tracking algorithms. Genetically related fault families were analysed in terms of their throw-depth (t-z) and throw-distance (t-x) gradient curves. A key result in this paper is that vertical fault propagation can be hindered by MTDs, as demonstrated for Eocene to Early Miocene faults in parts of the study area. Throw-depth variations in faults affected by MTDs are associated with: a) lithologic controls resulting from the presence of MTDs, b) local fault segmentation and c) reactivation by dip linkage. Based on their orientation and degree of interaction with MTDs, interpreted faults can be classified as decoupled and non-decoupled. Importantly, faults decoupled by MTDs have quasi-elliptical t-x profiles and show smaller cumulative throw values and fault propagation rates when compared to their non-decoupled counterparts. Recurrent MTDs can therefore be used as markers to estimate structural decoupling between distinct fault families.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes

NASA Astrophysics Data System (ADS)

Kireeva, Natalia V.; Ovchinnikova, Svetlana I.; Kuznetsov, Sergey L.; Kazennov, Andrey M.; Tsivadze, Aslan Yu.

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index

NASA Astrophysics Data System (ADS)

Köseoğlu, Denizcan; Belt, Simon T.; Smik, Lukas; Yao, Haoyi; Panieri, Giuliana; Knies, Jochen

2018-02-01

The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has significantly advanced our understanding of long-term paleo Arctic sea ice conditions over the past decade. We investigated the potential for classification tree (CT) models to provide a further approach to paleo Arctic sea ice reconstruction through analysis of a suite of highly branched isoprenoid (HBI) biomarkers in ca. 200 surface sediments from the Barents Sea. Four CT models constructed using different HBI assemblages revealed IP25 and an HBI triene as the most appropriate classifiers of sea ice conditions, achieving a >90% cross-validated classification rate. Additionally, lower model performance for locations in the Marginal Ice Zone (MIZ) highlighted difficulties in characterisation of this climatically-sensitive region. CT model classification and semi-quantitative PIP25-derived estimates of spring sea ice concentration (SpSIC) for four downcore records from the region were consistent, although agreement between proxy and satellite/observational records was weaker for a core from the west Svalbard margin, likely due to the highly variable sea ice conditions. The automatic selection of appropriate biomarkers for description of sea ice conditions, quantitative model assessment, and insensitivity to the c-factor used in the calculation of the PIP25 index are key attributes of the CT approach, and we provide an initial comparative assessment between these potentially complementary methods. The CT model should be capable of generating longer-term temporal shifts in sea ice conditions for the climatically sensitive Barents Sea.

Interaction between parenting and neighborhood quality on the risk of adolescent regular smoking.

PubMed

Wen, Xiaozhong; Shenassa, Edmond D

2012-03-01

To conduct the first study to examine potential interaction between parenting style and neighborhood quality on the risk of adolescent regular smoking. We analyzed data from a nationally representative sample of U.S. adolescents (n = 1,213 pairs of adolescents and their parents) who participated in the Panel Study of Income Dynamics during 2002-2003. Regular smoking behavior and parental monitoring level were reported by adolescents. Parenting style (i.e., authoritative, authoritarian, permissive, and uninvolved) was defined by cross-classifying self-reported parental warmth and control. Based on parents' perceived neighborhood quality regarding raising children, neighborhoods were identified as either higher quality or lower quality. Adolescents in lower-quality neighborhoods were more likely to be regular smokers (13.7% vs. 8.5%; adjusted odds ratio [AOR] = 1.93, 95% CI = 1.02-3.65) than those in higher-quality neighborhoods. In lower-quality neighborhoods, adolescents of authoritarian parents (16.9%; AOR = 10.97, 95% CI = 3.36-35.84) were more likely and those of uninvolved parents (20.3%; AOR = 3.47, 95% CI = 0.91-13.17) were marginally more likely to be regular smokers than those of authoritative parents (4.3%). However, among adolescents in higher-quality neighborhoods, parenting style was independent of the risk of regular smoking. There was marginally significant interaction between authoritarian parenting style and neighborhood quality. Parental monitoring was associated with reduced risk of adolescent smoking, regardless of neighborhood quality. There was no interaction between parental monitoring and neighborhood quality. Authoritative parenting is associated with reduced risk of adolescent regular smoking in lower-quality neighborhoods but not in higher-quality neighborhoods. Authoritative parenting style and parental monitoring may buffer adverse influences of low-quality neighborhood.

Tool Wear Feature Extraction Based on Hilbert Marginal Spectrum

NASA Astrophysics Data System (ADS)

Guan, Shan; Song, Weijie; Pang, Hongyang

2017-09-01

In the metal cutting process, the signal contains a wealth of tool wear state information. A tool wear signal’s analysis and feature extraction method based on Hilbert marginal spectrum is proposed. Firstly, the tool wear signal was decomposed by empirical mode decomposition algorithm and the intrinsic mode functions including the main information were screened out by the correlation coefficient and the variance contribution rate. Secondly, Hilbert transform was performed on the main intrinsic mode functions. Hilbert time-frequency spectrum and Hilbert marginal spectrum were obtained by Hilbert transform. Finally, Amplitude domain indexes were extracted on the basis of the Hilbert marginal spectrum and they structured recognition feature vector of tool wear state. The research results show that the extracted features can effectively characterize the different wear state of the tool, which provides a basis for monitoring tool wear condition.

The Kidney Donor Profile Index (KDPI) of Marginal Donors Allocated by Standardized Pre-Transplant Donor Biopsy Assessment: Distribution and Association with Graft Outcomes

PubMed Central

Gandolfini, I.; Buzio, C.; Zanelli, P.; Palmisano, A.; Cremaschi, E.; Vaglio, A.; Piotti, G.; Melfa, L.; La Manna, G.; Feliciangeli, G.; Cappuccilli, M.; Scolari, M.P.; Capelli, I.; Panicali, L.; Baraldi, O.; Stefoni, S.; Buscaroli, A.; Ridolfi, L.; D'Errico, A.; Cappelli, G.; Bonucchi, D.; Rubbiani, E.; Albertazzi, A.; Mehrotra, A.; Cravedi, P.; Maggiore, U.

2015-01-01

Pre-transplant donor biopsy (PTDB)-based marginal-donor allocation systems to single or dual renal transplantation could increase the use of organs with Kidney Donor Profile Index (KDPI) in the highest range (e.g. >80 or >90), whose discard rate approximates 50% in the US. To test this hypothesis, we retrospectively calculated the KDPI and analyzed the outcomes of 442 marginal kidney transplants (340 single transplants: 278 with a PTDB Remuzzi score <4 [median KDPI:87; interquartile range(IQR):78-94] and 62 with a score =4 [median KDPI:87; IQR:76-93]; 102 dual transplants [median KDPI: 93; IQR:86-96]) and 248 single standard transplant controls [median KDPI:36; IQR:18-51]. PTDB-based allocation of marginal grafts led to a limited discard rate of 15% for kidneys with KDPI of 80-90 and of 37% for kidneys with a KDPI of 91-100. Although 1-year eGFRs were significantly lower in recipients of marginal kidneys (-9.3, -17.9, and -18.8ml/min, for dual transplants, single kidneys with PTDB score <4, and =4, respectively; P<0.001), graft survival (median follow-up 3.3 years) was similar between marginal and standard kidney transplants (hazard ratio: 1.20 [95% confidence interval: 0.80 to 1.79; P=0.38]). In conclusion, PTDB-based allocation allows the safe transplantation of kidneys with KDPI in the highest range that may otherwise be discarded. PMID:25155294

Influence of incorrect application of a water-based adhesive system on the marginal adaptation of Class V restorations.

PubMed

Peschke, A; Blunck, U; Roulet, J F

2000-10-01

To determine the influence of incorrectly performed steps during the application of the water-based adhesive system OptiBond FL on the marginal adaptation of Class V composite restorations. In 96 extracted human teeth Class V cavities were prepared. Half of the margin length was situated in dentin. The teeth were randomly divided into 12 groups. The cavities were filled with Prodigy resin-based composite in combination with OptiBond FL according to the manufacturer's instructions (Group O) and including several incorrect application steps: Group A: prolonged etching (60 s); Group B: no etching of dentin; Group C: excessive drying after etching; Group D: short rewetting after excessive drying; Group E: air drying and rewetting; Group F: blot drying; Group G: saliva contamination; Group H: application of primer and immediate drying; group I: application of only primer; group J: application of only adhesive; Group K: no light curing of the adhesive before the application of composite. After thermocycling, replicas were taken and the margins were quantitatively analyzed in the SEM. Statistical analysis of the results was performed using non-parametric procedures. With exception of the "rewetting groups" (D and E) and the group with saliva contamination (G), all other application procedures showed a significantly higher amount of marginal openings in dentin compared to the control group (O). Margin quality in enamel was only affected when the primer was not applied.

Sub-1-V-60 nm vertical body channel MOSFET-based six-transistor static random access memory array with wide noise margin and excellent power delay product and its optimization with the cell ratio on static random access memory cell

NASA Astrophysics Data System (ADS)

Ogasawara, Ryosuke; Endoh, Tetsuo

2018-04-01

In this study, with the aim to achieve a wide noise margin and an excellent power delay product (PDP), a vertical body channel (BC)-MOSFET-based six-transistor (6T) static random access memory (SRAM) array is evaluated by changing the number of pillars in each part of a SRAM cell, that is, by changing the cell ratio in the SRAM cell. This 60 nm vertical BC-MOSFET-based 6T SRAM array realizes 0.84 V operation under the best PDP and up to 31% improvement of PDP compared with the 6T SRAM array based on a 90 nm planar MOSFET whose gate length and channel width are the same as those of the 60 nm vertical BC-MOSFET. Additionally, the vertical BC-MOSFET-based 6T SRAM array achieves an 8.8% wider read static noise margin (RSNM), a 16% wider write margin (WM), and an 89% smaller leakage. Moreover, it is shown that changing the cell ratio brings larger improvements of RSNM, WM, and write time in the vertical BC-MOSFET-based 6T SRAM array.

MARGINS: Toward a novel science plan

NASA Astrophysics Data System (ADS)

Mutter, John C.

A science plan to study continental margins has been in the works for the past 3 years, with almost 200 Earth scientists from a wide variety of disciplines gathering at meetings and workshops. Most geological hazards and resources are found at continental margins, yet our understanding of the processes that shape the margins is meager.In formulating this MARGINS research initiative, fundamental issues concerning our understanding of basic Earth-forming processes have arisen. It is clear that a business-as-usual approach will not solve the class of problems defined by the MARGINS program; the solutions demand approaches different from those used in the past. In many cases, a different class of experiment will be required, one that is well beyond the capability of individual principle investigators to undertake on their own. In most cases, broadly based interdisciplinary studies will be needed.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach

PubMed Central

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2018-01-01

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach, and has several attractive features compared to the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, since the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. PMID:26303591

Method for the simulation of blood platelet shape and its evolution during activation

PubMed Central

Muliukov, Artem R.; Litvinenko, Alena L.; Nekrasov, Vyacheslav M.; Chernyshev, Andrei V.; Maltsev, Valeri P.

2018-01-01

We present a simple physically based quantitative model of blood platelet shape and its evolution during agonist-induced activation. The model is based on the consideration of two major cytoskeletal elements: the marginal band of microtubules and the submembrane cortex. Mathematically, we consider the problem of minimization of surface area constrained to confine the marginal band and a certain cellular volume. For resting platelets, the marginal band appears as a peripheral ring, allowing for the analytical solution of the minimization problem. Upon activation, the marginal band coils out of plane and forms 3D convoluted structure. We show that its shape is well approximated by an overcurved circle, a mathematical concept of closed curve with constant excessive curvature. Possible mechanisms leading to such marginal band coiling are discussed, resulting in simple parametric expression for the marginal band shape during platelet activation. The excessive curvature of marginal band is a convenient state variable which tracks the progress of activation. The cell surface is determined using numerical optimization. The shapes are strictly mathematically defined by only three parameters and show good agreement with literature data. They can be utilized in simulation of platelets interaction with different physical fields, e.g. for the description of hydrodynamic and mechanical properties of platelets, leading to better understanding of platelets margination and adhesion and thrombus formation in blood flow. It would also facilitate precise characterization of platelets in clinical diagnosis, where a novel optical model is needed for the correct solution of inverse light-scattering problem. PMID:29518073

A novel method to quantify and compare anatomical shape: application in cervix cancer radiotherapy

NASA Astrophysics Data System (ADS)

Oh, Seungjong; Jaffray, David; Cho, Young-Bin

2014-06-01

Adaptive radiation therapy (ART) had been proposed to restore dosimetric deficiencies during treatment delivery. In this paper, we developed a technique of Geometric reLocation for analyzing anatomical OBjects' Evolution (GLOBE) for a numerical model of tumor evolution under radiation therapy and characterized geometric changes of the target using GLOBE. A total of 174 clinical target volumes (CTVs) obtained from 32 cervical cancer patients were analyzed. GLOBE consists of three main steps; step (1) deforming a 3D surface object to a sphere by parametric active contour (PAC), step (2) sampling a deformed PAC on 642 nodes of icosahedron geodesic dome for reference frame, and step (3) unfolding 3D data to 2D plane for convenient visualization and analysis. The performance was evaluated with respect to (1) convergence of deformation (iteration number and computation time) and (2) accuracy of deformation (residual deformation). Based on deformation vectors from planning CTV to weekly CTVs, target specific (TS) margins were calculated on each sampled node of GLOBE and the systematic (Σ) and random (σ) variations of the vectors were calculated. Population based anisotropic (PBA) margins were generated using van Herk's margin recipe. GLOBE successfully modeled 152 CTVs from 28 patients. Fast convergence was observed for most cases (137/152) with the iteration number of 65 ± 74 (average ± STD) and the computation time of 13.7 ± 18.6 min. Residual deformation of PAC was 0.9 ± 0.7 mm and more than 97% was less than 3 mm. Margin analysis showed random nature of TS-margin. As a consequence, PBA-margins perform similarly to ISO-margins. For example, PBA-margins for 90% patients' coverage with 95% dose level is close to 13 mm ISO-margins in the aspect of target coverage and OAR sparing. GLOBE demonstrates a systematic analysis of tumor motion and deformation of patients with cervix cancer during radiation therapy and numerical modeling of PBA-margin on 642 locations of CTV surface.

Decoding the Margins: What Can the Fractal Geometry of Basaltic Flow Margins Tell Us?

NASA Astrophysics Data System (ADS)

Schaefer, E. I.; Hamilton, C.; Neish, C.; Beard, S. P.; Bramson, A. M.; Sori, M.; Rader, E. L.

2016-12-01

Studying lava flows on other planetary bodies is essential to characterizing eruption styles and constraining the bodies' thermal evolution. Although planetary basaltic flows are common, many key features are not resolvable in orbital imagery. We are thus developing a technique to characterize basaltic flow type, sub-meter roughness, and sediment mantling from these data. We will present the results from upcoming fieldwork at Craters of the Moon National Monument and Preserve with FINESSE (August) and at Hawai'i Volcanoes National Park (September). We build on earlier work that showed that basaltic flow margins are approximately fractal [Bruno et al., 1992; Gaonac'h et al., 1992] and that their fractal dimensions (D) have distinct `a`ā and pāhoehoe ranges under simple conditions [Bruno et al., 1994]. Using a differential GPS rover, we have recently shown that the margin of Iceland's 2014 Holuhraun flow exhibits near-perfect (R2=0.9998) fractality for ≥24 km across dm to km scales [Schaefer et al., 2016]. This finding suggests that a fractal-based technique has significant potential to characterize flows at sub-resolution scales. We are simultaneously seeking to understand how margin fractality can be modified. A preliminary result for an `a'ā flow in Hawaii's Ka'ū Desert suggests that although aeolian mantling obscures the original flow margin, the apparent margin (i.e., sediment-lava interface) remains fractal [Schaefer et al., 2015]. Further, the apparent margin's D is likely significantly modified from that of the original margin. Other factors that we are exploring include erosion, transitional flow types, and topographic confinement. We will also rigorously test the intriguing possibility that margin D correlates with the sub-meter Hurst exponent H of the flow surface, a common metric of roughness scaling [e.g., Shepard et al., 2001]. This hypothesis is based on geometric arguments [Turcotte, 1997] and is qualitatively consistent with all results so far.

The impact of use of an intraoperative margin assessment device on re-excision rates.

PubMed

Sebastian, Molly; Akbari, Stephanie; Anglin, Beth; Lin, Erin H; Police, Alice M

2015-01-01

Historically there has been a high rate of surgical interventions to obtain clear margins for breast cancer patients undergoing breast conserving local therapy. An intraoperative margin assessment tool (MarginProbe) has been approved for use in the US since 2013. This study is the first compilation of data from routine use of the device, to assess the impact of device utilization on re-excision rates. We present a retrospective, observational, review from groups of consecutive patients, before and after the implementation of intraoperative use of the device during lumpectomy procedures. Lesions were localized by standard methods. The intraoperative margin assessment device was used on all circumferential margins of the main specimen, but not on any additional shavings. A positive reading by the device led to an additional shaving of the corresponding cavity location. Specimens were also, when feasible, imaged intra-operatively by X-ray, and additional shavings were taken if needed based on clinical assessment. For each surgeon, historical re-excision rates were established based on a consecutive set of patients from a time period proximal to initiation of use of the device. From March 2013 to April 2014 the device was routinely used by 4 surgeons in 3 centers. In total, 165 cases lumpectomy cases were performed. Positive margins resulted in additional re-excision procedures in 9.7% (16/165) of the cases. The corresponding historical set from 2012 and 2013 consisted of 186 Lumpectomy cases, in which additional re-excision procedures were performed in 25.8% (48/186) of the cases. The reduction in the rate of re-excision procedures was significant 62% (P < 0.0001). Use of an intraoperative margin assessment device contributes to achieving clear margins and reducing re-excision procedures. As in some cases positive margins were found on shavings, future studies of interest may include an analysis of the effect of using the device on the shavings intra-operatively.

Tumor margin detection using optical biopsy techniques

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-hui; Li, Jiyou; Li, Zhongwu; Zhou, Lixin; Chen, Ke; Pu, Yang; He, Yong; Zhu, Ke; Li, Qingbo; Alfano, Robert R.

2014-03-01

The aim of this study is to use the Resonance Raman (RR) and fluorescence spectroscopic technique for tumor margin detection with high accuracy based on native molecular fingerprints of breast and gastrointestinal (GI) tissues. This tumor margins detection method utilizes advantages of RR spectroscopic technique in situ and in real-time to diagnose tumor changes providing powerful tools for clinical guiding intraoperative margin assessments and postoperative treatments. The tumor margin detection procedures by RR spectroscopy were taken by scanning lesion from center or around tumor region in ex-vivo to find the changes in cancerous tissues with the rim of normal tissues using the native molecular fingerprints. The specimens used to analyze tumor margins include breast and GI carcinoma and normal tissues. The sharp margin of the tumor was found by the changes of RR spectral peaks within 2 mm distance. The result was verified using fluorescence spectra with 300 nm, 320 nm and 340 nm excitation, in a typical specimen of gastric cancerous tissue within a positive margin in comparison with normal gastric tissues. This study demonstrates the potential of RR and fluorescence spectroscopy as new approaches with labeling free to determine the intraoperative margin assessment.

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

Mascle, J.; Blarez, E.

The authors present a marine study of the eastern Ivory Coast-Ghana continental margins which they consider one of the most spectacular extinct transform margins. This margin has been created during Early-Lower Cretaceous time and has not been submitted to any major geodynamic reactivation since its fabric. Based on this example, they propose to consider during the evolution of the transform margin four main and successive stages. Shearing contact is first active between two probably thick continental crusts and then between progressively thinning continental crusts. This leads to the creation of specific geological structures such as pull-apart graben, elongated fault lineaments,more » major fault scarps, shear folds, and marginal ridges. After the final continental breakup, a hot center (the mid-oceanic ridge axis) is progressively drifting along the newly created margin. The contact between two lithospheres of different nature should necessarily induce, by thermal exchanges, vertical crustal readjustments. Finally, the transform margin remains directly adjacent to a hot but cooling oceanic lithosphere; its subsidence behavior should then progressively be comparable to the thermal subsidence of classic rifted margins.« less

A bench-top hyperspectral imaging system to classify beef from Nellore cattle based on tenderness

NASA Astrophysics Data System (ADS)

Nubiato, Keni Eduardo Zanoni; Mazon, Madeline Rezende; Antonelo, Daniel Silva; Calkins, Chris R.; Naganathan, Govindarajan Konda; Subbiah, Jeyamkondan; da Luz e Silva, Saulo

2018-03-01

The aim of this study was to evaluate the accuracy of classification of Nellore beef aged for 0, 7, 14, or 21 days and classification based on tenderness and aging period using a bench-top hyperspectral imaging system. A hyperspectral imaging system (λ = 928-2524 nm) was used to collect hyperspectral images of the Longissimus thoracis et lumborum (aging n = 376 and tenderness n = 345) of Nellore cattle. The image processing steps included selection of region of interest, extraction of spectra, and indentification and evalution of selected wavelengths for classification. Six linear discriminant models were developed to classify samples based on tenderness and aging period. The model using the first derivative of partial absorbance spectra (give wavelength range spectra) was able to classify steaks based on the tenderness with an overall accuracy of 89.8%. The model using the first derivative of full absorbance spectra was able to classify steaks based on aging period with an overall accuracy of 84.8%. The results demonstrate that the HIS may be a viable technology for classifying beef based on tenderness and aging period.

Transferring genomics to the clinic: distinguishing Burkitt and diffuse large B cell lymphomas.

PubMed

Sha, Chulin; Barrans, Sharon; Care, Matthew A; Cunningham, David; Tooze, Reuben M; Jack, Andrew; Westhead, David R

2015-01-01

Classifiers based on molecular criteria such as gene expression signatures have been developed to distinguish Burkitt lymphoma and diffuse large B cell lymphoma, which help to explore the intermediate cases where traditional diagnosis is difficult. Transfer of these research classifiers into a clinical setting is challenging because there are competing classifiers in the literature based on different methodology and gene sets with no clear best choice; classifiers based on one expression measurement platform may not transfer effectively to another; and, classifiers developed using fresh frozen samples may not work effectively with the commonly used and more convenient formalin fixed paraffin-embedded samples used in routine diagnosis. Here we thoroughly compared two published high profile classifiers developed on data from different Affymetrix array platforms and fresh-frozen tissue, examining their transferability and concordance. Based on this analysis, a new Burkitt and diffuse large B cell lymphoma classifier (BDC) was developed and employed on Illumina DASL data from our own paraffin-embedded samples, allowing comparison with the diagnosis made in a central haematopathology laboratory and evaluation of clinical relevance. We show that both previous classifiers can be recapitulated using very much smaller gene sets than originally employed, and that the classification result is closely dependent on the Burkitt lymphoma criteria applied in the training set. The BDC classification on our data exhibits high agreement (~95 %) with the original diagnosis. A simple outcome comparison in the patients presenting intermediate features on conventional criteria suggests that the cases classified as Burkitt lymphoma by BDC have worse response to standard diffuse large B cell lymphoma treatment than those classified as diffuse large B cell lymphoma. In this study, we comprehensively investigate two previous Burkitt lymphoma molecular classifiers, and implement a new gene expression classifier, BDC, that works effectively on paraffin-embedded samples and provides useful information for treatment decisions. The classifier is available as a free software package under the GNU public licence within the R statistical software environment through the link http://www.bioinformatics.leeds.ac.uk/labpages/softwares/ or on github https://github.com/Sharlene/BDC.

Developing tools to identify marginal lands and assess their potential for bioenergy production

NASA Astrophysics Data System (ADS)

Galatsidas, Spyridon; Gounaris, Nikolaos; Dimitriadis, Elias; Rettenmaier, Nils; Schmidt, Tobias; Vlachaki, Despoina

2017-04-01

The term "marginal land" is currently intertwined in discussions about bioenergy although its definition is neither specific nor firm. The uncertainty arising from marginal land classification and quantification is one of the major constraining factors for its potential use. The clarification of political aims, i.e. "what should be supported?" is also an important constraining factor. Many approaches have been developed to identify marginal lands, based on various definitions according to the management goals. Concerns have been frequently raised regarding the impacts of marginal land use on environment, ecosystem services and sustainability. Current tools of soil quality and land potentials assessment fail to meet the needs of marginal land identification and exploitation for biomass production, due to the lack of comprehensive analysis of interrelated land functions and their quantitative evaluation. Land marginality is determined by dynamic characteristics in many cases and may therefore constitute a transitional state, which requires reassessment in due time. Also, marginal land should not be considered simply a dormant natural resource waiting to be used, since it may already provide multiple benefits and services to society relating to wildlife, biodiversity, carbon sequestration, etc. The consequences of cultivating such lands need to be fully addressed to present a balanced view of their sustainable potential for bioenergy. This framework is the basis for the development of the SEEMLA tools, which aim at supporting the identification, assessment, management of marginal lands in Europe and the decision-making for sustainable biomass production of them using appropriate bioenergy crops. The tools comprise two applications, a web-based one (independent of spatial data) and a GIS-based application (land regionalization on the basis of spatial data), which both incorporate: - Land resource characteristics, restricting the cultivation of agricultural crops but effectively sustaining bioenergy plants (soil, climate, topography, vegetation, etc.) - Bioenergy plant characteristics and their ability to grow on marginal lands - Needs and concerns on environmental issues and ecosystem benefits and services (biodiversity, carbon sequestration potential, soil organic carbon trend, etc.) - Sustainability assessments (incl. e.g. LCA) of biomass production at market scale - Analysis results of generic scenarios for biomass production, harvesting, logistics and conditioning, as well as biomass conversion and use from pilot cases growing various crops The SEEMLA approach of marginal lands evaluation will provide private and public stakeholders with necessary guidance for selecting suitable lands and implementing efficient exploitation strategies for bioenergy production, on the basis of sound environmental and socio-economic criteria.

The marginal fit of E.max Press and E.max CAD lithium disilicate restorations: A critical review.

PubMed

Mounajjed, Radek; M Layton, Danielle; Azar, Basel

2016-12-01

This critical review aimed to assess the vertical marginal gap that was present when E.max lithium disilicate-based restoration (Press and CAD) are fabricated in-vitro. Published articles reporting vertical marginal gap measurements of in-vitro restorations that had been fabricated from E.Max lithium disilicate were sought with an electronic search of MEDLINE (PubMed) and hand search of selected dental journals. The outcomes were reviewed qualitatively. The majority of studies that compared the marginal fit of E.max press and E.max CAD restorations, found that the E.max lithium disilicate restorations fabricated with the press technique had significantly smaller marginal gaps than those fabricated with CAD technique. This research indicates that E.max lithium disilicate restorations fabricated with the press technique have measurably smaller marginal gaps when compared with those fabricated with CAD techniques within in-vitro environments. The marginal gaps achieved by the restorations across all groups were within a clinically acceptable range.

The Meandering Margin of the Meteorological Moist Tropics

NASA Astrophysics Data System (ADS)

Mapes, Brian E.; Chung, Eui Seok; Hannah, Walter M.; Masunaga, Hirohiko; Wimmers, Anthony J.; Velden, Christopher S.

2018-01-01

Bimodally distributed column water vapor (CWV) indicates a well-defined moist regime in the Tropics, above a margin value near 48 kg m-2 in current climate (about 80% of column saturation). Maps reveal this margin as a meandering, sinuous synoptic contour bounding broad plateaus of the moist regime. Within these plateaus, convective storms of distinctly smaller convective and mesoscales occur sporadically. Satellite data composites across the poleward most margin reveal its sharpness, despite the crude averaging: precipitation doubles within 100 km, marked by both enhancement and deepening of cloudiness. Transported patches and filaments of the moist regime cause consequential precipitation events within and beyond the Tropics. Distinguishing synoptic flows that cross the margin from flows that move the margin is made possible by a novel satellite-based Lagrangian CWV tendency estimate. Climate models do not reliably reproduce the observed bimodal distribution, so studying the moist mode's maintenance processes and the margin-zone air mass transformations, guided by the Lagrangian tendency product, might importantly constrain model moist process treatments.

The Ills of Marginality: New Perspectives on Health in South Asia.

PubMed

Ecks, Stefan; Sax, William S

2005-12-01

Social marginality and ill health can form an unholy dyad: firstly, groups who suffer from chronic or infectious diseases often find themselves pushed to the margins. Secondly, people who are already on the edge of society tend to suffer more from illness than those at the centre. In development discourse, marginal people are defined as those who are 'not yet' on the same level as the developed mainstream and are in urgent need of aid from the centre. The papers in this special issue take a different approach by insisting that marginality is a radically relational concept: the centre and its margins constitute each other, and the boundaries between them are constantly shifting. The papers show that there are many types of marginality (based on geography, class, caste, sex/gender, ethnicity, etc.), and that each of them has different effects on the health of a particular group. Yet instead of speaking of a plurality of unrelated 'group identities', marginality preserves a sharp sense of unequal power relations between groups. The specific ethnographic contribution to the study of marginality comes from its attention to the point of view of marginal people. This is of critical importance since marginality puts health most under stress when it is clearly and steadily perceived in everyday life. This, in turn, makes it possible to show that living on the margins is not always and everywhere bad for health. While all of the papers present South Asian case studies, the insights and questions are relevant for the study of the ills of marginality in a global perspective.

A Factor Graph Approach to Automated GO Annotation

PubMed Central

Spetale, Flavio E.; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463

Use of cccupancy models to evaluate expert knowledge-based species-habitat relationships

USGS Publications Warehouse

Iglecia, Monica N.; Collazo, Jaime A.; McKerrow, Alexa

2012-01-01

Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens) and Brown-headed Nuthatch (Sitta pusilla), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

A Factor Graph Approach to Automated GO Annotation.

PubMed

Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

2016-01-01

As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum.

Classifying Higher Education Institutions in Korea: A Performance-Based Approach

ERIC Educational Resources Information Center

Shin, Jung Cheol

2009-01-01

The purpose of this study was to classify higher education institutions according to institutional performance rather than predetermined benchmarks. Institutional performance was defined as research performance and classified using Hierarchical Cluster Analysis, a statistical method that classifies objects according to specified classification…

Combining classifiers using their receiver operating characteristics and maximum likelihood estimation.

PubMed

Haker, Steven; Wells, William M; Warfield, Simon K; Talos, Ion-Florin; Bhagwat, Jui G; Goldberg-Zimring, Daniel; Mian, Asim; Ohno-Machado, Lucila; Zou, Kelly H

2005-01-01

In any medical domain, it is common to have more than one test (classifier) to diagnose a disease. In image analysis, for example, there is often more than one reader or more than one algorithm applied to a certain data set. Combining of classifiers is often helpful, but determining the way in which classifiers should be combined is not trivial. Standard strategies are based on learning classifier combination functions from data. We describe a simple strategy to combine results from classifiers that have not been applied to a common data set, and therefore can not undergo this type of joint training. The strategy, which assumes conditional independence of classifiers, is based on the calculation of a combined Receiver Operating Characteristic (ROC) curve, using maximum likelihood analysis to determine a combination rule for each ROC operating point. We offer some insights into the use of ROC analysis in the field of medical imaging.

Combining Classifiers Using Their Receiver Operating Characteristics and Maximum Likelihood Estimation*

PubMed Central

Haker, Steven; Wells, William M.; Warfield, Simon K.; Talos, Ion-Florin; Bhagwat, Jui G.; Goldberg-Zimring, Daniel; Mian, Asim; Ohno-Machado, Lucila; Zou, Kelly H.

2010-01-01

In any medical domain, it is common to have more than one test (classifier) to diagnose a disease. In image analysis, for example, there is often more than one reader or more than one algorithm applied to a certain data set. Combining of classifiers is often helpful, but determining the way in which classifiers should be combined is not trivial. Standard strategies are based on learning classifier combination functions from data. We describe a simple strategy to combine results from classifiers that have not been applied to a common data set, and therefore can not undergo this type of joint training. The strategy, which assumes conditional independence of classifiers, is based on the calculation of a combined Receiver Operating Characteristic (ROC) curve, using maximum likelihood analysis to determine a combination rule for each ROC operating point. We offer some insights into the use of ROC analysis in the field of medical imaging. PMID:16685884

Robust Stability Analysis of the Space Launch System Control Design: A Singular Value Approach

NASA Technical Reports Server (NTRS)

Pei, Jing; Newsome, Jerry R.

2015-01-01

Classical stability analysis consists of breaking the feedback loops one at a time and determining separately how much gain or phase variations would destabilize the stable nominal feedback system. For typical launch vehicle control design, classical control techniques are generally employed. In addition to stability margins, frequency domain Monte Carlo methods are used to evaluate the robustness of the design. However, such techniques were developed for Single-Input-Single-Output (SISO) systems and do not take into consideration the off-diagonal terms in the transfer function matrix of Multi-Input-Multi-Output (MIMO) systems. Robust stability analysis techniques such as H(sub infinity) and mu are applicable to MIMO systems but have not been adopted as standard practices within the launch vehicle controls community. This paper took advantage of a simple singular-value-based MIMO stability margin evaluation method based on work done by Mukhopadhyay and Newsom and applied it to the SLS high-fidelity dynamics model. The method computes a simultaneous multi-loop gain and phase margin that could be related back to classical margins. The results presented in this paper suggest that for the SLS system, traditional SISO stability margins are similar to the MIMO margins. This additional level of verification provides confidence in the robustness of the control design.

Marginal and Random Intercepts Models for Longitudinal Binary Data With Examples From Criminology.

PubMed

Long, Jeffrey D; Loeber, Rolf; Farrington, David P

2009-01-01

Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides individual-level information including information about heterogeneity of growth. It is shown how a type of numerical averaging can be used with the random intercepts model to obtain group-level information, thus approximating individual and marginal aspects of the LMM. The types of inferences associated with each model are illustrated with longitudinal criminal offending data based on N = 506 males followed over a 22-year period. Violent offending indexed by official records and self-report were analyzed, with the marginal model estimated using generalized estimating equations and the random intercepts model estimated using maximum likelihood. The results show that the numerical averaging based on the random intercepts can produce prediction curves almost identical to those obtained directly from the marginal model parameter estimates. The results provide a basis for contrasting the models and the estimation procedures and key features are discussed to aid in selecting a method for empirical analysis.

Digital evaluation of absolute marginal discrepancy: A comparison of ceramic crowns fabricated with conventional and digital techniques.

PubMed

Liang, Shanshan; Yuan, Fusong; Luo, Xu; Yu, Zhuoren; Tang, Zhihui

2018-04-05

Marginal discrepancy is key to evaluating the accuracy of fixed dental prostheses. An improved method of evaluating marginal discrepancy is needed. The purpose of this in vitro study was to evaluate the absolute marginal discrepancy of ceramic crowns fabricated using conventional and digital methods with a digital method for the quantitative evaluation of absolute marginal discrepancy. The novel method was based on 3-dimensional scanning, iterative closest point registration techniques, and reverse engineering theory. Six standard tooth preparations for the right maxillary central incisor, right maxillary second premolar, right maxillary second molar, left mandibular lateral incisor, left mandibular first premolar, and left mandibular first molar were selected. Ten conventional ceramic crowns and 10 CEREC crowns were fabricated for each tooth preparation. A dental cast scanner was used to obtain 3-dimensional data of the preparations and ceramic crowns, and the data were compared with the "virtual seating" iterative closest point technique. Reverse engineering software used edge sharpening and other functional modules to extract the margins of the preparations and crowns. Finally, quantitative evaluation of the absolute marginal discrepancy of the ceramic crowns was obtained from the 2-dimensional cross-sectional straight-line distance between points on the margin of the ceramic crowns and the standard preparations based on the circumferential function module along the long axis. The absolute marginal discrepancy of the ceramic crowns fabricated using conventional methods was 115 ±15.2 μm, and 110 ±14.3 μm for those fabricated using the digital technique was. ANOVA showed no statistical difference between the 2 methods or among ceramic crowns for different teeth (P>.05). The digital quantitative evaluation method for the absolute marginal discrepancy of ceramic crowns was established. The evaluations determined that the absolute marginal discrepancies were within a clinically acceptable range. This method is acceptable for the digital evaluation of the accuracy of complete crowns. Copyright © 2017 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

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

Rottmann, J; Berbeco, R; Keall, P

Purpose: To maximize normal tissue sparing for treatments requiring motion encompassing margins. Motion mitigation techniques including DMLC or couch tracking can freeze tumor motion within the treatment aperture potentially allowing for smaller treatment margins and thus better sparing of normal tissue. To enable for a safe application of this concept in the clinic we propose adapting margins dynamically in real-time during radiotherapy delivery based on personalized tumor localization confidence. To demonstrate technical feasibility we present a phantom study. Methods: We utilize a realistic anthropomorphic dynamic thorax phantom with a lung tumor model embedded close to the spine. The tumor, amore » 3D-printout of a patient's GTV, is moved 15mm peak-to-peak by diaphragm compression and monitored by continuous EPID imaging in real-time. Two treatment apertures are created for each beam, one representing ITV -based and the other GTV-based margin expansion. A soft tissue localization (STiL) algorithm utilizing the continuous EPID images is employed to freeze tumor motion within the treatment aperture by means of DMLC tracking. Depending on a tracking confidence measure (TCM), the treatment aperture is adjusted between the ITV and the GTV leaf. Results: We successfully demonstrate real-time personalized margin adjustment in a phantom study. We measured a system latency of about 250 ms which we compensated by utilizing a respiratory motion prediction algorithm (ridge regression). With prediction in place we observe tracking accuracies better than 1mm. For TCM=0 (as during startup) an ITV-based treatment aperture is chosen, for TCM=1 a GTV-based aperture and for 0« less

A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data.

PubMed

Pandey, Gaurav; Pandey, Om P; Rogers, Angela J; Ahsen, Mehmet E; Hoffman, Gabriel E; Raby, Benjamin A; Weiss, Scott T; Schadt, Eric E; Bunyavanich, Supinda

2018-06-11

Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of nasal samples. A machine learning-based pipeline identified an asthma classifier consisting of 90 genes interpreted via an L2-regularized logistic regression classification model. This classifier performed with strong predictive value and sensitivity across eight test sets, including (1) a test set of independent asthmatic and control subjects profiled by RNA sequencing (positive and negative predictive values of 1.00 and 0.96, respectively; AUC of 0.994), (2) two independent case-control cohorts of asthma profiled by microarray, and (3) five cohorts with other respiratory conditions (allergic rhinitis, upper respiratory infection, cystic fibrosis, smoking), where the classifier had a low to zero misclassification rate. Following validation in large, prospective cohorts, this classifier could be developed into a nasal biomarker of asthma.

Towards SSVEP-based, portable, responsive Brain-Computer Interface.

PubMed

Kaczmarek, Piotr; Salomon, Pawel

2015-08-01

A Brain-Computer Interface in motion control application requires high system responsiveness and accuracy. SSVEP interface consisted of 2-8 stimuli and 2 channel EEG amplifier was presented in this paper. The observed stimulus is recognized based on a canonical correlation calculated in 1 second window, ensuring high interface responsiveness. A threshold classifier with hysteresis (T-H) was proposed for recognition purposes. Obtained results suggest that T-H classifier enables to significantly increase classifier performance (resulting in accuracy of 76%, while maintaining average false positive detection rate of stimulus different then observed one between 2-13%, depending on stimulus frequency). It was shown that the parameters of T-H classifier, maximizing true positive rate, can be estimated by gradient-based search since the single maximum was observed. Moreover the preliminary results, performed on a test group (N=4), suggest that for T-H classifier exists a certain set of parameters for which the system accuracy is similar to accuracy obtained for user-trained classifier.

Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis

PubMed Central

Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

2016-01-01

The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. PMID:27104948

Submarine landslide and tsunami hazards offshore southern Alaska: Seismic strengthening versus rapid sedimentation

NASA Astrophysics Data System (ADS)

Sawyer, Derek E.; Reece, Robert S.; Gulick, Sean P. S.; Lenz, Brandi L.

2017-08-01

The southern Alaskan offshore margin is prone to submarine landslides and tsunami hazards due to seismically active plate boundaries and extreme sedimentation rates from glacially enhanced mountain erosion. We examine the submarine landslide potential with new shear strength measurements acquired by Integrated Ocean Drilling Program Expedition 341 on the continental slope and Surveyor Fan. These data reveal lower than expected sediment strength. Contrary to other active margins where seismic strengthening enhances slope stability, the high-sedimentation margin offshore southern Alaska behaves like a passive margin from a shear strength perspective. We interpret that seismic strengthening occurs but is offset by high sedimentation rates and overpressure. This conclusion is supported by shear strength outside of the fan that follow an active margin trend. More broadly, seismically active margins with wet-based glaciers are susceptible to submarine landslide hazards because of the combination of high sedimentation rates and earthquake shaking.

Model-Based Systems Engineering Approach to Managing Mass Margin

NASA Technical Reports Server (NTRS)

Chung, Seung H.; Bayer, Todd J.; Cole, Bjorn; Cooke, Brian; Dekens, Frank; Delp, Christopher; Lam, Doris

2012-01-01

When designing a flight system from concept through implementation, one of the fundamental systems engineering tasks ismanaging the mass margin and a mass equipment list (MEL) of the flight system. While generating a MEL and computing a mass margin is conceptually a trivial task, maintaining consistent and correct MELs and mass margins can be challenging due to the current practices of maintaining duplicate information in various forms, such as diagrams and tables, and in various media, such as files and emails. We have overcome this challenge through a model-based systems engineering (MBSE) approach within which we allow only a single-source-of-truth. In this paper we describe the modeling patternsused to capture the single-source-of-truth and the views that have been developed for the Europa Habitability Mission (EHM) project, a mission concept study, at the Jet Propulsion Laboratory (JPL).

Sedimentary evolution of the Pliocene and Pleistocene Ebro margin, northeastern Spain

USGS Publications Warehouse

Alonso, B.; Field, M.E.; Gardner, J.V.; Maldonado, A.

1990-01-01

The Pliocene and Pleistocene deposits of the Spanish Ebro margin overlie a regional unconformity and contain a major disconformity. These unconformities, named Reflector M and Reflector G, mark the bases of two seismic sequences. Except for close to the upper boundary where a few small channel deposits are recognized, the lower sequence lacks channels. The upper sequence contains nine channel-levee complexes as well as base-of-slope aprons that represent the proximal part of the Valencia turbidite system. Diverse geometries and variations in seismic units distinguish shelf, slope, base-of-slope and basin-floor facies. Four events characterize the late Miocene to Pleistocene evolution of the Ebro margin: (a) formation of a paleodrainage system and an extensive erosion-to-depositional surface during the latest Miocene (Messinian), (b) deposition of hemipelagic units during the early Pliocene, (c) development of canyons during the late Pliocene to early Pleistocene, and (d) deposition of slope wedges, channel-levee complexes, and base-of-slope aprons alternating with hemipelagic deposition during the Pleistocene. Sea-level fluctuations influenced the evolution of the sedimentary sequences of the Ebro margin, but the major control was the sediment supply from the Ebro River. ?? 1990.

Text categorization of biomedical data sets using graph kernels and a controlled vocabulary.

PubMed

Bleik, Said; Mishra, Meenakshi; Huan, Jun; Song, Min

2013-01-01

Recently, graph representations of text have been showing improved performance over conventional bag-of-words representations in text categorization applications. In this paper, we present a graph-based representation for biomedical articles and use graph kernels to classify those articles into high-level categories. In our representation, common biomedical concepts and semantic relationships are identified with the help of an existing ontology and are used to build a rich graph structure that provides a consistent feature set and preserves additional semantic information that could improve a classifier's performance. We attempt to classify the graphs using both a set-based graph kernel that is capable of dealing with the disconnected nature of the graphs and a simple linear kernel. Finally, we report the results comparing the classification performance of the kernel classifiers to common text-based classifiers.

Metabolomic Analysis Reveals Extended Metabolic Consequences of Marginal Vitamin B-6 Deficiency in Healthy Human Subjects

PubMed Central

Lamers, Yvonne; Bandyopadhyay, Nirmalya; Chi, Yueh-Yun; Lee, Kichen; Kim, Steven; da Silva, Vanessa; Hove, Nikolas; Ranka, Sanjay; Kahveci, Tamer; Muller, Keith E.; Stevens, Robert D.; Newgard, Christopher B.; Stacpoole, Peter W.; Jones, Dean P.

2013-01-01

Marginal deficiency of vitamin B-6 is common among segments of the population worldwide. Because pyridoxal 5′-phosphate (PLP) serves as a coenzyme in the metabolism of amino acids, carbohydrates, organic acids, and neurotransmitters, as well as in aspects of one-carbon metabolism, vitamin B-6 deficiency could have many effects. Healthy men and women (age: 20-40 y; n = 23) were fed a 2-day controlled, nutritionally adequate diet followed by a 28-day low-vitamin B-6 diet (<0.5 mg/d) to induce marginal deficiency, as reflected by a decline of plasma PLP from 52.6±14.1 (mean ± SD) to 21.5±4.6 nmol/L (P<0.0001) and increased cystathionine from 131±65 to 199±56 nmol/L (P<0.001). Fasting plasma samples obtained before and after vitamin B6 restriction were analyzed by 1H-NMR with and without filtration and by targeted quantitative analysis by mass spectrometry (MS). Multilevel partial least squares-discriminant analysis and S-plots of NMR spectra showed that NMR is effective in classifying samples according to vitamin B-6 status and identified discriminating features. NMR spectral features of selected metabolites indicated that vitamin B-6 restriction significantly increased the ratios of glutamine/glutamate and 2-oxoglutarate/glutamate (P<0.001) and tended to increase concentrations of acetate, pyruvate, and trimethylamine-N-oxide (adjusted P<0.05). Tandem MS showed significantly greater plasma proline after vitamin B-6 restriction (adjusted P<0.05), but there were no effects on the profile of 14 other amino acids and 45 acylcarnitines. These findings demonstrate that marginal vitamin B-6 deficiency has widespread metabolic perturbations and illustrate the utility of metabolomics in evaluating complex effects of altered vitamin B-6 intake. PMID:23776431

Osteosarcoma of the spine: prognostic variables for local recurrence and overall survival, a multicenter ambispective study.

PubMed

Dekutoski, Mark B; Clarke, Michelle J; Rose, Peter; Luzzati, Alessandro; Rhines, Laurence D; Varga, Peter P; Fisher, Charles G; Chou, Dean; Fehlings, Michael G; Reynolds, Jeremy J; Williams, Richard; Quraishi, Nasir A; Germscheid, Niccole M; Sciubba, Daniel M; Gokaslan, Ziya L; Boriani, Stefano

2016-07-01

OBJECTIVE Primary spinal osteosarcomas are rare and aggressive neoplasms. Poor outcomes can occur, as obtaining marginal margins is technically demanding; further Enneking-appropriate en bloc resection can have significant morbidity. The goal of this study is to identify prognostic variables for local recurrence and mortality in surgically treated patients diagnosed with a primary osteosarcoma of the spine. METHODS A multicenter ambispective database of surgically treated patients with primary spine osteosarcomas was developed by AOSpine Knowledge Forum Tumor. Patient demographic, diagnosis, treatment, perioperative morbidity, local recurrence, and cross-sectional survival data were collected. Tumors were classified in 2 cohorts: Enneking appropriate (EA) and Enneking inappropriate (EI), as defined by pathology margin matching Enneking-recommended surgical margins. Prognostic variables were analyzed in reference to local recurrence and survival. RESULTS Between 1987 and 2012, 58 patients (32 female patients) underwent surgical treatment for primary spinal osteosarcoma. Patients were followed for a mean period of 3.5 ± 3.5 years (range 0.5 days to 14.3 years). The median survival for the entire cohort was 6.7 years postoperative. Twenty-four (41%) patients died, and 17 (30%) patients suffered a local recurrence, 10 (59%) of whom died. Twenty-nine (53%) patients underwent EA resection while 26 (47%) patients underwent EI resection with a postoperative median survival of 6.8 and 3.7 years, respectively (p = 0.048). EI patients had a higher rate of local recurrence than EA patients (p = 0.001). Patient age, previous surgery, biopsy type, tumor size, spine level, and chemotherapy timing did not significantly influence recurrence and survival. CONCLUSIONS Osteosarcoma of the spine presents a significant challenge, and most patients die in spite of aggressive surgery. There is a significant decrease in recurrence and an increase in survival with en bloc resection (EA) when compared with intralesional resection (EI). The effect of adjuvant and neoadjuvant chemotherapeutics, as well as method of biopsy, requires further exploration.

Playing jigsaw with large igneous provinces - a plate-tectonic reconstruction of Ontong Java Nui

NASA Astrophysics Data System (ADS)

Hochmuth, Katharina; Gohl, Karsten; Uenzelmann-Neben, Gabriele; Werner, Reinhard

2015-04-01

Ontong Java Nui is a Cretaceous large igneous province (LIP), which was rifted apart into various smaller plateaus shortly after its emplacement around 125 Ma in the central Pacific. It incorporated the Ontong Java Plateau, the Hikurangi Plateau and the Manihiki Plateau as well as multiple smaller fragments, which have been subducted. Its size has been estimated to be approximately 0.8% of the Earth's surface. A volcanic edifice of this size has potentially had a great impact on the environment such as its CO2 release. The break-up of the "Super"-LIP is poorly constrained, because the break-up and subsequent seafloor spreading occurred within the Cretaceous Quiet Period. The Manihiki Plateau is presumably the centerpiece of this "Super"-LIP and shows by its margins and internal fragmentation that its tectonic and volcanic activity is related to the break-up of Ontong Java Nui. By incorporating two new seismic refraction/wide-angle reflection lines across two of the main sub-plateaus of the Manihiki Plateau, we can classify the break-up modes of the individual margins of the Manihiki Plateau. The Western Plateaus experienced crustal stretching due to the westward motion of the Ontong Java Plateau. The High Plateau shows sharp strike-slip movements at its eastern boundary towards an earlier part of Ontong Java Nui, which is has been subducted, and a rifted margin with a strong volcanic overprint at its southern edges towards the Hikurangi Plateau. These observations allow us a re-examination of the conjugate margins of the Hikurangi Plateau and the Ontong Java Plateau. The repositioning of the different plateaus leads to the conclusion that Ontong Java Nui was larger (~1.2% of the Earth's surface at emplacement) than previously anticipated. We use these finding to improve the plate tectonic reconstruction of the Cretaceous Pacific and to illuminate the role of the LIPs within the plate tectonic circuit in the western and central Pacific.

Anatomy of the Kitimat fiord system, British Columbia

NASA Astrophysics Data System (ADS)

Shaw, John; Stacey, Cooper D.; Wu, Yongsheng; Lintern, D. Gwyn

2017-09-01

The geomorphic complexity of the Kitimat fiord system, on the active margin of British Columbia, Canada, is analysed from several perspectives. Sub-glacial landforms and sediments show that grounded ice exiting the fiord system at the last glacial maximum streamed down Moresby Trough towards the Queen Charlotte trough mouth fan. After brief halts on the inner shelf, grounded ice margins cleared the fiord threshold perhaps by c. 15.5 ka cal. yrs BP, and certainly before 13 ka cal. yrs BP. Just outside the fiords, meltwater plumes deposited stratified glaciomarine sediments interbedded with submarine slides. Inside the fiords, thick glaciomarine sediments were deposited, and large transverse moraines formed during temporary halts in retreat. Several glacial outburst floods eroded the Kitkiata moraine and deposited distinctive mud deposits. Postglacial sedimentation on fiord floors has been spatially variable: drifts of mud > 90 m-thick corresponding with areas of low current velocity alternate with areas of non-deposition and erosion corresponding with areas of high velocity. The fiord system hosts more than a hundred morphologically diverse fan deltas that can be classified in the Prior and Bornhold (1989, 1990) system. Submarine mass transport was most frequent immediately following ice retreat (15.5-11.5 ka cal. yrs BP). The largest event ( 1.2 km3) involved failure of glaciomarine sediment on a submarine moraine at Squally Channel, and consequent movement of material into the adjacent deep basin. This event occurred post-13 ka cal. yrs BP. In the postglacial phase, mass transport continued on a lesser scale up to the present day, most intensively in Kitimat Arm. From the perspective of glacial landforms, postglacial sedimentation and mass transport, this Pacific active margin fiord system has some parallels with fiord systems on Canada's east coast passive margin, and with Norwegian fiords, but the intensive development of Holocene fan deltas is strongly distinctive.

Structure and evolution of the NE Atlantic conjugate margins off Norway and Greenland (Invited)

NASA Astrophysics Data System (ADS)

Faleide, J.; Planke, S.; Theissen-Krah, S.; Abdelmalak, M.; Zastrozhnov, D.; Tsikalas, F.; Breivik, A. J.; Torsvik, T. H.; Gaina, C.; Schmid, D. W.; Myklebust, R.; Mjelde, R.

2013-12-01

The continental margins off Norway and NE Greenland evolved in response to the Cenozoic opening of the NE Atlantic. The margins exhibit a distinct along-margin segmentation reflecting structural inheritance extending back to a complex pre-breakup geological history. The sedimentary basins at the conjugate margins developed as a result of multiple phases of post-Caledonian rifting from Late Paleozoic time to final NE Atlantic breakup at the Paleocene-Eocene transition. The >200 million years of repeated extension caused comprehensive crustal thinning and formation of deep sedimentary basins. The main rift phases span the following time intervals: Late Permian, late Middle Jurassic-earliest Cretaceous, Early-mid Cretaceous and Late Cretaceous-Paleocene. The late Mesozoic-early Cenozoic rifting was related to the northward propagation of North Atlantic sea floor spreading, but also linked to important tectonic events in the Arctic. The pre-drift extension is quantified based on observed geometries of crustal thinning and stretching factors derived from tectonic modeling. The total (cumulative) pre-drift extension amounts to in the order of 300 km which correlates well with estimates from plate reconstructions based on paleomagnetic data. Final lithospheric breakup at the Paleocene-Eocene transition culminated in a 3-6 m.y. period of massive magmatic activity during breakup and onset of early sea-floor spreading, forming a part of the North Atlantic Volcanic Province. At the outer parts of the conjugate margins, the lavas form characteristic seaward dipping reflector sequences and lava deltas that drilling has demonstrated to be subaerially and/or neritically erupted basalts. The continent-ocean transition is usually well defined as a rapid increase of P-wave velocities at mid- to lower-crustal levels. Maximum igneous crustal thickness of about 18 km is found across the outer Vøring Plateau on the Norwegian Margin, and lower-crustal P-wave velocities of up to 7.3 km/s are found at the bottom of the igneous crust here. The igneous crust, including the characteristic 7+ km/s lower crustal body, is even thicker on the East Greenland Margin. During the main igneous episode, sills intruded into the thick Cretaceous successions throughout the NE Atlantic margins. Strong crustal reflections can be mapped widespread on both conjugate margins. In some areas they are associated with the top of the high-velocity lower crustal body, in other areas they may represent deeply buried sedimentary sequence boundaries or moho at the base of the crust. Following breakup, the subsiding margins experienced modest sedimentation until the late Pliocene when large wedges of glacial sediments prograded into the deep ocean from uplifted areas along the continental margins. The outbuilding was probably initiated in Miocene time indicating pre-glacial tectonic uplift of Greenland, Fennoscandia and the Barents Shelf. The NE Atlantic margins also reveal evidence of widespread Cenozoic compressional deformation.

Tailored Treatment Strategy for Locally Advanced Rectal Carcinoma Based on the Tumor Response to Induction Chemotherapy: Preliminary Results of the French Phase II Multicenter GRECCAR4 Trial.

PubMed

Rouanet, Philippe; Rullier, Eric; Lelong, Bernard; Maingon, Philippe; Tuech, Jean-Jacques; Pezet, Denis; Castan, Florence; Nougaret, Stéphanie

2017-07-01

Preoperative radiochemotherapy and total mesorectal excision are the standard-of-care for locally advanced rectal carcinoma, but some patients could be over- or undertreated. This study aimed to assess the feasibility of radiochemotherapy tailored based on the tumor response to induction chemotherapy (FOLFIRINOX) to obtain a minimum R0 resection rate of 90% in the 4 arms of the study. This study is a multicenter randomized trial (NCT01333709). This study was conducted at 16 French cancer specialty centers. Two hundred six patients with locally advanced rectal carcinoma were enrolled between 2011 and 2014. Good responders (≥75% tumor volume reduction) were randomly assigned to immediate surgery (arm A) or standard radiochemotherapy (Cap 50: 50 Gy irradiation and 1600 mg/m oral capecitabine daily) plus surgery (arm B). Poor responders were randomly assigned to Cap 50 (arm C) or intensive radiochemotherapy (Cap 60, 60 Gy irradiation, arm D) before surgery. The primary end point was a R0 resection rate (circumferential resection margin >1 mm). The experimental strategies were to be considered effective if at least 28 successes (R0 resection) among 31 patients in each arm of stratum I and 34 successes among 40 patients in each arm of stratum II were reported (Simon 2-stage design). After induction treatment (good compliance), 194 patients were classified as good (n = 30, 15%) or poor (n = 164, 85%) responders who were included in arms A and B (16 and 14 patients) and arms C and D (113 and 51 patients). The trial was prematurely stopped because of low accrual in arms A and B and recruitment completion in arms C and D. Data from 133 randomly assigned patients were analyzed: 11, 19, 52, and 51 patients in arms A, B, C, and D. Good responders had smaller tumors than poor responders (23 cm vs 45 cm; p < 0.001). The surgical procedure was similar among groups. The R0 resection rates [90% CI] were 100% [70-100], 100% [85-100], 83% [72-91], and 88% [77-95]. Among the first 40 patients, 34 successes were reported in arms C and D (85% R0 resection rate). The circumferential resection margin ≤1 rates were 0%, 0%, 12%, and 5% in arms A, B, C, and D. The rate of transformation from positive to negative circumferential resection margin was 93%. There was low accrual in arms A and B. Tailoring preoperative radiochemotherapy based on the induction treatment response appears safe for poor responders and promising for good responders. Long-term clinical results are needed to confirm its efficacy. See Video Abstract at http://links.lww.com/DCR/A359.

Land degradation and Poverty in maize producing areas of Kenya - Development of an interdisciplinary analysis framework using GIS and remote sensing

NASA Astrophysics Data System (ADS)

Graw, Valerie; Nkonya, Ephraim; Menz, Gunter

2014-05-01

Land degradation causes poverty and vice versa. But both processes are highly complex, hard to predict and to mitigate, and need insights from different perspectives. Therefore an interdisciplinary framework for the understanding of land degradation processes by linking biophysical data with socio-economic trends is necessary. Agricultural systems in Kenya are affected by land degradation and especially recent developments such as agricultural innovations including the use of hybrid seeds and chemical fertilizer have an impact on the environment. Vegetation analysis, used as a proxy indicator for the status of land is carried out to monitor environmental changes in maize producing areas of western Kenya. One of the methods used in this study includes time series analysis of vegetation data from 2001 to 2010 based on MODIS NDVI data with 250m and 500m resolution. Occurring trends are linked to rainfall estimation data and annually classified land use cover data with 500m resolution based on MODIS within the same time period. Analysis of significant trends in combination with land cover information show recent land change dynamics. As these changes are not solely biophysically driven, socio-economic variables representing marginality - defined as the root cause of poverty- are also considered. The most poor are primarily facing the most vulnerable and thereby less fertile soils. Moreover they are lacking access to information to eventually use existing potential. This makes the analysis of changing environmental processes and household characteristics in the interplay important to understand in order to highlight the most influencing variables. Within the new interdisciplinary analysis framework the concept of marginality includes different dimensions referring to certain livelihood characteristics such as health and education which describe a more diverse picture of poverty than the known economic perspective. Household surveys and census data from different time periods allow the analysis of socio-economic trends and link this information to biophysical factors. If relationships between certain variables are understood, adapted land management strategies can be developed. This study aims at linking pixel-level information with established remote sensing methods to the socio-economic concept of marginality based on household surveys and census data on administrative levels. Besides remote sensing and statistical analysis of socio-economic data a GIS is used for geospatial analysis. As most studies on land degradation focus on biophysical aspects such as vegetation or soil degradation this study uses an innovative approach by integrating biophysical analysis without neglecting a human oriented approach which plays a key role in environmental systems nowadays. This interdisciplinary research helps to get closer to the right and adapted policies and land management strategies as land degradation processes do not stick to administrative boundaries but policy advice does.

An ensemble-of-classifiers based approach for early diagnosis of Alzheimer's disease: classification using structural features of brain images.

PubMed

Farhan, Saima; Fahiem, Muhammad Abuzar; Tauseef, Huma

2014-01-01

Structural brain imaging is playing a vital role in identification of changes that occur in brain associated with Alzheimer's disease. This paper proposes an automated image processing based approach for the identification of AD from MRI of the brain. The proposed approach is novel in a sense that it has higher specificity/accuracy values despite the use of smaller feature set as compared to existing approaches. Moreover, the proposed approach is capable of identifying AD patients in early stages. The dataset selected consists of 85 age and gender matched individuals from OASIS database. The features selected are volume of GM, WM, and CSF and size of hippocampus. Three different classification models (SVM, MLP, and J48) are used for identification of patients and controls. In addition, an ensemble of classifiers, based on majority voting, is adopted to overcome the error caused by an independent base classifier. Ten-fold cross validation strategy is applied for the evaluation of our scheme. Moreover, to evaluate the performance of proposed approach, individual features and combination of features are fed to individual classifiers and ensemble based classifier. Using size of left hippocampus as feature, the accuracy achieved with ensemble of classifiers is 93.75%, with 100% specificity and 87.5% sensitivity.

Histologic processing and reporting of cutaneous pigmented lesions: recommendations based on a survey of 94 dermatopathologists.

PubMed

Kolman, Olga; Hoang, Mai P; Piris, Adriano; Mihm, Martin C; Duncan, Lyn M

2010-10-01

Standard operating procedures for laboratory processing and reporting of margins of cutaneous pigmented lesions do not exist. We conducted a survey of 94 dermatopathologists to evaluate these practices. We sought to: (1) identify dominant practices among dermatopathologists; (2) determine the impact of the procedure, intent to excise, and histologic diagnosis on the process of margin evaluation; and (3) propose guidelines based on these findings. The survey consisted of 44 questions focused on the impact of procedure (punch, shave, or ellipse), intent (excision or biopsy), and histologic diagnosis (common nevus, congenital nevus, atypical nevus, melanoma) on processing and margin reporting. For ellipses, or specimens indicated as excisions, the majority practice (76%-98%) was to ink the specimens. Although more than 90% of observers report the margins on all melanomas and atypical nevi, fewer than 50% of respondents report margins on all nonatypical nevi. The study consists of a survey sample of dermatopathologists and does not represent the practices of those who did not respond to the survey. Based on the results of this survey we have arrived at the following recommendations: (1) ink all specimens that are ellipses or designated as excisions; (2) tips should be evaluated separately if the specimen is an ellipse; (3) obtain levels in cases with tumor in the tip but not at ink if the specimen is an ellipse or excision and the diagnosis is atypical nevus or melanoma; and (4) report margins on all atypical nevi and melanomas. Copyright © 2009 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Regional Variability and Uncertainty of Electric Vehicle Life Cycle CO₂ Emissions across the United States.

PubMed

Tamayao, Mili-Ann M; Michalek, Jeremy J; Hendrickson, Chris; Azevedo, Inês M L

2015-07-21

We characterize regionally specific life cycle CO2 emissions per mile traveled for plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) across the United States under alternative assumptions for regional electricity emission factors, regional boundaries, and charging schemes. We find that estimates based on marginal vs average grid emission factors differ by as much as 50% (using National Electricity Reliability Commission (NERC) regional boundaries). Use of state boundaries versus NERC region boundaries results in estimates that differ by as much as 120% for the same location (using average emission factors). We argue that consumption-based marginal emission factors are conceptually appropriate for evaluating the emissions implications of policies that increase electric vehicle sales or use in a region. We also examine generation-based marginal emission factors to assess robustness. Using these two estimates of NERC region marginal emission factors, we find the following: (1) delayed charging (i.e., starting at midnight) leads to higher emissions in most cases due largely to increased coal in the marginal generation mix at night; (2) the Chevrolet Volt has higher expected life cycle emissions than the Toyota Prius hybrid electric vehicle (the most efficient U.S. gasoline vehicle) across the U.S. in nearly all scenarios; (3) the Nissan Leaf BEV has lower life cycle emissions than the Prius in the western U.S. and in Texas, but the Prius has lower emissions in the northern Midwest regardless of assumed charging scheme and marginal emissions estimation method; (4) in other regions the lowest emitting vehicle depends on charge timing and emission factor estimation assumptions.

The Kidney Donor Profile Index (KDPI) of marginal donors allocated by standardized pretransplant donor biopsy assessment: distribution and association with graft outcomes.

PubMed

Gandolfini, I; Buzio, C; Zanelli, P; Palmisano, A; Cremaschi, E; Vaglio, A; Piotti, G; Melfa, L; La Manna, G; Feliciangeli, G; Cappuccilli, M; Scolari, M P; Capelli, I; Panicali, L; Baraldi, O; Stefoni, S; Buscaroli, A; Ridolfi, L; D'Errico, A; Cappelli, G; Bonucchi, D; Rubbiani, E; Albertazzi, A; Mehrotra, A; Cravedi, P; Maggiore, U

2014-11-01

Pretransplant donor biopsy (PTDB)-based marginal donor allocation systems to single or dual renal transplantation could increase the use of organs with Kidney Donor Profile Index (KDPI) in the highest range (e.g. >80 or >90), whose discard rate approximates 50% in the United States. To test this hypothesis, we retrospectively calculated the KDPI and analyzed the outcomes of 442 marginal kidney transplants (340 single transplants: 278 with a PTDB Remuzzi score<4 [median KDPI: 87; interquartile range (IQR): 78-94] and 62 with a score=4 [median KDPI: 87; IQR: 76-93]; 102 dual transplants [median KDPI: 93; IQR: 86-96]) and 248 single standard transplant controls (median KDPI: 36; IQR: 18-51). PTDB-based allocation of marginal grafts led to a limited discard rate of 15% for kidneys with KDPI of 80-90 and of 37% for kidneys with a KDPI of 91-100. Although 1-year estimated GFRs were significantly lower in recipients of marginal kidneys (-9.3, -17.9 and -18.8 mL/min, for dual transplants, single kidneys with PTDB score<4 and =4, respectively; p<0.001), graft survival (median follow-up 3.3 years) was similar between marginal and standard kidney transplants (hazard ratio: 1.20 [95% confidence interval: 0.80-1.79; p=0.38]). In conclusion, PTDB-based allocation allows the safe transplantation of kidneys with KDPI in the highest range that may otherwise be discarded. © Copyright 2014 The American Society of Transplantation and the American Society of Transplant Surgeons.

Methods of defining the non-inferiority margin in randomized, double-blind controlled trials: a systematic review.

PubMed

Althunian, Turki A; de Boer, Anthonius; Klungel, Olaf H; Insani, Widya N; Groenwold, Rolf H H

2017-03-07

There is no consensus on the preferred method for defining the non-inferiority margin in non-inferiority trials, and previous studies showed that the rationale for its choice is often not reported. This study investigated how the non-inferiority margin is defined in the published literature, and whether its reporting has changed over time. A systematic PubMed search was conducted for all published randomized, double-blind, non-inferiority trials from January 1, 1966, to February 6, 2015. The primary outcome was the number of margins that were defined by methods other than the historical evidence of the active comparator. This was evaluated for a time trend. We also assessed the under-reporting of the methods of defining the margin as a secondary outcome, and whether this changed over time. Both outcomes were analyzed using a Poisson log-linear model. Predictors for better reporting of the methods, and the use of the fixed-margin method (one of the historical evidence methods) were also analyzed using logistic regression. Two hundred seventy-three articles were included, which account for 273 non-inferiority margins. There was no statistically significant difference in the number of margins that were defined by other methods compared to those defined based on the historical evidence (ratio 2.17, 95% CI 0.86 to 5.82, p = 0.11), and this did not change over time. The number of margins for which methods were unreported was similar to those with reported methods (ratio 1.35, 95% CI 0.76 to 2.43, p = 0.31), with no change over time. The method of defining the margin was less often reported in journals with low-impact factors compared to journals with high-impact factors (OR 0.20; 95% CI 0.10 to 0.37, p < 0.0001). The publication of the FDA draft guidance in 2010 was associated with increased reporting of the fixed-margin method (after versus before 2010) (OR 3.54; 95% CI 1.12 to 13.35, p = 0.04). Non-inferiority margins are not commonly defined based on the historical evidence of the active comparator, and they are poorly reported. Authors, reviewers, and editors need to take notice of reporting this critical information to allow for better judgment of non-inferiority trials.

Fit of cast commercially pure titanium and Ti-6Al-4V alloy crowns before and after marginal refinement by electrical discharge machining.

PubMed

Contreras, Edwin Fernando Ruiz; Henriques, Guilherme Elias Pessanha; Giolo, Suely Ruiz; Nobilo, Mauro Antonio Arruda

2002-11-01

Titanium has been suggested as a replacement for alloys currently used in single-tooth restorations and fixed partial dentures. However, difficulties in casting have resulted in incomplete margins and discrepancies in marginal fit. This study evaluated and compared the marginal fit of crowns fabricated from a commercially pure titanium (CP Ti) and from Ti-6Al-4V alloy with crowns fabricated from a Pd-Ag alloy that served as a control. Evaluations were performed before and after marginal refinement by electrical discharge machining (EDM). Forty-five bovine teeth were prepared to receive complete cast crowns. Stone and copper-plated dies were obtained from impressions. Fifteen crowns were cast with each alloy (CP Ti, Ti-6Al-4V, and Pd-Ag). Marginal fit measurements (in micrometers) were recorded at 4 reference points on each casting with a traveling microscope. Marginal refinement with EDM was conducted on the titanium-based crowns, and measurements were repeated. Data were analyzed with the Kruskal-Wallis test, paired t test, and independent t test at a 1% probability level. The Kruskal-Wallis test showed significant differences among mean values of marginal fit for the as-cast CP Ti crowns (mean [SD], 83.9 [26.1] microm) and the other groups: Ti-6Al-4V (50.8 [17.2] microm) and Pd-Ag (45.2 [10.4] microm). After EDM marginal refinement, significant differences were detected among the Ti-6Al-4V crowns (24.5 [10.9] microm) and the other 2 groups: CP Ti (50.6 [20.0] microm) and Pd-Ag (not modified by EDM). Paired t test results indicated that marginal refinement with EDM effectively improved the fit of CP Ti crowns (from 83.9 to 50.6 microm) and Ti-6Al-4V crowns (from 50.8 to 24.5 microm). However, the difference in improvement between the two groups was not significant by t test. Within the limitations of this study, despite the superior results for Ti-6Al-4V, both groups of titanium-based crowns had clinically acceptable marginal fits. After EDM marginal refinement, the fit of cast CP Ti and Ti-6Al-4V crowns improved significantly.

Constraints Imposed by Rift Inheritance on the Compressional Reactivation of a Hyperextended Margin: Mapping Rift Domains in the North Iberian Margin and in the Cantabrian Mountains

NASA Astrophysics Data System (ADS)

Cadenas, P.; Fernández-Viejo, G.; Pulgar, J. A.; Tugend, J.; Manatschal, G.; Minshull, T. A.

2018-03-01

The Alpine Pyrenean-Cantabrian orogen developed along the plate boundary between Iberia and Europe, involving the inversion of Mesozoic hyperextended basins along the southern Biscay margin. Thus, this margin represents a natural laboratory to analyze the control of structural rift inheritance on the compressional reactivation of a continental margin. With the aim to identify former rift domains and investigate their role during the subsequent compression, we performed a structural analysis of the central and western North Iberian margin, based on the interpretation of seismic reflection profiles and local constraints from drill-hole data. Seismic interpretations and published seismic velocity models enabled the development of crustal thickness maps that helped to constrain further the offshore and onshore segmentation. Based on all these constraints, we present a rift domain map across the central and western North Iberian margin, as far as the adjacent western Cantabrian Mountains. Furthermore, we provide a first-order description of the margin segmentation resulting from its polyphase tectonic evolution. The most striking result is the presence of a hyperthinned domain (e.g., Asturian Basin) along the central continental platform that is bounded to the north by the Le Danois High, interpreted as a rift-related continental block separating two distinctive hyperextended domains. From the analysis of the rift domain map and the distribution of reactivation structures, we conclude that the landward limit of the necking domain and the hyperextended domains, respectively, guide and localize the compressional overprint. The Le Danois block acted as a local buttress, conditioning the inversion of the Asturian Basin.

Towards Biogeochemical Modeling of Anaerobic Oxidation of Methane: Characterization of Microbial Communities in Methane-bearing North American Continental Margin Sediments

NASA Astrophysics Data System (ADS)

Graw, M. F.; Solomon, E. A.; Chrisler, W.; Krause, S.; Treude, T.; Ruppel, C. D.; Pohlman, J.; Colwell, F. S.

2015-12-01

Methane advecting through continental margin sediments may enter the water column and potentially contribute to ocean acidification and increase atmospheric methane concentrations. Anaerobic oxidation of methane (AOM), mediated by syntrophic consortia of anaerobic methanotrophic archaea and sulfate-reducing bacteria (ANME-SRB), consumes nearly all dissolved methane in methane-bearing sediments before it reaches the sediment-water interface. Despite the significant role ANME-SRB play in carbon cycling, our knowledge of these organisms and their surrounding microbial communities is limited. Our objective is to develop a metabolic model of ANME-SRB within methane-bearing sediments and to couple this to a geochemical reaction-transport model for these margins. As a first step towards this goal, we undertook fluorescent microscopic imaging, 16S rRNA gene deep-sequencing, and shotgun metagenomic sequencing of sediments from the US Pacific (Washington) and northern Atlantic margins where ANME-SRB are present. A successful Illumina MiSeq sequencing run yielded 106,257 bacterial and 857,834 archaeal 16S rRNA gene sequences from 12 communities from the Washington Margin using both universal prokaryotic and archaeal-specific primer sets. Fluorescent microscopy confirmed the presence of cells of the ANME-2c lineage in the sequenced communities. Microbial community characterization was coupled with measurements of sediment physical and geochemical properties and, for samples from the US Atlantic margin, 14C-based measurements of AOM rates and 35S-based measurements of sulfate reduction rates. These findings have the potential to increase understanding of ANME-SRB, their surrounding microbial communities, and their role in carbon cycling within continental margins. In addition, they pave the way for future efforts at developing a metabolic model of ANME-SRB and coupling it to geochemical models of the US Washington and Atlantic margins.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

PubMed

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2016-01-15

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

The scenario-based generalization of radiation therapy margins.

PubMed

Fredriksson, Albin; Bokrantz, Rasmus

2016-03-07

We give a scenario-based treatment plan optimization formulation that is equivalent to planning with geometric margins if the scenario doses are calculated using the static dose cloud approximation. If the scenario doses are instead calculated more accurately, then our formulation provides a novel robust planning method that overcomes many of the difficulties associated with previous scenario-based robust planning methods. In particular, our method protects only against uncertainties that can occur in practice, it gives a sharp dose fall-off outside high dose regions, and it avoids underdosage of the target in 'easy' scenarios. The method shares the benefits of the previous scenario-based robust planning methods over geometric margins for applications where the static dose cloud approximation is inaccurate, such as irradiation with few fields and irradiation with ion beams. These properties are demonstrated on a suite of phantom cases planned for treatment with scanned proton beams subject to systematic setup uncertainty.

Classifier ensemble based on feature selection and diversity measures for predicting the affinity of A(2B) adenosine receptor antagonists.

PubMed

Bonet, Isis; Franco-Montero, Pedro; Rivero, Virginia; Teijeira, Marta; Borges, Fernanda; Uriarte, Eugenio; Morales Helguera, Aliuska

2013-12-23

A(2B) adenosine receptor antagonists may be beneficial in treating diseases like asthma, diabetes, diabetic retinopathy, and certain cancers. This has stimulated research for the development of potent ligands for this subtype, based on quantitative structure-affinity relationships. In this work, a new ensemble machine learning algorithm is proposed for classification and prediction of the ligand-binding affinity of A(2B) adenosine receptor antagonists. This algorithm is based on the training of different classifier models with multiple training sets (composed of the same compounds but represented by diverse features). The k-nearest neighbor, decision trees, neural networks, and support vector machines were used as single classifiers. To select the base classifiers for combining into the ensemble, several diversity measures were employed. The final multiclassifier prediction results were computed from the output obtained by using a combination of selected base classifiers output, by utilizing different mathematical functions including the following: majority vote, maximum and average probability. In this work, 10-fold cross- and external validation were used. The strategy led to the following results: i) the single classifiers, together with previous features selections, resulted in good overall accuracy, ii) a comparison between single classifiers, and their combinations in the multiclassifier model, showed that using our ensemble gave a better performance than the single classifier model, and iii) our multiclassifier model performed better than the most widely used multiclassifier models in the literature. The results and statistical analysis demonstrated the supremacy of our multiclassifier approach for predicting the affinity of A(2B) adenosine receptor antagonists, and it can be used to develop other QSAR models.

Quantifying the Evolution of Melt Ponds in the Marginal Ice Zone Using High Resolution Optical Imagery and Neural Networks

NASA Astrophysics Data System (ADS)

Ortiz, M.; Pinales, J. C.; Graber, H. C.; Wilkinson, J.; Lund, B.

2016-02-01

Melt ponds on sea ice play a significant and complex role on the thermodynamics in the Marginal Ice Zone (MIZ). Ponding reduces the sea ice's ability to reflect sunlight, and in consequence, exacerbates the albedo positive feedback cycle. In order to understand how melt ponds work and their effect on the heat uptake of sea ice, we must quantify ponds through their seasonal evolution first. A semi-supervised neural network three-class learning scheme using a gradient descent with momentum and adaptive learning rate backpropagation function is applied to classify melt ponds/melt areas in the Beaufort Sea region. The network uses high resolution panchromatic satellite images from the MEDEA program, which are collocated with autonomous platform arrays from the Marginal Ice Zone Program, including ice mass-balance buoys, arctic weather stations and wave buoys. The goal of the study is to capture the spatial variation of melt onset and freeze-up of the ponds within the MIZ, and gather ponding statistics such as size and concentration. The innovation of this work comes from training the neural network as the melt ponds evolve over time; making the machine learning algorithm time-dependent, which has not been previously done. We will achieve this by analyzing the image histograms through quantification of the minima and maxima intensity changes as well as linking textural variation information of the imagery. We will compare the evolution of the melt ponds against several different array sites on the sea ice to explore if there are spatial differences among the separated platforms in the MIZ.

H. Pylori as a predictor of marginal ulceration: A nationwide analysis.

PubMed

Schulman, Allison R; Abougergi, Marwan S; Thompson, Christopher C

2017-03-01

Helicobacter pylori has been implicated as a risk factor for development of marginal ulceration following gastric bypass, although studies have been small and yielded conflicting results. This study sought to determine the relationship between H. pylori infection and development of marginal ulceration following bariatric surgery in a nationwide analysis. This was a retrospective cohort study using the 2012 Nationwide Inpatient Sample (NIS) database. Discharges with ICD-9-CM code indicating marginal ulceration and a secondary ICD-9-CM code for bariatric surgery were included. Primary outcome was incidence of marginal ulceration. A stepwise forward selection model was used to build the multivariate logistic regression model based on known risk factors. A P value of 0.05 was considered significant. There were 253,765 patients who met inclusion criteria. Prevalence of marginal ulceration was 3.90%. Of those patients found to have marginal ulceration, 31.20% of patients were H. pylori-positive. Final multivariate regression analysis revealed that H. pylori was the strongest independent predictor of marginal ulceration. H. pylori is an independent predictor of marginal ulceration using a large national database. Preoperative testing for and eradication of H. pylori prior to bariatric surgery may be an important preventive measure to reduce the incidence of ulcer development. © 2017 The Obesity Society.

Significance of post-resection tissue shrinkage on surgical margins of oral squamous cell carcinoma.

PubMed

El-Fol, Hossam Abdelkader; Noman, Samer Abduljabar; Beheiri, Mohamed Galal; Khalil, Abdalla M; Kamel, Mahmoud Mohamed

2015-05-01

Resecting oral squamous cell carcinoma (SCC) with an appropriate margin of uninvolved tissue is critical in preventing local recurrence and in making decisions regarding postoperative radiation therapy. This task can be difficult due to the discrepancy between margins measured intraoperatively and those measured microscopically by the pathologist after specimen processing. A total of 61 patients underwent resective surgery with curative intent for primary oral SCC were included in this study. All patients underwent resection of the tumor with a measured 1-cm margin. Specimens were then submitted for processing and reviewing, and histopathologic margins were measured. The closest histopathologic margin was compared with the in situ margin (1 cm) to determine the percentage discrepancy. The mean discrepancy between the in situ margins and the histopathological margins of all close and positive margins were 47.6% for the buccal mucosa (with a P value corresponding to 0.05 equaling 2.1), which is statistically significant, 4.8% for the floor of mouth, 9.5% for the mandibular alveolus, 4.8% for the retromolar trigon, and 33.3% for the tongue. There is a significant difference among resection margins based on tumor anatomical location. Margins shrinkage after resection and processing should be considered at the time of the initial resection. Tumors located in the buccal mucosa show significantly greater discrepancies than tumors at other sites. These findings suggest that it is critical to consider the oral site when outlining margins to ensure adequacy of resection. Buccal SCC is an aggressive disease, and should be considered as an aggressive subsite within the oral cavity, requiring a radical and aggressive resective approach. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Urinary Volatile Organic Compounds for the Detection of Prostate Cancer

PubMed Central

Khalid, Tanzeela; Aggio, Raphael; White, Paul; De Lacy Costello, Ben; Persad, Raj; Al-Kateb, Huda; Jones, Peter; Probert, Chris S.; Ratcliffe, Norman

2015-01-01

The aim of this work was to investigate volatile organic compounds (VOCs) emanating from urine samples to determine whether they can be used to classify samples into those from prostate cancer and non-cancer groups. Participants were men referred for a trans-rectal ultrasound-guided prostate biopsy because of an elevated prostate specific antigen (PSA) level or abnormal findings on digital rectal examination. Urine samples were collected from patients with prostate cancer (n = 59) and cancer-free controls (n = 43), on the day of their biopsy, prior to their procedure. VOCs from the headspace of basified urine samples were extracted using solid-phase micro-extraction and analysed by gas chromatography/mass spectrometry. Classifiers were developed using Random Forest (RF) and Linear Discriminant Analysis (LDA) classification techniques. PSA alone had an accuracy of 62–64% in these samples. A model based on 4 VOCs, 2,6-dimethyl-7-octen-2-ol, pentanal, 3-octanone, and 2-octanone, was marginally more accurate 63–65%. When combined, PSA level and these four VOCs had mean accuracies of 74% and 65%, using RF and LDA, respectively. With repeated double cross-validation, the mean accuracies fell to 71% and 65%, using RF and LDA, respectively. Results from VOC profiling of urine headspace are encouraging and suggest that there are other metabolomic avenues worth exploring which could help improve the stratification of men at risk of prostate cancer. This study also adds to our knowledge on the profile of compounds found in basified urine, from controls and cancer patients, which is useful information for future studies comparing the urine from patients with other disease states. PMID:26599280

The genus Pirenella Gray, 1847 (= Cerithideopsilla Thiele, 1929) (Gastropoda: Potamididae) in the Indo-West Pacific region and Mediterranean Sea.

PubMed

Reid, David G; Ozawa, Tomowo

2016-02-05

Members of the genus Pirenella are abundant inhabitants of intertidal sedimentary shores, often found in association with mangroves, on the continental margins of the western Pacific and Indian Oceans, and eastern Mediterranean Sea. Until recently, four morphological species were recognised in the tropical Indo-West Pacific region and classified in the genus Cerithideopsilla, while another species occupying the Mediterranean and Indian Ocean was classified as Pirenella conica. Molecular phylogenetic analysis has demonstrated that all these species are congeneric and here it is shown that the valid name for the genus is Pirenella. A recently published molecular study recognised a total of 16 species and the present work is a systematic account of these species. Of the 16, nine are described as new. Other significant nomenclatural acts are: fixation of type species of Pirenella as Pirenella mammillata J.E. Gray, 1847; designation of neotypes for Cerithium alatum Philippi, 1849, Cerithium microptera Kiener, 1841, Cerithium conicum Blainville, 1829, Pirenella mammillata J.E. Gray, 1847 and Murex cingulatus Gmelin, 1791; designation of lectotype for Cerithium retiferum G.B. Sowerby II, 1855. The species accounts include full synonymies, detailed descriptions of shells (based on 831 museum samples), distribution records and maps, reviews of life history, of habitat and of ecology, and some images of radulae. Details of shell sculpture are adequate for the diagnosis of most species. Distorted shells are common in some populations and are suggested to represent parasitised individuals. Some species are pests of fishponds in Southeast Asia and P. conica is the intermediate host of a trematode responsible for the human disease heterophyiasis, while others are threatened by habitat destruction.

Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks

NASA Astrophysics Data System (ADS)

Halicek, Martin; Little, James V.; Wang, Xu; Patel, Mihir; Griffith, Christopher C.; El-Deiry, Mark W.; Chen, Amy Y.; Fei, Baowei

2018-02-01

Successful outcomes of surgical cancer resection necessitate negative, cancer-free surgical margins. Currently, tissue samples are sent to pathology for diagnostic confirmation. Hyperspectral imaging (HSI) is an emerging, non-contact optical imaging technique. A reliable optical method could serve to diagnose and biopsy specimens in real-time. Using convolutional neural networks (CNNs) as a tissue classifier, we developed a method to use HSI to perform an optical biopsy of ex-vivo surgical specimens, collected from 21 patients undergoing surgical cancer resection. Training and testing on samples from different patients, the CNN can distinguish squamous cell carcinoma (SCCa) from normal aerodigestive tract tissues with an area under the curve (AUC) of 0.82, 81% accuracy, 81% sensitivity, and 80% specificity. Additionally, normal oral tissues can be sub-classified into epithelium, muscle, and glandular mucosa using a decision tree method, with an average AUC of 0.94, 90% accuracy, 93% sensitivity, and 89% specificity. After separately training on thyroid tissue, the CNN differentiates between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multi-nodular goiter (MNG) with an AUC of 0.93, 87% accuracy, 88% sensitivity, and 85% specificity. Classical-type papillary thyroid carcinoma is differentiated from benign MNG with an AUC of 0.91, 86% accuracy, 86% sensitivity, and 86% specificity. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multi-category diagnostic information for normal head-and-neck tissue, SCCa, and thyroid carcinomas. More patient data are needed in order to fully investigate the proposed technique to establish reliability and generalizability of the work.

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.

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data

PubMed Central

Su, Li; Farewell, Vernon T

2013-01-01

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally. PMID:24201470

A new algorithm for reducing the workload of experts in performing systematic reviews.

PubMed

Matwin, Stan; Kouznetsov, Alexandre; Inkpen, Diana; Frunza, Oana; O'Blenis, Peter

2010-01-01

To determine whether a factorized version of the complement naïve Bayes (FCNB) classifier can reduce the time spent by experts reviewing journal articles for inclusion in systematic reviews of drug class efficacy for disease treatment. The proposed classifier was evaluated on a test collection built from 15 systematic drug class reviews used in previous work. The FCNB classifier was constructed to classify each article as containing high-quality, drug class-specific evidence or not. Weight engineering (WE) techniques were added to reduce underestimation for Medical Subject Headings (MeSH)-based and Publication Type (PubType)-based features. Cross-validation experiments were performed to evaluate the classifier's parameters and performance. Work saved over sampling (WSS) at no less than a 95% recall was used as the main measure of performance. The minimum workload reduction for a systematic review for one topic, achieved with a FCNB/WE classifier, was 8.5%; the maximum was 62.2% and the average over the 15 topics was 33.5%. This is 15.0% higher than the average workload reduction obtained using a voting perceptron-based automated citation classification system. The FCNB/WE classifier is simple, easy to implement, and produces significantly better results in reducing the workload than previously achieved. The results support it being a useful algorithm for machine-learning-based automation of systematic reviews of drug class efficacy for disease treatment.

The Continental Margins Program in Georgia

USGS Publications Warehouse

Cocker, M.D.; Shapiro, E.A.

1999-01-01

From 1984 to 1993, the Georgia Geologic Survey (GGS) participated in the Minerals Management Service-funded Continental Margins Program. Geological and geophysical data acquisition focused on offshore stratigraphic framework studies, phosphate-bearing Miocene-age strata, distribution of heavy minerals, near-surface alternative sources of groundwater, and development of a PC-based Coastal Geographic Information System (GIS). Seven GGS publications document results of those investigations. In addition to those publications, direct benefits of the GGS's participation include an impetus to the GGS's investigations of economic minerals on the Georgia coast, establishment of a GIS that includes computer hardware and software, and seeds for additional investigations through the information and training acquired as a result of the Continental Margins Program. These addtional investigations are quite varied in scope, and many were made possible because of GIS expertise gained as a result of the Continental Margins Program. Future investigations will also reap the benefits of the Continental Margins Program.From 1984 to 1993, the Georgia Geologic Survey (GGS) participated in the Minerals Management Service-funded Continental Margins Program. Geological and geophysical data acquisition focused on offshore stratigraphic framework studies, phosphate-bearing Miocene-age strata, distribution of heavy minerals, near-surface alternative sources of groundwater, and development of a PC-based Coastal Geographic Information System (GIS). Seven GGS publications document results of those investigations. In addition to those publications, direct benefits of the GGS's participation include an impetus to the GGS's investigations of economic minerals on the Georgia coast, establishment of a GIS that includes computer hardware and software, and seeds for additional investigations through the information and training acquired as a result of the Continental Margins Program. These additional investigations are quite varied in scope, and many were made possible because of GIS expertise gained as a result of the Continental Margins Program. Future investigations will also reap the benefits of the Continental Margins Program.

Evaluation of overall setup accuracy and adequate setup margins in pelvic image-guided radiotherapy: Comparison of the male and female patients

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

Laaksomaa, Marko, E-mail: marko.laaksomaa@pshp.fi; Kapanen, Mika; Department of Medical Physics, Tampere University Hospital

We evaluated adequate setup margins for the radiotherapy (RT) of pelvic tumors based on overall position errors of bony landmarks. We also estimated the difference in setup accuracy between the male and female patients. Finally, we compared the patient rotation for 2 immobilization devices. The study cohort included consecutive 64 male and 64 female patients. Altogether, 1794 orthogonal setup images were analyzed. Observer-related deviation in image matching and the effect of patient rotation were explicitly determined. Overall systematic and random errors were calculated in 3 orthogonal directions. Anisotropic setup margins were evaluated based on residual errors after weekly image guidance.more » The van Herk formula was used to calculate the margins. Overall, 100 patients were immobilized with a house-made device. The patient rotation was compared against 28 patients immobilized with CIVCO's Kneefix and Feetfix. We found that the usually applied isotropic setup margin of 8 mm covered all the uncertainties related to patient setup for most RT treatments of the pelvis. However, margins of even 10.3 mm were needed for the female patients with very large pelvic target volumes centered either in the symphysis or in the sacrum containing both of these structures. This was because the effect of rotation (p ≤ 0.02) and the observer variation in image matching (p ≤ 0.04) were significantly larger for the female patients than for the male patients. Even with daily image guidance, the required margins remained larger for the women. Patient rotations were largest about the lateral axes. The difference between the required margins was only 1 mm for the 2 immobilization devices. The largest component of overall systematic position error came from patient rotation. This emphasizes the need for rotation correction. Overall, larger position errors and setup margins were observed for the female patients with pelvic cancer than for the male patients.« less

Automatic classification for mammogram backgrounds based on bi-rads complexity definition and on a multi content analysis framework

NASA Astrophysics Data System (ADS)

Wu, Jie; Besnehard, Quentin; Marchessoux, Cédric

2011-03-01

Clinical studies for the validation of new medical imaging devices require hundreds of images. An important step in creating and tuning the study protocol is the classification of images into "difficult" and "easy" cases. This consists of classifying the image based on features like the complexity of the background, the visibility of the disease (lesions). Therefore, an automatic medical background classification tool for mammograms would help for such clinical studies. This classification tool is based on a multi-content analysis framework (MCA) which was firstly developed to recognize image content of computer screen shots. With the implementation of new texture features and a defined breast density scale, the MCA framework is able to automatically classify digital mammograms with a satisfying accuracy. BI-RADS (Breast Imaging Reporting Data System) density scale is used for grouping the mammograms, which standardizes the mammography reporting terminology and assessment and recommendation categories. Selected features are input into a decision tree classification scheme in MCA framework, which is the so called "weak classifier" (any classifier with a global error rate below 50%). With the AdaBoost iteration algorithm, these "weak classifiers" are combined into a "strong classifier" (a classifier with a low global error rate) for classifying one category. The results of classification for one "strong classifier" show the good accuracy with the high true positive rates. For the four categories the results are: TP=90.38%, TN=67.88%, FP=32.12% and FN =9.62%.

A further step toward an optimal ensemble of classifiers for peptide classification, a case study: HIV protease.

PubMed

Nanni, Loris; Lumini, Alessandra

2009-01-01

The focuses of this work are: to propose a novel method for building an ensemble of classifiers for peptide classification based on substitution matrices; to show the importance to select a proper set of the parameters of the classifiers that build the ensemble of learning systems. The HIV-1 protease cleavage site prediction problem is here studied. The results obtained by a blind testing protocol are reported, the comparison with other state-of-the-art approaches, based on ensemble of classifiers, allows to quantify the performance improvement obtained by the systems proposed in this paper. The simulation based on experimentally determined protease cleavage data has demonstrated the success of these new ensemble algorithms. Particularly interesting it is to note that also if the HIV-1 protease cleavage site prediction problem is considered linearly separable we obtain the best performance using an ensemble of non-linear classifiers.

E-Nose Vapor Identification Based on Dempster-Shafer Fusion of Multiple Classifiers

NASA Technical Reports Server (NTRS)

Li, Winston; Leung, Henry; Kwan, Chiman; Linnell, Bruce R.

2005-01-01

Electronic nose (e-nose) vapor identification is an efficient approach to monitor air contaminants in space stations and shuttles in order to ensure the health and safety of astronauts. Data preprocessing (measurement denoising and feature extraction) and pattern classification are important components of an e-nose system. In this paper, a wavelet-based denoising method is applied to filter the noisy sensor measurements. Transient-state features are then extracted from the denoised sensor measurements, and are used to train multiple classifiers such as multi-layer perceptions (MLP), support vector machines (SVM), k nearest neighbor (KNN), and Parzen classifier. The Dempster-Shafer (DS) technique is used at the end to fuse the results of the multiple classifiers to get the final classification. Experimental analysis based on real vapor data shows that the wavelet denoising method can remove both random noise and outliers successfully, and the classification rate can be improved by using classifier fusion.

Verification of Dose Distribution in Carbon Ion Radiation Therapy for Stage I Lung Cancer

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

Irie, Daisuke; Saitoh, Jun-ichi, E-mail: junsaito@gunma-u.ac.jp; Shirai, Katsuyuki

Purpose: To evaluate robustness of dose distribution of carbon-ion radiation therapy (C-ion RT) in non-small cell lung cancer (NSCLC) and to identify factors affecting the dose distribution by simulated dose distribution. Methods and Materials: Eighty irradiation fields for delivery of C-ion RT were analyzed in 20 patients with stage I NSCLC. Computed tomography images were obtained twice before treatment initiation. Simulated dose distribution was reconstructed on computed tomography for confirmation under the same settings as actual treatment with respiratory gating and bony structure matching. Dose-volume histogram parameters, such as %D95 (percentage of D95 relative to the prescribed dose), were calculated.more » Patients with any field for which the %D95 of gross tumor volume (GTV) was below 90% were classified as unacceptable for treatment, and the optimal target margin for such cases was examined. Results: Five patients with a total of 8 fields (10% of total number of fields analyzed) were classified as unacceptable according to %D95 of GTV, although most patients showed no remarkable change in the dose-volume histogram parameters. Receiver operating characteristic curve analysis showed that tumor displacement and change in water-equivalent pathlength were significant predictive factors of unacceptable cases (P<.001 and P=.002, respectively). The main cause of degradation of the dose distribution was tumor displacement in 7 of the 8 unacceptable fields. A 6-mm planning target volume margin ensured a GTV %D95 of >90%, except in 1 extremely unacceptable field. Conclusions: According to this simulation analysis of C-ion RT for stage I NSCLC, a few fields were reported as unacceptable and required resetting of body position and reconfirmation. In addition, tumor displacement and change in water-equivalent pathlength (bone shift and/or chest wall thickness) were identified as factors influencing the robustness of dose distribution. Such uncertainties should be regarded in planning.« less

Pricing hospital care: Global budgets and marginal pricing strategies.

PubMed

Sutherland, Jason M

2015-08-01

The Canadian province of British Columbia (BC) is adding financial incentives to increase the volume of surgeries provided by hospitals using a marginal pricing approach. The objective of this study is to calculate marginal costs of surgeries based on assumptions regarding hospitals' availability of labor and equipment. This study is based on observational clinical, administrative and financial data generated by hospitals. Hospital inpatient and outpatient discharge summaries from the province are linked with detailed activity-based costing information, stratified by assigned case mix categorizations. To reflect a range of operating constraints governing hospitals' ability to increase their volume of surgeries, a number of scenarios are proposed. Under these scenarios, estimated marginal costs are calculated and compared to prices being offered as incentives to hospitals. Existing data can be used to support alternative strategies for pricing hospital care. Prices for inpatient surgeries do not generate positive margins under a range of operating scenarios. Hip and knee surgeries generate surpluses for hospitals even under the most costly labor conditions and are expected to generate additional volume. In health systems that wish to fine-tune financial incentives, setting prices that create incentives for additional volume should reflect knowledge of hospitals' underlying cost structures. Possible implications of mis-pricing include no response to the incentives or uneven increases in supply. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Hyperspectral imaging based on compressive sensing to determine cancer margins in human pancreatic tissue ex vivo

NASA Astrophysics Data System (ADS)

Peller, Joseph; Thompson, Kyle J.; Siddiqui, Imran; Martinie, John; Iannitti, David A.; Trammell, Susan R.

2017-02-01

Pancreatic cancer is the fourth leading cause of cancer death in the US. Currently, surgery is the only treatment that offers a chance of cure, however, accurately identifying tumor margins in real-time is difficult. Research has demonstrated that optical spectroscopy can be used to distinguish between healthy and diseased tissue. The design of a single-pixel imaging system for cancer detection is discussed. The system differentiates between healthy and diseased tissue based on differences in the optical reflectance spectra of these regions. In this study, pancreatic tissue samples from 6 patients undergoing Whipple procedures are imaged with the system (total number of tissue sample imaged was N=11). Regions of healthy and unhealthy tissue are determined based on SAM analysis of these spectral images. Hyperspectral imaging results are then compared to white light imaging and histological analysis. Cancerous regions were clearly visible in the hyperspectral images. Margins determined via spectral imaging were in good agreement with margins identified by histology, indicating that hyperspectral imaging system can differentiate between healthy and diseased tissue. After imaging the system was able to detect cancerous regions with a sensitivity of 74.50±5.89% and a specificity of 75.53±10.81%. Possible applications of this imaging system include determination of tumor margins during surgery/biopsy and assistance with cancer diagnosis and staging.

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 complementary to LCA and can be combined with it to yield conservative prediction sets of very high confidence. The simple parameterization of LCA and ε-NB allows for tuning of the balance between more predictions and increased precision, allowing the user to account for the sensitivity of downstream analyses to misclassified or unclassified sequences. PMID:21827705

Breakup magmatism style on the North Atlantic Igneous Province: insight from Mid-Norwegian volcanic margin

NASA Astrophysics Data System (ADS)

Mansour Abdelmalak, Mohamed; Faleide, Jan Inge; Planke, Sverre; Theissen-Krah, Sonja; Zastrozhnov, Dmitrii; Breivik, Asbjørn Johan; Gernigon, Laurent; Myklebust, Reidun

2014-05-01

The distribution of breakup-related igneous rocks on rifted margins provide important constraints on the magmatic processes during continental extension and lithosphere separation which lead to a better understanding of the melt supply from the upper mantle and the relationship between tectonic setting and volcanism. The results can lead to a better understanding of the processes forming volcanic margins and thermal evolution of associated prospective basins. We present a revised mapping of the breakup-related igneous rocks in the NE Atlantic area, which are mainly based on the Mid-Norwegian (case example) margin. We divided the breakup related igneous rocks into (1) extrusive complexes, (2) shallow intrusive complexes (sills/dykes) and (3) deep intrusive complexes (Lower Crustal Body: LCB). The extrusive complex has been mapped using the seismic volcanostratigraphic method. Several distinct volcanic seismic facies units have been identified. The top basalt reflection is easily identified because of the high impedance contrast between the sedimentary and volcanic rocks resulting in a major reflector. The basal sequence boundary is frequently difficult to identify but it lies usually over the intruded sedimentary basin. Then the base is usually picked above the shallow sill intrusions identified on seismic profile. The mapping of the top and the base of the basaltic sequences allows us to determine the basalt thickness and estimate the volume of the magma production on the Mid- Norwegian margin. The thicker part of the basalt corresponds to the seaward dipping reflector (SDR). The magma feeder system, mainly formed by dyke and sill intrusions, represents the shallow intrusive complex. Deeper interconnected high-velocity sills are also mappable in the margin. Interconnected sill complexes can define continuous magma network >10 km in vertical ascent. The large-scale sill complexes, in addition to dyke swarm intrusions, represent a mode of vertical long-range magma transport through the upper crust. The deep intrusive complex represents the Lower Crustal Body (LCB) which is observed along the margin and characterized by high P-wave velocity bodies (Vp> 7km/s). On the Vøring margin a strong amplitude dome-shaped reflection (the so-called T-Reflection) has been identified and interpreted as the top LCB. In the sedimentary part of the margin, sill intrusions are the major feeder system and seem to be connected with LCB. In the volcanic part of the margin, dykes represent the main feeder system and lie above the thicker part of the LCB.

On the Performance of the Marginal Homogeneity Test to Detect Rater Drift.

PubMed

Sgammato, Adrienne; Donoghue, John R

2018-06-01

When constructed response items are administered repeatedly, "trend scoring" can be used to test for rater drift. In trend scoring, raters rescore responses from the previous administration. Two simulation studies evaluated the utility of Stuart's Q measure of marginal homogeneity as a way of evaluating rater drift when monitoring trend scoring. In the first study, data were generated based on trend scoring tables obtained from an operational assessment. The second study tightly controlled table margins to disentangle certain features present in the empirical data. In addition to Q , the paired t test was included as a comparison, because of its widespread use in monitoring trend scoring. Sample size, number of score categories, interrater agreement, and symmetry/asymmetry of the margins were manipulated. For identical margins, both statistics had good Type I error control. For a unidirectional shift in margins, both statistics had good power. As expected, when shifts in the margins were balanced across categories, the t test had little power. Q demonstrated good power for all conditions and identified almost all items identified by the t test. Q shows substantial promise for monitoring of trend scoring.

The effect of repeated preheating of dimethacrylate and silorane-based composite resins on marginal gap of class V restorations.

PubMed

Alizadeh Oskoee, Parnian; Pournaghi Azar, Fatemeh; Jafari Navimipour, Elmira; Ebrahimi Chaharom, Mohammad Esmaeel; Naser Alavi, Fereshteh; Salari, Ashkan

2017-01-01

Background. One of the problems with composite resin restorations is gap formation at resin‒tooth interface. The present study evaluated the effect of preheating cycles of silorane- and dimethacrylate-based composite resins on gap formation at the gingival margins of Class V restorations. Methods. In this in vitro study, standard Class V cavities were prepared on the buccal surfaces of 48 bovine incisors. For restorative procedure, the samples were randomly divided into 2 groups based on the type of composite resin (group 1: di-methacrylate composite [Filtek Z250]; group 2: silorane composite [Filtek P90]) and each group was randomly divided into 2 subgroups based on the composite temperature (A: room temperature; B: after 40 preheating cycles up to 55°C). Marginal gaps were measured using a stereomicroscope at ×40 and analyzed with two-way ANOVA. Inter- and intra-group comparisons were analyzed with post-hoc Tukey tests. Significance level was defined at P < 0.05. Results. The maximum and minimum gaps were detected in groups 1-A and 2-B, respectively. The effects of composite resin type, preheating and interactive effect of these variables on gap formation were significant (P<0.001). Post-hoc Tukey tests showed greater gap in dimethacrylate compared to silorane composite resins (P< 0.001). In each group, gap values were greater in composite resins at room temperature compared to composite resins after 40 preheating cycles (P<0.001). Conclusion. Gap formation at the gingival margins of Class V cavities decreased due to preheating of both composite re-sins. Preheating of silorane-based composites can result in the best marginal adaptation.

The effect of repeated preheating of dimethacrylate and silorane-based composite resins on marginal gap of class V restorations

PubMed Central

Alizadeh Oskoee, Parnian; Pournaghi Azar, Fatemeh; Jafari Navimipour, Elmira; Ebrahimi chaharom, Mohammad Esmaeel; Naser Alavi, Fereshteh; Salari, Ashkan

2017-01-01

Background. One of the problems with composite resin restorations is gap formation at resin‒tooth interface. The present study evaluated the effect of preheating cycles of silorane- and dimethacrylate-based composite resins on gap formation at the gingival margins of Class V restorations. Methods. In this in vitro study, standard Class V cavities were prepared on the buccal surfaces of 48 bovine incisors. For restorative procedure, the samples were randomly divided into 2 groups based on the type of composite resin (group 1: di-methacrylate composite [Filtek Z250]; group 2: silorane composite [Filtek P90]) and each group was randomly divided into 2 subgroups based on the composite temperature (A: room temperature; B: after 40 preheating cycles up to 55°C). Marginal gaps were measured using a stereomicroscope at ×40 and analyzed with two-way ANOVA. Inter- and intra-group comparisons were analyzed with post-hoc Tukey tests. Significance level was defined at P < 0.05. Results. The maximum and minimum gaps were detected in groups 1-A and 2-B, respectively. The effects of composite resin type, preheating and interactive effect of these variables on gap formation were significant (P<0.001). Post-hoc Tukey tests showed greater gap in dimethacrylate compared to silorane composite resins (P< 0.001). In each group, gap values were greater in composite resins at room temperature compared to composite resins after 40 preheating cycles (P<0.001). Conclusion. Gap formation at the gingival margins of Class V cavities decreased due to preheating of both composite re-sins. Preheating of silorane-based composites can result in the best marginal adaptation. PMID:28413594

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 through the evolutionary algorithms. In addition, experimental and statistical significance tests are carried out to study the applicability and effectiveness of the reviewed methods.

Early Oral Tongue Squamous Cell Carcinoma: Sampling of Margins From Tumor Bed and Worse Local Control.

PubMed

Maxwell, Jessica H; Thompson, Lester D R; Brandwein-Gensler, Margaret S; Weiss, Bernhard G; Canis, Martin; Purgina, Bibianna; Prabhu, Arpan V; Lai, Chi; Shuai, Yongli; Carroll, William R; Morlandt, Anthony; Duvvuri, Umamaheswar; Kim, Seungwon; Johnson, Jonas T; Ferris, Robert L; Seethala, Raja; Chiosea, Simion I

2015-12-01

Positive margins are associated with poor prognosis among patients with oral tongue squamous cell carcinoma (SCC). However, wide variation exists in the margin sampling technique. To determine the effect of the margin sampling technique on local recurrence (LR) in patients with stage I or II oral tongue SCC. A retrospective study was conducted from January 1, 1986, to December 31, 2012, in 5 tertiary care centers following tumor resection and elective neck dissection in 280 patients with pathologic (p)T1-2 pN0 oral tongue SCC. Analysis was conducted from June 1, 2013, to January 20, 2015. In group 1 (n = 119), tumor bed margins were not sampled. In group 2 (n = 61), margins were examined from the glossectomy specimen, found to be positive or suboptimal, and revised with additional tumor bed margins. In group 3 (n = 100), margins were primarily sampled from the tumor bed without preceding examination of the glossectomy specimen. The margin status (both as a binary [positive vs negative] and continuous [distance to the margin in millimeters] variable) and other clinicopathologic parameters were compared across the 3 groups and correlated with LR. Local recurrence. Age, sex, pT stage, lymphovascular or perineural invasion, and adjuvant radiation treatment were similar across the 3 groups. The probability of LR-free survival at 3 years was 0.9 and 0.8 in groups 1 and 3, respectively (P = .03). The frequency of positive glossectomy margins was lowest in group 1 (9 of 117 [7.7%]) compared with groups 2 and 3 (28 of 61 [45.9%] and 23 of 95 [24.2%], respectively) (P < .001). Even after excluding cases with positive margins, the median distance to the closest margin was significantly narrower in group 3 (2 mm) compared with group 1 (3 mm) (P = .008). The status (positive vs negative) of margins obtained from the glossectomy specimen correlated with LR (P = .007), while the status of tumor bed margins did not. The status of the tumor bed margin was 24% sensitive (95% CI, 16%-34%) and 92% specific (95% CI, 85%-97%) for detecting a positive glossectomy margin. The margin sampling technique affects local control in patients with oral tongue SCC. Reliance on margin sampling from the tumor bed is associated with worse local control, most likely owing to narrower margin clearance and greater incidence of positive margins. A resection specimen-based margin assessment is recommended.

Early Oral Tongue Squamous Cell Carcinoma Sampling of Margins From Tumor Bed and Worse Local Control

PubMed Central

Maxwell, Jessica H.; Thompson, Lester D. R.; Brandwein-Gensler, Margaret S.; Weiss, Bernhard G.; Canis, Martin; Purgina, Bibianna; Prabhu, Arpan V.; Lai, Chi; Shuai, Yongli; Carroll, William R.; Morlandt, Anthony; Duvvuri, Umamaheswar; Kim, Seungwon; Johnson, Jonas T.; Ferris, Robert L.; Seethala, Raja; Chiosea, Simion I.

2017-01-01

IMPORTANCE Positive margins are associated with poor prognosis among patients with oral tongue squamous cell carcinoma (SCC). However, wide variation exists in the margin sampling technique. OBJECTIVE To determine the effect of the margin sampling technique on local recurrence (LR) in patients with stage I or II oral tongue SCC. DESIGN, SETTING, AND PARTICIPANTS A retrospective study was conducted from January 1, 1986, to December 31, 2012, in 5 tertiary care centers following tumor resection and elective neck dissection in 280 patients with pathologic (p)T1-2 pN0 oral tongue SCC. Analysis was conducted from June 1, 2013, to January 20, 2015. INTERVENTIONS In group 1 (n = 119), tumor bed margins were not sampled. In group 2 (n = 61), margins were examined from the glossectomy specimen, found to be positive or suboptimal, and revised with additional tumor bed margins. In group 3 (n = 100), margins were primarily sampled from the tumor bed without preceding examination of the glossectomy specimen. The margin status (both as a binary [positive vs negative] and continuous [distance to the margin in millimeters] variable) and other clinicopathologic parameters were compared across the 3 groups and correlated with LR. MAIN OUTCOMES AND MEASURES Local recurrence. RESULTS Age, sex, pT stage, lymphovascular or perineural invasion, and adjuvant radiation treatment were similar across the 3 groups. The probability of LR-free survival at 3 years was 0.9 and 0.8 in groups 1 and 3, respectively (P = .03). The frequency of positive glossectomy margins was lowest in group 1 (9 of 117 [7.7%]) compared with groups 2 and 3 (28 of 61 [45.9%] and 23 of 95 [24.2%], respectively) (P < .001). Even after excluding cases with positive margins, the median distance to the closest margin was significantly narrower in group 3 (2 mm) compared with group 1 (3 mm) (P = .008). The status (positive vs negative) of margins obtained from the glossectomy specimen correlated with LR (P = .007), while the status of tumor bed margins did not. The status of the tumor bed margin was 24% sensitive (95% CI, 16%-34%) and 92% specific (95% CI, 85%-97%) for detecting a positive glossectomy margin. CONCLUSIONS AND RELEVANCE The margin sampling technique affects local control in patients with oral tongue SCC. Reliance on margin sampling from the tumor bed is associated with worse local control, most likely owing to narrower margin clearance and greater incidence of positive margins. A resection specimen–based margin assessment is recommended. PMID:26225798

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.

Evaluation of Microleakage and Marginal Ridge Fracture Resistance of Primary Molars Restored with Three Restorative Materials: A Comparative in vitro Study

PubMed Central

Yeolekar, Tapan Satish; Mukunda, KS; Kiran, NK

2015-01-01

ABSTRACT Composite restorations are popular because of their superior esthetics and acceptable clinical performance. But shrinkage is still a drawback. Polymerization shrinkage results in volumetric contraction, leading to deformation of the cusps, microleakage, decrease of marginal adaptation, enamel micro-cracks and postoperative sensitivity. A new class of ring opening resin composite based on silorane chemistry has been introduced with claims of less than 1% shrinkage during polymerization. The present study was conducted to evaluate and compare the ability of low shrink silorane based material, a packable composite and a compomer to resist microleakage in class II restorations on primary molars and evaluate marginal ridge fracture resistance of these materials. Sixty human primary molars were selected. Class II cavities were prepared and the teeth were divided into three groups of twenty each. Groups were as follows group I: low shrink composite resin (Filtek P90). Group II: packable composite (Filtek P60) and Group III: compomer (Compoglass F). Half of the teeth were used for microleakage and the rest for marginal ridge fracture resistance. For microleakage testing, dye penetration method was used with 1% methylene blue dye. Followed by evaluation and grading under stereomicroscope at 10* magnification. Fracture resistance was tested with universal testing machine. It was concluded that low shrink silorane based composite resin showed the least amount of microleakage, whereas compomer showed the highest microleakage. Packable composite resisted fracture of marginal ridge better than other composite resins. Marginal ridge fracture resistance of packable composite was comparable to the intact side. How to cite this article: Yeolekar TS, Chowdhary NR, Mukunda KS, Kiran NK. Evaluation of Microleakage and Marginal Ridge Fracture Resistance of Primary Molars Restored with Three Restorative Materials: A Comparative in vitro Study. Int J Clin Pediatr Dent 2015;8(2):108-113. PMID:26379377

Time Safety Margin: Theory and Practice

DTIC Science & Technology

2016-09-01

Basic Dive Recovery Terminology The Simplest Definition of TSM: Time Safety Margin is the time to directly travel from the worst-case vector to an...Safety Margin (TSM). TSM is defined as the time in seconds to directly travel from the worst case vector (i.e. worst case combination of parameters...invoked by this AFI, base recovery planning and risk management upon the calculated TSM. TSM is the time in seconds to di- rectly travel from the worst case

Wave attenuation in the marginal ice zone during LIMEX

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Peng, Chih Y.; Vachon, Paris W.

1991-01-01

During LIMEX'87 and '89, the CCRS CV-580 aircraft collected SAR (synthetic aperture radar) data over the marginal ice zone off the coast of Newfoundland. Based upon the wavenumber spectra from SAR data, the wave attenuation rate is estimated and compared with a model. The model-data comparisons are reasonably good for the ice conditions during LIMEX (Labrador Ice Margin Experiment). Both model and SAR-derived wave attenuation rates show a roll-over at high wavenumbers.

An integrated policy framework for the sustainable exploitation of biomass for bioenergy from marginal lands

NASA Astrophysics Data System (ADS)

Panoutsou, Calliope

2017-04-01

Currently, there are not sufficiently tailored policies focusing on biomass and bioenergy from marginal lands. This paper will provide an integrated policy framework and recommendations to facilitate understanding for the market sectors involved and the key principles which can be used to form future sustainable policies for this issue. The work will focus at EU level policy recommendations and discuss how these can interrelate with national and regional level policies to promote the usage of marginal lands for biomass and bioenergy. Recommended policy measures will be based on the findings of the Biomass Policies (www.biomasspolicies.eu) and S2Biom (www.s2biom.eu) projects and will be prepared taking into account the key influencing factors (technical, environmental, social and economic) on biomass and bioenergy from marginal lands: • across different types of marginality (biophysical such as: low temperature, dryness, excess soil moisture, poor chemical properties, steep slope, etc., and socio-economic resulting from lack of economic competitiveness in certain regions and crops, abandonment or rural areas, etc.) • across the different stages of the biomass value chain (supply, logistics, conversion, distribution and end-use). The aim of recommendations will be to inform policy makers on how to distinguish key policy related attributes across biomass and bioenergy from marginal lands, measure them and prioritise actions with a 'system' based approach.

A cDNA microarray gene expression data classifier for clinical diagnostics based on graph theory.

PubMed

Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco

2011-01-01

Despite great advances in discovering cancer molecular profiles, the proper application of microarray technology to routine clinical diagnostics is still a challenge. Current practices in the classification of microarrays' data show two main limitations: the reliability of the training data sets used to build the classifiers, and the classifiers' performances, especially when the sample to be classified does not belong to any of the available classes. In this case, state-of-the-art algorithms usually produce a high rate of false positives that, in real diagnostic applications, are unacceptable. To address this problem, this paper presents a new cDNA microarray data classification algorithm based on graph theory and is able to overcome most of the limitations of known classification methodologies. The classifier works by analyzing gene expression data organized in an innovative data structure based on graphs, where vertices correspond to genes and edges to gene expression relationships. To demonstrate the novelty of the proposed approach, the authors present an experimental performance comparison between the proposed classifier and several state-of-the-art classification algorithms.

A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification

NASA Astrophysics Data System (ADS)

Zhang, Ce; Pan, Xin; Li, Huapeng; Gardiner, Andy; Sargent, Isabel; Hare, Jonathon; Atkinson, Peter M.

2018-06-01

The contextual-based convolutional neural network (CNN) with deep architecture and pixel-based multilayer perceptron (MLP) with shallow structure are well-recognized neural network algorithms, representing the state-of-the-art deep learning method and the classical non-parametric machine learning approach, respectively. The two algorithms, which have very different behaviours, were integrated in a concise and effective way using a rule-based decision fusion approach for the classification of very fine spatial resolution (VFSR) remotely sensed imagery. The decision fusion rules, designed primarily based on the classification confidence of the CNN, reflect the generally complementary patterns of the individual classifiers. In consequence, the proposed ensemble classifier MLP-CNN harvests the complementary results acquired from the CNN based on deep spatial feature representation and from the MLP based on spectral discrimination. Meanwhile, limitations of the CNN due to the adoption of convolutional filters such as the uncertainty in object boundary partition and loss of useful fine spatial resolution detail were compensated. The effectiveness of the ensemble MLP-CNN classifier was tested in both urban and rural areas using aerial photography together with an additional satellite sensor dataset. The MLP-CNN classifier achieved promising performance, consistently outperforming the pixel-based MLP, spectral and textural-based MLP, and the contextual-based CNN in terms of classification accuracy. This research paves the way to effectively address the complicated problem of VFSR image classification.

Margins in breast conserving surgery: The financial cost & potential savings associated with the new margin guidelines.

PubMed

Singer, Lauren; Brown, Eric; Lanni, Thomas

2016-08-01

In this study, we compare the indications for re-excision, the findings of additional tumor in the re-excision specimen as they relate to margin status, and costs associated with re-excision based on recent new consensus statements. A retrospective analysis was performed on 462 patients with invasive breast carcinoma who underwent at least one lumpectomy between January 2011 and December 2013. Postoperative data was analyzed based on where additional disease was found, as it relates to the margin status of the initial lumpectomy and the additional direct costs associated with additional procedures. Of the 462 patients sampled, 149 underwent a re-excision surgery (32.2%). Four patients underwent mastectomy as their second operation. In the 40 patients with additional disease found on re-excision, 36 (90.0%) of them had a positive margin on their initial lumpectomy. None of the four mastectomy patients had residual disease. The mean cost of the initial lumpectomy for all 462 patients was $2118.01 plus an additional $1801.92 for those who underwent re-excision. A positive margin was most predictive of finding residual tumor on re-excision as would be expected. Using old criteria only 0.07% (4/61) of patients who had undergone re-excision with a 'clear' margin, had additional tumor found, at a total cost of $106,354.11. Thus, the new consensus guidelines will lead to less overall cost, at no clinical risk to patients while reducing a patient's surgical risk and essentially eliminating delays in adjuvant care. Copyright © 2016 Elsevier Ltd. All rights reserved.

Area Determination of Diabetic Foot Ulcer Images Using a Cascaded Two-Stage SVM-Based Classification.

PubMed

Wang, Lei; Pedersen, Peder C; Agu, Emmanuel; Strong, Diane M; Tulu, Bengisu

2017-09-01

The standard chronic wound assessment method based on visual examination is potentially inaccurate and also represents a significant clinical workload. Hence, computer-based systems providing quantitative wound assessment may be valuable for accurately monitoring wound healing status, with the wound area the best suited for automated analysis. Here, we present a novel approach, using support vector machines (SVM) to determine the wound boundaries on foot ulcer images captured with an image capture box, which provides controlled lighting and range. After superpixel segmentation, a cascaded two-stage classifier operates as follows: in the first stage, a set of k binary SVM classifiers are trained and applied to different subsets of the entire training images dataset, and incorrectly classified instances are collected. In the second stage, another binary SVM classifier is trained on the incorrectly classified set. We extracted various color and texture descriptors from superpixels that are used as input for each stage in the classifier training. Specifically, color and bag-of-word representations of local dense scale invariant feature transformation features are descriptors for ruling out irrelevant regions, and color and wavelet-based features are descriptors for distinguishing healthy tissue from wound regions. Finally, the detected wound boundary is refined by applying the conditional random field method. We have implemented the wound classification on a Nexus 5 smartphone platform, except for training which was done offline. Results are compared with other classifiers and show that our approach provides high global performance rates (average sensitivity = 73.3%, specificity = 94.6%) and is sufficiently efficient for a smartphone-based image analysis.

Positive Margins by Oropharyngeal Subsite in Transoral Robotic Surgery for T1/T2 Squamous Cell Carcinoma.

PubMed

Persky, Michael J; Albergotti, William G; Rath, Tanya J; Kubik, Mark W; Abberbock, Shira; Geltzeiler, Mathew; Kim, Seungwon; Duvvuri, Umamaheswar; Ferris, Robert L

2018-04-01

Objective To compare positive margin rates between the 2 most common subsites of oropharyngeal transoral robotic surgery (TORS), the base of tongue (BOT) and the tonsil, as well as identify preoperative imaging characteristics that predispose toward positive margins. Study Design Case series with chart review. Setting Tertiary care referral center. Subjects and Methods We compared the final and intraoperative positive margin rate between TORS resections for tonsil and BOT oropharyngeal squamous cell carcinoma (OPSCC), as well as the effect of margins on treatment. A blinded neuroradiologist examined the preoperative imaging of BOT tumors to measure their dimensions and patterns of spread and provided a prediction of final margin results. Results Between January 2010 and May 2016, a total of 254 patients underwent TORS for OPSCC. A total of 140 patients who underwent TORS for T1/T2 OPSCC met inclusion criteria. A final positive margin is significantly more likely for BOT tumors than tonsil tumors (19.6% vs 4.5%, respectively, P = .004) and likewise for intraoperative margins of BOT and tonsil tumors (35.3% vs 12.4%, respectively; P = .002). A positive final margin is 10 times more likely to receive chemoradiation compared to a negative margin, controlling for extracapsular spread and nodal status (odds ratio, 9.6; 95% confidence interval, 1.6-59.6; P = .02). Preoperative imaging characteristics and subjective radiologic examination of BOT tumors did not correlate with final margin status. Conclusion Positive margins are significantly more likely during TORS BOT resections compared to tonsil resections. More research is needed to help surgeons predict which T1/T2 tumors will be difficult to completely extirpate.

Classifier Subset Selection for the Stacked Generalization Method Applied to Emotion Recognition in Speech

PubMed Central

Álvarez, Aitor; Sierra, Basilio; Arruti, Andoni; López-Gil, Juan-Miguel; Garay-Vitoria, Nestor

2015-01-01

In this paper, a new supervised classification paradigm, called classifier subset selection for stacked generalization (CSS stacking), is presented to deal with speech emotion recognition. The new approach consists of an improvement of a bi-level multi-classifier system known as stacking generalization by means of an integration of an estimation of distribution algorithm (EDA) in the first layer to select the optimal subset from the standard base classifiers. The good performance of the proposed new paradigm was demonstrated over different configurations and datasets. First, several CSS stacking classifiers were constructed on the RekEmozio dataset, using some specific standard base classifiers and a total of 123 spectral, quality and prosodic features computed using in-house feature extraction algorithms. These initial CSS stacking classifiers were compared to other multi-classifier systems and the employed standard classifiers built on the same set of speech features. Then, new CSS stacking classifiers were built on RekEmozio using a different set of both acoustic parameters (extended version of the Geneva Minimalistic Acoustic Parameter Set (eGeMAPS)) and standard classifiers and employing the best meta-classifier of the initial experiments. The performance of these two CSS stacking classifiers was evaluated and compared. Finally, the new paradigm was tested on the well-known Berlin Emotional Speech database. We compared the performance of single, standard stacking and CSS stacking systems using the same parametrization of the second phase. All of the classifications were performed at the categorical level, including the six primary emotions plus the neutral one. PMID:26712757

Intra-surgical total and re-constructible pathological prostate examination for safer margins and nerve preservation (Istanbul preserve).

PubMed

Öbek, Can; Saglican, Yesim; Ince, Umit; Argun, Omer Burak; Tuna, Mustafa Bilal; Doganca, Tunkut; Tufek, Ilter; Keskin, Selcuk; Kural, Ali Riza

2018-04-01

To demonstrate a novel frozen section analysis technique during robot assisted radical prostatectomy with 2 distinct advantages: evaluation of the entire circumference and easier reconstruction for whole mount evaluation. Istanbul Preserve was performed on patients who underwent robotic prostatectomy with nerve sparing between 10/2014 and 7/2016. Gland was sectioned at 3-4mm intervals from apex to bladder neck. Entire tissue representing margins (except for the most anterior portion) was circumferentially excised and microscopically analyzed. In margin positivity, approach was individualized based on extent of positive margin and Gleason pattern. A matched cohort was established for comparison. Retrospective analysis of a prospectively maintained database was performed. Impact of FSA on PSM rate was primarily assessed. Data on 170 patients was analyzed. Positive surgical margin was reported in 56(33%) on frozen section. Neurovascular bundle was partially or totally resected in 79% and 18%. Conversion of positive margin to negative was achieved in 85%. Overall positive margin rate decreased from 22.5% to 7.5%. Nerve sparing increased from 87% to 93%. Location of positive margin at frozen was at the neurovascular bundle area in 39%; thus Istanbul Preserve detected 61% additional margin positivity compared to other techniques. Reconstruction for whole mount was easy. Istanbul Preserve is a novel technique for intraoperative FSA during RARP allowing for microscopic examination of the entire prostate for margin status and easy re-construction for whole mount examination. It guarantees safer margins together with increased rate of nerve sparing. Copyright © 2017 Elsevier Inc. All rights reserved.

Acoustic classification of zooplankton

NASA Astrophysics Data System (ADS)

Martin Traykovski, Linda V.

1998-11-01

Work on the forward problem in zooplankton bioacoustics has resulted in the identification of three categories of acoustic scatterers: elastic-shelled (e.g. pteropods), fluid-like (e.g. euphausiids), and gas-bearing (e.g. siphonophores). The relationship between backscattered energy and animal biomass has been shown to vary by a factor of ~19,000 across these categories, so that to make accurate estimates of zooplankton biomass from acoustic backscatter measurements of the ocean, the acoustic characteristics of the species of interest must be well-understood. This thesis describes the development of both feature based and model based classification techniques to invert broadband acoustic echoes from individual zooplankton for scatterer type, as well as for particular parameters such as animal orientation. The feature based Empirical Orthogonal Function Classifier (EOFC) discriminates scatterer types by identifying characteristic modes of variability in the echo spectra, exploiting only the inherent characteristic structure of the acoustic signatures. The model based Model Parameterisation Classifier (MPC) classifies based on correlation of observed echo spectra with simplified parameterisations of theoretical scattering models for the three classes. The Covariance Mean Variance Classifiers (CMVC) are a set of advanced model based techniques which exploit the full complexity of the theoretical models by searching the entire physical model parameter space without employing simplifying parameterisations. Three different CMVC algorithms were developed: the Integrated Score Classifier (ISC), the Pairwise Score Classifier (PSC) and the Bayesian Probability Classifier (BPC); these classifiers assign observations to a class based on similarities in covariance, mean, and variance, while accounting for model ambiguity and validity. These feature based and model based inversion techniques were successfully applied to several thousand echoes acquired from broadband (~350 kHz-750 kHz) insonifications of live zooplankton collected on Georges Bank and the Gulf of Maine to determine scatterer class. CMVC techniques were also applied to echoes from fluid-like zooplankton (Antarctic krill) to invert for angle of orientation using generic and animal-specific theoretical and empirical models. Application of these inversion techniques in situ will allow correct apportionment of backscattered energy to animal biomass, significantly improving estimates of zooplankton biomass based on acoustic surveys. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach.

PubMed

Weng, Wei-Hung; Wagholikar, Kavishwar B; McCray, Alexa T; Szolovits, Peter; Chueh, Henry C

2017-12-01

The medical subdomain of a clinical note, such as cardiology or neurology, is useful content-derived metadata for developing machine learning downstream applications. To classify the medical subdomain of a note accurately, we have constructed a machine learning-based natural language processing (NLP) pipeline and developed medical subdomain classifiers based on the content of the note. We constructed the pipeline using the clinical NLP system, clinical Text Analysis and Knowledge Extraction System (cTAKES), the Unified Medical Language System (UMLS) Metathesaurus, Semantic Network, and learning algorithms to extract features from two datasets - clinical notes from Integrating Data for Analysis, Anonymization, and Sharing (iDASH) data repository (n = 431) and Massachusetts General Hospital (MGH) (n = 91,237), and built medical subdomain classifiers with different combinations of data representation methods and supervised learning algorithms. We evaluated the performance of classifiers and their portability across the two datasets. The convolutional recurrent neural network with neural word embeddings trained-medical subdomain classifier yielded the best performance measurement on iDASH and MGH datasets with area under receiver operating characteristic curve (AUC) of 0.975 and 0.991, and F1 scores of 0.845 and 0.870, respectively. Considering better clinical interpretability, linear support vector machine-trained medical subdomain classifier using hybrid bag-of-words and clinically relevant UMLS concepts as the feature representation, with term frequency-inverse document frequency (tf-idf)-weighting, outperformed other shallow learning classifiers on iDASH and MGH datasets with AUC of 0.957 and 0.964, and F1 scores of 0.932 and 0.934 respectively. We trained classifiers on one dataset, applied to the other dataset and yielded the threshold of F1 score of 0.7 in classifiers for half of the medical subdomains we studied. Our study shows that a supervised learning-based NLP approach is useful to develop medical subdomain classifiers. The deep learning algorithm with distributed word representation yields better performance yet shallow learning algorithms with the word and concept representation achieves comparable performance with better clinical interpretability. Portable classifiers may also be used across datasets from different institutions.

Multiclass cancer classification using a feature subset-based ensemble from microRNA expression profiles.

PubMed

Piao, Yongjun; Piao, Minghao; Ryu, Keun Ho

2017-01-01

Cancer classification has been a crucial topic of research in cancer treatment. In the last decade, messenger RNA (mRNA) expression profiles have been widely used to classify different types of cancers. With the discovery of a new class of small non-coding RNAs; known as microRNAs (miRNAs), various studies have shown that the expression patterns of miRNA can also accurately classify human cancers. Therefore, there is a great demand for the development of machine learning approaches to accurately classify various types of cancers using miRNA expression data. In this article, we propose a feature subset-based ensemble method in which each model is learned from a different projection of the original feature space to classify multiple cancers. In our method, the feature relevance and redundancy are considered to generate multiple feature subsets, the base classifiers are learned from each independent miRNA subset, and the average posterior probability is used to combine the base classifiers. To test the performance of our method, we used bead-based and sequence-based miRNA expression datasets and conducted 10-fold and leave-one-out cross validations. The experimental results show that the proposed method yields good results and has higher prediction accuracy than popular ensemble methods. The Java program and source code of the proposed method and the datasets in the experiments are freely available at https://sourceforge.net/projects/mirna-ensemble/. Copyright © 2016 Elsevier Ltd. All rights reserved.

Immunohistochemical characterization of neuroendocrine differentiation of canine anal sac glandular tumours.

PubMed

Suzuki, K; Morita, R; Hojo, Y; Nomura, K; Shibutani, M; Mitsumori, K

2013-01-01

Histological features and expression of neuroendocrine markers were examined in 69 samples of canine anal sac glandular carcinomas (ASGCs). The tumours were classified into solid, rosette and tubular types and mixtures of these types. Tumour-associated death in dogs with solid tumours and mixed tumours with solid components was higher than in dogs with rosette and tubular type tumours. Chromogranin A immunoreactivity was observed in 28 of 69 samples (40.6%) irrespective of histological type and was localized to the marginal areas of the tumour nest and the basal areas of the tubular and rosette structures. Neuron-specific enolase immunoreactivity in neoplastic epithelial cells was observed in 32 cases (46.4%) and was less frequently observed in the tubular type (14.3%). Synaptophysin expression was present in 15.9% of cases and was least frequent in the tubular type. Twenty-one of the 69 samples expressed more than two neuroendocrine markers and were classified as carcinomas with neuroendocrine differentiation. There was no relationship between neuroendocrine differentiation and clinical outcome. These results suggest that some ASGCs have neuroendocrine differentiation regardless of histological pattern, but clinical outcome is more related to the histological pattern than to neuroendocrine differentiation. Copyright © 2013 Elsevier Ltd. All rights reserved.

The 'Antenna Balloon Anemone' Found in the Seto Inland Sea: New Genus and Species of Sea Anemone, Antennapeachia setouchi (Cnidaria, Actinaria, Haloclavidae).

PubMed

Izumi, Takato; Yanagi, Kensuke; Fujita, Toshihiko

2016-08-01

In the present study, we report the identification of a sea anemone, Antennapeachia setouchi, collected in the Seto Inland Sea, which represents a new genus and new species. This new species has unusual tentacle and mesenterial arrangements that have not been observed in other species of Haloclavidae. There are 12 regular marginal tentacles and two 'antenna tentacles,' with the latter always rising upward and located on the oral disk near the mouth; the species is also characterized by its peculiar mesenterial pairs, consisting of a macrocneme and a microcneme. Furthermore, this species shows an interesting behavior: it can inflate its body like a balloon, lift above the seafloor, and drift with the sea current. The presence of a single, strong siphonoglyph, physa-like aboral end, and the lack of sphincter muscle classify this sea anemone within Haloclavidae. It resembles Peachia species, but cannot be classified in this genus as the new species has two pairs of mesenteries, consisting of a macrocneme and a microcneme, and irregular antenna tentacles. Therefore, we propose a new genus Antennapeachia to accommodate this species.

Marginalization of girl mothers during reintegration from armed groups in Sierra Leone.

PubMed

Burman, M E; McKay, S

2007-12-01

Although the widespread presence of girls who participate in fighting forces is increasingly recognized, they remain a highly marginalized group globally, receiving little attention either during or after armed conflict. This is especially true for "girl mothers," girls who return to communities with children born while members of fighting forces. The concept of marginalization (Hall et al. 1994) is used to examine what happens to girl soldiers, especially girl mothers, in the aftermath of armed conflict when they seek to reintegrate back into their communities. This analysis, as part of a larger study of reintegration of girl mothers, is based on field work with girls who were in fighting forces in northwest Sierra Leone, especially those who returned with children. The type and level of marginalization these girls experience is consistent with the conceptualization of marginalization; however, they lack voice and experience shame and vulnerability. Moreover, economics were fundamentally related to their marginalization. The girls' access to resources was significantly constrained because the area was heavily impacted by the war and because of widespread poverty throughout Sierra Leone. The findings raise important questions about marginalization of girls affected by war. Girls and girl mothers experience an extremely high level of marginalization; however, some aspects are not consistent with the original conceptualization of marginalization. Theory development in nursing needs to incorporate multiple voices, especially those of the very marginalized and be done in such a manner that benefits and empowers.

A three-year clinical evaluation of two-bottle versus one-bottle dentin adhesives.

PubMed

Aw, Tar C; Lepe, Xavier; Johnson, Glen H; Mancl, Lloyd A

2005-03-01

The authors conducted an in vivo investigation to compare the clinical performance of two commercial one-bottle adhesives and a two-bottle adhesive for restoration of noncarious cervical lesions (NCCLs). The patient pool consisted of 57 patients and 171 teeth (three teeth per patient), with one NCCL per tooth. Each patient received three resin-based composite restorations, each with a different adhesive: one tooth with a two-bottle, water-based adhesive as the control; another tooth with a one-bottle, ethanol-based adhesive; and a third tooth with a one-bottle, solvent-free adhesive. The authors assessed restorations in terms of retention, marginal integrity, margin discoloration and air sensitivity at baseline, six months, one year, two years and three years after initial placement. The retention rates at 36 months were 88 percent for the first adhesive, 81 percent for the second adhesive and 90 percent for the third adhesive. No statistically significant differences in retention rates could be shown, with 86 percent of restorations retained overall. Measures of marginal integrity, marginal discoloration and sensitivity also had no statistically significant differences between the three adhesives (P > .05). All three adhesives performed with acceptable outcomes after a 36-month period, with small differences between the one- and two-bottle systems and between the various solvents. Retention rate was moderately high and air sensitivity was markedly reduced; however, superficial marginal discoloration and marginal degradation was notable. Certain lesion, tooth and patient characteristics may predispose restorations to retention failure. The type of solvent may not be a major factor in retention of Class V restorations in NCCLs. Both single-bottle adhesives and conventional two-bottle adhesives performed acceptably.

Inter- and Intrafraction Uncertainty in Prostate Bed Image-Guided Radiotherapy

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

Huang, Kitty; Palma, David A.; Department of Oncology, University of Western Ontario, London

2012-10-01

Purpose: The goals of this study were to measure inter- and intrafraction setup error and prostate bed motion (PBM) in patients undergoing post-prostatectomy image-guided radiotherapy (IGRT) and to propose appropriate population-based three-dimensional clinical target volume to planning target volume (CTV-PTV) margins in both non-IGRT and IGRT scenarios. Methods and Materials: In this prospective study, 14 patients underwent adjuvant or salvage radiotherapy to the prostate bed under image guidance using linac-based kilovoltage cone-beam CT (kV-CBCT). Inter- and intrafraction uncertainty/motion was assessed by offline analysis of three consecutive daily kV-CBCT images of each patient: (1) after initial setup to skin marks, (2)more » after correction for positional error/immediately before radiation treatment, and (3) immediately after treatment. Results: The magnitude of interfraction PBM was 2.1 mm, and intrafraction PBM was 0.4 mm. The maximum inter- and intrafraction prostate bed motion was primarily in the anterior-posterior direction. Margins of at least 3-5 mm with IGRT and 4-7 mm without IGRT (aligning to skin marks) will ensure 95% of the prescribed dose to the clinical target volume in 90% of patients. Conclusions: PBM is a predominant source of intrafraction error compared with setup error and has implications for appropriate PTV margins. Based on inter- and estimated intrafraction motion of the prostate bed using pre- and post-kV-CBCT images, CBCT IGRT to correct for day-to-day variances can potentially reduce CTV-PTV margins by 1-2 mm. CTV-PTV margins for prostate bed treatment in the IGRT and non-IGRT scenarios are proposed; however, in cases with more uncertainty of target delineation and image guidance accuracy, larger margins are recommended.« less

A method of neighbor classes based SVM classification for optical printed Chinese character recognition.

PubMed

Zhang, Jie; Wu, Xiaohong; Yu, Yanmei; Luo, Daisheng

2013-01-01

In optical printed Chinese character recognition (OPCCR), many classifiers have been proposed for the recognition. Among the classifiers, support vector machine (SVM) might be the best classifier. However, SVM is a classifier for two classes. When it is used for multi-classes in OPCCR, its computation is time-consuming. Thus, we propose a neighbor classes based SVM (NC-SVM) to reduce the computation consumption of SVM. Experiments of NC-SVM classification for OPCCR have been done. The results of the experiments have shown that the NC-SVM we proposed can effectively reduce the computation time in OPCCR.

Automatic construction of a recurrent neural network based classifier for vehicle passage detection

NASA Astrophysics Data System (ADS)

Burnaev, Evgeny; Koptelov, Ivan; Novikov, German; Khanipov, Timur

2017-03-01

Recurrent Neural Networks (RNNs) are extensively used for time-series modeling and prediction. We propose an approach for automatic construction of a binary classifier based on Long Short-Term Memory RNNs (LSTM-RNNs) for detection of a vehicle passage through a checkpoint. As an input to the classifier we use multidimensional signals of various sensors that are installed on the checkpoint. Obtained results demonstrate that the previous approach to handcrafting a classifier, consisting of a set of deterministic rules, can be successfully replaced by an automatic RNN training on an appropriately labelled data.

Research on classified real-time flood forecasting framework based on K-means cluster and rough set.

PubMed

Xu, Wei; Peng, Yong

2015-01-01

This research presents a new classified real-time flood forecasting framework. In this framework, historical floods are classified by a K-means cluster according to the spatial and temporal distribution of precipitation, the time variance of precipitation intensity and other hydrological factors. Based on the classified results, a rough set is used to extract the identification rules for real-time flood forecasting. Then, the parameters of different categories within the conceptual hydrological model are calibrated using a genetic algorithm. In real-time forecasting, the corresponding category of parameters is selected for flood forecasting according to the obtained flood information. This research tests the new classified framework on Guanyinge Reservoir and compares the framework with the traditional flood forecasting method. It finds that the performance of the new classified framework is significantly better in terms of accuracy. Furthermore, the framework can be considered in a catchment with fewer historical floods.

Clearing margin system in the futures markets—Applying the value-at-risk model to Taiwanese data

NASA Astrophysics Data System (ADS)

Chiu, Chien-Liang; Chiang, Shu-Mei; Hung, Jui-Cheng; Chen, Yu-Lung

2006-07-01

This article sets out to investigate if the TAIFEX has adequate clearing margin adjustment system via unconditional coverage, conditional coverage test and mean relative scaled bias to assess the performance of three value-at-risk (VaR) models (i.e., the TAIFEX, RiskMetrics and GARCH-t). For the same model, original and absolute returns are compared to explore which can accurately capture the true risk. For the same return, daily and tiered adjustment methods are examined to evaluate which corresponds to risk best. The results indicate that the clearing margin adjustment of the TAIFEX cannot reflect true risks. The adjustment rules, including the use of absolute return and tiered adjustment of the clearing margin, have distorted VaR-based margin requirements. Besides, the results suggest that the TAIFEX should use original return to compute VaR and daily adjustment system to set clearing margin. This approach would improve the funds operation efficiency and the liquidity of the futures markets.

Submarine Landslide Hazards Offshore Southern Alaska: Seismic Strengthening Versus Rapid Sedimentation

NASA Astrophysics Data System (ADS)

Sawyer, D.; Reece, R.; Gulick, S. P. S.; Lenz, B. L.

2017-12-01

The southern Alaskan offshore margin is prone to submarine landslides and tsunami hazards due to seismically active plate boundaries and extreme sedimentation rates from glacially enhanced mountain erosion. We examine the submarine landslide potential with new shear strength measurements acquired by Integrated Ocean Drilling Program Expedition 341 on the continental slope and Surveyor Fan. These data reveal lower than expected sediment strength. Contrary to other active margins where seismic strengthening enhances slope stability, the high-sedimentation margin offshore southern Alaska behaves like a passive margin from a shear strength perspective. We interpret that seismic strengthening occurs but is offset by high sedimentation rates and overpressure within the slope and Surveyor Fan. This conclusion is supported because shear strength follows an expected active margin profile outside of the fan, where background sedimentation rates occur. More broadly, seismically active margins with wet-based glaciers are susceptible to submarine landslide hazards because of the combination of high sedimentation rates and earthquake shaking

Stability evaluation of short-circuiting gas metal arc welding based on ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Huang, Yong; Wang, Kehong; Zhou, Zhilan; Zhou, Xiaoxiao; Fang, Jimi

2017-03-01

The arc of gas metal arc welding (GMAW) contains abundant information about its stability and droplet transition, which can be effectively characterized by extracting the arc electrical signals. In this study, ensemble empirical mode decomposition (EEMD) was used to evaluate the stability of electrical current signals. The welding electrical signals were first decomposed by EEMD, and then transformed to a Hilbert-Huang spectrum and a marginal spectrum. The marginal spectrum is an approximate distribution of amplitude with frequency of signals, and can be described by a marginal index. Analysis of various welding process parameters showed that the marginal index of current signals increased when the welding process was more stable, and vice versa. Thus EEMD combined with the marginal index can effectively uncover the stability and droplet transition of GMAW.

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data.

PubMed

Tom, Brian Dm; Su, Li; Farewell, Vernon T

2016-10-01

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally. © The Author(s) 2013.

Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

PubMed Central

Islam, Md. Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al. PMID:25114676

Feature and score fusion based multiple classifier selection for iris recognition.

PubMed

Islam, Md Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Comparison of disease prevalence in two populations in the presence of misclassification.

PubMed

Tang, Man-Lai; Qiu, Shi-Fang; Poon, Wai-Yin

2012-11-01

Comparing disease prevalence in two groups is an important topic in medical research, and prevalence rates are obtained by classifying subjects according to whether they have the disease. Both high-cost infallible gold-standard classifiers or low-cost fallible classifiers can be used to classify subjects. However, statistical analysis that is based on data sets with misclassifications leads to biased results. As a compromise between the two classification approaches, partially validated sets are often used in which all individuals are classified by fallible classifiers, and some of the individuals are validated by the accurate gold-standard classifiers. In this article, we develop several reliable test procedures and approximate sample size formulas for disease prevalence studies based on the difference between two disease prevalence rates with two independent partially validated series. Empirical studies show that (i) the Score test produces close-to-nominal level and is preferred in practice; and (ii) the sample size formula based on the Score test is also fairly accurate in terms of the empirical power and type I error rate, and is hence recommended. A real example from an aplastic anemia study is used to illustrate the proposed methodologies. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Generative Models for Similarity-based Classification

DTIC Science & Technology

2007-01-01

NC), local nearest centroid (local NC), k-nearest neighbors ( kNN ), and condensed nearest neighbors (CNN) are all similarity-based classifiers which...vector machine to the k nearest neighbors of the test sample [80]. The SVM- KNN method was developed to address the robustness and dimensionality...concerns that afflict nearest neighbors and SVMs. Similarly to the nearest-means classifier, the SVM- KNN is a hybrid local and global classifier developed

Nucleotide sequence analysis of the 3' terminal region of a wasabi strain of crucifer tobamovirus genomic RNA: subgrouping of crucifer tobamoviruses.

PubMed

Shimamoto, I; Sonoda, S; Vazquez, P; Minaka, N; Nishiguchi, M

1998-01-01

The 3' terminal 2378 nucleotides of a wasabi strain of crucifer tobamovirus (CTMV-W) infectious to crucifer plants was determined. This includes the 3' non-coding region of 235 nucleotides, coat protein (CP) gene (468 nucleotides), movement protein (MP) gene (798 nucleotides) and C-terminal partial readthrough portion of 180 K protein gene (940 nucleotides). Comparison of the sequence with homologous regions of thirteen other tobamovirus genomes showed that it had much higher identity to those of four other crucifer tobamoviruses, 85.2% to cr-TMV and turnip vein-clearing virus (TVCV), 87.4% to oilseed rape mosaic virus (ORMV) and 87.1% to TMV-Cg, than to those of other tobamoviruses. Thus CTMV-W was most similar to ORMV and TMV-Cg in sequence, but only marginally so, whereas the location and size of its MP gene was the same as cr-TMV amd TVCV. These results, together with other analyses, show that CTMV-W is a new crucifer tobamovirus, that the five crucifer tobamoviruses can be classified into two subgroups based on MP gene organization, and that the rate of sequence change is not the same in all lineages.

A novel and reliable computational intelligence system for breast cancer detection.

PubMed

Zadeh Shirazi, Amin; Seyyed Mahdavi Chabok, Seyyed Javad; Mohammadi, Zahra

2018-05-01

Cancer is the second important morbidity and mortality factor among women and the most incident type is breast cancer. This paper suggests a hybrid computational intelligence model based on unsupervised and supervised learning techniques, i.e., self-organizing map (SOM) and complex-valued neural network (CVNN), for reliable detection of breast cancer. The dataset used in this paper consists of 822 patients with five features (patient's breast mass shape, margin, density, patient's age, and Breast Imaging Reporting and Data System assessment). The proposed model was used for the first time and can be categorized in two stages. In the first stage, considering the input features, SOM technique was used to cluster the patients with the most similarity. Then, in the second stage, for each cluster, the patient's features were applied to complex-valued neural network and dealt with to classify breast cancer severity (benign or malign). The obtained results corresponding to each patient were compared to the medical diagnosis results using receiver operating characteristic analyses and confusion matrix. In the testing phase, health and disease detection ratios were 94 and 95%, respectively. Accordingly, the superiority of the proposed model was proved and can be used for reliable and robust detection of breast cancer.

Assessment of accident severity in the construction industry using the Bayesian theorem.

PubMed

Alizadeh, Seyed Shamseddin; Mortazavi, Seyed Bagher; Mehdi Sepehri, Mohammad

2015-01-01

Construction is a major source of employment in many countries. In construction, workers perform a great diversity of activities, each one with a specific associated risk. The aim of this paper is to identify workers who are at risk of accidents with severe consequences and classify these workers to determine appropriate control measures. We defined 48 groups of workers and used the Bayesian theorem to estimate posterior probabilities about the severity of accidents at the level of individuals in construction sector. First, the posterior probabilities of injuries based on four variables were provided. Then the probabilities of injury for 48 groups of workers were determined. With regard to marginal frequency of injury, slight injury (0.856), fatal injury (0.086) and severe injury (0.058) had the highest probability of occurrence. It was observed that workers with <1 year's work experience (0.168) had the highest probability of injury occurrence. The first group of workers, who were extensively exposed to risk of severe and fatal accidents, involved workers ≥ 50 years old, married, with 1-5 years' work experience, who had no past accident experience. The findings provide a direction for more effective safety strategies and occupational accident prevention and emergency programmes.

Betwixt and Between: Academic Developers in the Margins

ERIC Educational Resources Information Center

Little, Deandra; Green, David A.

2012-01-01

Previously, the authors developed a theoretical framework drawing on an early sociological study of migration to explore how marginality--being between cultures--might account for academic developers' "hybrid" academic identities and help them navigate institutional power dynamics. Based on data from semi-structured interviews, this…

Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

PubMed Central

Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

2014-01-01

Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability. PMID:25405514

Force sensor based tool condition monitoring using a heterogeneous ensemble learning model.

PubMed

Wang, Guofeng; Yang, Yinwei; Li, Zhimeng

2014-11-14

Tool condition monitoring (TCM) plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM), hidden Markov model (HMM) and radius basis function (RBF) are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR) algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

Marginal and Internal Discrepancies of Posterior Zirconia-Based Crowns Fabricated with Three Different CAD/CAM Systems Versus Metal-Ceramic.

PubMed

Ortega, Rocio; Gonzalo, Esther; Gomez-Polo, Miguel; Suárez, María J

2015-01-01

The aim of this study was to analyze the marginal and internal fit of metalceramic and zirconia-based crowns. Forty standardized steel specimens were prepared to receive posterior crowns and randomly divided into four groups (n = 10): (1) metal-ceramic, (2) NobelProcera Zirconia, (3) Lava Zirconia, and (4) VITA In-Ceram YZ. All crowns were cemented with glass-ionomer agent and sectioned buccolingually. A scanning electron microscope was used for measurements. Kruskal-Wallis and Wilcoxon signed rank test (α = .05) statistical analyses were conducted. Significant differences (P < .0001) in marginal discrepancies were observed between metal-ceramic and zirconia groups. No differences were found for the axial wall fit (P = .057). Significant differences were shown among the groups in discrepancies at the occlusal cusp (P = .0012) and at the fossa (P = .0062). No differences were observed between surfaces. All zirconia groups showed better values of marginal discrepancies than the metal-ceramic group. Procera Zirconia showed the lowest gaps.

Anatomy-based image processing analysis of the running pattern of the perioral artery for minimally invasive surgery.

PubMed

Lee, Sang-Hee; Lee, Minho; Kim, Hee-Jin

2014-10-01

We aimed to elucidate the tortuous course of the perioral artery with the aid of image processing, and to suggest accurate reference points for minimally invasive surgery. We used 59 hemifaces from 19 Korean and 20 Thai cadavers. A perioral line was defined to connect the point at which the facial artery emerged on the mandibular margin, and the ramification point of the lateral nasal artery and the inferior alar branch. The course of the perioral artery was reproduced as a graph based on the perioral line and analysed by adding the image of the artery using MATLAB. The course of the artery could be classified into 2 according to the course of the alar branch - oblique and vertical. Two distinct inflection points appeared in the course of the artery along the perioral line at the ramification points of the alar branch and the inferior labial artery, respectively, and the course of the artery across the face can be predicted based on the following references: the perioral line, the ramification point of the alar branch (5∼10 mm medial to the perioral line at the level of the lower third of the upper lip) and the inferior labial artery (5∼10 mm medial to the perioral line at the level of the middle of the lower lip). Copyright © 2014 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Rippability Assessment of Weathered Sedimentary Rock Mass using Seismic Refraction Methods

NASA Astrophysics Data System (ADS)

Ismail, M. A. M.; Kumar, N. S.; Abidin, M. H. Z.; Madun, A.

2018-04-01

Rippability or ease of excavation in sedimentary rocks is a significant aspect of the preliminary work of any civil engineering project. Rippability assessment was performed in this study to select an available ripping machine to rip off earth materials using the seismic velocity chart provided by Caterpillar. The research area is located at the proposed construction site for the development of a water reservoir and related infrastructure in Kampus Pauh Putra, Universiti Malaysia Perlis. The research was aimed at obtaining seismic velocity, P-wave (Vp) using a seismic refraction method to produce a 2D tomography model. A 2D seismic model was used to delineate the layers into the velocity profile. The conventional geotechnical method of using a borehole was integrated with the seismic velocity method to provide appropriate correlation. The correlated data can be used to categorize machineries for excavation activities based on the available systematic analysis procedure to predict rock rippability. The seismic velocity profile obtained was used to interpret rock layers within the ranges labelled as rippable, marginal, and non-rippable. Based on the seismic velocity method the site can be classified into loose sand stone to moderately weathered rock. Laboratory test results shows that the site’s rock material falls between low strength and high strength. Results suggest that Caterpillar’s smallest ripper, namely, D8R, can successfully excavate materials based on the test results integration from seismic velocity method and laboratory test.

Determination of the availability of appropriate aged flight rocket motors. [captive tests to determine case bond separation and grain bore cracking

NASA Technical Reports Server (NTRS)

Martin, P. J.

1974-01-01

A program to identify surplus solid rocket propellant engines which would be available for a program of functional integrity testing was conducted. The engines are classified as: (1) upper stage and apogee engines, (2) sounding rocket and launch vehicle engines, and (3) jato, sled, and tactical engines. Nearly all the engines were available because their age exceeds the warranted shelf life. The preference for testing included tests at nominal flight conditions, at design limits, and to establish margin limits. The principal failure modes of interest were case bond separation and grain bore cracking. Data concerning the identification and characteristics of each engine are tabulated. Methods for conducting the tests are described.

Faster Trees: Strategies for Accelerated Training and Prediction of Random Forests for Classification of Polsar Images

NASA Astrophysics Data System (ADS)

Hänsch, Ronny; Hellwich, Olaf

2018-04-01

Random Forests have continuously proven to be one of the most accurate, robust, as well as efficient methods for the supervised classification of images in general and polarimetric synthetic aperture radar data in particular. While the majority of previous work focus on improving classification accuracy, we aim for accelerating the training of the classifier as well as its usage during prediction while maintaining its accuracy. Unlike other approaches we mainly consider algorithmic changes to stay as much as possible independent of platform and programming language. The final model achieves an approximately 60 times faster training and a 500 times faster prediction, while the accuracy is only marginally decreased by roughly 1 %.

Northeastern Brazilian margin: Regional tectonic evolution based on integrated analysis of seismic reflection and potential field data and modelling

NASA Astrophysics Data System (ADS)

Blaich, Olav A.; Tsikalas, Filippos; Faleide, Jan Inge

2008-10-01

Integration of regional seismic reflection and potential field data along the northeastern Brazilian margin, complemented by crustal-scale gravity modelling, is used to reveal and illustrate onshore-offshore crustal structure correlation, the character of the continent-ocean boundary, and the relationship of crustal structure to regional variation of potential field anomalies. The study reveals distinct along-margin structural and magmatic changes that are spatially related to a number of conjugate Brazil-West Africa transfer systems, governing the margin segmentation and evolution. Several conceptual tectonic models are invoked to explain the structural evolution of the different margin segments in a conjugate margin context. Furthermore, the constructed transects, the observed and modelled Moho relief, and the potential field anomalies indicate that the Recôncavo, Tucano and Jatobá rift system may reflect a polyphase deformation rifting-mode associated with a complex time-dependent thermal structure of the lithosphere. The constructed transects and available seismic reflection profiles, indicate that the northern part of the study area lacks major breakup-related magmatic activity, suggesting a rifted non-volcanic margin affinity. In contrast, the southern part of the study area is characterized by abrupt crustal thinning and evidence for breakup magmatic activity, suggesting that this region evolved, partially, with a rifted volcanic margin affinity and character.

Patterns of care and outcomes of adjuvant therapy for high-risk head and neck cancer after surgery.

PubMed

Osborn, Virginia Wedell; Givi, Babak; Rineer, Justin; Roden, Dylan; Sheth, Niki; Lederman, Ariel; Katsoulakis, Evangelia; Hu, Kenneth; Schreiber, David

2018-06-01

Postoperative chemoradiotherapy (CRT) is considered standard of care in patients with locally advanced head and neck cancer with positive margins and/or extracapsular extension (ECE). The National Cancer Data Base (NCDB) was queried to identify patients with squamous cell carcinoma of the head and neck with stages III to IVB disease or with positive margins and/or ECE diagnosed between 2004 and 2012 receiving postoperative radiotherapy (RT). Using univariable and multivariable logistic and Cox regression, we assessed for predictors of CRT use and covariables impacting overall survival (OS), including in a propensity-matched subset. Of 12 224 patients, 67.1% with positive margins and/or ECE received CRT as well as 54.0% without positive margins and/or ECE. The 5-year OS was 61.6% for RT alone versus 67.4% for CRT. In the propensity-matched cohort, OS benefit persisted with CRT, including in a subset with positive margins and/or ECE but not without. Postoperative CRT seems underutilized with positive margins and/or ECE and overutilized without positive margins and/or ECE. The CRT was associated with improved OS but the benefit persisted only in the subset with positive margins and/or ECE. © 2018 Wiley Periodicals, Inc.

Unobtrusive Multi-Static Serial LiDAR Imager (UMSLI) First Generation Shape-Matching Based Classifier for 2D Contours

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

Cao, Zheng; Ouyang, Bing; Principe, Jose

A multi-static serial LiDAR system prototype was developed under DE-EE0006787 to detect, classify, and record interactions of marine life with marine hydrokinetic generation equipment. This software implements a shape-matching based classifier algorithm for the underwater automated detection of marine life for that system. In addition to applying shape descriptors, the algorithm also adopts information theoretical learning based affine shape registration, improving point correspondences found by shape descriptors as well as the final similarity measure.

Remote sensing of the marginal ice zone during Marginal Ice Zone Experiment (MIZEX) 83

NASA Technical Reports Server (NTRS)

Shuchman, R. A.; Campbell, W. J.; Burns, B. A.; Ellingsen, E.; Farrelly, B. A.; Gloersen, P.; Grenfell, T. C.; Hollinger, J.; Horn, D.; Johannessen, J. A.

1984-01-01

The remote sensing techniques utilized in the Marginal Ice Zone Experiment (MIZEX) to study the physical characteristics and geophysical processes of the Fram Strait Region of the Greenland Sea are described. The studies, which utilized satellites, aircraft, helicopters, and ship and ground-based remote sensors, focused on the use of microwave remote sensors. Results indicate that remote sensors can provide marginal ice zone characteristics which include ice edge and ice boundary locations, ice types and concentration, ice deformation, ice kinematics, gravity waves and swell (in the water and the ice), location of internal wave fields, location of eddies and current boundaries, surface currents and sea surface winds.

WSEAT Shock Testing Margin Assessment Using Energy Spectra Final Report.

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

Sisemore, Carl; Babuska, Vit; Booher, Jason

Several programs at Sandia National Laboratories have adopted energy spectra as a metric to relate the severity of mechanical insults to structural capacity. The purpose being to gain insight into the system's capability, reliability, and to quantify the ultimate margin between the normal operating envelope and the likely system failure point -- a system margin assessment. The fundamental concern with the use of energy metrics was that the applicability domain and implementation details were not completely defined for many problems of interest. The goal of this WSEAT project was to examine that domain of applicability and work out the necessarymore » implementation details. The goal of this project was to provide experimental validation for the energy spectra based methods in the context of margin assessment as they relate to shock environments. The extensive test results concluded that failure predictions using energy methods did not agree with failure predictions using S-N data. As a result, a modification to the energy methods was developed following the form of Basquin's equation to incorporate the power law exponent for fatigue damage. This update to the energy-based framework brings the energy based metrics into agreement with experimental data and historical S-N data.« less

Automatic detection of Floating Ice at Antarctic Continental Margin from Remotely Sensed Image with Object-oriented Matching

NASA Astrophysics Data System (ADS)

Zhao, Z.

2011-12-01

Changes in ice sheet and floating ices around that have great significance for global change research. In the context of global warming, rapidly changing of Antarctic continental margin, caving of ice shelves, movement of iceberg are all closely related to climate change and ocean circulation. Using automatic change detection technology to rapid positioning the melting Region of Polar ice sheet and the location of ice drift would not only strong support for Global Change Research but also lay the foundation for establishing early warning mechanism for melting of the polar ice and Ice displacement. This paper proposed an automatic change detection method using object-based segmentation technology. The process includes three parts: ice extraction using image segmentation, object-baed ice tracking, change detection based on similarity matching. An approach based on similarity matching of eigenvector is proposed in this paper, which used area, perimeter, Hausdorff distance, contour, shape and other information of each ice-object. Different time of LANDSAT ETM+ data, Chinese environment disaster satellite HJ1B date, MODIS 1B date are used to detect changes of Floating ice at Antarctic continental margin respectively. We select different time of ETM+ data(January 7, 2003 and January 16, 2003) with the area around Antarctic continental margin near the Lazarev Bay, which is from 70.27454853 degrees south latitude, longitude 12.38573410 degrees to 71.44474167 degrees south latitude, longitude 10.39252222 degrees,included 11628 sq km of Antarctic continental margin area, as a sample. Then we can obtain the area of floating ices reduced 371km2, and the number of them reduced 402 during the time. In addition, the changes of all the floating ices around the margin region of Antarctic within 1200 km are detected using MODIS 1B data. During the time from January 1, 2008 to January 7, 2008, the floating ice area decreased by 21644732 km2, and the number of them reduced by 83080. The results show that the object-based information extraction algorithm can obtain more precise details of a single object, while the change detection method based on similarity matching can effectively tracking the change of floating ice.

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

Truong, Pauline T., E-mail: ptruong@bccancer.bc.ca; Breast Cancer Outcomes Unit, British Columbia Cancer Agency, Vancouver Island Centre, University of British Columbia, Victoria, BC; Sadek, Betro T.

Purpose: To examine locoregional and distant recurrence (LRR and DR) in women with pT1-2N0 breast cancer according to approximated subtype and clinicopathologic characteristics. Methods and Materials: Two independent datasets were pooled and analyzed. The study participants were 1994 patients with pT1-2N0M0 breast cancer, treated with mastectomy without radiation therapy. The patients were classified into 1 of 5 subtypes: luminal A (ER+ or PR+/HER 2−/grade 1-2, n=1202); luminal B (ER+ or PR+/HER 2−/grade 3, n=294); luminal HER 2 (ER+ or PR+/HER 2+, n=221); HER 2 (ER−/PR−/HER 2+, n=105) and triple-negative breast cancer (TNBC) (ER−/PR−/HER 2−, n=172). Results: The median follow-up timemore » was 4.3 years. The 5-year Kaplan-Meier (KM) LRR were 1.8% in luminal A, 3.1% in luminal B, 1.7% in luminal HER 2, 1.9% in HER 2, and 1.9% in TNBC cohorts (P=.81). The 5-year KM DR was highest among women with TNBC: 1.8% in luminal A, 5.0% in luminal B, 2.4% in luminal HER 2, 1.1% in HER 2, and 9.6% in TNBC cohorts (P<.001). Among 172 women with TNBC, the 5-year KM LRR were 1.3% with clear margins versus 12.5% with close or positive margins (P=.04). On multivariable analysis, factors that conferred higher LRR risk were tumors >2 cm, lobular histology, and close/positive surgical margins. Conclusions: The 5-year risk of LRR in our pT1-2N0 cohort treated with mastectomy was generally low, with no significant differences observed between approximated subtypes. Among the subtypes, TNBC conferred the highest risk of DR and an elevated risk of LRR in the presence of positive or close margins. Our data suggest that although subtype alone cannot be used as the sole criterion to offer postmastectomy radiation therapy, it may reasonably be considered in conjunction with other clinicopathologic factors including tumor size, histology, and margin status. Larger cohorts and longer follow-up times are needed to define which women with node-negative disease have high postmastectomy LRR risks in contemporary practice.« less

Correlations between pathologic subtypes/immunohistochemical implication and CT characteristics of lung adenocarcinoma ≤ 1 cm with ground-glass opacity.

PubMed

Wu, Fang; Cai, Zu-long; Tian, Shu-ping; Jin, Xin; Jing, Rui; Yang, Yue-qing; Li, Ying-na; Zhao, Shao-hong

2015-04-01

To discuss the correlation of pathologic subtypes and immunohistochemical implication with CT features of lung adenocarcinoma 1 cm or less in diameter with focal ground-glass opacity (fGGO). CT appearances of 59 patients who underwent curative resection of lung adenocarcinoma ≤ 1 cm with fGGO were analyzed in terms of lesion location, size, density, shape (round, oval, polygonal, irregular), margin (smooth, lobular, spiculated, lobular and spiculated), bubble-like sign, air bronchogram, pleural tag, and tumor-lung interface. Histopathologic subtypes were classified according to International Association for the Study of Lung Cancer/ American Thoracic Society/European Respiratory Society classification of lung adenocarcinoma. Common molecular markers in immunohistochemical study included human epidermal growth factor receptor (HER)-1,HER-2,Ki-67, vascular endothelial growth factor (VEGF) and DNA topoisomerase 2Α.Patients' age and lesions' size and density were compared with pathologic subtypes using analysis of variance or nonparametric Wilcoxon tests. Patients' gender, lesion location, shape and margin, bubble-like sign, air bronchogram, pleural tag, and tumor-lung interface were compared with histopathologic subtypes and immunohistochemical implication using ψ² test or Fisher's exact test. The patients' gender, age, lesion location, shape, air bronchogram, pleural tag, and tumor-lung interface were not significantly different among different histopathologic subtypes (P=0.194, 0.126, 0.609, 0.678, 0.091, 0.374, and 0.339, respectively), whereas the lesion size,density,bubble-like sign, and margin showed significant differences (P=0.028, 0.002, 0.003, 0.046, respectively). The expression of Ki-67 significantly differed among nodules with different shapes(P=0.015). Statistically significant difference also existed between tumor-lung interface and HER-1 expression (P=0.019) and between bubble sign and HER-2 expression (P=0.049). Of lung adenocarcinoma ≤ 1 cm with fGGO,bubble-like sign occurs more frequently in invasive pulmonary adenocarcinoma and less frequently in atypical adenomatous hyperplasia. In addition, preinvasive lesions (atypical adenomatous hyperplasia and adenocarcinoma in situ) more frequently demonstrates smooth margin,while invasive lesions (minimally invasive adenocarcinoma and invasive pulmonary adenocarcinoma) more frequently demonstrates lobular and spiculated margin. Some CT features are associated with immunohistochemical implication of lung adenocarcinoma ≤ 1 cm with fGGO.

A distributed approach for optimizing cascaded classifier topologies in real-time stream mining systems.

PubMed

Foo, Brian; van der Schaar, Mihaela

2010-11-01

In this paper, we discuss distributed optimization techniques for configuring classifiers in a real-time, informationally-distributed stream mining system. Due to the large volume of streaming data, stream mining systems must often cope with overload, which can lead to poor performance and intolerable processing delay for real-time applications. Furthermore, optimizing over an entire system of classifiers is a difficult task since changing the filtering process at one classifier can impact both the feature values of data arriving at classifiers further downstream and thus, the classification performance achieved by an ensemble of classifiers, as well as the end-to-end processing delay. To address this problem, this paper makes three main contributions: 1) Based on classification and queuing theoretic models, we propose a utility metric that captures both the performance and the delay of a binary filtering classifier system. 2) We introduce a low-complexity framework for estimating the system utility by observing, estimating, and/or exchanging parameters between the inter-related classifiers deployed across the system. 3) We provide distributed algorithms to reconfigure the system, and analyze the algorithms based on their convergence properties, optimality, information exchange overhead, and rate of adaptation to non-stationary data sources. We provide results using different video classifier systems.

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

Plausibility assessment of a 2-state self-paced mental task-based BCI using the no-control performance analysis.

PubMed

Faradji, Farhad; Ward, Rabab K; Birch, Gary E

2009-06-15

The feasibility of having a self-paced brain-computer interface (BCI) based on mental tasks is investigated. The EEG signals of four subjects performing five mental tasks each are used in the design of a 2-state self-paced BCI. The output of the BCI should only be activated when the subject performs a specific mental task and should remain inactive otherwise. For each subject and each task, the feature coefficient and the classifier that yield the best performance are selected, using the autoregressive coefficients as the features. The classifier with a zero false positive rate and the highest true positive rate is selected as the best classifier. The classifiers tested include: linear discriminant analysis, quadratic discriminant analysis, Mahalanobis discriminant analysis, support vector machine, and radial basis function neural network. The results show that: (1) some classifiers obtained the desired zero false positive rate; (2) the linear discriminant analysis classifier does not yield acceptable performance; (3) the quadratic discriminant analysis classifier outperforms the Mahalanobis discriminant analysis classifier and performs almost as well as the radial basis function neural network; and (4) the support vector machine classifier has the highest true positive rates but unfortunately has nonzero false positive rates in most cases.

Using Neural Networks to Classify Digitized Images of Galaxies

NASA Astrophysics Data System (ADS)

Goderya, S. N.; McGuire, P. C.

2000-12-01

Automated classification of Galaxies into Hubble types is of paramount importance to study the large scale structure of the Universe, particularly as survey projects like the Sloan Digital Sky Survey complete their data acquisition of one million galaxies. At present it is not possible to find robust and efficient artificial intelligence based galaxy classifiers. In this study we will summarize progress made in the development of automated galaxy classifiers using neural networks as machine learning tools. We explore the Bayesian linear algorithm, the higher order probabilistic network, the multilayer perceptron neural network and Support Vector Machine Classifier. The performance of any machine classifier is dependant on the quality of the parameters that characterize the different groups of galaxies. Our effort is to develop geometric and invariant moment based parameters as input to the machine classifiers instead of the raw pixel data. Such an approach reduces the dimensionality of the classifier considerably, and removes the effects of scaling and rotation, and makes it easier to solve for the unknown parameters in the galaxy classifier. To judge the quality of training and classification we develop the concept of Mathews coefficients for the galaxy classification community. Mathews coefficients are single numbers that quantify classifier performance even with unequal prior probabilities of the classes.

Non-proliferative diabetic retinopathy symptoms detection and classification using neural network.

PubMed

Al-Jarrah, Mohammad A; Shatnawi, Hadeel

2017-08-01

Diabetic retinopathy (DR) causes blindness in the working age for people with diabetes in most countries. The increasing number of people with diabetes worldwide suggests that DR will continue to be major contributors to vision loss. Early detection of retinopathy progress in individuals with diabetes is critical for preventing visual loss. Non-proliferative DR (NPDR) is an early stage of DR. Moreover, NPDR can be classified into mild, moderate and severe. This paper proposes a novel morphology-based algorithm for detecting retinal lesions and classifying each case. First, the proposed algorithm detects the three DR lesions, namely haemorrhages, microaneurysms and exudates. Second, we defined and extracted a set of features from detected lesions. The set of selected feature emulates what physicians looked for in classifying NPDR case. Finally, we designed an artificial neural network (ANN) classifier with three layers to classify NPDR to normal, mild, moderate and severe. Bayesian regularisation and resilient backpropagation algorithms are used to train ANN. The accuracy for the proposed classifiers based on Bayesian regularisation and resilient backpropagation algorithms are 96.6 and 89.9, respectively. The obtained results are compared with results of the recent published classifier. Our proposed classifier outperforms the best in terms of sensitivity and specificity.

Multi-class biological tissue classification based on a multi-classifier: Preliminary study of an automatic output power control for ultrasonic surgical units.

PubMed

Youn, Su Hyun; Sim, Taeyong; Choi, Ahnryul; Song, Jinsung; Shin, Ki Young; Lee, Il Kwon; Heo, Hyun Mu; Lee, Daeweon; Mun, Joung Hwan

2015-06-01

Ultrasonic surgical units (USUs) have the advantage of minimizing tissue damage during surgeries that require tissue dissection by reducing problems such as coagulation and unwanted carbonization, but the disadvantage of requiring manual adjustment of power output according to the target tissue. In order to overcome this limitation, it is necessary to determine the properties of in vivo tissues automatically. We propose a multi-classifier that can accurately classify tissues based on the unique impedance of each tissue. For this purpose, a multi-classifier was built based on single classifiers with high classification rates, and the classification accuracy of the proposed model was compared with that of single classifiers for various electrode types (Type-I: 6 mm invasive; Type-II: 3 mm invasive; Type-III: surface). The sensitivity and positive predictive value (PPV) of the multi-classifier by cross checks were determined. According to the 10-fold cross validation results, the classification accuracy of the proposed model was significantly higher (p<0.05 or <0.01) than that of existing single classifiers for all electrode types. In particular, the classification accuracy of the proposed model was highest when the 3mm invasive electrode (Type-II) was used (sensitivity=97.33-100.00%; PPV=96.71-100.00%). The results of this study are an important contribution to achieving automatic optimal output power adjustment of USUs according to the properties of individual tissues. Copyright © 2015 Elsevier Ltd. All rights reserved.

Summary measures of agreement and association between many raters' ordinal classifications.

PubMed

Mitani, Aya A; Freer, Phoebe E; Nelson, Kerrie P

2017-10-01

Interpretation of screening tests such as mammograms usually require a radiologist's subjective visual assessment of images, often resulting in substantial discrepancies between radiologists' classifications of subjects' test results. In clinical screening studies to assess the strength of agreement between experts, multiple raters are often recruited to assess subjects' test results using an ordinal classification scale. However, using traditional measures of agreement in some studies is challenging because of the presence of many raters, the use of an ordinal classification scale, and unbalanced data. We assess and compare the performances of existing measures of agreement and association as well as a newly developed model-based measure of agreement to three large-scale clinical screening studies involving many raters' ordinal classifications. We also conduct a simulation study to demonstrate the key properties of the summary measures. The assessment of agreement and association varied according to the choice of summary measure. Some measures were influenced by the underlying prevalence of disease and raters' marginal distributions and/or were limited in use to balanced data sets where every rater classifies every subject. Our simulation study indicated that popular measures of agreement and association are prone to underlying disease prevalence. Model-based measures provide a flexible approach for calculating agreement and association and are robust to missing and unbalanced data as well as the underlying disease prevalence. Copyright © 2017 Elsevier Inc. All rights reserved.

28 CFR 17.26 - Derivative classification.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 28 Judicial Administration 1 2014-07-01 2014-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons need not possess original classification authority to derivatively classify information based on source...

28 CFR 17.26 - Derivative classification.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 28 Judicial Administration 1 2013-07-01 2013-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons need not possess original classification authority to derivatively classify information based on source...

28 CFR 17.26 - Derivative classification.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 28 Judicial Administration 1 2012-07-01 2012-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons need not possess original classification authority to derivatively classify information based on source...

28 CFR 17.26 - Derivative classification.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 28 Judicial Administration 1 2011-07-01 2011-07-01 false Derivative classification. 17.26 Section... ACCESS TO CLASSIFIED INFORMATION Classified Information § 17.26 Derivative classification. (a) Persons need not possess original classification authority to derivatively classify information based on source...

A Hybrid Stochastic-Neuro-Fuzzy Model-Based System for In-Flight Gas Turbine Engine Diagnostics

DTIC Science & Technology

2001-04-05

Margin (ADM) and (ii) Fault Detection Margin (FDM). Key Words: ANFIS, Engine Health Monitoring , Gas Path Analysis, and Stochastic Analysis Adaptive Network...The paper illustrates the application of a hybrid Stochastic- Fuzzy -Inference Model-Based System (StoFIS) to fault diagnostics and prognostics for both...operational history monitored on-line by the engine health management (EHM) system. To capture the complex functional relationships between different

Instances selection algorithm by ensemble margin

NASA Astrophysics Data System (ADS)

Saidi, Meryem; Bechar, Mohammed El Amine; Settouti, Nesma; Chikh, Mohamed Amine

2018-05-01

The main limit of data mining algorithms is their inability to deal with the huge amount of available data in a reasonable processing time. A solution of producing fast and accurate results is instances and features selection. This process eliminates noisy or redundant data in order to reduce the storage and computational cost without performances degradation. In this paper, a new instance selection approach called Ensemble Margin Instance Selection (EMIS) algorithm is proposed. This approach is based on the ensemble margin. To evaluate our approach, we have conducted several experiments on different real-world classification problems from UCI Machine learning repository. The pixel-based image segmentation is a field where the storage requirement and computational cost of applied model become higher. To solve these limitations we conduct a study based on the application of EMIS and other instance selection techniques for the segmentation and automatic recognition of white blood cells WBC (nucleus and cytoplasm) in cytological images.

A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots

PubMed Central

Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub

2015-01-01

An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases. PMID:26528986

A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots.

PubMed

Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub

2015-10-30

An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases.

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.

Surface expression of Eastern Mediterranean slab dynamics: Uplift at the SW margin of the Central Anatolian Plateau

NASA Astrophysics Data System (ADS)

Schildgen, T. F.; Cosentino, D.; Caruso, A.; Yildirim, C.; Echtler, H.; Strecker, M. R.

2011-12-01

The Central Anatolian plateau in Turkey borders one of the most complex tectonic regions on Earth, where collision of the Arabian plate with Eurasia in Eastern Anatolia transitions to a cryptic pattern of subduction of the African beneath the Eurasian plate, with concurrent westward extrusion of the Anatolian microplate. Topographic growth of the southern margin of the Central Anatolian plateau has proceeded in discrete stages that can be distinguished based on the outcrop pattern and ages of uplifted marine sediments. These marine units, together with older basement rocks and younger continental sedimentary fills, also record an evolving nature of crustal deformation and uplift patterns that can be used to test the viability of different uplift mechanisms that have contributed to generate the world's third-largest orogenic plateau. Late Miocene marine sediments outcrop along the SW plateau margin at 1.5 km elevation, while they blanket the S and SE margins at up to more than 2 km elevation. Our new biostratigraphic data limit the age of 1.5-km-high marine sediments along the SW plateau margin to < 7.17 Ma, while regional lithostratigraphic correlations imply that the age is < 6.7 Ma. After reconstructing the post-Late Miocene surface uplift pattern from elevations of uplifted marine sediments and geomorphic reference surfaces, it is clear that regional surface uplift reaches maximum values along the modern plateau margin, with the SW margin experiencing less cumulative uplift compared to the S and SE margins. Our structural measurements and inversion modeling of faults within the uplifted region agree with previous findings in surrounding regions, with early contraction followed by strike-slip and extensional deformation. Shallow earthquake focal mechanisms show that the extensional phase has continued to the present. Broad similarities in the onset of surface uplift (after 7 Ma) and a change in the kinematic evolution of the plateau margin (after 8 Ma) suggest that these phenomena may have been linked with a change in the tectonic stress field associated with the process(es) causing post-7 Ma surface uplift. The complex geometry of lithospheric slabs beneath the southern plateau margin, early Pliocene to recent alkaline volcanism, and the localized uplift pattern with accompanying tensional/transtensional stresses point toward slab tearing and localized heating at the base of the lithosphere as a probable mechanism for post-7 Ma uplift of the SW margin. Considering previous work in the region, slab break-off is more likely responsible for non-contractional uplift along the S and SE margins. Overall there appears to be an important link between slab dynamics and surface uplift across the whole southern margin of the Central Anatolian plateau.

4-d magnetism: Electronic structure and magnetism of some Mo-based alloys

NASA Astrophysics Data System (ADS)

Liu, Yong; Bose, S. K.; Kudrnovský, J.

2017-02-01

We report results of a first-principles density-functional study of alloys of the 4 d -element Mo with group IV elements Si, Ge and Sn in zinc blende (ZB) and rock salt (RS) structures. The study was motivated by a similar study of ours based on the 4 d -element Tc, which showed the presence of half-metallic states with integer magnetic moment (1μB) per formula unit in TcX (X=C, Si, Ge) alloys. The calculated Curie temperatures for the ferromagnetic (FM) phases were low, around or less than 300 K. Searching for the possibility of 4 d -based alloys with higher Curie temperatures we have carried out the study involving the elements Mo, Ru and Rh. Among these the most promising case appears to be that involving the element Mo. Among the MoX (X=Si, Ge, Sn) alloys in ZB and RS structures, both MoGe and MoSn in ZB structures are found to possess an integer magnetic moment of 2μB per formula unit. ZB MoSn can be classified as a marginal/weak half-metal or a spin gapless semiconductor, while ZB MoGe would be best described as a gapless magnetic semiconductor. The calculated Curie temperatures are in the range 300-700 K. Considering the theoretical uncertainty in the band gaps due not only to the treatment of exchange and correlation effects, but density functional theory itself, these classifications may change somewhat, but both merit investigation from the viewpoint of potential spintronic application. Based on their higher Curie temperatures, Mo-based alloys would serve such purpose better than the previously reported Tc-based ones.

Marginalization and symbolic violence in a world of differences: war and parallels to nursing practice.

PubMed

Hall, Joanne M

2004-04-01

Marginalization has been used as a guiding concept for nursing research, theory and practice. Its properties have been identified and updated in 1994 and 1999, respectively. This article re-examines marginalization, considering it to be a concept that changes with pivotal historical events. The events of September 11, 2001, and the war between the US/UK and Iraq are such pivotal events. The notion of the linguistic habitus and symbolic violence as outlined by Bourdieu provide new insights about the dynamics of marginalization. Specifically noted is the marginalization of persons and cultures based on their designation by the current US administration, and as interpreted through mainstream media, as actual or potential 'terrorists'. A parallel situation in nursing is discussed, beginning with nursing's own marginality, related to the dynamics of symbolic violence. Nursing is argued to be vulnerable to having essential words and practices co-opted by dominant institutions and altered in meaning, that is, made incongruent with the discipline's emphasis on core values of confidentiality, equity and care. In response to marginalization and exteriorization those affected can use voice and testimony to 'recreate the centre'. Suggestions for protecting our practices and philosophy are included.

Marginal adaptation, fracture load and macroscopic failure mode of adhesively luted PMMA-based CAD/CAM inlays.

PubMed

Ender, Andreas; Bienz, Stefan; Mörmann, Werner; Mehl, Albert; Attin, Thomas; Stawarczyk, Bogna

2016-02-01

To evaluate marginal adaptation, fracture load and failure types of CAD/CAM polymeric inlays. Standardized prepared human molars (48) were divided into four groups (n=12): (A) PCG (positive control group); adhesively luted glass-ceramic inlays, (B) TRX; CAD/CAM polymeric inlays luted using a self-adhesive resin cement, (C) TAC; CAD/CAM polymeric inlays luted using a conventional resin cement, and (D) NCG (negative control group); direct-filled resin-based composite restorations. All specimens were subjected to a chewing simulator. Before and after chewing fatigue, marginal adaptation was assessed at two interfaces: (1) between dental hard tissues and luting cement and (2) between luting cement and restoration. Thereafter, the specimens were loaded and the fracture loads, as well as the failure types, were determined. The data were analysed using three- and one-way ANOVA with post hoc Scheffé test, two sample Student's t-test (p<0.05). Before and after chewing fatigue, marginal adaptation for interface 1 showed significantly better results for TRX and PCG than for TAC (p=0.001-0.02) and NCG (p=0.001-0.047). For interface 2, marginal adaptation for TAC was significantly inferior to TRX (p<0.001) and PCG (p<0.001). Chewing fatigue had a negative impact on the marginal adaptation of TAC and NCG. No significant differences in fracture load were found between all tested groups. Self-adhesive luted polymeric CAD/CAM inlays showed similar marginal adaptation and fracture load values compared to adhesively luted glass-ceramic inlays. Copyright © 2015 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Future View: Web Navigation based on Learning User's Browsing Strategy

NASA Astrophysics Data System (ADS)

Nagino, Norikatsu; Yamada, Seiji

In this paper, we propose a Future View system that assists user's usual Web browsing. The Future View will prefetch Web pages based on user's browsing strategies and present them to a user in order to assist Web browsing. To learn user's browsing strategy, the Future View uses two types of learning classifier systems: a content-based classifier system for contents change patterns and an action-based classifier system for user's action patterns. The results of learning is applied to crawling by Web robots, and the gathered Web pages are presented to a user through a Web browser interface. We experimentally show effectiveness of navigation using the Future View.

Combining contour detection algorithms for the automatic extraction of the preparation line from a dental 3D measurement

NASA Astrophysics Data System (ADS)

Ahlers, Volker; Weigl, Paul; Schachtzabel, Hartmut

2005-04-01

Due to the increasing demand for high-quality ceramic crowns and bridges, the CAD/CAM-based production of dental restorations has been a subject of intensive research during the last fifteen years. A prerequisite for the efficient processing of the 3D measurement of prepared teeth with a minimal amount of user interaction is the automatic determination of the preparation line, which defines the sealing margin between the restoration and the prepared tooth. Current dental CAD/CAM systems mostly require the interactive definition of the preparation line by the user, at least by means of giving a number of start points. Previous approaches to the automatic extraction of the preparation line rely on single contour detection algorithms. In contrast, we use a combination of different contour detection algorithms to find several independent potential preparation lines from a height profile of the measured data. The different algorithms (gradient-based, contour-based, and region-based) show their strengths and weaknesses in different clinical situations. A classifier consisting of three stages (range check, decision tree, support vector machine), which is trained by human experts with real-world data, finally decides which is the correct preparation line. In a test with 101 clinical preparations, a success rate of 92.0% has been achieved. Thus the combination of different contour detection algorithms yields a reliable method for the automatic extraction of the preparation line, which enables the setup of a turn-key dental CAD/CAM process chain with a minimal amount of interactive screen work.

A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjects.

PubMed

Cacha, L A; Parida, S; Dehuri, S; Cho, S-B; Poznanski, R R

2016-12-01

The huge number of voxels in fMRI over time poses a major challenge to for effective analysis. Fast, accurate, and reliable classifiers are required for estimating the decoding accuracy of brain activities. Although machine-learning classifiers seem promising, individual classifiers have their own limitations. To address this limitation, the present paper proposes a method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification for application across multiple subjects. Similarly, the fuzzy integral (FI) approach has been employed as an efficient tool for combining different classifiers. The FI approach led to the development of a classifiers ensemble technique that performs better than any of the single classifier by reducing the misclassification, the bias, and the variance. The proposed method successfully classified the different cognitive states for multiple subjects with high accuracy of classification. Comparison of the performance improvement, while applying ensemble neural networks method, vs. that of the individual neural network strongly points toward the usefulness of the proposed method.

Assessment of safety margins in zircaloy oxidation and embrittlement criteria for ECCS acceptance

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

Williford, R.E.

1986-04-01

Current Emergency Core Cooling System (ECCS) Acceptance Criteria for light-water reactors include certain requirements pertaining to calculations of core performance during a Loss of Coolant Accident (LOCA). The Baker-Just correlation must be used to calculate Zircaloy-steam oxidation, calculated peak cladding temperatures (PCT) must not exceed 1204/sup 0/C, and calculated oxidation must not exceed 17% equivalent cladding reacted (17% ECR). The minimum margin of safety was estimated for each of these criteria, based on research performed in the last decade. Margins were defined as the amounts of conservatism over and above the expected extreme values computed from the data base atmore » specified confidence levels. The currently required Baker-Just oxidation correlation provides margins only over the 1100/sup 0/C to 1500/sup 0/C temperature range at the 95% confidence level. The PCT margins for thermal shock and handling failures are adequate at oxidation temperatures above 1204/sup 0/C for 210 and 160 seconds, respectively, at the 95% confidence level. ECR thermal shock and handling margins at the 50% and 95% confidence levels, respectively, range between 2% and 7% ECR for the Baker-Just correlation, but vanish at temperatures between 1100/sup 0/C and 1160/sup 0/C for the best-estimate Cathcart-Pawel correlation. Use of the Cathcart-Pawel correlation for LOCA calculations can be justified at the 85% to 88% confidence level if cooling rate effects can be neglected. 75 refs., 21 figs.« less

Nonlinear dynamics near the stability margin in rotating pipe flow

NASA Technical Reports Server (NTRS)

Yang, Z.; Leibovich, S.

1991-01-01

The nonlinear evolution of marginally unstable wave packets in rotating pipe flow is studied. These flows depend on two control parameters, which may be taken to be the axial Reynolds number R and a Rossby number, q. Marginal stability is realized on a curve in the (R, q)-plane, and the entire marginal stability boundary is explored. As the flow passes through any point on the marginal stability curve, it undergoes a supercritical Hopf bifurcation and the steady base flow is replaced by a traveling wave. The envelope of the wave system is governed by a complex Ginzburg-Landau equation. The Ginzburg-Landau equation admits Stokes waves, which correspond to standing modulations of the linear traveling wavetrain, as well as traveling wave modulations of the linear wavetrain. Bands of wavenumbers are identified in which the nonlinear modulated waves are subject to a sideband instability.

Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Ishihara, Abraham K.; Krishnakumar, Kalmanje Srinlvas; Bakhtiari-Nejad, Maryam

2009-01-01

This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.

A Method of Neighbor Classes Based SVM Classification for Optical Printed Chinese Character Recognition

PubMed Central

Zhang, Jie; Wu, Xiaohong; Yu, Yanmei; Luo, Daisheng

2013-01-01

In optical printed Chinese character recognition (OPCCR), many classifiers have been proposed for the recognition. Among the classifiers, support vector machine (SVM) might be the best classifier. However, SVM is a classifier for two classes. When it is used for multi-classes in OPCCR, its computation is time-consuming. Thus, we propose a neighbor classes based SVM (NC-SVM) to reduce the computation consumption of SVM. Experiments of NC-SVM classification for OPCCR have been done. The results of the experiments have shown that the NC-SVM we proposed can effectively reduce the computation time in OPCCR. PMID:23536777

A New Adaptive Structural Signature for Symbol Recognition by Using a Galois Lattice as a Classifier.

PubMed

Coustaty, M; Bertet, K; Visani, M; Ogier, J

2011-08-01

In this paper, we propose a new approach for symbol recognition using structural signatures and a Galois lattice as a classifier. The structural signatures are based on topological graphs computed from segments which are extracted from the symbol images by using an adapted Hough transform. These structural signatures-that can be seen as dynamic paths which carry high-level information-are robust toward various transformations. They are classified by using a Galois lattice as a classifier. The performance of the proposed approach is evaluated based on the GREC'03 symbol database, and the experimental results we obtain are encouraging.

Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification.

PubMed

Haque, Mohammad Nazmul; Noman, Nasimul; Berretta, Regina; Moscato, Pablo

2016-01-01

Classification of datasets with imbalanced sample distributions has always been a challenge. In general, a popular approach for enhancing classification performance is the construction of an ensemble of classifiers. However, the performance of an ensemble is dependent on the choice of constituent base classifiers. Therefore, we propose a genetic algorithm-based search method for finding the optimum combination from a pool of base classifiers to form a heterogeneous ensemble. The algorithm, called GA-EoC, utilises 10 fold-cross validation on training data for evaluating the quality of each candidate ensembles. In order to combine the base classifiers decision into ensemble's output, we used the simple and widely used majority voting approach. The proposed algorithm, along with the random sub-sampling approach to balance the class distribution, has been used for classifying class-imbalanced datasets. Additionally, if a feature set was not available, we used the (α, β) - k Feature Set method to select a better subset of features for classification. We have tested GA-EoC with three benchmarking datasets from the UCI-Machine Learning repository, one Alzheimer's disease dataset and a subset of the PubFig database of Columbia University. In general, the performance of the proposed method on the chosen datasets is robust and better than that of the constituent base classifiers and many other well-known ensembles. Based on our empirical study we claim that a genetic algorithm is a superior and reliable approach to heterogeneous ensemble construction and we expect that the proposed GA-EoC would perform consistently in other cases.

Subsurface event detection and classification using Wireless Signal Networks.

PubMed

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

2012-11-05

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification

PubMed Central

Haque, Mohammad Nazmul; Noman, Nasimul; Berretta, Regina; Moscato, Pablo

2016-01-01

Classification of datasets with imbalanced sample distributions has always been a challenge. In general, a popular approach for enhancing classification performance is the construction of an ensemble of classifiers. However, the performance of an ensemble is dependent on the choice of constituent base classifiers. Therefore, we propose a genetic algorithm-based search method for finding the optimum combination from a pool of base classifiers to form a heterogeneous ensemble. The algorithm, called GA-EoC, utilises 10 fold-cross validation on training data for evaluating the quality of each candidate ensembles. In order to combine the base classifiers decision into ensemble’s output, we used the simple and widely used majority voting approach. The proposed algorithm, along with the random sub-sampling approach to balance the class distribution, has been used for classifying class-imbalanced datasets. Additionally, if a feature set was not available, we used the (α, β) − k Feature Set method to select a better subset of features for classification. We have tested GA-EoC with three benchmarking datasets from the UCI-Machine Learning repository, one Alzheimer’s disease dataset and a subset of the PubFig database of Columbia University. In general, the performance of the proposed method on the chosen datasets is robust and better than that of the constituent base classifiers and many other well-known ensembles. Based on our empirical study we claim that a genetic algorithm is a superior and reliable approach to heterogeneous ensemble construction and we expect that the proposed GA-EoC would perform consistently in other cases. PMID:26764911

Subsurface Event Detection and Classification Using Wireless Signal Networks

PubMed Central

Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

2012-01-01

Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

Lower Crustal Strength Controls on Melting and Serpentinization at Magma-Poor Margins: Potential Implications for the South Atlantic

NASA Astrophysics Data System (ADS)

Ros, Elena; Pérez-Gussinyé, Marta; Araújo, Mario; Thoaldo Romeiro, Marco; Andrés-Martínez, Miguel; Morgan, Jason P.

2017-12-01

Rifted continental margins may present a predominantly magmatic continent-ocean transition (COT), or one characterized by large exposures of serpentinized mantle. In this study we use numerical modeling to show the importance of the lower crustal strength in controlling the amount and onset of melting and serpentinization during rifting. We propose that the relative timing between both events controls the nature of the COT. Numerical experiments for half-extension velocities <=10 mm/yr suggest there is a genetic link between margin tectonic style and COT nature that strongly depends on the lower crustal strength. Our results imply that very slow extension velocities (< 5 mm/yr) and a strong lower crust lead to margins characterized by large oceanward dipping faults, strong syn-rift subsidence and abrupt crustal tapering beneath the continental shelf. These margins can be either narrow symmetric or asymmetric and present a COT with exhumed serpentinized mantle underlain by some magmatic products. In contrast, a weak lower crust promotes margins with a gentle crustal tapering, small faults dipping both ocean- and landward and small syn-rift subsidence. Their COT is predominantly magmatic at any ultra-slow extension velocity and perhaps underlain by some serpentinized mantle. These margins can also be either symmetric or asymmetric. Our models predict that magmatic underplating mostly underlies the wide margin at weak asymmetric conjugates, whereas the wide margin is mainly underlain by serpentinized mantle at strong asymmetric margins. Based on this conceptual template, we propose different natures for the COTs in the South Atlantic.

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers.

PubMed

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (Danio rerio)

EPA Science Inventory

Development and application of transcriptomics-based gene classifiers for ecotoxicological applications lag far behind those of human biomedical science. Many such classifiers discovered thus far lack vigorous statistical and experimental validations, with their stability and rel...

Mobile robots traversability awareness based on terrain visual sensory data fusion

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir

2007-04-01

In this paper, we have presented methods that significantly improve the robot awareness of its terrain traversability conditions. The terrain traversability awareness is achieved by association of terrain image appearances from different poses and fusion of extracted information from multimodality imaging and range sensor data for localization and clustering environment landmarks. Initially, we describe methods for extraction of salient features of the terrain for the purpose of landmarks registration from two or more images taken from different via points along the trajectory path of the robot. The method of image registration is applied as a means of overlaying (two or more) of the same terrain scene at different viewpoints. The registration geometrically aligns salient landmarks of two images (the reference and sensed images). A Similarity matching techniques is proposed for matching the terrain salient landmarks. Secondly, we present three terrain classifier models based on rule-based, supervised neural network, and fuzzy logic for classification of terrain condition under uncertainty and mapping the robot's terrain perception to apt traversability measures. This paper addresses the technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain spatial and textural cues.

Internet-Based Cognitive Behavior Therapy vs. Cognitive Behavioral Group Therapy for Social Anxiety Disorder: A Randomized Controlled Non-inferiority Trial

PubMed Central

Hedman, Erik; Andersson, Gerhard; Ljótsson, Brjánn; Andersson, Erik; Rück, Christian; Mörtberg, Ewa; Lindefors, Nils

2011-01-01

Background and Aims Cognitive behavioral group therapy (CBGT) is an effective, well-established, but not widely available treatment for social anxiety disorder (SAD). Internet-based cognitive behavior therapy (ICBT) has the potential to increase availability and facilitate dissemination of therapeutic services for SAD. However, ICBT for SAD has not been directly compared with in-person treatments such as CBGT and few studies investigating ICBT have been conducted in clinical settings. Our aim was to investigate if ICBT is at least as effective as CBGT for SAD when treatments are delivered in a psychiatric setting. Methods We conducted a randomized controlled non-inferiority trial with allocation to ICBT (n = 64) or CBGT (n = 62) with blinded assessment immediately following treatment and six months post-treatment. Participants were 126 individuals with SAD who received CBGT or ICBT for a duration of 15 weeks. The Liebowitz Social Anxiety Scale (LSAS) was the main outcome measure. The following non-inferiority margin was set: following treatment, the lower bound of the 95 % confidence interval (CI) of the mean difference between groups should be less than 10 LSAS-points. Results Both groups made large improvements. At follow-up, 41 (64%) participants in the ICBT group were classified as responders (95% CI, 52%–76%). In the CBGT group, 28 participants (45%) responded to the treatment (95% CI, 33%–58%). At post-treatment and follow-up respectively, the 95 % CI of the LSAS mean difference was 0.68–17.66 (Cohen’s d between group = 0.41) and −2.51–15.69 (Cohen’s d between group = 0.36) favoring ICBT, which was well within the non-inferiority margin. Mixed effects models analyses showed no significant interaction effect for LSAS, indicating similar improvement across treatments (F = 1.58; df = 2, 219; p = .21). Conclusions ICBT delivered in a psychiatric setting can be as effective as CBGT in the treatment of SAD and could be used to increase availability to CBT. Trial Registration ClinicalTrials.gov NCT00564967 PMID:21483704

Clinical practice guidelines from the French College of Gynecologists and Obstetricians (CNGOF): benign breast tumors - short text.

PubMed

Lavoué, Vincent; Fritel, Xavier; Antoine, Martine; Beltjens, Françoise; Bendifallah, Sofiane; Boisserie-Lacroix, Martine; Boulanger, Loic; Canlorbe, Geoffroy; Catteau-Jonard, Sophie; Chabbert-Buffet, Nathalie; Chamming's, Foucauld; Chéreau, Elisabeth; Chopier, Jocelyne; Coutant, Charles; Demetz, Julie; Guilhen, Nicolas; Fauvet, Raffaele; Kerdraon, Olivier; Laas, Enora; Legendre, Guillaume; Mathelin, Carole; Nadeau, Cédric; Naggara, Isabelle Thomassin; Ngô, Charlotte; Ouldamer, Lobna; Rafii, Arash; Roedlich, Marie-Noelle; Seror, Jérémy; Séror, Jean-Yves; Touboul, Cyril; Uzan, Catherine; Daraï, Emile

2016-05-01

Screening with breast ultrasound in combination with mammography is needed to investigate a clinical breast mass (Grade B), colored single-pore breast nipple discharge (Grade C), or mastitis (Grade C). The BI-RADS system is recommended for describing and classifying abnormal breast imaging findings. For a breast abscess, a percutaneous biopsy is recommended in the case of a mass or persistent symptoms (Grade C). For mastalgia, when breast imaging is normal, no MRI or breast biopsy is recommended (Grade C). Percutaneous biopsy is recommended for a BI-RADS category 4-5 mass (Grade B). For persistent erythematous nipple or atypical eczema lesions, a nipple biopsy is recommended (Grade C). For distortion and asymmetry, a vacuum core-needle biopsy is recommended due to the risk of underestimation by simple core-needle biopsy (Grade C). For BI-RADS category 4-5 microcalcifications without any ultrasound signal, a minimum 11-G vacuum core-needle biopsy is recommended (Grade B). In the absence of microcalcifications on radiography cores additional samples are recommended (Grade B). For atypical ductal hyperplasia, atypical lobular hyperplasia, lobular carcinoma in situ, flat epithelial atypia, radial scar and mucocele with atypia, surgical excision is commonly recommended (Grade C). Expectant management is feasible after multidisciplinary consensus. For these lesions, when excision margins are not clear, no new excision is recommended except for LCIS characterized as pleomorphic or with necrosis (Grade C). For grade 1 phyllodes tumor, surgical resection with clear margins is recommended. For grade 2 phyllodes tumor, 10mm margins are recommended (Grade C). For papillary breast lesions without atypia, complete disappearance of the radiological signal is recommended (Grade C). For papillary breast lesions with atypia, complete surgical excision is recommended (Grade C). Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Flood hazard assessment for french NPPs

NASA Astrophysics Data System (ADS)

Rebour, Vincent; Duluc, Claire-Marie; Guimier, Laurent

2015-04-01

This paper presents the approach for flood hazard assessment for NPP which is on-going in France in the framework of post-Fukushima activities. These activities were initially defined considering both European "stress tests" of NPPs pursuant to the request of the European Council, and the French safety audit of civilian nuclear facilities in the light of the Fukushima Daiichi accident. The main actors in that process are the utility (EDF is, up to date, the unique NPP's operator in France), the regulatory authority (ASN) and its technical support organization (IRSN). This paper was prepared by IRSN, considering official positions of the other main actors in the current review process, it was not officially endorsed by them. In France, flood hazard to be considered for design basis definition (for new NPPs and for existing NPPs in periodic safety reviews conducted every 10 years) was revised before Fukushima-Daichi accident, due to le Blayais NPP December 1999 experience (partial site flooding and loss of some safety classified systems). The paper presents in the first part an overview of the revised guidance for design basis flood. In order to address design extension conditions (conditions that could result from natural events exceeding the design basis events), a set of flooding scenarios have been defined by adding margins on the scenarios that are considered for the design. Due to the diversity of phenomena to be considered for flooding hazard, the margin assessment is specific to each flooding scenario in terms of parameter to be penalized and of degree of variation of this parameter. The general approach to address design extension conditions is presented in the second part of the paper. The next parts present the approach for five flooding scenarios including design basis scenario and additional margin to define design extension scenarios.

Geochemical fingerprinting of ∼2.5 Ga forearc-arc-backarc related magmatic suites in the Bastar Craton, central India

NASA Astrophysics Data System (ADS)

Asthana, Deepanker; Kumar, Sirish; Vind, Aditya Kumar; Zehra, Fatima; Kumar, Harshavardhan; Pophare, Anil M.

2018-05-01

The Pitepani volcanic suite of the Dongargarh Supergroup, central India comprises of a calc-alkaline suite and a tholeiitic suite, respectively. The rare earth element (REE) patterns, mantle normalized plots and relict clinopyroxene chemistry of the Pitepani calc-alkaline suite are akin to high-Mg andesites (HMA) and reveal remarkable similarity to the Cenozoic Setouchi HMA from Japan. The Pitepani HMAs are geochemically correlated with similar rocks in the Kotri-Dongargarh mobile belt (KDMB) and in the mafic dykes of the Bastar Craton. The rationale behind lithogeochemical correlations are that sanukitic HMAs represent fore-arc volcanism over a very limited period of time, under abnormally high temperature conditions and are excellent regional and tectonic time markers. Furthermore, the tholeiitic suites that are temporally and spatially associated with the HMAs in the KDMB and in the mafic dykes of the Bastar Craton are classified into: (a) a continental back-arc suite that are depleted in incompatible elements, and (b) a continental arc suite that are more depleted in incompatible elements, respectively. The HMA suite, the continental back-arc and continental arc suites are lithogeochemically correlated in the KDMB and in the mafic dykes of the Bastar Craton. The three geochemically distinct Neoarchaean magmatic suites are temporally and spatially related to each other and to an active continental margin. The identification of three active continental margin magmatic suites for the first time, provides a robust conceptual framework to unravel the Neoarchaean geodynamic evolution of the Bastar Craton. We propose an active continental margin along the Neoarchaen KDMB with eastward subduction coupled with slab roll back or preferably, ridge-subduction along the Central Indian Tectonic Zone (CITZ) to account for the three distinct magmatic suites and the Neoarchean geodynamic evolution of the Bastar Craton.

Consumer governance may harm health center financial performance.

PubMed

Wright, Brad

2013-07-01

Federally qualified health centers (FQHCs), which must be governed by a patient majority, have historically struggled to remain financially viable while caring for a disproportionately low-income and uninsured population. Consumer governance is credited with making FQHCs responsive to community needs, but to the extent that patient trustees resemble the typical low-income FQHC patient, patient trustees might lack the capacity to govern, harming financial performance as a result. Thus, this study sought to empirically evaluate the relationship between FQHC board composition and financial performance. Using data from years 2002-2007 of the Uniform Data System and the Area Resource File, and years 2003-2006 of FQHC grant applications, FQHC operating margin was modeled as a function of board and executive committee composition, the interaction between them, general time trends, other FQHC and county-level factors, and FQHC-level fixed effects. Trustees were classified as representative (ie, low-income) consumers, nonrepresentative (ie, high-income) consumers, and nonconsumers on the basis of their self-reported patient status and occupation. Each 10 percentage point increase in the proportion of representative consumers on the board is associated with a 1.7 percentage point decrease in operating margin. This effect becomes insignificant if any consumers serve on the executive committee. There is no significant relationship between the proportion of nonrepresentative consumers and operating margin. If consumers are given leadership roles on the board, consumer governance does not harm financial performance and may be beneficial enough in other respects to justify its being required as a condition of federal FQHC funding. Without such strengthening of the provision, consumer governance appears to harm financial performance and it is unclear from this study whether it offers other benefits that are significant enough to justify this financial risk.

Optical Coherence Tomography Angiography: A Useful Tool for Diagnosis of Treatment-Naïve Quiescent Choroidal Neovascularization.

PubMed

Carnevali, Adriano; Cicinelli, Maria Vittoria; Capuano, Vittorio; Corvi, Federico; Mazzaferro, Andrea; Querques, Lea; Scorcia, Vincenzo; Souied, Eric H; Bandello, Francesco; Querques, Giuseppe

2016-09-01

To describe the optical coherence tomography angiography (OCT-A) features of treatment-naïve quiescent choroidal neovascularization (CNV) secondary to age-related macular degeneration, and to estimate the detection rate for neovascularization by means of OCT-A. Diagnostic tool validity assessment. Treatment-naïve quiescent CNV were identified from a pool of patients at 2 retina referral centers. Patients underwent a complete ophthalmologic examination including fluorescein angiography, indocyanine green angiography, spectral-domain optical coherence tomography, and OCT-A. Detection rates of CNV by means of OCT-A were estimated with a second cohort of patients without CNV (negative controls). Twenty-two eyes of 20 consecutive patients with quiescent CNV were included. In 4 out of 22 eyes it was not possible to classify the CNV "shape," "core," "margin," and "location," either because the vascular network was not clearly shown (3 cases) or because it was not visible at all (1 case). CNV shape on OCT-A was rated as circular in 8 eyes and irregular in 10 eyes. CNV core was visible in 2 eyes. CNV margin was considered as well defined in 15 eyes and poorly defined in 3 eyes. CNV margin showed small loops in 9 eyes and large loops in the other 6 eyes. CNV location was foveal-sparing in 12 eyes. Sensitivity and specificity of quiescent CNV detection by OCT-A turned out to be 81.8% and 100%, respectively. OCT-A allows the clinician to noninvasively identify treatment-naïve quiescent CNV and may be considered as a useful tool to guide the frequency of return visits and, possibly, make treatment decisions. Copyright © 2016 Elsevier Inc. All rights reserved.

Grandmothers, fathers and depressive symptoms are associated with food insecurity among low income first-time African-American mothers in North Carolina

PubMed Central

Laraia, Barbara A.; Borja, Judith B.; Bentley, Margaret E.

2009-01-01

African Americans experience household food insecurity—the limited availability of nutritionally adequate and safe food, or ability to acquire acceptable foods in socially acceptable ways—at three times the rate of non-Hispanic whites. Thirty percent of all African American children live in food insecurity households. The purpose of this study was to identify characteristics associated with household food insecurity among a high risk postpartum population. 206 low-income, African-American mother-infant dyads were recruited through WIC clinics. The six-item USDA food security scale was used to classify households as food secure, marginally food secure or food insecure. Multinomial logistic regression was used to estimate the association between selected maternal/household characteristics and household food security status. Fifty-three percent of households were food secure, 34% were marginally food secure and 13% were food insecure. Maternal education less than college (Relative Risk Ratio = 0.46, 95% Confidence Interval: 0.22, 0.98) was inversely associated with marginal food security. Depressive symptoms (RRR = 1.09, 95% CI: 1.02, 1.16) and having the baby’s father in the household (RRR = 3.46, 95% CI: 1.22, 9.82) were associated with household food insecurity, while having a grandmother in the household (RRR = 0.15, 95% CI: 0.03, 0.80) was inversely associated with experiencing household food insecurity. Findings from this study suggest that young low-income African American families with only one child are particularly susceptible to experiencing household food insecurity. Intergenerational support and transfer of knowledge may be a key protective attribute among low-income African American households. PMID:19465186

Nitrogen dynamics in corn and switchgrass production influenced by soils of varying depths in central Missouri

USDA-ARS?s Scientific Manuscript database

Sustainable biomass feedstock production systems involve biomass generation from non-agricultural or marginal lands with minimal external inputs. Switch grass based alley cropping systems have been proposed as biomass feedstock crop systems in marginal lands. In many areas in the Midwest United Stat...

Nitrogen uptake by corn and switchgrass plants in soils of varying depths in Central Missouri

USDA-ARS?s Scientific Manuscript database

Sustainable biomass feedstock production systems involve biomass generation from non-agricultural or marginal lands with minimal external inputs. Switchgrass based alley cropping systems have been proposed as biomass feedstock crop systems in marginal lands. In many areas in the Midwest United State...

Control of hyper-extended passive margin architecture on subduction initiation with application to the Alps and present-day North Atlantic ocean

NASA Astrophysics Data System (ADS)

Candioti, Lorenzo; Bauville, Arthur; Picazo, Suzanne; Mohn, Geoffroy; Kaus, Boris

2016-04-01

Hyper-extended magma-poor margins are characterized by extremely thinned crust and partially serpentinized mantle exhumation. As this can act as a zone of weakness during a subsequent compression event, a hyper-extended margin can thus potentially facilitate subduction initiation. Hyper-extended margins are also found today as passive margins fringing the Atlantic and North Atlantic ocean, e.g. Iberia and New Foundland margins [1] and Porcupine, Rockwall and Hatton basins. It has been proposed in the literature that hyper-extension in the Alpine Tethys does not exceed ~600 km in width [2]. The geodynamical evolution of the Alpine and Atlantic passive margins are distinct: no subduction is yet initiated in the North Atlantic, whereas the Alpine Tethys basin has undergone subduction. Here, we investigate the control of the presence of a hyper-extended margin on subduction initiation. We perform high resolution 2D simulations considering realistic rheologies and temperature profiles for these locations. We systematically vary the length and thickness of the hyper-extended crust and serpentinized mantle, to better understand the conditions for subduction initiation. References: [1] G. Manatschal. New models for evolution of magma-poor rifted margins based on a review of data and concepts from West Iberia and the Alps. Int J Earth Sci (Geol Rundsch) (2004); 432-466. [2] G. Mohn, G. Manatschal, M. Beltrando, I. Haupert. The role of rift-inherited hyper-extension in alpine-type orogens. Terra Nova (2014); 347-353.

Society of Surgical Oncology–American Society for Radiation Oncology Consensus Guideline on Margins for Breast-Conserving Surgery With Whole-Breast Irradiation in Stages I and II Invasive Breast Cancer

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

Moran, Meena S.; Schnitt, Stuart J.; Giuliano, Armando E.

Purpose: To convene a multidisciplinary panel of breast experts to examine the relationship between margin width and ipsilateral breast tumor recurrence (IBTR) and develop a guideline for defining adequate margins in the setting of breast conserving surgery and adjuvant radiation therapy. Methods and Materials: A multidisciplinary consensus panel used a meta-analysis of margin width and IBTR from a systematic review of 33 studies including 28,162 patients as the primary evidence base for consensus. Results: Positive margins (ink on invasive carcinoma or ductal carcinoma in situ) are associated with a 2-fold increase in the risk of IBTR compared with negative margins.more » This increased risk is not mitigated by favorable biology, endocrine therapy, or a radiation boost. More widely clear margins than no ink on tumor do not significantly decrease the rate of IBTR compared with no ink on tumor. There is no evidence that more widely clear margins reduce IBTR for young patients or for those with unfavorable biology, lobular cancers, or cancers with an extensive intraductal component. Conclusions: The use of no ink on tumor as the standard for an adequate margin in invasive cancer in the era of multidisciplinary therapy is associated with low rates of IBTR and has the potential to decrease re-excision rates, improve cosmetic outcomes, and decrease health care costs.« less

Hypoxic ischemic encephalopathy in newborns linked to placental and umbilical cord abnormalities.

PubMed

Nasiell, Josefine; Papadogiannakis, Nikos; Löf, Erika; Elofsson, Fanny; Hallberg, Boubou

2016-03-01

Birth asphyxia and hypoxic ischemic encephalopathy (HIE) of the newborn remain serious complications. We present a study investigating if placental or umbilical cord abnormalities in newborns at term are associated with HIE. A prospective cohort study of the placenta and umbilical cord of infants treated with hypothermia (HT) due to hypoxic brain injury and follow-up at 12 months of age has been carried out. The study population included 41 infants treated for HT whose placentas were submitted for histopathological analysis. Main outcome measures were infant development at 12 months, classified as normal, cerebral palsy, or death. A healthy group of 100 infants without HIE and normal follow-up at 12 months of age were used as controls. A velamentous or marginal umbilical cord insertion and histological abruption was associated with the risk of severe HIE, OR = 5.63, p = 0.006, respectively, OR = 20.3, p = 0.01 (multiple-logistic regression). Velamentous or marginal umbilical cord insertion was found in 39% among HIE cases compared to 7% in controls. Placental and umbilical cord abnormalities have a profound association with HIE. A prompt examination of the placentas of newborns suffering from asphyxia can provide important information on the pathogenesis behind the incident and contribute to make a better early prognosis.

Correlation between Resection Margin and Disease Recurrence with a Restricted Cubic Spline Model in Patients with Resected Hepatocellular Carcinoma.

PubMed

Lee, Woohyung; Han, Ho-Seong; Ahn, Soyeon; Yoon, Yoo-Seok; Cho, Jai Young; Choi, YoungRok

2018-01-17

The relationship between resection margin (RM) and recurrence of resected hepatocellular carcinoma (HCC) is unclear. We reviewed clinical data for 419 patients with HCC. The oncologic outcomes were compared between 2 groups of patients classified according to the inflexion point of the restricted cubic spline plot. The patients were divided according to an RM of <1 cm (n = 233; narrow RM group) or ≥1 cm (n = 186; wide RM group). The 5-year recurrence-free survival (RFS) rate was lower (34.8 vs. 43.8%, p = 0.042) and recurrence near the resection site was more frequent (4.7 vs. 0%, p = 0.010) in the narrow RM group. Patients with multiple lesions, or prior transarterial chemoembolization (TACE) or radiofrequency ablation (RFA) were excluded from subgroup analyses. In patients with a 2-5 cm HCC, the 5-year RFS was greater in the wide RM group (54.4 vs. 32.5%, p = 0.036). Narrow RM (hazard ratio 1.750, 95% CI 1.029-2.976, p = 0.039) was independently associated with disease recurrence. In patients with a single 2-5 cm HCC without prior TACE/RFA, an RM of ≥1 cm was associated with lower risk of recurrence after liver resection. © 2018 S. Karger AG, Basel.