Sample records for randomly selected classes

  1. Group Counseling With Emotionally Disturbed School Children in Taiwan.

    ERIC Educational Resources Information Center

    Chiu, Peter

    The application of group counseling to emotionally disturbed school children in Chinese culture was examined. Two junior high schools located in Tao-Yuan Province were randomly selected with two eighth-grade classes randomly selected from each school. Ten emotionally disturbed students were chosen from each class and randomly assigned to two…

  2. Attenders versus Slackers: A Classroom Demonstration of Quasi-Experimentation and Self-Selecting Samples

    ERIC Educational Resources Information Center

    Stellmack, Mark A.

    2013-01-01

    Studies of the effects of class attendance on class performance typically are quasi-experimental because students choose whether or not to attend class; that is, the samples are self-selecting. The lack of random assignment prevents one from establishing a causal relationship between attendance and performance. Relating attendance to performance…

  3. Effects of Teaching a Library Usage Unit to Seventh Graders.

    ERIC Educational Resources Information Center

    Gifford, Vernon; Gifford, Jean

    This document reports the results of a study undertaken to determine if teaching a 2-week unit on library usage to 7th graders would increase their use of the library. From three non-ability grouped 7th grade classes, two classes of 26 students each were randomly selected for the study. One class was randomly assigned as the experimental group and…

  4. Varying levels of difficulty index of skills-test items randomly selected by examinees on the Korean emergency medical technician licensing examination.

    PubMed

    Koh, Bongyeun; Hong, Sunggi; Kim, Soon-Sim; Hyun, Jin-Sook; Baek, Milye; Moon, Jundong; Kwon, Hayran; Kim, Gyoungyong; Min, Seonggi; Kang, Gu-Hyun

    2016-01-01

    The goal of this study was to characterize the difficulty index of the items in the skills test components of the class I and II Korean emergency medical technician licensing examination (KEMTLE), which requires examinees to select items randomly. The results of 1,309 class I KEMTLE examinations and 1,801 class II KEMTLE examinations in 2013 were subjected to analysis. Items from the basic and advanced skills test sections of the KEMTLE were compared to determine whether some were significantly more difficult than others. In the class I KEMTLE, all 4 of the items on the basic skills test showed significant variation in difficulty index (P<0.01), as well as 4 of the 5 items on the advanced skills test (P<0.05). In the class II KEMTLE, 4 of the 5 items on the basic skills test showed significantly different difficulty index (P<0.01), as well as all 3 of the advanced skills test items (P<0.01). In the skills test components of the class I and II KEMTLE, the procedure in which examinees randomly select questions should be revised to require examinees to respond to a set of fixed items in order to improve the reliability of the national licensing examination.

  5. Varying levels of difficulty index of skills-test items randomly selected by examinees on the Korean emergency medical technician licensing examination

    PubMed Central

    2016-01-01

    Purpose: The goal of this study was to characterize the difficulty index of the items in the skills test components of the class I and II Korean emergency medical technician licensing examination (KEMTLE), which requires examinees to select items randomly. Methods: The results of 1,309 class I KEMTLE examinations and 1,801 class II KEMTLE examinations in 2013 were subjected to analysis. Items from the basic and advanced skills test sections of the KEMTLE were compared to determine whether some were significantly more difficult than others. Results: In the class I KEMTLE, all 4 of the items on the basic skills test showed significant variation in difficulty index (P<0.01), as well as 4 of the 5 items on the advanced skills test (P<0.05). In the class II KEMTLE, 4 of the 5 items on the basic skills test showed significantly different difficulty index (P<0.01), as well as all 3 of the advanced skills test items (P<0.01). Conclusion: In the skills test components of the class I and II KEMTLE, the procedure in which examinees randomly select questions should be revised to require examinees to respond to a set of fixed items in order to improve the reliability of the national licensing examination. PMID:26883810

  6. Education for Parenthood: Eighth Graders Change Child Rearing Attitudes.

    ERIC Educational Resources Information Center

    Richett, Diana; Towns, Kathryn

    This study examined the effects of an Education for Parenthood Program (EPP) on the childrearing attitudes of eighth grade students. Two eighth grade classes were randomly selected from five sections at a middle school in south central Pennsylvania. One of the classes (both of which were approximatley 60% male and 70% black) was randomly assigned…

  7. Comparative levels of creative ability in black and white college students.

    PubMed

    Glover, J A

    1976-03-01

    Eighty-seven black, educational psychology students from three intact, randomly selected classes at Tennessee State University were compared to ninety-four white, educational phychology students from three intact, randomly selected classes at the University of Tennessee on Torrance's Unusual Uses and Ask and Guess activities. No differences were found on the frequency of flexibility measures of either activity. No attempt was made to examine the results on this "Level II" mental ability measure on any variable except race. There were no differences based on race.

  8. Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythmia diagnosis.

    PubMed

    Ozçift, Akin

    2011-05-01

    Supervised classification algorithms are commonly used in the designing of computer-aided diagnosis systems. In this study, we present a resampling strategy based Random Forests (RF) ensemble classifier to improve diagnosis of cardiac arrhythmia. Random forests is an ensemble classifier that consists of many decision trees and outputs the class that is the mode of the class's output by individual trees. In this way, an RF ensemble classifier performs better than a single tree from classification performance point of view. In general, multiclass datasets having unbalanced distribution of sample sizes are difficult to analyze in terms of class discrimination. Cardiac arrhythmia is such a dataset that has multiple classes with small sample sizes and it is therefore adequate to test our resampling based training strategy. The dataset contains 452 samples in fourteen types of arrhythmias and eleven of these classes have sample sizes less than 15. Our diagnosis strategy consists of two parts: (i) a correlation based feature selection algorithm is used to select relevant features from cardiac arrhythmia dataset. (ii) RF machine learning algorithm is used to evaluate the performance of selected features with and without simple random sampling to evaluate the efficiency of proposed training strategy. The resultant accuracy of the classifier is found to be 90.0% and this is a quite high diagnosis performance for cardiac arrhythmia. Furthermore, three case studies, i.e., thyroid, cardiotocography and audiology, are used to benchmark the effectiveness of the proposed method. The results of experiments demonstrated the efficiency of random sampling strategy in training RF ensemble classification algorithm. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. Defining fitness in an uncertain world.

    PubMed

    Crewe, Paul; Gratwick, Richard; Grafen, Alan

    2018-04-01

    The recently elucidated definition of fitness employed by Fisher in his fundamental theorem of natural selection is combined with reproductive values as appropriately defined in the context of both random environments and continuing fluctuations in the distribution over classes in a class-structured population. We obtain astonishingly simple results, generalisations of the Price Equation and the fundamental theorem, that show natural selection acting only through the arithmetic expectation of fitness over all uncertainties, in contrast to previous studies with fluctuating demography, in which natural selection looks rather complicated. Furthermore, our setting permits each class to have its characteristic ploidy, thus covering haploidy, diploidy and haplodiploidy at the same time; and allows arbitrary classes, including continuous variables such as condition. The simplicity is achieved by focussing just on the effects of natural selection on genotype frequencies: while other causes are present in the model, and the effect of natural selection is assessed in their presence, these causes will have their own further effects on genoytpe frequencies that are not assessed here. Also, Fisher's uses of reproductive value are shown to have two ambivalences, and a new axiomatic foundation for reproductive value is endorsed. The results continue the formal darwinism project, and extend support for the individual-as-maximising-agent analogy to finite populations with random environments and fluctuating class-distributions. The model may also lead to improved ways to measure fitness in real populations.

  10. Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discovery.

    PubMed

    Crabtree, Nathaniel M; Moore, Jason H; Bowyer, John F; George, Nysia I

    2017-01-01

    A computational evolution system (CES) is a knowledge discovery engine that can identify subtle, synergistic relationships in large datasets. Pareto optimization allows CESs to balance accuracy with model complexity when evolving classifiers. Using Pareto optimization, a CES is able to identify a very small number of features while maintaining high classification accuracy. A CES can be designed for various types of data, and the user can exploit expert knowledge about the classification problem in order to improve discrimination between classes. These characteristics give CES an advantage over other classification and feature selection algorithms, particularly when the goal is to identify a small number of highly relevant, non-redundant biomarkers. Previously, CESs have been developed only for binary class datasets. In this study, we developed a multi-class CES. The multi-class CES was compared to three common feature selection and classification algorithms: support vector machine (SVM), random k-nearest neighbor (RKNN), and random forest (RF). The algorithms were evaluated on three distinct multi-class RNA sequencing datasets. The comparison criteria were run-time, classification accuracy, number of selected features, and stability of selected feature set (as measured by the Tanimoto distance). The performance of each algorithm was data-dependent. CES performed best on the dataset with the smallest sample size, indicating that CES has a unique advantage since the accuracy of most classification methods suffer when sample size is small. The multi-class extension of CES increases the appeal of its application to complex, multi-class datasets in order to identify important biomarkers and features.

  11. Correlations between Learners' Initial EFL Proficiency and Variables of Clicker-Aided Flipped EFL Class

    ERIC Educational Resources Information Center

    Yu, Zhonggen; Yu, Liheng

    2017-01-01

    Although the flipped class has been hotly discussed, the clicker-aided flipped EFL class (CFEC) still remains a mystery for most scholars. This study aims to determine the correlations between the initial EFL proficiency and other variables of the clicker-aided EFL flipped class. The sample was made up of randomly selected 79 participants (Female…

  12. Balancing Participation across Students in Large College Classes via Randomized Participation Credit

    ERIC Educational Resources Information Center

    McCleary, Daniel F.; Aspiranti, Kathleen B.; Foster, Lisa N.; Blondin, Carolyn A.; Gaylon, Charles E.; Yaw, Jared S.; Forbes, Bethany N.; Williams, Robert L.

    2011-01-01

    The study examines the effects of randomized credit on the percentage of students participating at four predefined levels. Students recorded their comments on specially designed record cards, and days were randomly selected for participation credit. This arrangement balanced participation across students while cutting instructor time for recording…

  13. Obstacles of Teaching Mathematics Faced by the Class Teachers in Jordan

    ERIC Educational Resources Information Center

    Nejem, Khamis Mousa; Muhanna, Waffa

    2013-01-01

    The purpose of the study is to investigate the obstacles of teaching mathematics faced by the class teachers in Jordan. To achieve this purpose a study sample of 192 male and female class teachers was selected randomly from government schools. The instrument of the study was a questionnaire used to investigate the obstacles of mathematics…

  14. Teaching Semantic Prosody of English Verbs through the DDL Approach and Its Effect on Learners' Vocabulary Choice Appropriateness in a Persian EFL Context

    ERIC Educational Resources Information Center

    Mansoory, Niloofar; Jafarpour, Mohsen

    2014-01-01

    This study examined teaching SP of English verbs through the data-driven learning (DDL) approach and its effect on learners' vocabulary choice appropriateness in the Persian English foreign language (EFL) context. In the present study, two male intact classes were selected. One of these two classes was randomly selected as a treatment group and…

  15. Group Random Call Can Positively Affect Student In-Class Clicker Discussions

    PubMed Central

    Knight, Jennifer K.; Wise, Sarah B.; Sieke, Scott

    2016-01-01

    Understanding how instructional techniques and classroom norms influence in-class student interactions has the potential to positively impact student learning. Many previous studies have shown that students benefit from discussing their ideas with one another in class. In this study of introductory biology students, we explored how using an in-class accountability system might affect the nature of clicker-question discussions. Clicker-question discussions in which student groups were asked to report their ideas voluntarily (volunteer call) were compared with discussions in which student groups were randomly selected to report their ideas (random call). We hypothesized that the higher-accountability condition (random call) would impress upon students the importance of their discussions and thus positively influence how they interacted. Our results suggest that a higher proportion of discussions in the random call condition contained exchanges of reasoning, some forms of questioning, and both on- and off-topic comments compared with discussion in the volunteer call condition. Although group random call does not impact student performance on clicker questions, the positive impact of this instructional approach on exchanges of reasoning and other features suggests it may encourage some types of student interactions that support learning. PMID:27856544

  16. Teacher Aides, Class Size and Academic Achievement: A Preliminary Evaluation of Indiana's Prime Time.

    ERIC Educational Resources Information Center

    Lapsley, Daniel K.; Daytner, Katrina M.; Kelly, Ken; Maxwell, Scott E.

    This large-scale evaluation of Indiana's Prime Time, a funding mechanism designed to reduce class size or pupil-teacher ratio (PTR) in grades K-3 examined the academic performance of nearly 11,000 randomly selected third graders on the state mandated standardized achievement test as a function of class size, PTR, and presence of an instructional…

  17. Influence of Problem Based Learning on Critical Thinking Skills and Competence Class VIII SMPN 1 Gunuang Omeh, 2016/2017

    NASA Astrophysics Data System (ADS)

    Aswan, D. M.; Lufri, L.; Sumarmin, R.

    2018-04-01

    This research intends to determine the effect of Problem Based Learning models on students' critical thinking skills and competences. This study was a quasi-experimental research. The population of the study was the students of class VIII SMPN 1 Subdistrict Gunuang Omeh. Random sample selection is done by randomizing the class. Sample class that was chosen VIII3 as an experimental class given that treatment study based on problems and class VIII1 as control class that treatment usually given study. Instrument that used to consist of critical thinking test, cognitive tests, observation sheet of affective and psychomotor. Independent t-test and Mann Whitney U test was used for the analysis. Results showed that there was significant difference (sig <0.05) between control and experimental group. The conclusion of this study was Problem Based Learning models affected the students’ critical thinking skills and competences.

  18. CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes.

    PubMed

    White, Clarence; Ismail, Hamid D; Saigo, Hiroto; Kc, Dukka B

    2017-12-28

    The β-Lactamase (BL) enzyme family is an important class of enzymes that plays a key role in bacterial resistance to antibiotics. As the newly identified number of BL enzymes is increasing daily, it is imperative to develop a computational tool to classify the newly identified BL enzymes into one of its classes. There are two types of classification of BL enzymes: Molecular Classification and Functional Classification. Existing computational methods only address Molecular Classification and the performance of these existing methods is unsatisfactory. We addressed the unsatisfactory performance of the existing methods by implementing a Deep Learning approach called Convolutional Neural Network (CNN). We developed CNN-BLPred, an approach for the classification of BL proteins. The CNN-BLPred uses Gradient Boosted Feature Selection (GBFS) in order to select the ideal feature set for each BL classification. Based on the rigorous benchmarking of CCN-BLPred using both leave-one-out cross-validation and independent test sets, CCN-BLPred performed better than the other existing algorithms. Compared with other architectures of CNN, Recurrent Neural Network, and Random Forest, the simple CNN architecture with only one convolutional layer performs the best. After feature extraction, we were able to remove ~95% of the 10,912 features using Gradient Boosted Trees. During 10-fold cross validation, we increased the accuracy of the classic BL predictions by 7%. We also increased the accuracy of Class A, Class B, Class C, and Class D performance by an average of 25.64%. The independent test results followed a similar trend. We implemented a deep learning algorithm known as Convolutional Neural Network (CNN) to develop a classifier for BL classification. Combined with feature selection on an exhaustive feature set and using balancing method such as Random Oversampling (ROS), Random Undersampling (RUS) and Synthetic Minority Oversampling Technique (SMOTE), CNN-BLPred performs significantly better than existing algorithms for BL classification.

  19. Using Pseudozoids to Teach Classification and Phylogeny to Middle School Students

    ERIC Educational Resources Information Center

    Freidenberg, Rolfe Jr.; Kelly, Martin G.

    2004-01-01

    This research compared the outcomes of teaching middle school students two different methods of classification and phylogeny. Two classes were randomly selected and taught using traditional methods of instruction. Three classes were taught using the "Pseudozoid" approach, where students learned to classify, develop and read dichotomous keys, and…

  20. A Fitness Intervention Program within a Physical Education Class on Cardiovascular Endurance among Malaysia Secondary School Students

    ERIC Educational Resources Information Center

    Rengasamy, Shabeshan; Raju, Subramaniam; Lee, Wee Akina Sia Seng; Roa, Ramachandran

    2014-01-01

    The aim of the study was to investigate the effect of a physical fitness intervention program within a physical education class on cardiovascular endurance of Malaysian secondary school boys and girls. A quasi experimental design was adopted for the study. Two schools in a district were randomly selected. In each school, two classes were randomly…

  1. Topology-selective jamming of fully-connected, code-division random-access networks

    NASA Technical Reports Server (NTRS)

    Polydoros, Andreas; Cheng, Unjeng

    1990-01-01

    The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.

  2. The Coalescent Process in Models with Selection

    PubMed Central

    Kaplan, N. L.; Darden, T.; Hudson, R. R.

    1988-01-01

    Statistical properties of the process describing the genealogical history of a random sample of genes are obtained for a class of population genetics models with selection. For models with selection, in contrast to models without selection, the distribution of this process, the coalescent process, depends on the distribution of the frequencies of alleles in the ancestral generations. If the ancestral frequency process can be approximated by a diffusion, then the mean and the variance of the number of segregating sites due to selectively neutral mutations in random samples can be numerically calculated. The calculations are greatly simplified if the frequencies of the alleles are tightly regulated. If the mutation rates between alleles maintained by balancing selection are low, then the number of selectively neutral segregating sites in a random sample of genes is expected to substantially exceed the number predicted under a neutral model. PMID:3066685

  3. ORAL DRILLS AND WRITING IMPROVEMENT IN THE FOURTH GRADE.

    ERIC Educational Resources Information Center

    MILLER, BARBARA D.; NEY, JAMES W.

    BELIEVING FORMAL WRITTEN ENGLISH TO BE A "FOREIGN LANGUAGE" TO MOST AMERICAN PUBLIC SCHOOL STUDENTS, RESEARCHERS USED THE AUDIO-LINGUAL METHOD OF FOREIGN LANGUAGE INSTRUCTION TO PROMOTE WRITING IMPROVEMENT IN FOURTH-GRADERS. TWO RANDOMLY-SELECTED CLASSES OF STUDENTS OF AVERAGE ABILITY COMPOSED THE STUDY POPULATION--ONE CLASS FOR THE EXPERIMENT,…

  4. A Feasibility Study to Determine the Possibility of Teaching Freshman Composition and Rhetoric with a Programmed Text. Final Report.

    ERIC Educational Resources Information Center

    Lutz, William D.

    The question of whether a significant amount of time could be saved if freshman composition were taught with a programed text was studied. Two sections of English I were randomly selected from the regular class schedule. Class A was taught using the usual syllabus and texts. Class B was taught using the same syllabus and texts with one exception.…

  5. Development of Multiple Regression Equations To Predict Fourth Graders' Achievement in Reading and Selected Content Areas.

    ERIC Educational Resources Information Center

    Hafner, Lawrence E.

    A study developed a multiple regression prediction equation for each of six selected achievement variables in a popular standardized test of achievement. Subjects, 42 fourth-grade pupils randomly selected across several classes in a large elementary school in a north Florida city, were administered several standardized tests to determine predictor…

  6. A Controlled Trial of Teaching Clinical Biochemistry by the Keller Plan.

    ERIC Educational Resources Information Center

    Schwartz, Peter L.

    1980-01-01

    Thirty medical students at the University of Otago were randomly chosen to learn clinical biochemistry by the Keller Plan. The rest of the class acted as controls. The randomly selected Keller group scored significantly higher than the control group on a practice/review test and the final examination. (Author/MLW)

  7. Towards an Analysis of Review Article in Applied Linguistics: Its Classes, Purposes and Characteristics

    ERIC Educational Resources Information Center

    Azar, Ali Sorayyaei; Hashim, Azirah

    2014-01-01

    The classes, purposes and characteristics associated with the review article in the field of applied linguistics were analyzed. The data were collected from a randomly selected corpus of thirty two review articles from a discipline-related key journal in applied linguistics. The findings revealed that different sub-genres can be identified within…

  8. Implementation of Structured Inquiry Based Model Learning toward Students' Understanding of Geometry

    ERIC Educational Resources Information Center

    Salim, Kalbin; Tiawa, Dayang Hjh

    2015-01-01

    The purpose of this study is implementation of a structured inquiry learning model in instruction of geometry. The model used is a model with a quasi-experimental study amounted to two classes of samples selected from the population of the ten classes with cluster random sampling technique. Data collection tool consists of a test item…

  9. Analysis of creative mathematic thinking ability in problem based learning model based on self-regulation learning

    NASA Astrophysics Data System (ADS)

    Munahefi, D. N.; Waluya, S. B.; Rochmad

    2018-03-01

    The purpose of this research identified the effectiveness of Problem Based Learning (PBL) models based on Self Regulation Leaning (SRL) on the ability of mathematical creative thinking and analyzed the ability of mathematical creative thinking of high school students in solving mathematical problems. The population of this study was students of grade X SMA N 3 Klaten. The research method used in this research was sequential explanatory. Quantitative stages with simple random sampling technique, where two classes were selected randomly as experimental class was taught with the PBL model based on SRL and control class was taught with expository model. The selection of samples at the qualitative stage was non-probability sampling technique in which each selected 3 students were high, medium, and low academic levels. PBL model with SRL approach effectived to students’ mathematical creative thinking ability. The ability of mathematical creative thinking of low academic level students with PBL model approach of SRL were achieving the aspect of fluency and flexibility. Students of academic level were achieving fluency and flexibility aspects well. But the originality of students at the academic level was not yet well structured. Students of high academic level could reach the aspect of originality.

  10. Bridging the Gap: A Longitudinal Study of the Relationship between Pedagogical Continuity and Early Chinese Literacy Acquisition

    ERIC Educational Resources Information Center

    Li, Hui; Rao, Nirmala; Tse, Shek Kam

    2011-01-01

    This longitudinal study examined the relationship between pedagogical continuity in literacy education and early literacy development by comparing Chinese children in Hong Kong and Shenzhen. Stratified random sampling was used to select 24 preschool and Primary 1 classes in four communities catering to middle-class families in each city. The 24…

  11. Quality of human spermatozoa: relationship between high-magnification sperm morphology and DNA integrity.

    PubMed

    Maettner, R; Sterzik, K; Isachenko, V; Strehler, E; Rahimi, G; Alabart, J L; Sánchez, R; Mallmann, P; Isachenko, E

    2014-06-01

    The aim of this work is to establish the relationship between the morphology of Intracytoplasmic Morphologically Selected Sperm Injection (IMSI)-selected spermatozoa and their DNA integrity. The 45 ejaculates were randomly distributed into three treatment groups: normozoospermic, oligoasthenozoospermic and oligoasthenotheratozoospermic samples. The evaluation of DNA integrity was performed using the sperm chromatin dispersion test. It was established that DNA integrity of spermatozoa is strongly dependent on ejaculate quality (P < 0.05). The count of spermatozoa with nonfragmented DNA in normozoospermic samples was high and independent from IMSI-morphological classes (Class 1 versus Class 3, respectively) (P > 0.1). With decreased ejaculate quality, the percentage of spermatozoa with nonfragmented DNA decreased significantly (P < 0.05) independent from morphological class. Nevertheless, the rate of IMSI-selected spermatozoa with fragmented DNA within of Class 1 in normozoospermic (Group 1), in oligoasthenozoospermic (Group 2) and in oligoasthenotheratozoospermic (Group 3) samples was 21.1%, 31.8% and 54.1%, respectively. In conclusion, there is a direct relationship between morphological parameters of spermatozoa and their DNA integrity. However, the IMSI technique alone is not enough for the selection of spermatozoa with intact nuclei. © 2013 Blackwell Verlag GmbH.

  12. Ground sample data for the Conterminous U.S. Land Cover Characteristics Database

    Treesearch

    Robert Burgan; Colin Hardy; Donald Ohlen; Gene Fosnight; Robert Treder

    1999-01-01

    Ground sample data were collected for a land cover database and raster map that portray 159 vegetation classes at 1 km2 resolution for the conterminous United States. Locations for 3,500 1 km2 ground sample plots were selected randomly across the United States. The number of plots representing each vegetation class was weighted by the proportionate coverage of each...

  13. Information Assurance in Sensor Networks

    DTIC Science & Technology

    2009-09-15

    minority class instance and a randomly selected neighbor. Expanding on the SMOTE framework, the Borderline -SMOTE algorithm [15] locates those minority...instances form a Tomek link then they either both reside on the borderline of the two classes or one of them is attributed to noise; therefore, by...the synthetic dataset to testify the effectiveness of our proposed algorithm. Despite the popularity of STAGGER [76] and the SEA [77] synthetic

  14. Measuring CAMD technique performance. 2. How "druglike" are drugs? Implications of Random test set selection exemplified using druglikeness classification models.

    PubMed

    Good, Andrew C; Hermsmeier, Mark A

    2007-01-01

    Research into the advancement of computer-aided molecular design (CAMD) has a tendency to focus on the discipline of algorithm development. Such efforts are often wrought to the detriment of the data set selection and analysis used in said algorithm validation. Here we highlight the potential problems this can cause in the context of druglikeness classification. More rigorous efforts are applied to the selection of decoy (nondruglike) molecules from the ACD. Comparisons are made between model performance using the standard technique of random test set creation with test sets derived from explicit ontological separation by drug class. The dangers of viewing druglike space as sufficiently coherent to permit simple classification are highlighted. In addition the issues inherent in applying unfiltered data and random test set selection to (Q)SAR models utilizing large and supposedly heterogeneous databases are discussed.

  15. Sex-role patterns, paternal rearing attitudes and child development in different social classes.

    PubMed

    Nettelbladt, P; Uddenberg, N; Englesson, I

    1981-07-01

    Sex-role patterns, the father's rearing attitude and the child's intellectual and emotional development in different social classes were studied in a randomly selected sample of 58 Swedish unbroken families of a small child. Working class men and women married younger and the women were more often house-wives. Working class men had more often been reared in an "authoritarian" way and more often reared their children in the same way. Upper middle class men had taken a more active part in the care of the child. Working class children scored lower on the intelligence tests, especially the verbal ones and were more often estimated as socially immature.

  16. Effects of Computer-Assisted Instruction on Performance of Senior High School Biology Students in Ghana

    ERIC Educational Resources Information Center

    Owusu, K. A.; Monney, K. A.; Appiah, J. Y.; Wilmot, E. M.

    2010-01-01

    This study investigated the comparative efficiency of computer-assisted instruction (CAI) and conventional teaching method in biology on senior high school students. A science class was selected in each of two randomly selected schools. The pretest-posttest non equivalent quasi experimental design was used. The students in the experimental group…

  17. Self Assessment and Student-Centred Learning

    ERIC Educational Resources Information Center

    McDonald, Betty

    2012-01-01

    This paper seeks to show how self assessment facilitates student-centred learning (SCL) and fills a gap in the literature. Two groups of students were selected from a single class in a tertiary educational institution. The control group of 25 was selected randomly by the tossing of an unbiased coin (heads = control group). They were trained in the…

  18. My Body and Its Reflection: A Case Study of Eight Dance Students and the Mirror in the Ballet Classroom

    ERIC Educational Resources Information Center

    Radell, Sally Anne; Keneman, Margaret Lynn; Adame, Daniel D.; Cole, Steven P.

    2014-01-01

    This qualitative study investigated the impact of the mirror on a dancer's body image. Two groups of students enrolled in beginner ballet classes were taught the same classroom material; one group was taught with mirrors, the other, without. At the end of the semester four students from each class were randomly selected to participate in a private…

  19. Effectiveness of Conceptual Change Text-Oriented Instruction on Students' Understanding of Energy in Chemical Reactions

    ERIC Educational Resources Information Center

    Tastan, Ozgecan; Yalcinkaya, Eylem; Boz, Yezdan

    2008-01-01

    The aim of this study is to compare the effectiveness of conceptual change text instruction (CCT) in the context of energy in chemical reactions. The subjects of the study were 60, 10th grade students at a high school, who were in two different classes and taught by the same teacher. One of the classes was randomly selected as the experimental…

  20. The genealogy of sequences containing multiple sites subject to strong selection in a subdivided population.

    PubMed Central

    Nordborg, Magnus; Innan, Hideki

    2003-01-01

    A stochastic model for the genealogy of a sample of recombining sequences containing one or more sites subject to selection in a subdivided population is described. Selection is incorporated by dividing the population into allelic classes and then conditioning on the past sizes of these classes. The past allele frequencies at the selected sites are thus treated as parameters rather than as random variables. The purpose of the model is not to investigate the dynamics of selection, but to investigate effects of linkage to the selected sites on the genealogy of the surrounding chromosomal region. This approach is useful for modeling strong selection, when it is natural to parameterize the past allele frequencies at the selected sites. Several models of strong balancing selection are used as examples, and the effects on the pattern of neutral polymorphism in the chromosomal region are discussed. We focus in particular on the statistical power to detect balancing selection when it is present. PMID:12663556

  1. The genealogy of sequences containing multiple sites subject to strong selection in a subdivided population.

    PubMed

    Nordborg, Magnus; Innan, Hideki

    2003-03-01

    A stochastic model for the genealogy of a sample of recombining sequences containing one or more sites subject to selection in a subdivided population is described. Selection is incorporated by dividing the population into allelic classes and then conditioning on the past sizes of these classes. The past allele frequencies at the selected sites are thus treated as parameters rather than as random variables. The purpose of the model is not to investigate the dynamics of selection, but to investigate effects of linkage to the selected sites on the genealogy of the surrounding chromosomal region. This approach is useful for modeling strong selection, when it is natural to parameterize the past allele frequencies at the selected sites. Several models of strong balancing selection are used as examples, and the effects on the pattern of neutral polymorphism in the chromosomal region are discussed. We focus in particular on the statistical power to detect balancing selection when it is present.

  2. Effect of Multi Modal Representations on the Critical Thinking Skills of the Fifth Grade Students

    ERIC Educational Resources Information Center

    Öz, Muhittin; Memis, Esra Kabatas

    2018-01-01

    The purpose of this study was to explore the effects of multi modal representations within writing to learn activities on students' critical thinking. Mixed method was used. The participants included 32 students 5th grade from elementary school. The groups were randomly selected as a control group and the other class was selected as the…

  3. Group Random Call Can Positively Affect Student In-Class Clicker Discussions.

    PubMed

    Knight, Jennifer K; Wise, Sarah B; Sieke, Scott

    2016-01-01

    Understanding how instructional techniques and classroom norms influence in-class student interactions has the potential to positively impact student learning. Many previous studies have shown that students benefit from discussing their ideas with one another in class. In this study of introductory biology students, we explored how using an in-class accountability system might affect the nature of clicker-question discussions. Clicker-question discussions in which student groups were asked to report their ideas voluntarily (volunteer call) were compared with discussions in which student groups were randomly selected to report their ideas (random call). We hypothesized that the higher-accountability condition (random call) would impress upon students the importance of their discussions and thus positively influence how they interacted. Our results suggest that a higher proportion of discussions in the random call condition contained exchanges of reasoning, some forms of questioning, and both on- and off-topic comments compared with discussion in the volunteer call condition. Although group random call does not impact student performance on clicker questions, the positive impact of this instructional approach on exchanges of reasoning and other features suggests it may encourage some types of student interactions that support learning. © 2016 J. K. Knight et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  4. Social space, social class and Bourdieu: health inequalities in British Columbia, Canada.

    PubMed

    Veenstra, Gerry

    2007-03-01

    This article adopts Pierre Bourdieu's cultural-structuralist approach to conceptualizing and identifying social classes in social space and seeks to identify health effects of class in one Canadian province. Utilizing data from an original questionnaire survey of randomly selected adults from 25 communities in British Columbia, social (class) groupings defined by cultural tastes and dispositions, lifestyle practices, social background, educational capital, economic capital, social capital and occupational categories are presented in visual mappings of social space constructed by use of exploratory multiple correspondence analysis techniques. Indicators of physical and mental health are then situated within this social space, enabling speculations pertaining to health effects of social class in British Columbia.

  5. Testing mate choice and overdominance at MH in natural families of Atlantic salmon Salmo salar.

    PubMed

    Tentelier, C; Barroso-Gomila, O; Lepais, O; Manicki, A; Romero-Garmendia, I; Jugo, B M

    2017-04-01

    This study aimed to test mate choice and selection during early life stages on major histocompatibility (MH) genotype in natural families of Atlantic salmon Salmo salar spawners and juveniles, using nine microsatellites to reconstruct families, one microsatellite linked to an MH class I gene and one minisatellite linked to an MH class II gene. MH-based mate choice was only detected for the class I locus on the first year, with lower expected heterozygosity in the offspring of actually mated pairs than predicted under random mating. The genotype frequencies of MH-linked loci observed in the juveniles were compared with frequencies expected from Mendelian inheritance of parental alleles to detect selection during early life stages. No selection was detected on the locus linked to class I gene. For the locus linked to class II gene, observed heterozygosity was higher than expected in the first year and lower in the second year, suggesting overdominance and underdominance, respectively. Within family, juveniles' body size was linked to heterozygosity at the same locus, with longer heterozygotes in the first year and longer homozygotes in the second year. Selection therefore seems to differ from one locus to the other and from year to year. © 2017 The Fisheries Society of the British Isles.

  6. Gain in Student Understanding of the Role of Random Variation in Evolution Following Teaching Intervention Based on Luria-Delbruck Experiment†

    PubMed Central

    Robson, Rachel L.; Burns, Susan

    2011-01-01

    Undergraduate students in introductory biology classes are typically saddled with pre-existing popular beliefs that impede their ability to learn about biological evolution. One of the most common misconceptions about evolution is that the environment causes advantageous mutations, rather than the correct view that mutations occur randomly and the environment only selects for mutants with advantageous traits. In this study, a significant gain in student understanding of the role of randomness in evolution was observed after students participated in an inquiry-based pedagogical intervention based on the Luria-Delbruck experiment. Questionnaires with isomorphic questions regarding environmental selection among random mutants were administered to study participants (N = 82) in five separate sections of a sophomore-level microbiology class before and after the teaching intervention. Demographic data on each participant was also collected, in a way that preserved anonymity. Repeated measures analysis showed that post-test scores were significantly higher than pre-test scores with regard to the questions about evolution (F(1, 77) = 25.913, p < 0.001). Participants’ pre-existing beliefs about evolution had no significant effect on gain in understanding of this concept. This study indicates that conducting and discussing an experiment about phage resistance in E. coli may improve student understanding of the role of stochastic events in evolution more broadly, as post-test answers showed that students were able to apply the lesson of the Luria-Delbruck experiment to other organisms subjected to other kinds of selection. PMID:23653732

  7. Different hunting strategies select for different weights in red deer.

    PubMed

    Martínez, María; Rodríguez-Vigal, Carlos; Jones, Owen R; Coulson, Tim; San Miguel, Alfonso

    2005-09-22

    Much insight can be derived from records of shot animals. Most researchers using such data assume that their data represents a random sample of a particular demographic class. However, hunters typically select a non-random subset of the population and hunting is, therefore, not a random process. Here, with red deer (Cervus elaphus) hunting data from a ranch in Toledo, Spain, we demonstrate that data collection methods have a significant influence upon the apparent relationship between age and weight. We argue that a failure to correct for such methodological bias may have significant consequences for the interpretation of analyses involving weight or correlated traits such as breeding success, and urge researchers to explore methods to identify and correct for such bias in their data.

  8. Reach and effectiveness of DVD and in-person diabetes self-management education.

    PubMed

    Glasgow, Russell E; Edwards, Linda L; Whitesides, Holly; Carroll, Nikki; Sanders, Tristan J; McCray, Barbara L

    2009-12-01

    To evaluate the reach and effectiveness of a diabetes self-management DVD compared to classroom-based instruction. A hybrid preference/randomized design was used with participants assigned to Choice v. Randomized and DVD v. Class conditions. One hundred and eighty-nine adults with type 2 diabetes participated. Key outcomes included self-management behaviours, process measures including DVD implementation and hypothesized mediators and clinical risk factors. In the Choice condition, four times as many participants chose the mailed DVD as selected Class-based instruction (38.8 v. 9.4%, p<0.001). At the 6-month follow-up, the DVD produced results generally not significantly different than classroom-based instruction, but a combined Class plus DVD condition did not improve outcomes beyond those produced by the classes alone. The DVD appears to have merit as an efficient and appealing alternative to brief classroom-based diabetes education, and the hybrid design is recommended to provide estimates of programme reach.

  9. Non-urban mobile radio market demand forecast

    NASA Technical Reports Server (NTRS)

    Castruccio, P. A.; Cooper, J.

    1982-01-01

    A national nonmetropolitan land mobile traffic model for 1990-2000 addresses user classes, density classes, traffic mix statistics, distance distribution, geographic distribution, price elasticity, and service quality elasticity. Traffic demands for business, special industrial, and police were determined on the basis of surveys in 73 randomly selected nonurban counties. The selected services represent 69% of total demand. The results were extrapolated to all services in the non-SMSA areas of the contiguous United States. Radiotelephone services were considered separately. Total non-SMSA mobile radio demand (one way) estimates are given. General functional requirements include: hand portability, privacy, reduction of blind spots, two way data transmission, position location, slow scan imagery.

  10. A novel one-class SVM based negative data sampling method for reconstructing proteome-wide HTLV-human protein interaction networks.

    PubMed

    Mei, Suyu; Zhu, Hao

    2015-01-26

    Protein-protein interaction (PPI) prediction is generally treated as a problem of binary classification wherein negative data sampling is still an open problem to be addressed. The commonly used random sampling is prone to yield less representative negative data with considerable false negatives. Meanwhile rational constraints are seldom exerted on model selection to reduce the risk of false positive predictions for most of the existing computational methods. In this work, we propose a novel negative data sampling method based on one-class SVM (support vector machine, SVM) to predict proteome-wide protein interactions between HTLV retrovirus and Homo sapiens, wherein one-class SVM is used to choose reliable and representative negative data, and two-class SVM is used to yield proteome-wide outcomes as predictive feedback for rational model selection. Computational results suggest that one-class SVM is more suited to be used as negative data sampling method than two-class PPI predictor, and the predictive feedback constrained model selection helps to yield a rational predictive model that reduces the risk of false positive predictions. Some predictions have been validated by the recent literature. Lastly, gene ontology based clustering of the predicted PPI networks is conducted to provide valuable cues for the pathogenesis of HTLV retrovirus.

  11. Selection of nesting habitat by sharp-tailed grouse in the Nebraska sandhills

    USGS Publications Warehouse

    Prose, Bart L.; Cade, Brian S.; Hein, Dale

    2002-01-01

    We evaluated nesting habitat selection (disproportionate use compared to availability) by plains sharp-tailed grouse (Tympanuchus phasianellus jamesi) on rangelands grazed by cattle (Bos taurus) relative to height, density, and heterogeneity of residual herbaceous vegetation remaining from previous growing seasons. Residual cover is critical for nesting sharp-tailed grouse and can be lacking on grazed rangelands. Aerial photography and a geographic information system were used to analyze residual cover height classes and several measures of residual cover heterogeneity in nest (n = 38) and random (n = 38) plots. Height classes corresponded to visual obstruction readings (VORs), the height to which total visual obstruction by vegetation occurs. Analyses were conducted for five spatial scales ranging from 1 to 16 ha to test for scale effects on nesting habitat selection. Sharp-tailed grouse selected nesting habitat with more area in tall (greater than or equal to 4 cm VOR) residual cover than at random sites at all scales, less area in short residual cover (less than 2 cm VOR) at the I-ha scale, and less area in short and medium (2 to 3.9 cm YOR) residual cover at the 2- through 16-ha scales. Selection of shrub habitat containing patches of shrubs was evident only at the 16-ha scale. Patches of tall residual cover were larger in nest plots than in random plots at the 8- and 16-ha scales, and patches of short cover were smaller in nest plots at the I-ha scale. Two scales of pattern defined by mean patch size were detected for overall residual cover, but did not relate to nesting habitat selection.

  12. College Climate and Teacher-Trainee's Academic Work in Selected Colleges of Education in the Ashanti Region of Ghana

    ERIC Educational Resources Information Center

    Adjei, Augustine; Dontoh, Samuel; Baafi-Frimpong, Stephen

    2017-01-01

    The study aimed at investigating the extent to which College climate (Leadership roles/practices and Class size) impact on academic work of Teacher-trainees. A survey research design was used for the study because it involved a study of relatively large population who were purposively and randomly selected. A sample size of 322 out of the…

  13. The genealogy of samples in models with selection.

    PubMed

    Neuhauser, C; Krone, S M

    1997-02-01

    We introduce the genealogy of a random sample of genes taken from a large haploid population that evolves according to random reproduction with selection and mutation. Without selection, the genealogy is described by Kingman's well-known coalescent process. In the selective case, the genealogy of the sample is embedded in a graph with a coalescing and branching structure. We describe this graph, called the ancestral selection graph, and point out differences and similarities with Kingman's coalescent. We present simulations for a two-allele model with symmetric mutation in which one of the alleles has a selective advantage over the other. We find that when the allele frequencies in the population are already in equilibrium, then the genealogy does not differ much from the neutral case. This is supported by rigorous results. Furthermore, we describe the ancestral selection graph for other selective models with finitely many selection classes, such as the K-allele models, infinitely-many-alleles models. DNA sequence models, and infinitely-many-sites models, and briefly discuss the diploid case.

  14. The Genealogy of Samples in Models with Selection

    PubMed Central

    Neuhauser, C.; Krone, S. M.

    1997-01-01

    We introduce the genealogy of a random sample of genes taken from a large haploid population that evolves according to random reproduction with selection and mutation. Without selection, the genealogy is described by Kingman's well-known coalescent process. In the selective case, the genealogy of the sample is embedded in a graph with a coalescing and branching structure. We describe this graph, called the ancestral selection graph, and point out differences and similarities with Kingman's coalescent. We present simulations for a two-allele model with symmetric mutation in which one of the alleles has a selective advantage over the other. We find that when the allele frequencies in the population are already in equilibrium, then the genealogy does not differ much from the neutral case. This is supported by rigorous results. Furthermore, we describe the ancestral selection graph for other selective models with finitely many selection classes, such as the K-allele models, infinitely-many-alleles models, DNA sequence models, and infinitely-many-sites models, and briefly discuss the diploid case. PMID:9071604

  15. A mechanistic assessment of seasonal microhabitat selection by drift-feeding rainbow trout Oncorhynchus mykiss in a southwestern headwater stream

    USGS Publications Warehouse

    Kalb, Bradley W.; Huntsman, Brock M.; Caldwell, Colleen A.; Bozek, Michael A.

    2018-01-01

    The positioning of fishes within a riverscape is dependent on the proximity of complementary habitats. In this study, foraging and non-foraging habitat were quantified monthly over an entire year for a rainbow trout (Oncorhynchus mykiss) population in an isolated, headwater stream in southcentral New Mexico. The stream follows a seasonal thermal and hydrologic pattern typical for a Southwestern stream and was deemed suitable for re-introduction of the native and close relative, Rio Grande cutthroat trout (O. clarkii virginalis). However, uncertainty associated with limited habitat needed to be resolved if repatriation of the native fish was to be successful. Habitat was evaluated using resource selection functions with a mechanistic drift-foraging model to explain trout distributions. Macroinvertebrate drift was strongly season- and temperature-dependent (lower in winter and spring, higher in summer and fall). Models identified stream depth as the most limiting factor for habitat selection across seasons and size-classes. Additionally, positions closer to cover were selected during the winter by smaller size-classes (0, 1, 2), while net energy intake was important during the spring for most size-classes (0, 1, 2, 3). Drift-foraging models identified that 81% of observed trout selected positions that could meet maintenance levels throughout the year. Moreover, 40% of selected habitats could sustain maximum growth. Stream positions occupied by rainbow trout were more energetically profitable than random sites regardless of season or size-class. Larger size-classes (3, 4+) were energetically more limited throughout the year than were smaller size-classes. This research suggests that habitat in the form of deep pools is of paramount importance for rainbow trout or native cutthroat trout.

  16. Different hunting strategies select for different weights in red deer

    PubMed Central

    Martínez, María; Rodríguez-Vigal, Carlos; Jones, Owen R; Coulson, Tim; Miguel, Alfonso San

    2005-01-01

    Much insight can be derived from records of shot animals. Most researchers using such data assume that their data represents a random sample of a particular demographic class. However, hunters typically select a non-random subset of the population and hunting is, therefore, not a random process. Here, with red deer (Cervus elaphus) hunting data from a ranch in Toledo, Spain, we demonstrate that data collection methods have a significant influence upon the apparent relationship between age and weight. We argue that a failure to correct for such methodological bias may have significant consequences for the interpretation of analyses involving weight or correlated traits such as breeding success, and urge researchers to explore methods to identify and correct for such bias in their data. PMID:17148205

  17. Coupling GIS and multivariate approaches to reference site selection for wadeable stream monitoring.

    PubMed

    Collier, Kevin J; Haigh, Andy; Kelly, Johlene

    2007-04-01

    Geographic Information System (GIS) was used to identify potential reference sites for wadeable stream monitoring, and multivariate analyses were applied to test whether invertebrate communities reflected a priori spatial and stream type classifications. We identified potential reference sites in segments with unmodified vegetation cover adjacent to the stream and in >85% of the upstream catchment. We then used various landcover, amenity and environmental impact databases to eliminate sites that had potential anthropogenic influences upstream and that fell into a range of access classes. Each site identified by this process was coded by four dominant stream classes and seven zones, and 119 candidate sites were randomly selected for follow-up assessment. This process yielded 16 sites conforming to reference site criteria using a conditional-probabilistic design, and these were augmented by an additional 14 existing or special interest reference sites. Non-metric multidimensional scaling (NMS) analysis of percent abundance invertebrate data indicated significant differences in community composition among some of the zones and stream classes identified a priori providing qualified support for this framework in reference site selection. NMS analysis of a range standardised condition and diversity metrics derived from the invertebrate data indicated a core set of 26 closely related sites, and four outliers that were considered atypical of reference site conditions and subsequently dropped from the network. Use of GIS linked to stream typology, available spatial databases and aerial photography greatly enhanced the objectivity and efficiency of reference site selection. The multi-metric ordination approach reduced variability among stream types and bias associated with non-random site selection, and provided an effective way to identify representative reference sites.

  18. Modeling Teacher Beliefs and Practices in Context: A Multimethods Approach

    ERIC Educational Resources Information Center

    Nishino, Takako

    2012-01-01

    This study investigates the relationship among Japanese high school teachers' beliefs, their practices, and socioeducational factors regarding communicative language teaching (CLT). A multimethods approach was used consisting of a survey, interviews, and class observations. A Teacher Beliefs Questionnaire was sent to 188 randomly selected Japanese…

  19. A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

    USGS Publications Warehouse

    Thomas, D.L.; Johnson, D.; Griffith, B.

    2006-01-01

    Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a Bayesian hierarchical discrete-choice model for resource selection can provide managers with 2 components of population-level inference: average population selection and variability of selection. Both components are necessary to make sound management decisions based on animal selection.

  20. Anti-Depressants, Suicide, and Drug Regulation

    ERIC Educational Resources Information Center

    Ludwig, Jens; Marcotte, Dave E.

    2005-01-01

    Policymakers are increasingly concerned that a relatively new class of anti-depressant drugs, selective serotonin re-uptake inhibitors (SSRI), may increase the risk of suicide for at least some patients, particularly children. Prior randomized trials are not informative on this question because of small sample sizes and other limitations. Using…

  1. Health Behaviors of Culturally Diverse Inner-City Community College Students

    ERIC Educational Resources Information Center

    Heller, Janet R.; Sarmiento, Ariel L.

    2016-01-01

    Objective: To determine the prevalence of risk behaviors related to cigarette use, alcohol use, nutrition, physical fitness, and sexual behavior. Participants: Participants were 1,075 students attending an urban community college during the Spring 2012 semester. Methods: Data were collected in randomly selected classes using the American College…

  2. Delivery Systems: "Saber Tooth" Effect in Counseling.

    ERIC Educational Resources Information Center

    Traylor, Elwood B.

    This study reported the role of counselors as perceived by black students in a secondary school. Observational and interview methods were employed to obtain data from 24 black students selected at random from the junior and senior classes of a large metropolitan secondary school. Findings include: counselors were essentially concerned with…

  3. Correlates of School Stress.

    ERIC Educational Resources Information Center

    Matthews, Doris B.

    As part of a continuing series of research studies on stress in schools, this study examined the construct validity of peripheral temperature at the fingertips as a measure of school stress. Measurements were made in classes selected at random from 11 volunteer schools in South Carolina. Three types of correlational studies were undertaken: (1)…

  4. Employment of College Students.

    ERIC Educational Resources Information Center

    High, Robert V.

    A survey was conducted to determine the effect on academic performance, if any, of employment on undergraduate college students. A questionnaire was sent to professors at 3 four-year colleges on Long Island (New York); various day classes were randomly selected. The final sample of n=257 represented approximately a 30 percent response. The…

  5. Talk Show Viewing Motives: Does Gender Make a Difference?

    ERIC Educational Resources Information Center

    Cress, Stacy L.; Rapert, Kevin D.

    A study explored the relationship between gender and talk show viewing motives. Students (109) from 6 randomly selected introductory communication classes in a midwestern university, 30 people belonging to a non-traditional student organization called "Oasis," and 8 residents of a retirement home were given Rubin's instrument to assess…

  6. Estimation and classification by sigmoids based on mutual information

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1994-01-01

    An estimate of the probability density function of a random vector is obtained by maximizing the mutual information between the input and the output of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's s method, applied to an estimated density, yields a recursive maximum likelihood estimator, consisting of a single internal layer of sigmoids, for a random variable or a random sequence. Applications to the diamond classification and to the prediction of a sun-spot process are demonstrated.

  7. Effectiveness of discovery learning model on mathematical problem solving

    NASA Astrophysics Data System (ADS)

    Herdiana, Yunita; Wahyudin, Sispiyati, Ririn

    2017-08-01

    This research is aimed to describe the effectiveness of discovery learning model on mathematical problem solving. This research investigate the students' problem solving competency before and after learned by using discovery learning model. The population used in this research was student in grade VII in one of junior high school in West Bandung Regency. From nine classes, class VII B were randomly selected as the sample of experiment class, and class VII C as control class, which consist of 35 students every class. The method in this research was quasi experiment. The instrument in this research is pre-test, worksheet and post-test about problem solving of mathematics. Based on the research, it can be conclude that the qualification of problem solving competency of students who gets discovery learning model on level 80%, including in medium category and it show that discovery learning model effective to improve mathematical problem solving.

  8. Science Teacher Candidates' Learning and Studying Strategies in the Context of Self-Regulation

    ERIC Educational Resources Information Center

    Yilmaz, Özkan

    2017-01-01

    This study investigated the students' individual study and learning strategies. Toward this purpose, open ended question form was administered to 40 university students who have enrolled department of mathematics and science education, faculty of education. Students were selected randomly in all level of class. Qualitative research method was used…

  9. The Relationship of Practice, Attitude, and Perception of Competence in Middle School Physical Education

    ERIC Educational Resources Information Center

    Scrabis-Fletcher, Kristin; Rasmussen, Jennifer; Silverman, Stephen

    2016-01-01

    Purpose: Grounded in social cognitive theory this study examined attitude and perception of competence and their relationship with skill practice in middle school physical education. Method: Participants (N = 81) were randomly selected from nine teachers' classes. Two lessons were videotaped and students completed a middle school perception of…

  10. The Relationship between Multiple Intelligences and Listening Self-Efficacy among Iranian EFL Learners

    ERIC Educational Resources Information Center

    Davoudi, Mohammad; Chavosh, Milad

    2016-01-01

    The present paper aimed at investigating the relationship between listening self-efficacy and multiple intelligences of Iranian EFL learners. Initially, ninety intermediate male learners were selected randomly from among 20 intermediate classes in a Language Academy in Yazd. In order to assure the homogeneity of the participants in terms of…

  11. The Public Mind: Views of Pennsylvania Citizens. Report No. 3.

    ERIC Educational Resources Information Center

    Mansfield Univ., PA.

    During February-March 1991, 1,518 randomly selected Pennsylvania adults with listed telephone numbers were surveyed on political, educational, and health issues. With regard to education, respondents: (1) strongly favored limiting class size to 15 students in grades K-3, and funding public education through the state income tax (not local taxes);…

  12. The Competitive Advantage of Foreign Languages and Cultural Knowledge

    ERIC Educational Resources Information Center

    Grosse, Christine Uber

    2004-01-01

    This study presents the results of an electronic survey of 2,500 randomly selected alumni from the graduating classes of 1970 through 2002 of Thunderbird, The American Graduate School of International Management. Of the 2,500 alumni, 581 responded. Thunderbird required a minimum of 4 semesters of foreign language for graduation. The survey…

  13. Assessing Community College Student Knowledge in the Liberal Arts.

    ERIC Educational Resources Information Center

    Cohen, Arthur M.; Schuetz, Pam; Chang, June C.; Plecha, Michelle D.

    This paper describes an assessment of community college student knowledge in the liberal arts at two-year colleges in Southern California. A survey instrument with multiple choice questions covering five liberal arts subject areas was distributed to 4,200 students in randomly selected classes at ten colleges. More than 2,500 questionnaires were…

  14. Academic Achievements and Satisfaction of the Clicker-Aided Flipped Business English Writing Class

    ERIC Educational Resources Information Center

    Zhonggen, Yu; Guifang, Wang

    2016-01-01

    The flipped classroom has been achieving a great success in teaching innovation. This study, aiming to determine the effectiveness of the flipped model in business English writing course, combined the quantitative with the qualitative research methods. Participants were randomly selected from undergraduate students majoring in business English.…

  15. Effect of Training in Math Metacognitive Strategy on Fractional Achievement of Nigerian Schoolchildren

    ERIC Educational Resources Information Center

    Onu, V. C.; Eskay, M.; Igbo, J. N.; Obiyo, N.; Agbo, O.

    2012-01-01

    This study examined the effect of training in math metacognition on fractional mathematics among primary school pupils, with a quasi-experimental design, specifically a post-test only control group design. Two intact classes were randomly selected and assigned to treatment and control conditions. Sixty primary six pupils constituted the sample…

  16. Corrective Feedback, Spoken Accuracy and Fluency, and the Trade-Off Hypothesis

    ERIC Educational Resources Information Center

    Chehr Azad, Mohammad Hassan; Farrokhi, Farahman; Zohrabi, Mohammad

    2018-01-01

    The current study was an attempt to investigate the effects of different corrective feedback (CF) conditions on Iranian EFL learners' spoken accuracy and fluency (AF) and the trade-off between them. Consequently, four pre-intermediate intact classes were randomly selected as the control, delayed explicit metalinguistic CF, extensive recast, and…

  17. Increasing Word Recognition Skills in High School Remedial Readers through Systematic Intersensory Transfer.

    ERIC Educational Resources Information Center

    Silverston, Randall A.; Deichmann, John W.

    The purpose of this study was to design and test a remedial reading instructional strategy for word recognition skills utilizing specific intersensory transfer components. The subjects were 56 high school sophomores and juniors enrolled in special education classes. Eight subjects were randomly selected from each of seven special education…

  18. Location Based Services for Outdoor Ecological Learning System: Design and Implementation

    ERIC Educational Resources Information Center

    Hsiao, Hsien-Sheng; Lin, Chih-Cheng; Feng, Ruei-Ting; Li, Kun Jing

    2010-01-01

    This paper aimed to demonstrate how location-based services were implemented in ubiquitous outdoor ecological learning system. In an elementary school in northern Taiwan, two fifth grade classes on an ecology project were randomly selected: The experimental group could access the ecological learning system on hand-held devices while the control…

  19. Los Angeles Community College District Fall 1996 Student Survey.

    ERIC Educational Resources Information Center

    Prather, George; Kelly, Dexter

    This report presents the results of the 1996 Los Angeles Community College District Student Survey. The survey was administered in a randomly selected group of classes. Each college sample is independent of the others and the proportion of students sampled within each college will vary. Responses were weighted inversely to account for…

  20. The Effect of Chin-cup Therapy in Class III Malocclusion: A Systematic Review

    PubMed Central

    Mousoulea, Sophia; Tsolakis, Ioannis; Ferdianakis, Efstratios; Tsolakis, Apostolos I.

    2016-01-01

    Background: The treatment of Class III malocclusion has been challenging for orthodontists. Among a plethora of treatment modalities, the chin-cup is considered a traditional appliance for early orthopedic intervention. Objective: The present study aims to investigate the current scientific evidence regarding the effectiveness of chin-cup therapy in Class III malocclusion of prognathic growing patients. Method: A systematic review of the literature was conducted using PubMed/Medline and the Cochrane Central Register of Controlled Trials from January 1954 to October 2015. Articles were selected based on established inclusion/ exclusion criteria. Results: The search strategy resulted in 3285 articles.14 studies were selected for the final analysis. They were all CCTs, 13 of retrospective and 1 of prospective design. Methodological quality was evaluated by a risk of bias assessment, as suggested by the Cochrane Risk of Bias Assessment Tool for Non-Randomized Studies on Interventions. The reported evidence presented favorable short-term outcomes both in hard and soft tissues improving the Class III profile, as well as desirable dento-alveolar changes, positively affecting the Class III malocclusion. Conclusion: There is considerable agreement between studies that chin-cup therapy can be considered for the short-term treatment of growing patients with Class III malocclusion, as indicated by favorable changes both in the hard and soft tissues. The existence of considerable risk of bias in all selected studies and the unclear long-term effectiveness of chin-cup therapy highlight the need for further investigation to draw reliable conclusions. PMID:28077971

  1. Ensemble Feature Learning of Genomic Data Using Support Vector Machine

    PubMed Central

    Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R.; Braytee, Ali; Kennedy, Paul J.

    2016-01-01

    The identification of a subset of genes having the ability to capture the necessary information to distinguish classes of patients is crucial in bioinformatics applications. Ensemble and bagging methods have been shown to work effectively in the process of gene selection and classification. Testament to that is random forest which combines random decision trees with bagging to improve overall feature selection and classification accuracy. Surprisingly, the adoption of these methods in support vector machines has only recently received attention but mostly on classification not gene selection. This paper introduces an ensemble SVM-Recursive Feature Elimination (ESVM-RFE) for gene selection that follows the concepts of ensemble and bagging used in random forest but adopts the backward elimination strategy which is the rationale of RFE algorithm. The rationale behind this is, building ensemble SVM models using randomly drawn bootstrap samples from the training set, will produce different feature rankings which will be subsequently aggregated as one feature ranking. As a result, the decision for elimination of features is based upon the ranking of multiple SVM models instead of choosing one particular model. Moreover, this approach will address the problem of imbalanced datasets by constructing a nearly balanced bootstrap sample. Our experiments show that ESVM-RFE for gene selection substantially increased the classification performance on five microarray datasets compared to state-of-the-art methods. Experiments on the childhood leukaemia dataset show that an average 9% better accuracy is achieved by ESVM-RFE over SVM-RFE, and 5% over random forest based approach. The selected genes by the ESVM-RFE algorithm were further explored with Singular Value Decomposition (SVD) which reveals significant clusters with the selected data. PMID:27304923

  2. Sex differences in obesity, dietary habits, and physical activity among urban middle-class Bangladeshis.

    PubMed

    Saquib, Juliann; Saquib, Nazmus; Stefanick, Marcia L; Khanam, Masuma Akter; Anand, Shuchi; Rahman, Mahbubur; Chertow, Glenn M; Barry, Michele; Ahmed, Tahmeed; Cullen, Mark R

    2016-07-01

    The sustained economic growth in Bangladesh during the previous decade has created a substantial middle-class population, who have adequate income to spend on food, clothing, and lifestyle management. Along with the improvements in living standards, has also come negative impact on health for the middle class. The study objective was to assess sex differences in obesity prevalence, diet, and physical activity among urban middle-class Bangladeshi. In this cross-sectional study, conducted in 2012, we randomly selected 402 adults from Mohammedpur, Dhaka. The sampling technique was multi-stage random sampling. We used standardized questionnaires for data collection and measured height, weight, and waist circumference. Mean age (standard deviation) was 49.4 (12.7) years. The prevalence of both generalized (79% vs. 53%) and central obesity (85% vs. 42%) were significantly higher in women than men. Women reported spending more time watching TV and spending less time walking than men (p<.05); however, men reported a higher intake of unhealthy foods such as fast food and soft drinks. We conclude that the prevalence of obesity is significantly higher in urban middle-class Bangladeshis than previous urban estimates, and the burden of obesity disproportionately affects women. Future research and public health efforts are needed to address this severe obesity problem and to promote active lifestyles.

  3. Health of women: associations among life events, social support, and personality for selected patient groups.

    PubMed

    Norlander, T; Dahlin, A; Archer, T

    2000-02-01

    This study examined the effects of life events, social support, personality traits, and siblings' birth-order on the health of women. 199 middle-class participants were included. 95 women, randomly assigned from four different patient groups, were compared with a control group of 96 randomly selected women without any special health problems. They completed a questionnaire which included questions regarding family background, health, different life events, social support, and signs of disease and a projective test, the Sivik Psychosomatism Test. Analysis indicated that report of negative life events was associated with more physical symptoms than positive life events and that the patient groups reported more negative life events and less social support than the control group.

  4. Effects of prey abundance, distribution, visual contrast and morphology on selection by a pelagic piscivore

    USGS Publications Warehouse

    Hansen, Adam G.; Beauchamp, David A.

    2014-01-01

    Most predators eat only a subset of possible prey. However, studies evaluating diet selection rarely measure prey availability in a manner that accounts for temporal–spatial overlap with predators, the sensory mechanisms employed to detect prey, and constraints on prey capture.We evaluated the diet selection of cutthroat trout (Oncorhynchus clarkii) feeding on a diverse planktivore assemblage in Lake Washington to test the hypothesis that the diet selection of piscivores would reflect random (opportunistic) as opposed to non-random (targeted) feeding, after accounting for predator–prey overlap, visual detection and capture constraints.Diets of cutthroat trout were sampled in autumn 2005, when the abundance of transparent, age-0 longfin smelt (Spirinchus thaleichthys) was low, and 2006, when the abundance of smelt was nearly seven times higher. Diet selection was evaluated separately using depth-integrated and depth-specific (accounted for predator–prey overlap) prey abundance. The abundance of different prey was then adjusted for differences in detectability and vulnerability to predation to see whether these factors could explain diet selection.In 2005, cutthroat trout fed non-randomly by selecting against the smaller, transparent age-0 longfin smelt, but for the larger age-1 longfin smelt. After adjusting prey abundance for visual detection and capture, cutthroat trout fed randomly. In 2006, depth-integrated and depth-specific abundance explained the diets of cutthroat trout well, indicating random feeding. Feeding became non-random after adjusting for visual detection and capture. Cutthroat trout selected strongly for age-0 longfin smelt, but against similar sized threespine stickleback (Gasterosteus aculeatus) and larger age-1 longfin smelt in 2006. Overlap with juvenile sockeye salmon (O. nerka) was minimal in both years, and sockeye salmon were rare in the diets of cutthroat trout.The direction of the shift between random and non-random selection depended on the presence of a weak versus a strong year class of age-0 longfin smelt. These fish were easy to catch, but hard to see. When their density was low, poor detection could explain their rarity in the diet. When their density was high, poor detection was compensated by higher encounter rates with cutthroat trout, sufficient to elicit a targeted feeding response. The nature of the feeding selectivity of a predator can be highly dependent on fluctuations in the abundance and suitability of key prey.

  5. Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

    PubMed Central

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

    Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and caution should be taken when applying filter FS methods in selecting predictive models. PMID:26890307

  6. Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness.

    PubMed

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

    Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to 'small p and large n' problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and caution should be taken when applying filter FS methods in selecting predictive models.

  7. Seven Years Later: Effects of a Neighborhood Mobility Program on Poor Black and Latino Adults' Well-Being

    ERIC Educational Resources Information Center

    Fauth, Rebecca C.; Leventhal, Tama; Brooks-Gunn, Jeanne

    2008-01-01

    This study explored program effects on adults' well-being seven years following the implementation of a court-ordered neighborhood mobility program. Low-income black and Latino adults residing in poor, segregated neighborhoods in Yonkers, New York were randomly selected to relocate to publicly funded town-houses in middle-class neighborhoods…

  8. The Cloze Procedure: A Measure for Determining Readability Level for Vocational Junior College Students.

    ERIC Educational Resources Information Center

    Caffey, Musa B.

    One hundred students enrolled in the welding and air-conditioning/refrigeration classes at Delgado Community College (Louisiana) were randomly selected to participate in a study to evaluate their effective reading comprehension level, to investigate the impact of a study skill "preview" method such as the SQ3R on their test-taking…

  9. A Methodological Study of a Computer-Managed Instructional Program in High School Physics.

    ERIC Educational Resources Information Center

    Denton, Jon James

    The purpose of this study was to develop and evaluate an instructional model which utilized the computer to produce individually prescribed instructional guides in physics at the secondary school level. The sample consisted of three classes. Of these, two were randomly selected to serve as the treatment groups, e.g., individualized instruction and…

  10. ANIMATED SERIAL SECTIONS, A TEACHING AID FOR ORAL HISTOLOGY AND EMBRYOLOGY.

    ERIC Educational Resources Information Center

    HAYDEN, JESS; AND OTHERS

    THE RELATIVE EFFECTIVENESS OF TWO TYPES OF VISUAL MEDIA FOR THE DEVELOPMENT OF A THREE-DIMENSIONAL CONCEPT OF A GIVEN ANATOMICAL REGION WAS INVESTIGATED. EXPERIMENTAL AND CONTROL GROUPS WERE RANDOMLY SELECTED FROM 119 FIRST-YEAR MEDICAL AND DENTAL STUDENTS IN AN HISTOLOGY CLASS. BOTH GROUPS ATTENDED THE SAME ONE-HOUR LECTURE. FOLLOWING THE LECTURE…

  11. Understanding Sample Surveys: Selective Learning about Social Science Research Methods

    ERIC Educational Resources Information Center

    Currin-Percival, Mary; Johnson, Martin

    2010-01-01

    We investigate differences in what students learn about survey methodology in a class on public opinion presented in two critically different ways: with the inclusion or exclusion of an original research project using a random-digit-dial telephone survey. Using a quasi-experimental design and data obtained from pretests and posttests in two public…

  12. Problem-Based Learning in an Eleventh Grade Chemistry Class: "Factors Affecting Cell Potential"

    ERIC Educational Resources Information Center

    Tarhan, Leman; Acar, Burcin

    2007-01-01

    The purpose of this research study was to examine the effectiveness of problem-based learning (PBL) on eleventh grade students' understanding of "The effects of temperature, concentration and pressure on cell potential" and also their social skills. Stratified randomly selected control and experimental groups with 20 students each were used in…

  13. Developing Academic Motivation Scale for Learning Information Technology (AMSLIT): A Study of Validity and Reliability

    ERIC Educational Resources Information Center

    Schreglmann, Sinan

    2018-01-01

    This study aimed to develop Academic Motivation Scale for Learning Information Technology for university students. For this purpose, 120 randomly selected university students studying in different classes and faculties at KSU were invited to the study during the 2016-2017 academic year. To define the scale indicators students were asked to answer…

  14. A Virtual Room to Enhance Writing Skills in the EFL Class

    ERIC Educational Resources Information Center

    Ochoa Alpala, Dayra Piedad; Medina Peña, Nieves

    2014-01-01

    This article reports an action research that intended to study to what extent students shape their writing skill in English through the use of a virtual room. As the study, we randomly selected six ninth graders in high school from thirty two students at a Colombian private institution. Three instruments were used, namely, interviews, students'…

  15. Does the Adoption of Plagiarism-Detection Software in Higher Education Reduce Plagiarism?

    ERIC Educational Resources Information Center

    Youmans, Robert J.

    2011-01-01

    In two studies, students at California State University, Northridge wrote papers that were checked for plagiarism using plagiarism-detection software. In the first study, half of the students in two classes were randomly selected and told by the professor that their term papers would be scanned for plagiarism using the software. Students in the…

  16. The Effect of Cluster-Based Instruction on Mathematic Achievement in Inclusive Schools

    ERIC Educational Resources Information Center

    Gunarhadi, Sunardi; Anwar, Mohammad; Andayani, Tri Rejeki; Shaari, Abdull Sukor

    2016-01-01

    The research aimed to investigate the effect of Cluster-Based Instruction (CBI) on the academic achievement of Mathematics in inclusive schools. The sample was 68 students in two intact classes, including those with learning disabilities, selected using a cluster random technique among 17 inclusive schools in the regency of Surakarta. The two…

  17. Adoption of Blogging by a Chinese Language Composition Class in a Vocational High School in Taiwan

    ERIC Educational Resources Information Center

    Lou, Shi-Jer; Wu, Shi-Chiao; Shih, Ru-Chu; Tseng, Kuo-Hung

    2010-01-01

    The purpose of this study was to examine the effect of adopting blogging upon Chinese language composition instruction in a vocational high school in Taiwan. The researchers developed a model that utilises blogging in Chinese language composition instruction. Forty randomly selected students from a public vocational high school served as the…

  18. Universal statistics of selected values

    NASA Astrophysics Data System (ADS)

    Smerlak, Matteo; Youssef, Ahmed

    2017-03-01

    Selection, the tendency of some traits to become more frequent than others under the influence of some (natural or artificial) agency, is a key component of Darwinian evolution and countless other natural and social phenomena. Yet a general theory of selection, analogous to the Fisher-Tippett-Gnedenko theory of extreme events, is lacking. Here we introduce a probabilistic definition of selection and show that selected values are attracted to a universal family of limiting distributions which generalize the log-normal distribution. The universality classes and scaling exponents are determined by the tail thickness of the random variable under selection. Our results provide a possible explanation for skewed distributions observed in diverse contexts where selection plays a key role, from molecular biology to agriculture and sport.

  19. Genetic analyses of protein yield in dairy cows applying random regression models with time-dependent and temperature x humidity-dependent covariates.

    PubMed

    Brügemann, K; Gernand, E; von Borstel, U U; König, S

    2011-08-01

    Data used in the present study included 1,095,980 first-lactation test-day records for protein yield of 154,880 Holstein cows housed on 196 large-scale dairy farms in Germany. Data were recorded between 2002 and 2009 and merged with meteorological data from public weather stations. The maximum distance between each farm and its corresponding weather station was 50 km. Hourly temperature-humidity indexes (THI) were calculated using the mean of hourly measurements of dry bulb temperature and relative humidity. On the phenotypic scale, an increase in THI was generally associated with a decrease in daily protein yield. For genetic analyses, a random regression model was applied using time-dependent (d in milk, DIM) and THI-dependent covariates. Additive genetic and permanent environmental effects were fitted with this random regression model and Legendre polynomials of order 3 for DIM and THI. In addition, the fixed curve was modeled with Legendre polynomials of order 3. Heterogeneous residuals were fitted by dividing DIM into 5 classes, and by dividing THI into 4 classes, resulting in 20 different classes. Additive genetic variances for daily protein yield decreased with increasing degrees of heat stress and were lowest at the beginning of lactation and at extreme THI. Due to higher additive genetic variances, slightly higher permanent environment variances, and similar residual variances, heritabilities were highest for low THI in combination with DIM at the end of lactation. Genetic correlations among individual values for THI were generally >0.90. These trends from the complex random regression model were verified by applying relatively simple bivariate animal models for protein yield measured in 2 THI environments; that is, defining a THI value of 60 as a threshold. These high correlations indicate the absence of any substantial genotype × environment interaction for protein yield. However, heritabilities and additive genetic variances from the random regression model tended to be slightly higher in the THI range corresponding to cows' comfort zone. Selecting such superior environments for progeny testing can contribute to an accurate genetic differentiation among selection candidates. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  20. Machine learning for predicting soil classes in three semi-arid landscapes

    USGS Publications Warehouse

    Brungard, Colby W.; Boettinger, Janis L.; Duniway, Michael C.; Wills, Skye A.; Edwards, Thomas C.

    2015-01-01

    Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

  1. Different functional classes of genes are characterized by different compositional properties.

    PubMed

    D'Onofrio, Giuseppe; Ghosh, Tapash Chandra; Saccone, Salvatore

    2007-12-22

    A compositional analysis on a set of human genes classified in several functional classes was performed. We found out that the GC3, i.e. the GC level at the third codon positions, of the genes involved in cellular metabolism was significantly higher than those involved in information storage and processing. Analyses of human/Xenopus ortologous genes showed that: (i) the GC3 increment of the genes involved in cellular metabolism was significantly higher than those involved in information storage and processing; and (ii) a strong correlation between the GC3 and the corresponding GCi, i.e. the GC level of introns, was found in each functional class. The non-randomness of the GC increments favours the selective hypothesis of gene/genome evolution.

  2. Active learning in the presence of unlabelable examples

    NASA Technical Reports Server (NTRS)

    Mazzoni, Dominic; Wagstaff, Kiri

    2004-01-01

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

  3. Effects of Music Instruction with Bamboo Xylophone Accompaniment on Singing Achievement among Second-Grade Children

    ERIC Educational Resources Information Center

    Simeon, Jinky Jane C.; Ku, Agnes Chun Moi

    2015-01-01

    The aim of this research is to determine the effect of music instruction with bamboo xylophone as harmonic accompaniment on the singing achievement of second-grade children. Eighty children (N = 80) from four randomly selected classes in two different public schools in the city of Kota Kinabalu participated in this study and they were assigned to…

  4. The Effect of Instructional Analogies in Interaction with Logical Thinking Ability on Achievement and Attitude toward Chemistry

    ERIC Educational Resources Information Center

    Eskandar, Fathi-Azar; Bayrami, Mansor; Vahedi, Shahram; Ansar, Vahideh Abdollahi Adli

    2013-01-01

    We investigated the effect of instructional analogies in interaction with logical thinking ability on achievement and attitude towards chemistry. The participants were 147 female students from 6 8th grade classes in three public junior high schools selected by using a random multistage sampling method from five education districts in Tabriz, a…

  5. The Availability of Vocal Training for Improvement of Accent and Articulation Defects in Speech Education

    ERIC Educational Resources Information Center

    Aycan, Kivanc; Cimen, Gul; Yerer, M. Betul

    2012-01-01

    This study is designed to test the use of vocal training for articulation and accent defects which might be an important trouble while Turkish speaking. For this reason vocal training has been performed on a group of students selected randomly form the Erciyes University Turkish teaching profession 3rd class and the difference before and after…

  6. First Steps in the Development of the "Inventario de Comportamiento de Estudio": The Spanish Version of the "Study Behavior Inventory."

    ERIC Educational Resources Information Center

    Bliss, Leonard B.; And Others

    The Inventario de Comportamiento de Estudio (ICE), a Spanish translation of the Study Behavior Inventory (SBI) was developed and tested using a group of 594 undergraduate students from randomly selected classes at a private comprehensive university in Mexico. Both instruments were designed to assess the study behaviors of students in institutions…

  7. Individual and Familial Correlates of Career Salience among Upwardly Mobile College Women. Final Report.

    ERIC Educational Resources Information Center

    Guttmacher, Mary Johnson

    A case study was conducted using a sample of 271 women selected from a state college by a stratified random cluster technique that approximates proportional representation of women in all four classes and all college majors. The data source was an extensive questionnaire designed to measure the attitudes and behavior of interest. The major…

  8. Analysis of Perceived Stress, Coping Resources and Life Satisfaction among Students at a Newly Established Institution of Higher Learning

    ERIC Educational Resources Information Center

    Mudhovozi, P.

    2011-01-01

    A survey was conducted to analyse perceived stress, coping resources and life satisfaction among university students at an institution of higher learning. Seventy-three students randomly selected from third year Social Sciences class participated in the study. A self-report questionnaire was administered to the participants. The results showed…

  9. Effects of Problem-Solving Method on Secondary School Students' Achievement and Retention in Social Studies, in Ekiti State, Nigeria

    ERIC Educational Resources Information Center

    Abdu-Raheem, B. O.

    2012-01-01

    This study investigated the effects of problem-solving method of teaching on secondary school students' achievement and retention in Social Studies. The study adopted the quasi-experimental, pre-test, post-test, control group design. The sample for the study consisted of 240 Junior Secondary School Class II students randomly selected from six…

  10. Estimating Treatment Effects from Contaminated Multi-Period Education Experiments: The Dynamic Impacts of Class Size Reductions. NBER Working Paper No. 15200

    ERIC Educational Resources Information Center

    Ding, Weili; Lehrer, Steven F.

    2009-01-01

    This paper introduces an empirical strategy to estimate dynamic treatment effects in randomized trials that provide treatment in multiple stages and in which various noncompliance problems arise such as attrition and selective transitions between treatment and control groups. Our approach is applied to the highly influential four year randomized…

  11. Mixed-Method Research on Learning Vocabulary through Technology Reveals Vocabulary Growth in Second-Grade Students

    ERIC Educational Resources Information Center

    Huang, SuHua

    2015-01-01

    A mixed-method embedded research design was employed to investigate the effectiveness of the integration of technology for second-grade students' vocabulary development and learning. Two second-grade classes with a total of 40 students (21 boys and 19 girls) were randomly selected to participate in this study for the course of a semester. One…

  12. Body Image, Dieting and Disordered Eating and Activity Practices among Teacher Trainees: Implications for School-Based Health Education and Obesity Prevention Programs

    ERIC Educational Resources Information Center

    Yager, Zali; O'Dea, Jennifer

    2009-01-01

    The aim was to investigate and compare body image, body dissatisfaction, dieting, disordered eating, exercise and eating disorders among trainee health education/physical education (H&PE) and non-H&PE teachers. Participants were 502 trainee teachers randomly selected from class groups at three Australian universities who completed the…

  13. A Science-Technology-Society Paradigm and Cross River State Secondary School Students' Scientific Literacy: Problem Solving and Decision Making

    ERIC Educational Resources Information Center

    Umoren, Grace

    2007-01-01

    The aim of this study was to investigate the effect of Science-Technology-Society (STS) curriculum on students' scientific literacy, problem solving and decision making. Four hundred and eighty (480) Senior Secondary two science and non-science students were randomly selected from intact classes in six secondary schools in Calabar Municipality of…

  14. The Effects of Computer Animated Dissection versus Preserved Animal Dissection on the Student Achievement in a High School Biology Class.

    ERIC Educational Resources Information Center

    Kariuki, Patrick; Paulson, Ronda

    The purpose of this study was to examine the effectiveness of computer-animated dissection techniques versus the effectiveness of traditional dissection techniques as related to student achievement. The sample used was 104 general biology students from a small, rural high school in Northeast Tennessee. Random selection was used to separate the…

  15. Preliminary classification of forest vegetation of the Kenai Peninsula, Alaska.

    Treesearch

    K.M. Reynolds

    1990-01-01

    A total of 5,597 photo points was systematically located on 1:60,000-scale high altitude photographs of the Kenai Peninsula, Alaska; photo interpretation was used to classify the vegetation at each grid position. Of the total grid points, 12.3 percent were classified as timberland; 129 photo points within the timberland class were randomly selected for field survey....

  16. Impact of Physical, Psychological, and Sexual Violence on Social Adjustment of School Children in India

    ERIC Educational Resources Information Center

    Deb, Sibnath; Walsh, Kerryann

    2012-01-01

    This study sought to understand the pervasiveness and impact of physical, psychological, and sexual violence on the social adjustment of Grade 8 and 9 school children in the state of Tripura, India. The study participants, 160 boys and 160 girls, were randomly selected from classes in eight English and Bengali medium schools in Agartala city,…

  17. 1993 annual status report: a summary of fish data in six reaches of the upper Mississippi River system

    USGS Publications Warehouse

    Gutreuter, Steve; Burkhardt, Randy W.; Stopyro, Mark; Bartels, Andrew; Kramer, Eric; Bowler, Melvin C.; Cronin, Frederick A.; Soergel, Dirk W.; Petersen, Michael D.; Herzog, David P.; Raibley, Paul T.; Irons, Kevin S.; O'Hara, Timothy M.

    1997-01-01

    The Long Term Resource Monitoring Program (LTRMP) completed 1,994 collections of fishes from stratified random and permanently fixed sampling locations in six study reaches of the Upper Mississippi River System during 1993. Collection methods included day and night electrofishing, hoop netting, fyke netting (two net sizes), gill netting, seining, and trawling in select aquatic area classes. The six LTRMP study reaches are Pools 4 (excluding Lake Pepin), 8, 13, and 26 of the Upper Mississippi River, an unimpounded reach of the Mississippi River near Cape Girardeau, Missouri, and the La Grange Pool of the Illinois River. A total of 62-78 fish species were detected in each study reach. For each of the six LTRMP study reaches, this report contains summaries of: (1) sampling efforts in each combination of gear type and aquatic area class, (2) total catches of each species from each gear type, (3) mean catch-per-unit of gear effort statistics and standard errors for common species from each combination of aquatic area class and selected gear type, and (4) length distributions of common species from selected gear types.

  18. 1994 annual status report: a summary of fish data in six reaches of the upper Mississippi River system

    USGS Publications Warehouse

    Gutreuter, Steve; Burkhardt, Randy W.; Stopyro, Mark; Bartels, Andrew; Kramer, Eric; Bowler, Melvin C.; Cronin, Frederick A.; Soergel, Dirk W.; Petersen, Michael D.; Herzog, David P.; Raibley, Paul T.; Irons, Kevin S.; O'Hara, Timothy M.

    1997-01-01

    The Long Term Resource Monitoring Program (LTRMP) completed 2,653 collections of fishes from stratified random and permanently fixed sampling locations in six study reaches of the Upper Mississippi River System during 1994. Collection methods included day and night electrofishing, hoop netting, fyke netting (two net sizes), gill netting, seining, and trawling in select aquatic area classes. The six LTRMP study areas are Pools 4 (excluding Lake Pepin), 8, 13, and 26 of the Upper Mississippi River, and unimpounded reach of the Mississippi River near Cape Girardeau, Missouri, and the La Grange Pool of the Illinois River. A total of 61-79 fish species were detected in each study area. For each of the six LTRMP study areas, this report contains summaries of (1) sampling efforts in each combination of gear type and aquatic area class, (2) total catches of each species from each gear type, (3) mean catch-per-unit of gear effort statistics and standard errors for common species from each combination of aquatic area class and selected gear type, and (4) length distributions of common species from selected gear types.

  19. [Self-concept of school-age children: the norm in Kaohsiung].

    PubMed

    Chin, C C; Liu, Y Y; Ka, J K

    1989-05-01

    This study has two objectives: (1) to establish the norm of three graphical projective tests (Children's Social-Self Test, Children's Attitude Inventory and Children's Self-Concept Inventory), and (2) to explore the influence of sex, order of birth, social economic status of family, and leadership of class that effect self-concept of the school-age children. These subjects are selected from elementary schools in Kaohsiung, twenty-two classes are drawn out from each grade by systemic-random sampling. Then two classes are drawn out from 22 classes at random to arrange retest for reliability. The total subjects are 6207 students. From October 1987 to June 1988, six researchers are divided into three group to conduct the test. Besides establishing the norm, we find results from analysis of data as follow: 1. The reliability and validity of three graphical projective tests are good, they can be used for assessing the self-concept of school-age children. 2. The grade, sex, order of birth, social economic status of family, leadership of class all influence the self-concept of school-age children. 3. The self-concept and the grade has negative correlation. 4. The self-concept and the social economic status of family has positive correlation. 5. The girls have higher self-concept than the boys. 6. The order of first-born or second-born has higher self-concept than the others. 7. The ones who are leaders of class have higher self-concept than the others.

  20. Education and Intelligence: Pity the Poor Teacher because Student Characteristics are more Significant than Teachers or Schools.

    PubMed

    Detterman, Douglas K

    2016-12-06

    Education has not changed from the beginning of recorded history. The problem is that focus has been on schools and teachers and not students. Here is a simple thought experiment with two conditions: 1) 50 teachers are assigned by their teaching quality to randomly composed classes of 20 students, 2) 50 classes of 20 each are composed by selecting the most able students to fill each class in order and teachers are assigned randomly to classes. In condition 1, teaching ability of each teacher and in condition 2, mean ability level of students in each class is correlated with average gain over the course of instruction. Educational gain will be best predicted by student abilities (up to r = 0.95) and much less by teachers' skill (up to r = 0.32). I argue that seemingly immutable education will not change until we fully understand students and particularly human intelligence. Over the last 50 years in developed countries, evidence has accumulated that only about 10% of school achievement can be attributed to schools and teachers while the remaining 90% is due to characteristics associated with students. Teachers account for from 1% to 7% of total variance at every level of education. For students, intelligence accounts for much of the 90% of variance associated with learning gains. This evidence is reviewed.

  1. Sex differences in obesity, dietary habits, and physical activity among urban middle-class Bangladeshis

    PubMed Central

    Saquib, Juliann; Saquib, Nazmus; Stefanick, Marcia L.; Khanam, Masuma Akter; Anand, Shuchi; Rahman, Mahbubur; Chertow, Glenn M.; Barry, Michele; Ahmed, Tahmeed; Cullen, Mark R.

    2016-01-01

    Background The sustained economic growth in Bangladesh during the previous decade has created a substantial middle-class population, who have adequate income to spend on food, clothing, and lifestyle management. Along with the improvements in living standards, has also come negative impact on health for the middle class. The study objective was to assess sex differences in obesity prevalence, diet, and physical activity among urban middle-class Bangladeshi. Methods In this cross-sectional study, conducted in 2012, we randomly selected 402 adults from Mohammedpur, Dhaka. The sampling technique was multi-stage random sampling. We used standardized questionnaires for data collection and measured height, weight, and waist circumference. Results Mean age (standard deviation) was 49.4 (12.7) years. The prevalence of both generalized (79% vs. 53%) and central obesity (85% vs. 42%) were significantly higher in women than men. Women reported spending more time watching TV and spending less time walking than men (p<.05); however, men reported a higher intake of unhealthy foods such as fast food and soft drinks. Conclusions We conclude that the prevalence of obesity is significantly higher in urban middle-class Bangladeshis than previous urban estimates, and the burden of obesity disproportionately affects women. Future research and public health efforts are needed to address this severe obesity problem and to promote active lifestyles. PMID:27610059

  2. On the asymptotic standard error of a class of robust estimators of ability in dichotomous item response models.

    PubMed

    Magis, David

    2014-11-01

    In item response theory, the classical estimators of ability are highly sensitive to response disturbances and can return strongly biased estimates of the true underlying ability level. Robust methods were introduced to lessen the impact of such aberrant responses on the estimation process. The computation of asymptotic (i.e., large-sample) standard errors (ASE) for these robust estimators, however, has not yet been fully considered. This paper focuses on a broad class of robust ability estimators, defined by an appropriate selection of the weight function and the residual measure, for which the ASE is derived from the theory of estimating equations. The maximum likelihood (ML) and the robust estimators, together with their estimated ASEs, are then compared in a simulation study by generating random guessing disturbances. It is concluded that both the estimators and their ASE perform similarly in the absence of random guessing, while the robust estimator and its estimated ASE are less biased and outperform their ML counterparts in the presence of random guessing with large impact on the item response process. © 2013 The British Psychological Society.

  3. The prevalence of domestic violence within different socio-economic classes in Central Trinidad.

    PubMed

    Nagassar, R P; Rawlins, J M; Sampson, N R; Zackerali, J; Chankadyal, K; Ramasir, C; Boodram, R

    2010-01-01

    Domestic violence is a medical and social issue that often leads to negative consequences for society. This paper examines the association between the prevalence of domestic violence in relation to the different socio-economic classes in Central Trinidad. The paper also explores the major perceived causes of physical abuse in Central Trinidad. Participants were selected using a two-stage stratified sampling method within the Couva district. Households, each contributing one participant, were stratified into different socioeconomic classes (SES Class) and each stratum size (or its share in the sample) was determined by the portion of its size in the sampling frame to the total sample; then its members were randomly selected. The sampling method attempted to balance and then minimize racial, age, cultural biases and confounding factors. The participant chosen had to be older than 16-years of age, female and a resident of the household. If more than one female was at home, the most senior was interviewed. The study found a statistically significant relationship between verbal abuse (p = 0.0017), physical abuse (p = 0.0012) and financial abuse (p = 0.001) and socio-economic class. For all the socio-economic classes considered, the highest prevalence of domestic violence occurred amongst the working class and lower middle socio-economic classes. The most prominent reasons cited for the physical violence was drug and alcohol abuse (37%) and communication differences (16.3%). These were the other two main perceived causes of the violence. The power of the study was 0.78 and the all strata prevalence of domestic violence was 41%. Domestic violence was reported within all socio-economic class groupings but it was most prevalent within the working class and lower middle socio-economic classes. The major perceived cause of domestic violence was alcohol/drug abuse.

  4. A Network Meta-Analysis Comparing Effects of Various Antidepressant Classes on the Digit Symbol Substitution Test (DSST) as a Measure of Cognitive Dysfunction in Patients with Major Depressive Disorder.

    PubMed

    Baune, Bernhard T; Brignone, Mélanie; Larsen, Klaus Groes

    2018-02-01

    Major depressive disorder is a common condition that often includes cognitive dysfunction. A systematic literature review of studies and a network meta-analysis were carried out to assess the relative effect of antidepressants on cognitive dysfunction in major depressive disorder. MEDLINE, Embase, Cochrane, CDSR, and PsychINFO databases; clinical trial registries; and relevant conference abstracts were searched for randomized controlled trials assessing the effects of antidepressants/placebo on cognition. A network meta-analysis comparing antidepressants was conducted using a random effects model. The database search retrieved 11337 citations, of which 72 randomized controlled trials from 103 publications met the inclusion criteria. The review identified 86 cognitive tests assessing the effect of antidepressants on cognitive functioning. However, the Digit Symbol Substitution Test, which targets multiple domains of cognition and is recognized as being sensitive to change, was the only test that was used across 12 of the included randomized controlled trials and that allowed the construction of a stable network suitable for the network meta-analysis. The interventions assessed included selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and other non-selective serotonin reuptake inhibitors/serotonin-norepinephrine reuptake inhibitors. The network meta-analysis using the Digit Symbol Substitution Test showed that vortioxetine was the only antidepressant that improved cognitive dysfunction on the Digit Symbol Substitution Test vs placebo {standardized mean difference: 0.325 (95% CI = 0.120; 0.529, P=.009}. Compared with other antidepressants, vortioxetine was statistically more efficacious on the Digit Symbol Substitution Test vs escitalopram, nortriptyline, and the selective serotonin reuptake inhibitor and tricyclic antidepressant classes. This study highlighted the large variability in measures used to assess cognitive functioning. The findings on the Digit Symbol Substitution Test indicate differential effects of various antidepressants on improving cognitive function in patients with major depressive disorder. © The Author 2017. Published by Oxford University Press on behalf of CINP.

  5. Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials.

    PubMed

    Mota, L F M; Martins, P G M A; Littiere, T O; Abreu, L R A; Silva, M A; Bonafé, C M

    2018-04-01

    The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

  6. Random waves in the brain: Symmetries and defect generation in the visual cortex

    NASA Astrophysics Data System (ADS)

    Schnabel, M.; Kaschube, M.; Löwel, S.; Wolf, F.

    2007-06-01

    How orientation maps in the visual cortex of the brain develop is a matter of long standing debate. Experimental and theoretical evidence suggests that their development represents an activity-dependent self-organization process. Theoretical analysis [1] exploring this hypothesis predicted that maps at an early developmental stage are realizations of Gaussian random fields exhibiting a rigorous lower bound for their densities of topological defects, called pinwheels. As a consequence, lower pinwheel densities, if observed in adult animals, are predicted to develop through the motion and annihilation of pinwheel pairs. Despite of being valid for a large class of developmental models this result depends on the symmetries of the models and thus of the predicted random field ensembles. In [1] invariance of the orientation map's statistical properties under independent space rotations and orientation shifts was assumed. However, full rotation symmetry appears to be broken by interactions of cortical neurons, e.g. selective couplings between groups of neurons with collinear orientation preferences [2]. A recently proposed new symmetry, called shift-twist symmetry [3], stating that spatial rotations have to occur together with orientation shifts in order to be an appropriate symmetry transformation, is more consistent with this organization. Here we generalize our random field approach to this important symmetry class. We propose a new class of shift-twist symmetric Gaussian random fields and derive the general correlation functions of this ensemble. It turns out that despite strong effects of the shift-twist symmetry on the structure of the correlation functions and on the map layout the lower bound on the pinwheel densities remains unaffected, predicting pinwheel annihilation in systems with low pinwheel densities.

  7. Pareto genealogies arising from a Poisson branching evolution model with selection.

    PubMed

    Huillet, Thierry E

    2014-02-01

    We study a class of coalescents derived from a sampling procedure out of N i.i.d. Pareto(α) random variables, normalized by their sum, including β-size-biasing on total length effects (β < α). Depending on the range of α we derive the large N limit coalescents structure, leading either to a discrete-time Poisson-Dirichlet (α, -β) Ξ-coalescent (α ε[0, 1)), or to a family of continuous-time Beta (2 - α, α - β)Λ-coalescents (α ε[1, 2)), or to the Kingman coalescent (α ≥ 2). We indicate that this class of coalescent processes (and their scaling limits) may be viewed as the genealogical processes of some forward in time evolving branching population models including selection effects. In such constant-size population models, the reproduction step, which is based on a fitness-dependent Poisson Point Process with scaling power-law(α) intensity, is coupled to a selection step consisting of sorting out the N fittest individuals issued from the reproduction step.

  8. Analysis of the error of the developed method of determination the active conductivity reducing the insulation level between one phase of the network and ground, and insulation parameters in a non-symmetric network with isolated neutral with voltage above 1000 V

    NASA Astrophysics Data System (ADS)

    Utegulov, B. B.

    2018-02-01

    In the work the study of the developed method was carried out for reliability by analyzing the error in indirect determination of the insulation parameters in an asymmetric network with an isolated neutral voltage above 1000 V. The conducted studies of the random relative mean square errors show that the accuracy of indirect measurements in the developed method can be effectively regulated not only by selecting a capacitive additional conductivity, which are connected between phases of the electrical network and the ground, but also by the selection of measuring instruments according to the accuracy class. When choosing meters with accuracy class of 0.5 with the correct selection of capacitive additional conductivity that are connected between the phases of the electrical network and the ground, the errors in measuring the insulation parameters will not exceed 10%.

  9. Frequency and severity of decay in street tree maples in four upstate New York cities Arboric

    Treesearch

    Christopher Luley; David Nowak; Eric Greenfield

    2009-01-01

    A proportional random selection of street tree Norway, silver, and sugar maples, and other species among four diameter classes were surveyed in the U.S. New York cities of Albany, Buffalo, Rochester, and Syracuse for decay incidence and severity. Decay was determined by drilling sampled trees with a Resistograph and calculating the ratio of sound wood to radius....

  10. Creating Message Strategies for an AIDS Campaign: A Survey of the Basis of Student Awareness.

    ERIC Educational Resources Information Center

    Brislin, Tom; Miyamoto, Craig T.

    A study assessed the general knowledge of AIDS and its prevention among college students, and determined the source of that knowledge. A class of 17 senior-level journalism students used a focus group approach to select the most useful questions about AIDS and its prevention. The survey was administered by telephone to a random sample of 372…

  11. The Effectiveness of a Computer-Assisted Instruction Package in Supplementing Teaching of Selected Concepts in High School Chemistry: Writing Formulas and Balancing Chemical Equations.

    ERIC Educational Resources Information Center

    Wainwright, Camille L.

    Four classes of high school chemistry students (N=108) were randomly assigned to experimental and control groups to investigate the effectiveness of a computer assisted instruction (CAI) package during a unit on writing/naming of chemical formulas and balancing equations. Students in the experimental group received drill, review, and reinforcement…

  12. A Descriptive Analysis of the Community College Liberal Arts Curriculum. ERIC Digest.

    ERIC Educational Resources Information Center

    ERIC Clearinghouse for Junior Colleges, Los Angeles, CA.

    In spring 1986, the Center for the Study of Community Colleges analyzed the class schedules of 95 randomly selected two-year colleges to determine the types of liberal arts courses offered by the colleges and to spot changes in the curriculum over the past 11 years. Study findings included the following: (1) the humanities made up 48% of the total…

  13. The Effectiveness of Alternative Cancer Education Programs in Promoting Knowledge, Attitudes, and Self-Examination Behavior in a Population of College-Aged Men.

    ERIC Educational Resources Information Center

    Marty, Phillip J.; McDermott, Robert J.

    A study determined whether changes in knowledge, selected attitudes, and self-examination behavior occurred among college-aged men after exposure to alternative cancer education programs. College-aged men (n=128) from two large health education classes at a mid-western university were randomly assigned to two treatment groups. The first group…

  14. What Effect Does Story Time Have on Toddlers' Social and Emotional Skills

    ERIC Educational Resources Information Center

    Betawi, I. A.

    2015-01-01

    The purpose of this study is to investigate the effect of story time and reading stories on the development of toddlers' social and emotional skills between 24 and 36 months of age. A sample of 10 toddlers was randomly selected from three different classes at the laboratory nursery of The University of Jordan. A pre-test and post-test were…

  15. Gender Factors Associated with Sexual Abstinent Behaviour of Rural South African High School Going Youth in KwaZulu-Natal, South Africa

    ERIC Educational Resources Information Center

    Dlamini, Siyabonga; Taylor, Myra; Mkhize, Nosipho; Huver, Rosemarie; Sathiparsad, Reshma; de Vries, Hein; Naidoo, Kala; Jinabhai, Champak

    2009-01-01

    The cross-sectional study investigated South African rural high school learners' choice of sexual abstinence in order to be able to develop tailored health education messages. All Grade 9 learners from one class at each of 10 randomly selected rural high schools participated. The Integrated Model for Motivational and Behavioural Change was used to…

  16. Bayesian spatial prediction of the site index in the study of the Missouri Ozark Forest Ecosystem Project

    Treesearch

    Xiaoqian Sun; Zhuoqiong He; John Kabrick

    2008-01-01

    This paper presents a Bayesian spatial method for analysing the site index data from the Missouri Ozark Forest Ecosystem Project (MOFEP). Based on ecological background and availability, we select three variables, the aspect class, the soil depth and the land type association as covariates for analysis. To allow great flexibility of the smoothness of the random field,...

  17. The Effects of Pupil-Corrected Tests and Written Teacher Comments on Learning to Spell in the Upper Elementary Grades.

    ERIC Educational Resources Information Center

    Lesner, Julius

    To determine the effects of teacher comments on spelling test papers, 32 randomly selected fourth- and sixth-grade teachers from low and high socioeconomic area Los Angeles elementary schools used 965 pupils in their regular classes as subjects. The teachers gave the regular weekly spelling test, and one of four evaluation treatments was randomly…

  18. In Darwinian evolution, feedback from natural selection leads to biased mutations.

    PubMed

    Caporale, Lynn Helena; Doyle, John

    2013-12-01

    Natural selection provides feedback through which information about the environment and its recurring challenges is captured, inherited, and accumulated within genomes in the form of variations that contribute to survival. The variation upon which natural selection acts is generally described as "random." Yet evidence has been mounting for decades, from such phenomena as mutation hotspots, horizontal gene transfer, and highly mutable repetitive sequences, that variation is far from the simplifying idealization of random processes as white (uniform in space and time and independent of the environment or context).  This paper focuses on what is known about the generation and control of mutational variation, emphasizing that it is not uniform across the genome or in time, not unstructured with respect to survival, and is neither memoryless nor independent of the (also far from white) environment. We suggest that, as opposed to frequentist methods, Bayesian analysis could capture the evolution of nonuniform probabilities of distinct classes of mutation, and argue not only that the locations, styles, and timing of real mutations are not correctly modeled as generated by a white noise random process, but that such a process would be inconsistent with evolutionary theory. © 2013 New York Academy of Sciences.

  19. Proteomics Versus Clinical Data and Stochastic Local Search Based Feature Selection for Acute Myeloid Leukemia Patients' Classification.

    PubMed

    Chebouba, Lokmane; Boughaci, Dalila; Guziolowski, Carito

    2018-06-04

    The use of data issued from high throughput technologies in drug target problems is widely widespread during the last decades. This study proposes a meta-heuristic framework using stochastic local search (SLS) combined with random forest (RF) where the aim is to specify the most important genes and proteins leading to the best classification of Acute Myeloid Leukemia (AML) patients. First we use a stochastic local search meta-heuristic as a feature selection technique to select the most significant proteins to be used in the classification task step. Then we apply RF to classify new patients into their corresponding classes. The evaluation technique is to run the RF classifier on the training data to get a model. Then, we apply this model on the test data to find the appropriate class. We use as metrics the balanced accuracy (BAC) and the area under the receiver operating characteristic curve (AUROC) to measure the performance of our model. The proposed method is evaluated on the dataset issued from DREAM 9 challenge. The comparison is done with a pure random forest (without feature selection), and with the two best ranked results of the DREAM 9 challenge. We used three types of data: only clinical data, only proteomics data, and finally clinical and proteomics data combined. The numerical results show that the highest scores are obtained when using clinical data alone, and the lowest is obtained when using proteomics data alone. Further, our method succeeds in finding promising results compared to the methods presented in the DREAM challenge.

  20. Effectiveness comparison of cardio-selective to non-selective β-blockers and their association with mortality and morbidity in end-stage renal disease: a retrospective cohort study.

    PubMed

    Shireman, Theresa I; Mahnken, Jonathan D; Phadnis, Milind A; Ellerbeck, Edward F

    2016-03-25

    Within-class comparative effectiveness studies of β-blockers have not been performed in the chronic dialysis setting. With widespread cardiac disease in these patients and potential mechanistic differences within the class, we examined whether mortality and morbidity outcomes varied between cardio-selective and non-selective β-blockers. Retrospective observational study of within class β-blocker exposure among a national cohort of new chronic dialysis patients (N = 52,922) with hypertension and dual eligibility (Medicare-Medicaid). New β-blocker users were classified according to their exclusive use of one of the subclasses. Outcomes were all-cause mortality (ACM) and cardiovascular morbidity and mortality (CVMM). The associations of cardio-selective and non-selective agents on outcomes were adjusted for baseline characteristics using Cox proportional hazards. There were 4938 new β-blocker users included in the ACM model and 4537 in the CVMM model: 77 % on cardio-selective β-blockers. Exposure to cardio-selective and non-selective agents during the follow-up period was comparable, as measured by proportion of days covered (0.56 vs. 0.53 in the ACM model; 0.56 vs 0.54 in the CVMM model). Use of cardio-selective β-blockers was associated with lower risk for mortality (AHR = 0.84; 99 % CI = 0.72-0.97, p = 0.0026) and lower risk for CVMM events (AHR = 0.86; 99 % CI = 0.75-0.99, p = 0.0042). Among new β-blockers users on chronic dialysis, cardio-selective agents were associated with a statistically significant 16 % reduction in mortality and 14 % in cardiovascular morbidity and mortality relative to non-selective β-blocker users. A randomized clinical trial would be appropriate to more definitively answer whether cardio-selective β-blockers are superior to non-selective β-blockers in the setting of chronic dialysis.

  1. Brunet-Derrida Behavior of Branching-Selection Particle Systems on the Line

    NASA Astrophysics Data System (ADS)

    Bérard, Jean; Gouéré, Jean-Baptiste

    2010-09-01

    We consider a class of branching-selection particle systems on {mathbb{R}} similar to the one considered by E. Brunet and B. Derrida in their 1997 paper “Shift in the velocity of a front due to a cutoff”. Based on numerical simulations and heuristic arguments, Brunet and Derrida showed that, as the population size N of the particle system goes to infinity, the asymptotic velocity of the system converges to a limiting value at the unexpectedly slow rate (log N)-2. In this paper, we give a rigorous mathematical proof of this fact, for the class of particle systems we consider. The proof makes use of ideas and results by R. Pemantle, and by N. Gantert, Y. Hu and Z. Shi, and relies on a comparison of the particle system with a family of N independent branching random walks killed below a linear space-time barrier.

  2. Empirical study of seven data mining algorithms on different characteristics of datasets for biomedical classification applications.

    PubMed

    Zhang, Yiyan; Xin, Yi; Li, Qin; Ma, Jianshe; Li, Shuai; Lv, Xiaodan; Lv, Weiqi

    2017-11-02

    Various kinds of data mining algorithms are continuously raised with the development of related disciplines. The applicable scopes and their performances of these algorithms are different. Hence, finding a suitable algorithm for a dataset is becoming an important emphasis for biomedical researchers to solve practical problems promptly. In this paper, seven kinds of sophisticated active algorithms, namely, C4.5, support vector machine, AdaBoost, k-nearest neighbor, naïve Bayes, random forest, and logistic regression, were selected as the research objects. The seven algorithms were applied to the 12 top-click UCI public datasets with the task of classification, and their performances were compared through induction and analysis. The sample size, number of attributes, number of missing values, and the sample size of each class, correlation coefficients between variables, class entropy of task variable, and the ratio of the sample size of the largest class to the least class were calculated to character the 12 research datasets. The two ensemble algorithms reach high accuracy of classification on most datasets. Moreover, random forest performs better than AdaBoost on the unbalanced dataset of the multi-class task. Simple algorithms, such as the naïve Bayes and logistic regression model are suitable for a small dataset with high correlation between the task and other non-task attribute variables. K-nearest neighbor and C4.5 decision tree algorithms perform well on binary- and multi-class task datasets. Support vector machine is more adept on the balanced small dataset of the binary-class task. No algorithm can maintain the best performance in all datasets. The applicability of the seven data mining algorithms on the datasets with different characteristics was summarized to provide a reference for biomedical researchers or beginners in different fields.

  3. Prevalence of dental anomalies in Saudi orthodontic patients.

    PubMed

    Al-Jabaa, Aljazi H; Aldrees, Abdullah M

    2013-07-01

    This study aimed to investigate the prevalence of dental anomalies and study the association of these anomalies with different types of malocclusion in a random sample of Saudi orthodontic patients. Six hundred and two randomly selected pretreatment records including orthopantomographs (OPG), and study models were evaluated. The molar relationship was determined using pretreatment study models, and OPG were examined to investigate the prevalence of dental anomalies among the sample. The most common types of the investigated anomalies were: impaction followed by hypodontia, microdontia, macrodontia, ectopic eruption and supernumerary. No statistical significant correlations were observed between sex and dental anomalies. Dental anomalies were more commonly found in class I followed by asymmetric molar relation, then class II and finally class III molar relation. No malocclusion group had a statistically significant relation with any individual dental anomaly. The prevalence of dental anomalies among Saudi orthodontic patients was higher than the general population. Although, orthodontic patients have been reported to have high rates of dental anomalies, orthodontists often fail to consider this. If not detected, dental anomalies can complicate dental and orthodontic treatment; therefore, their presence should be carefully investigated during orthodontic diagnosis and considered during treatment planning.

  4. The Effects of Team-Based Learning on Social Studies Knowledge Acquisition in High School

    ERIC Educational Resources Information Center

    Wanzek, Jeanne; Vaughn, Sharon; Kent, Shawn C.; Swanson, Elizabeth A.; Roberts, Greg; Haynes, Martha; Fall, Anna-Mária; Stillman-Spisak, Stephanie J.; Solis, Michael

    2014-01-01

    This randomized control trial examined the efficacy of team-based learning implemented within 11th-grade social studies classes. A randomized blocked design was implemented with 26 classes randomly assigned to treatment or comparison. In the treatment classes teachers implemented team-based learning practices to support students in engaging in…

  5. Selective randomized load balancing and mesh networks with changing demands

    NASA Astrophysics Data System (ADS)

    Shepherd, F. B.; Winzer, P. J.

    2006-05-01

    We consider the problem of building cost-effective networks that are robust to dynamic changes in demand patterns. We compare several architectures using demand-oblivious routing strategies. Traditional approaches include single-hop architectures based on a (static or dynamic) circuit-switched core infrastructure and multihop (packet-switched) architectures based on point-to-point circuits in the core. To address demand uncertainty, we seek minimum cost networks that can carry the class of hose demand matrices. Apart from shortest-path routing, Valiant's randomized load balancing (RLB), and virtual private network (VPN) tree routing, we propose a third, highly attractive approach: selective randomized load balancing (SRLB). This is a blend of dual-hop hub routing and randomized load balancing that combines the advantages of both architectures in terms of network cost, delay, and delay jitter. In particular, we give empirical analyses for the cost (in terms of transport and switching equipment) for the discussed architectures, based on three representative carrier networks. Of these three networks, SRLB maintains the resilience properties of RLB while achieving significant cost reduction over all other architectures, including RLB and multihop Internet protocol/multiprotocol label switching (IP/MPLS) networks using VPN-tree routing.

  6. Five-class differential diagnostics of neurodegenerative diseases using random undersampling boosting.

    PubMed

    Tong, Tong; Ledig, Christian; Guerrero, Ricardo; Schuh, Andreas; Koikkalainen, Juha; Tolonen, Antti; Rhodius, Hanneke; Barkhof, Frederik; Tijms, Betty; Lemstra, Afina W; Soininen, Hilkka; Remes, Anne M; Waldemar, Gunhild; Hasselbalch, Steen; Mecocci, Patrizia; Baroni, Marta; Lötjönen, Jyrki; Flier, Wiesje van der; Rueckert, Daniel

    2017-01-01

    Differentiating between different types of neurodegenerative diseases is not only crucial in clinical practice when treatment decisions have to be made, but also has a significant potential for the enrichment of clinical trials. The purpose of this study is to develop a classification framework for distinguishing the four most common neurodegenerative diseases, including Alzheimer's disease, frontotemporal lobe degeneration, Dementia with Lewy bodies and vascular dementia, as well as patients with subjective memory complaints. Different biomarkers including features from images (volume features, region-wise grading features) and non-imaging features (CSF measures) were extracted for each subject. In clinical practice, the prevalence of different dementia types is imbalanced, posing challenges for learning an effective classification model. Therefore, we propose the use of the RUSBoost algorithm in order to train classifiers and to handle the class imbalance training problem. Furthermore, a multi-class feature selection method based on sparsity is integrated into the proposed framework to improve the classification performance. It also provides a way for investigating the importance of different features and regions. Using a dataset of 500 subjects, the proposed framework achieved a high accuracy of 75.2% with a balanced accuracy of 69.3% for the five-class classification using ten-fold cross validation, which is significantly better than the results using support vector machine or random forest, demonstrating the feasibility of the proposed framework to support clinical decision making.

  7. Evaluation of family intervention through unobtrusive audio recordings: experiences in "bugging" children.

    PubMed

    Johnson, S M; Christensen, A; Bellamy, G T

    1976-01-01

    Five children referred to a child-family intervention program wore a radio transmitter in the home during pre-intervention and termination assessments. The transmitter broadcast to a receiver-recording apparatus in the home (either activated by an interval timer at predetermined "random" times or by parents at predetermined "picked" times). "Picked" times were parent-selected situations during which problems typically occurred (e.g., bedtime). Parents activated the recorder regularly whether or not problems occurred. Child-deviant, parent-negative, and parent-commanding behaviors were significantly higher at the picked times during pretest than at random times. At posttest, behaviors in all three classes were substantially reduced at picked times, but not at random times. For individual subject data, reductions occurred in at least two of the three dependent variables for three of the five cases during random time assessments. In general, the behavioral outcome data corresponded to parent-attitude reports and parent-collected observation data.

  8. Supercluster simulations: impact of baryons on the matter power spectrum and weak lensing forecasts for Super-CLASS

    NASA Astrophysics Data System (ADS)

    Peters, Aaron; Brown, Michael L.; Kay, Scott T.; Barnes, David J.

    2018-03-01

    We use a combination of full hydrodynamic and dark matter only simulations to investigate the effect that supercluster environments and baryonic physics have on the matter power spectrum, by re-simulating a sample of supercluster sub-volumes. On large scales we find that the matter power spectrum measured from our supercluster sample has at least twice as much power as that measured from our random sample. Our investigation of the effect of baryonic physics on the matter power spectrum is found to be in agreement with previous studies and is weaker than the selection effect over the majority of scales. In addition, we investigate the effect of targeting a cosmologically non-representative, supercluster region of the sky on the weak lensing shear power spectrum. We do this by generating shear and convergence maps using a line-of-sight integration technique, which intercepts our random and supercluster sub-volumes. We find the convergence power spectrum measured from our supercluster sample has a larger amplitude than that measured from the random sample at all scales. We frame our results within the context of the Super-CLuster Assisted Shear Survey (Super-CLASS), which aims to measure the cosmic shear signal in the radio band by targeting a region of the sky that contains five Abell clusters. Assuming the Super-CLASS survey will have a source density of 1.5 galaxies arcmin-2, we forecast a detection significance of 2.7^{+1.5}_{-1.2}, which indicates that in the absence of systematics the Super-CLASS project could make a cosmic shear detection with radio data alone.

  9. Impact of training of teachers on their ability, skills, and confidence to teach HIV/AIDS in classroom: a qualitative assessment

    PubMed Central

    2013-01-01

    Background Considering the significant impact of school-based HIV/AIDS education, in 2007, a curriculum on HIV/AIDS was incorporated in the national curriculum for high school students of Bangladesh through the Government’s HIV-prevention program. Based on the curriculum, an intervention was designed to train teachers responsible for teaching HIV/AIDS in classes. Methods In-depth interviews were conducted with teachers to understand their ability, skills, and confidence in conducting HIV/AIDS classes. Focus-group discussions (FGDs) were conducted with students who participated in HIV/AIDS classes. HIV/AIDS classes were also observed in randomly-selected schools. Thematic assessment was made to analyze data. Results The findings showed that the trained teachers were more comfortable in using interactive teaching methods and in explaining sensitive issues to their students in HIV/AIDS classes. They were also competent in using interactive teaching methods and could ensure the participation of students in HIV/AIDS classes. Conclusions The findings suggest that cascading training may be scaled up as it helped increase ability, skills, and confidence of teachers to successfully conduct HIV/AIDS classes. PMID:24144065

  10. The effectivenes of science domain-based science learning integrated with local potency

    NASA Astrophysics Data System (ADS)

    Kurniawati, Arifah Putri; Prasetyo, Zuhdan Kun; Wilujeng, Insih; Suryadarma, I. Gusti Putu

    2017-08-01

    This research aimed to determine the significant effect of science domain-based science learning integrated with local potency toward science process skills. The research method used was a quasi-experimental design with nonequivalent control group design. The population of this research was all students of class VII SMP Negeri 1 Muntilan. The sample of this research was selected through cluster random sampling, namely class VII B as an experiment class (24 students) and class VII C as a control class (24 students). This research used a test instrument that was adapted from Agus Dwianto's research. The aspect of science process skills in this research was observation, classification, interpretation and communication. The analysis of data used the one factor anova at 0,05 significance level and normalized gain score. The significance level result of science process skills with one factor anova is 0,000. It shows that the significance level < alpha (0,05). It means that there was significant effect of science domain-based science learning integrated with local potency toward science learning process skills. The results of analysis show that the normalized gain score are 0,29 (low category) in control class and 0,67 (medium category) in experiment class.

  11. Treatment effects of fixed functional appliances in patients with Class II malocclusion: a systematic review and meta-analysis

    PubMed Central

    Zymperdikas, Vasileios F.; Koretsi, Vasiliki; Papageorgiou, Spyridon N.

    2016-01-01

    Summary Objective: To assess the treatment effects of fixed functional appliances (FFAs) in treated versus untreated Class II patients by means of lateral cephalometric radiographs. Search methods: Unrestricted electronic search of 18 databases and additional manual searches up to October 2014. Selection criteria: Prospective randomized and non-randomized controlled trials reporting on cephalometric angular measurements of Class II patients treated with FFAs and their matched untreated controls. Data collection and analysis: Skeletal, dental, and soft tissue cephalometric data were annualized and stratified according to the time of evaluation in effects. Following risk of bias evaluation, the mean differences (MDs) and 95 % confidence intervals (CIs) were calculated with random-effects models. Patient- and appliance-related subgroup analyses and sensitivity analyses were performed with mixed-effects models. Results: Nine studies were included (244 patients; mean age: 13.5 years and 174 untreated controls; mean age: 12.8 years) reporting on cephalometric effects directly after the removal of FFAs. FFAs were found to induce a small reduction of SNA angle (MD = −0.83 degree/year, 95 % CI: −1.17 to −0.48), a small increase of SNB angle (MD = 0.87 degree/year, 95 % CI: 0.30–1.43), and moderate decrease of ANB angle (MD = −1.74 degree/year, 95 % CI: −2.50 to −0.98) compared to untreated Class II patients. FFA treatment resulted in significant dentoalveolar and soft tissue changes. Several patient- or appliance-related factors seem to affect the treatment outcome. Long-term effectiveness of FFAs could not be assessed due to limited evidence. Conclusions: According to existing evidence, FFAs seem to be effective in improving Class II malocclusion in the short term, although their effects seem to be mainly dentoalveolar rather than skeletal. PMID:25995359

  12. Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries

    NASA Astrophysics Data System (ADS)

    Le Bris, A.; Chehata, N.; Briottet, X.; Paparoditis, N.

    2016-06-01

    In urban areas, information concerning very high resolution land cover and especially material maps are necessary for several city modelling or monitoring applications. That is to say, knowledge concerning the roofing materials or the different kinds of ground areas is required. Airborne remote sensing techniques appear to be convenient for providing such information at a large scale. However, results obtained using most traditional processing methods based on usual red-green-blue-near infrared multispectral images remain limited for such applications. A possible way to improve classification results is to enhance the imagery spectral resolution using superspectral or hyperspectral sensors. In this study, it is intended to design a superspectral sensor dedicated to urban materials classification and this work particularly focused on the selection of the optimal spectral band subsets for such sensor. First, reflectance spectral signatures of urban materials were collected from 7 spectral libraires. Then, spectral optimization was performed using this data set. The band selection workflow included two steps, optimising first the number of spectral bands using an incremental method and then examining several possible optimised band subsets using a stochastic algorithm. The same wrapper relevance criterion relying on a confidence measure of Random Forests classifier was used at both steps. To cope with the limited number of available spectra for several classes, additional synthetic spectra were generated from the collection of reference spectra: intra-class variability was simulated by multiplying reference spectra by a random coefficient. At the end, selected band subsets were evaluated considering the classification quality reached using a rbf svm classifier. It was confirmed that a limited band subset was sufficient to classify common urban materials. The important contribution of bands from the Short Wave Infra-Red (SWIR) spectral domain (1000-2400 nm) to material classification was also shown.

  13. Cheating Tendency in Examinations among Secondary School Students in Nigeria: A Case Study of Schools in the Odukpani Local Government Area, Cross River State

    ERIC Educational Resources Information Center

    Bisong, Nonso Ngozika; Akpama, Felicia; Edet, Pauline B.

    2009-01-01

    This study is designed to examine cheating tendency among secondary school students in Nigeria, with evidence from schools in the Odukpani Local Government Area of Cross River State. A total of 331 respondents in Senior Secondary 3 classes were randomly selected from 10 post-primary schools in the area. A survey questionnaire was used to elicit…

  14. The Investigation of Attitude Changes of Elementary Preservice Teachers in a Competency-Based, Field-Oriented Science Methods Course and Attitude Changes of Classroom Teachers Cooperating with the Field Component.

    ERIC Educational Resources Information Center

    Piper, Martha K.

    Thirty-six students enrolled in an elementary science methods course were randomly selected and given an instrument using Osgood's semantic differential approach the first week of class, the sixth week on campus prior to field experiences, and the thirteenth week following field experiences. The elementary teachers who had observed the university…

  15. Two Universality Classes for the Many-Body Localization Transition

    NASA Astrophysics Data System (ADS)

    Khemani, Vedika; Sheng, D. N.; Huse, David A.

    2017-08-01

    We provide a systematic comparison of the many-body localization (MBL) transition in spin chains with nonrandom quasiperiodic versus random fields. We find evidence suggesting that these belong to two separate universality classes: the first dominated by "intrinsic" intrasample randomness, and the second dominated by external intersample quenched randomness. We show that the effects of intersample quenched randomness are strongly growing, but not yet dominant, at the system sizes probed by exact-diagonalization studies on random models. Thus, the observed finite-size critical scaling collapses in such studies appear to be in a preasymptotic regime near the nonrandom universality class, but showing signs of the initial crossover towards the external-randomness-dominated universality class. Our results provide an explanation for why exact-diagonalization studies on random models see an apparent scaling near the transition while also obtaining finite-size scaling exponents that strongly violate Harris-Chayes bounds that apply to disorder-driven transitions. We also show that the MBL phase is more stable for the quasiperiodic model as compared to the random one, and the transition in the quasiperiodic model suffers less from certain finite-size effects.

  16. Student Performance on Conceptual Questions: Does Instruction Matter?

    NASA Astrophysics Data System (ADS)

    Heron, Paula

    2012-10-01

    As part of the tutorial component of introductory calculus-based physics at the University of Washington, students take weekly pretests that consist of conceptual questions. Pretests are so named because they precede each tutorial, but they are frequently administered after lecture instruction. Many variables associated with class composition and prior instruction could, in principle, affect student performance. Nonetheless, the results are often found to be ``essentially the same'' in all classes. Selected questions for which we have accumulated thousands of responses, from dozens of classes representing different conditions with respect to the textbook in use, the amount of prior instruction, etc., serve as examples. A preliminary analysis suggests that the variation in performance across all classes is essentially random. No statistically significant difference is observed between results obtained before relevant instruction begins and after it has been completed. The results provide evidence that exposure to concepts in lecture and textbook is not sufficient to ensure an improvement in performance on questions that require qualitative reasoning.

  17. Histone deacetylase inhibitors: Isoform selectivity improves survival in a hemorrhagic shock model.

    PubMed

    Chang, Panpan; Weykamp, Michael; Dennahy, Isabel S; Williams, Aaron M; Bhatti, Umar F; Liu, Baoling; Nikolian, Vahagn C; Li, Yongqing; Alam, Hasan B

    2018-05-01

    Hemorrhage is a leading preventable cause of death. Nonselective histone deacetylase inhibitors (HDACIs), such as valproic acid (VPA), have been shown to improve outcomes in hemorrhagic shock (HS). The HDACs can be divided into four functional classes (I, IIa/IIb, III, and IV). Classes I, IIa/IIb, and III have previously been implicated in the pathophysiology of HS. This study aimed to determine which HDAC class, or classes, are responsible for the survival benefit observed with nonselective HDACIs. Survival study: Sprague-Dawley rats were subjected to lethal HS (50% hemorrhage) and randomized to the following groups (n = 8): (1) no treatment, (2) normal saline vehicle, (3) cyclodextrin vehicle, (4) MS275 (class I HDACI), (5) VPA (class I/IIa HDACI), (6) MC1568 (class IIa HDACI), (7) ACY1083 (class IIb HDACI), and (8) EX527 (class III HDACI). Survival was monitored for 24 hours. Mechanistic study: Sprague-Dawley rats were subjected to sublethal HS (40% hemorrhage) and randomized to the same groups (n = 3), excluding EX527, based on results of the survival study. Tissues were harvested at 3 hours posttreatment, and expression of phosphorylated-AKT, β-catenin, acetylated histones H3 and H4, and acetylated α-tubulin were analyzed in myocardial tissue. Survival rate was 12.5% in the untreated group, and did not improve with vehicle or MS275 treatment. EX527 improved survival to 50%, although this did not achieve statistical significance (p = 0.082). However, treatment with VPA, MC1568, and ACY1083 improved survival rates to 87.5%, 75%, and 75%, respectively (p < 0.05). The VPA-induced acetylation of both histones H3 and H4, while MC1568 and ACY1083 increased acetylation of histone H4. ACY1083 also induced acetylation of α-tubulin. All treatment groups, except MS275, increased phosphorylated-AKT, and β-catenin. Inhibition of HDAC classes IIa or IIb, but not class I, activates prosurvival pathways, which may be responsible for the improved outcomes in rodent models of HS.

  18. Modified Angle's Classification for Primary Dentition.

    PubMed

    Chandranee, Kaushik Narendra; Chandranee, Narendra Jayantilal; Nagpal, Devendra; Lamba, Gagandeep; Choudhari, Purva; Hotwani, Kavita

    2017-01-01

    This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3-6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry.

  19. Understanding and Improving the Activity of Flavin Dependent Halogenases via Random and Targeted Mutagenesis

    PubMed Central

    Andorfer, Mary C.

    2018-01-01

    Flavin dependent halogenases (FDHs) catalyze the halogenation of organic substrates by coordinating reactions of reduced flavin, molecular oxygen, and chloride. Targeted and random mutagenesis of these enzymes has been used to both understand and alter their reactivity. These studies have led to insights into residues essential for catalysis and FDH variants with improved stability, expanded substrate scope, and altered site selectivity. Mutations throughout FDH structures have contributed to all of these advances. More recent studies have sought to rationalize the impact of these mutations on FDH function and to identify new FDHs to deepen our understanding of this enzyme class and to expand their utility for biocatalytic applications. PMID:29589959

  20. The impact of clickers instruction on cognitive loads and listening and speaking skills in college English class.

    PubMed

    Yu, Zhonggen; Chen, Wentao; Kong, Yong; Sun, Xiao Ling; Zheng, Jing

    2014-01-01

    Clickers might own a bright future in China if properly introduced although they have not been widely acknowledged as an effective tool to facilitate English learning and teaching in Chinese contexts. By randomly selecting participants from undergraduates in a university in China over four academic years, this study aims to identify the impact of clickers on college English listening and speaking skills, and differences in cognitive loads between clickers and traditional multimedia assisted instruction modes. It was concluded that in China's college English class, compared with multimedia assisted instruction, (1) clickers could improve college English listening skills; (2) clickers could improve college English speaking skills; and (3) clickers could reduce undergraduates' cognitive loads in College English Class. Reasons for the results and defects in this study were also explored and discussed, based on learning, teaching and cognitive load theories. Some Suggestions for future research were also raised.

  1. The Impact of Clickers Instruction on Cognitive Loads and Listening and Speaking Skills in College English Class

    PubMed Central

    Yu, Zhonggen; Chen, Wentao; Kong, Yong; Sun, Xiao Ling; Zheng, Jing

    2014-01-01

    Clickers might own a bright future in China if properly introduced although they have not been widely acknowledged as an effective tool to facilitate English learning and teaching in Chinese contexts. By randomly selecting participants from undergraduates in a university in China over four academic years, this study aims to identify the impact of clickers on college English listening and speaking skills, and differences in cognitive loads between clickers and traditional multimedia assisted instruction modes. It was concluded that in China's college English class, compared with multimedia assisted instruction, (1) clickers could improve college English listening skills; (2) clickers could improve college English speaking skills; and (3) clickers could reduce undergraduates' cognitive loads in College English Class. Reasons for the results and defects in this study were also explored and discussed, based on learning, teaching and cognitive load theories. Some Suggestions for future research were also raised. PMID:25192424

  2. Factors impacting the assessment of maternal culpability in cases of alleged fetal abuse.

    PubMed

    McCoy, Monica L

    2003-01-01

    These studies explored attitudes toward maternal culpability in cases of alleged fetal abuse. In experiment one, general culpability for the use of various substances during pregnancy was assessed as well as the impact of other potentially relevant factors. One hundred and twenty students completed the survey. Participants overwhelmingly supported treating drug use by pregnant women as a criminal offense. With regard to the assessment of more specific questions, the lack of consensus regarding what factors effect culpability is striking. Experiment two examined the possible impact of the mothers' race (White or Black) and social class (Poor or Middle class) on the assessment of culpability. One hundred and sixty-four community members responded to a survey sent to randomly selected persons in upstate South Carolina. The results indicate that at least in response to a brief, written, case scenario, neither race nor social class make a large impact on participants' sanction recommendations.

  3. Multidimensional density shaping by sigmoids.

    PubMed

    Roth, Z; Baram, Y

    1996-01-01

    An estimate of the probability density function of a random vector is obtained by maximizing the output entropy of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's optimization method, applied to the estimated density, yields a recursive estimator for a random variable or a random sequence. A constrained connectivity structure yields a linear estimator, which is particularly suitable for "real time" prediction. A Gaussian nonlinearity yields a closed-form solution for the network's parameters, which may also be used for initializing the optimization algorithm when other nonlinearities are employed. A triangular connectivity between the neurons and the input, which is naturally suggested by the statistical setting, reduces the number of parameters. Applications to classification and forecasting problems are demonstrated.

  4. Simulating the component counts of combinatorial structures.

    PubMed

    Arratia, Richard; Barbour, A D; Ewens, W J; Tavaré, Simon

    2018-02-09

    This article describes and compares methods for simulating the component counts of random logarithmic combinatorial structures such as permutations and mappings. We exploit the Feller coupling for simulating permutations to provide a very fast method for simulating logarithmic assemblies more generally. For logarithmic multisets and selections, this approach is replaced by an acceptance/rejection method based on a particular conditioning relationship that represents the distribution of the combinatorial structure as that of independent random variables conditioned on a weighted sum. We show how to improve its acceptance rate. We illustrate the method by estimating the probability that a random mapping has no repeated component sizes, and establish the asymptotic distribution of the difference between the number of components and the number of distinct component sizes for a very general class of logarithmic structures. Copyright © 2018. Published by Elsevier Inc.

  5. Prevalence of paratuberculosis in the dairy goat and dairy sheep industries in Ontario, Canada.

    PubMed

    Bauman, Cathy A; Jones-Bitton, Andria; Menzies, Paula; Toft, Nils; Jansen, Jocelyn; Kelton, David

    2016-02-01

    A cross-sectional study was undertaken (October 2010 to August 2011) to estimate the prevalence of paratuberculosis in the small ruminant dairy industries in Ontario, Canada. Blood and feces were sampled from 580 goats and 397 sheep (lactating and 2 y of age or older) that were randomly selected from 29 randomly selected dairy goat herds and 21 convenience-selected dairy sheep flocks. Fecal samples were analyzed using bacterial culture (BD BACTEC MGIT 960) and polymerase chain reaction (Tetracore); serum samples were tested with the Prionics Parachek enzyme-linked immunosorbent assay (ELISA). Using 3-test latent class Bayesian models, true farm-level prevalence was estimated to be 83.0% [95% probability interval (PI): 62.6% to 98.1%] for dairy goats and 66.8% (95% PI: 41.6% to 91.4%) for dairy sheep. The within-farm true prevalence for dairy goats was 35.2% (95% PI: 23.0% to 49.8%) and for dairy sheep was 48.3% (95% PI: 27.6% to 74.3%). These data indicate that a paratuberculosis control program for small ruminants is needed in Ontario.

  6. Selection of habitats by Emperor Geese during brood rearing

    USGS Publications Warehouse

    Schmutz, J.A.

    2001-01-01

    Although forage quality strongly affects gosling growth and consequently juvenile survival, the relative use of different plant communities by brood rearing geese has been poorly studied. On the Yukon-Kuskokwim Delta, Alaska, population growth and juvenile recruitment of Emperor Geese (Chen canagica) are comparatively low, and it is unknown whether their selection of habitats during brood rearing differs from other goose species. Radio-telemetry was used to document the use of habitats by 56 families of Emperor Geese in a 70 km2 portion of the Yukon-Kuskokwim Delta during brood rearing in 1994-1996. When contrasted with available habitats (a set of six habitat classes), as estimated from 398 random sampling locations, Emperor Geese strongly selected Saline Ponds, Mudflat, and Ramenskii Meadow habitats and avoided Levee Meadow, Bog Meadow, and Sedge Meadow. These selected habitats were the most saline, comprised one-third of the study area, and 43% of all locations were in Ramenskii Meadow. I contrasted these Emperor Goose locations with habitats used by the composite goose community, as inferred from the presence of goose feces at random locations. The marked difference between groups in this comparison implied that Cackling Canada Geese (Branta canadensis minima) and Greater White-fronted Geese (Anser albifrons) collectively selected much different brood rearing habitats than Emperor Geese. Received 20 February 2001, accepted 18 April 2001.

  7. Avian influenza virus and Newcastle disease virus (NDV) surveillance in commercial breeding farm in China and the characterization of Class I NDV isolates.

    PubMed

    Hu, Beixia; Huang, Yanyan; He, Yefeng; Xu, Chuantian; Lu, Xishan; Zhang, Wei; Meng, Bin; Yan, Shigan; Zhang, Xiumei

    2010-07-29

    In order to determine the actual prevalence of avian influenza virus (AIV) and Newcastle disease virus (NDV) in ducks in Shandong province of China, extensive surveillance studies were carried out in the breeding ducks of an intensive farm from July 2007 to September 2008. Each month cloacal and tracheal swabs were taken from 30 randomly selected birds that appeared healthy. All of the swabs were negative for influenza A virus recovery, whereas 87.5% of tracheal swabs and 100% cloacal swabs collected in September 2007, were positive for Newcastle disease virus isolation. Several NDV isolates were recovered from tracheal and cloacal swabs of apparently healthy ducks. All of the isolates were apathogenic as determined by the MDT and ICPI. The HN gene and the variable region of F gene (nt 47-420) of four isolates selected at random were sequenced. A 374 bp region of F gene and the full length of HN gene were used for phylogenetic analysis. Four isolates were identified as the same isolate based on nucleotide sequences identities of 99.2-100%, displaying a closer phylogenetic relationship to lentogenic Class I viruses. There were 1.9-9.9% nucleotide differences between the isolates and other Class I virus in the variable region of F gene (nt 47-420), whereas there were 38.5-41.2% nucleotide difference between the isolates and Class II viruses. The amino acid sequences of the F protein cleavage sites in these isolates were 112-ERQERL-117. The full length of HN gene of these isolates was 1851 bp, coding 585 amino acids. The homology analysis of the nucleotide sequence of HN gene indicated that there were 2.0-4.2% nucleotide differences between the isolates and other Class I viruses, whereas there were 29.5-40.9% differences between the isolates and Class II viruses. The results shows that these isolates are not phylogenetically related to the vaccine strain (LaSota). This study adds to the understanding of the ecology of influenza viruses and Newcastle disease viruses in ducks and emphasizes the need for constant surveillance in times of an ongoing and expanding epidemic of AIV and NDV. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  8. Effectiveness of orthodontic treatment with functional appliances on maxillary growth in the short term: A systematic review and meta-analysis.

    PubMed

    Nucera, Riccardo; Lo Giudice, Antonino; Rustico, Lorenzo; Matarese, Giovanni; Papadopoulos, Moschos A; Cordasco, Giancarlo

    2016-05-01

    The aim of this systematic review was to evaluate the treatment effects on maxillary growth of removable functional appliances that advance the mandible to a more forward position in patients with Class II malocclusion. Sixteen electronic databases and reference lists of studies were searched up to April 2015. Only randomized clinical trials and prospective controlled clinical trials investigating Class II growing patients treated with removable functional appliances were included. Two authors independently accomplished study selection, data extraction, and risk of bias assessment. All pooled analyses of data were based on random-effects models. Statistical heterogeneity was evaluated. In total, 14 studies were included (5 randomized clinical trials, 9 prospective controlled clinical trials) that collected data from 765 patients (405 treated, 360 untreated controls). The mean differences in treatment effect of functional appliances, relative to the untreated controls, were -0.61° per year (95% CI, -0.69° to -0.25°) for SNA angle, -0.61 mm per year (95% CI, -0.90 to -0.32 mm) for anterior maxillary displacement, and +0.07° per year (95% CI, -0.17° to +0.32°) for maxillary plane rotation. Removable functional appliances in Class II growing patients have a slight inhibitory effect on the sagittal growth of the maxilla in the short term, but they do not seem to affect rotation of the maxillary plane. Copyright © 2016 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

  9. Warfarin versus aspirin in patients with reduced cardiac ejection fraction (WARCEF): rationale, objectives, and design.

    PubMed

    Pullicino, Patrick; Thompson, John L P; Barton, Bruce; Levin, Bruce; Graham, Susan; Freudenberger, Ronald S

    2006-02-01

    Warfarin is widely prescribed for patients with heart failure without level 1 evidence, and an adequately powered randomized study is needed. The Warfarin versus Aspirin in Reduced Cardiac Ejection Fraction study is a National Institutes of Health-funded, randomized, double-blind clinical trial with a target enrollment of 2860 patients. It is designed to test with 90% power the 2-sided primary null hypothesis of no difference between warfarin (International Normalized Ratio 2.5-3) and aspirin (325 mg) in 3- to 5-year event-free survival for the composite endpoint of death, or stroke (ischemic or hemorrhagic) among patients with cardiac ejection fraction < or =35% who do not have atrial fibrillation or mechanical prosthetic heart valves. Secondary analyses will compare warfarin and aspirin for reduction of all-cause mortality, ischemic stroke, and myocardial infarction (MI), balanced against the risk of intracerebral hemorrhage, among women and African Americans; and compare warfarin and aspirin for prevention of stroke alone. Randomization is stratified by site, New York Heart Association (NYHA) heart class (I vs II-IV), and stroke or transient ischemic attack (TIA) within 1 year before randomization versus no stroke or TIA in that period. NYHA class I patients will not exceed 20%, and the study has a target of 20% (or more) patients with stroke or TIA within 12 months. Randomized patients receive active warfarin plus placebo or active aspirin plus placebo, double-blind. The results should help guide the selection of optimum antithrombotic therapy for patients with left ventricular dysfunction.

  10. Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar

    NASA Astrophysics Data System (ADS)

    Fedrigo, Melissa; Newnham, Glenn J.; Coops, Nicholas C.; Culvenor, Darius S.; Bolton, Douglas K.; Nitschke, Craig R.

    2018-02-01

    Light detection and ranging (lidar) data have been increasingly used for forest classification due to its ability to penetrate the forest canopy and provide detail about the structure of the lower strata. In this study we demonstrate forest classification approaches using airborne lidar data as inputs to random forest and linear unmixing classification algorithms. Our results demonstrated that both random forest and linear unmixing models identified a distribution of rainforest and eucalypt stands that was comparable to existing ecological vegetation class (EVC) maps based primarily on manual interpretation of high resolution aerial imagery. Rainforest stands were also identified in the region that have not previously been identified in the EVC maps. The transition between stand types was better characterised by the random forest modelling approach. In contrast, the linear unmixing model placed greater emphasis on field plots selected as endmembers which may not have captured the variability in stand structure within a single stand type. The random forest model had the highest overall accuracy (84%) and Cohen's kappa coefficient (0.62). However, the classification accuracy was only marginally better than linear unmixing. The random forest model was applied to a region in the Central Highlands of south-eastern Australia to produce maps of stand type probability, including areas of transition (the 'ecotone') between rainforest and eucalypt forest. The resulting map provided a detailed delineation of forest classes, which specifically recognised the coalescing of stand types at the landscape scale. This represents a key step towards mapping the structural and spatial complexity of these ecosystems, which is important for both their management and conservation.

  11. The Relationship of Class Size Effects and Teacher Salary

    ERIC Educational Resources Information Center

    Peevely, Gary; Hedges, Larry; Nye, Barbara A.

    2005-01-01

    The effects of class size on academic achievement have been studied for decades. Although the results of small-scale, randomized experiments and large-scale, econometric studies point to positive effects of small classes, some scholars see the evidence as ambiguous. Recent analyses from a 4-year, large-scale, randomized experiment on the effects…

  12. A new class of random processes with application to helicopter noise

    NASA Technical Reports Server (NTRS)

    Hardin, Jay C.; Miamee, A. G.

    1989-01-01

    The concept of dividing random processes into classes (e.g., stationary, locally stationary, periodically correlated, and harmonizable) has long been employed. A new class of random processes is introduced which includes many of these processes as well as other interesting processes which fall into none of the above classes. Such random processes are denoted as linearly correlated. This class is shown to include the familiar stationary and periodically correlated processes as well as many other, both harmonizable and non-harmonizable, nonstationary processes. When a process is linearly correlated for all t and harmonizable, its two-dimensional power spectral density S(x) (omega 1, omega 2) is shown to take a particularly simple form, being non-zero only on lines such that omega 1 to omega 2 = + or - r(k) where the r(k's) are (not necessarily equally spaced) roots of a characteristic function. The relationship of such processes to the class of stationary processes is examined. In addition, the application of such processes in the analysis of typical helicopter noise signals is described.

  13. A new class of random processes with application to helicopter noise

    NASA Technical Reports Server (NTRS)

    Hardin, Jay C.; Miamee, A. G.

    1989-01-01

    The concept of dividing random processes into classes (e.g., stationary, locally stationary, periodically correlated, and harmonizable) has long been employed. A new class of random processes is introduced which includes many of these processes as well as other interesting processes which fall into none of the above classes. Such random processes are denoted as linearly correlated. This class is shown to include the familiar stationary and periodically correlated processes as well as many other, both harmonizable and non-harmonizable, nonstationary processes. When a process is linearly correlated for all t and harmonizable, its two-dimensional power spectral density S(x)(omega 1, omega 2) is shown to take a particularly simple form, being non-zero only on lines such that omega 1 to omega 2 = + or - r(k) where the r(k's) are (not necessarily equally spaced) roots of a characteristic function. The relationship of such processes to the class of stationary processes is examined. In addition, the application of such processes in the analysis of typical helicopter noise signals is described.

  14. Health lifestyles in Ukraine.

    PubMed

    Cockerham, William C; Hinote, Brian P; Abbott, Pamela; Haerpfer, Christian

    2005-01-01

    Several studies have identified negative health lifestyles as a primary determinant of the mortality crisis in Europe's post-communist states, but little is known about Ukraine. In order to address this gap in the literature, this paper provides data on Ukrainian health lifestyles. Data were collected by face-to-face interviews in the households (N = 2 400) of a random sample of respondents in Ukraine in November, 2001. The sample was selected using multi-stage random sampling with stratification by region and area (urban/rural). Data were analyzed using logistic regression. Male gender was found to be the most powerful single predictor of negative health lifestyles as shown in the results for frequent drinking, heavy vodka use at one occasion, smoking, and diet. Males rated their health status better than females, but over one-third of the males and one-half of the females rated their health status as rather bad or bad. Gender and class differences in health lifestyle practices appear to be key variables, with working-class males showing the most negative practices. The results for health status suggest that the overall level of health in Ukraine is not good.

  15. Fuzziness-based active learning framework to enhance hyperspectral image classification performance for discriminative and generative classifiers

    PubMed Central

    2018-01-01

    Hyperspectral image classification with a limited number of training samples without loss of accuracy is desirable, as collecting such data is often expensive and time-consuming. However, classifiers trained with limited samples usually end up with a large generalization error. To overcome the said problem, we propose a fuzziness-based active learning framework (FALF), in which we implement the idea of selecting optimal training samples to enhance generalization performance for two different kinds of classifiers, discriminative and generative (e.g. SVM and KNN). The optimal samples are selected by first estimating the boundary of each class and then calculating the fuzziness-based distance between each sample and the estimated class boundaries. Those samples that are at smaller distances from the boundaries and have higher fuzziness are chosen as target candidates for the training set. Through detailed experimentation on three publically available datasets, we showed that when trained with the proposed sample selection framework, both classifiers achieved higher classification accuracy and lower processing time with the small amount of training data as opposed to the case where the training samples were selected randomly. Our experiments demonstrate the effectiveness of our proposed method, which equates favorably with the state-of-the-art methods. PMID:29304512

  16. Paths to tobacco abstinence: A repeated-measures latent class analysis.

    PubMed

    McCarthy, Danielle E; Ebssa, Lemma; Witkiewitz, Katie; Shiffman, Saul

    2015-08-01

    Knowledge of smoking change processes may be enhanced by identifying pathways to stable abstinence. We sought to identify latent classes of smokers based on their day-to-day smoking status in the first weeks of a cessation attempt. We examined treatment effects on class membership and compared classes on baseline individual differences and 6-month abstinence rates. In this secondary analysis of a double-blind randomized placebo-controlled clinical trial (N = 1,433) of 5 smoking cessation pharmacotherapies (nicotine patch, nicotine lozenge, bupropion SR, patch and lozenge, or bupropion SR and lozenge), we conducted repeated-measures latent class analysis of daily smoking status (any smoking vs. none) for the first 27 days of a quit attempt. Treatment and covariate relations with latent class membership were examined. Distal outcome analysis compared confirmed 6-month abstinence rates among the latent classes. A 5-class solution was selected. Three-quarters of smokers were in stable smoking or abstinent classes, but 25% were in classes with unstable abstinence probabilities over time. Active treatment (compared to placebo), and particularly the patch and lozenge combination, promoted early quitting. Latent classes differed in 6-month abstinence rates and on several baseline variables, including nicotine dependence, quitting history, self-efficacy, sleep disturbance, and minority status. Repeated-measures latent class analysis identified latent classes of smoking change patterns affected by treatment, related to known risk factors, and predictive of distal outcomes. Tracking behavior early in a change attempt may identify prognostic patterns of change and facilitate adaptive treatment planning. (c) 2015 APA, all rights reserved).

  17. Tooth size discrepancies in Class II division 1 and Class III malocclusion requiring surgical-orthodontic or orthodontic treatment.

    PubMed

    McSwiney, Timothy P; Millett, Declan T; McIntyre, Grant T; Barry, Mark K; Cronin, Michael S

    2014-06-01

    To compare mean anterior (AR) and mean overall (OR) tooth size ratios, prevalence of clinically significant tooth size discrepancies (TSDs) and correlation between AR and OR in subjects with Class II division 1 and Class III malocclusion treated by surgical-orthodontic or orthodontic means. Retrospective, cross-sectional. State-funded and private clinics. From pre-treatment cohorts of 770 surgical and 610 non-surgical subjects, Class II division 1 and Class III malocclusion groups were identified with 60 surgical and 60 non-surgical subjects, comprising 30 males and 30 females, in each. AR and OR were calculated by landmarking digital models. Differences in AR and OR and their relationship were analysed using two-way analysis of variance (ANOVA) and a correlation coefficient, respectively. The proportions of the surgical and non-surgical groups with a TSD were assessed using logistic regression. Intra-examiner reproducibility involved re-landmarking 30 randomly selected image sets and differences in ARs and ORs were compared using a paired t-test. Random error was assessed using the intraclass correlation coefficient (ICC). Analyses were performed using SAS (SAS Institute Inc., Cary, NC, USA) at the 5% level of significance. There were no statistically significant differences associated with the measurement of either the mean AR (P = 0·913) or the mean OR (P = 0·874). ICC values were very high (AR = 0·95; OR = 0·90). Differences existed between both Class II and Class III surgical (AR: P<0·001; OR: P<0·001) and non-surgical groups (AR: P = 0·012; OR: P = 0·003). The AR and OR relationship was strong (correlation coefficient = 0·72). The highest percentage of clinically significant TSDs was seen in the AR of both Class II and Class III surgical groups (23·3%). In the cohort examined: AR and OR differed significantly for malocclusion groups. The prevalence of clinically significant TSDs did not differ significantly between surgical and non-surgical groups although the highest percentage of clinically significant TSDs was recorded for AR in Class II and Class III surgical cases. AR and OR were closely related. © 2014 British Orthodontic Society.

  18. Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences.

    PubMed

    Warris, Sven; Boymans, Sander; Muiser, Iwe; Noback, Michiel; Krijnen, Wim; Nap, Jan-Peter

    2014-01-13

    Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification.

  19. A new educational film control for use in studies of active mind-body therapies: acceptability and feasibility.

    PubMed

    Innes, Kim E; Selfe, Terry Kit; Alexander, Gina K; Taylor, Ann Gill

    2011-05-01

    The study objectives were to ascertain whether a novel educational film class is an acceptable and feasible comparison group for a randomized controlled trial regarding the effects of an active mind-body therapy on cardiovascular disease risk in postmenopausal women. Seventy-five (75) participants attended a baseline assessment visit and were randomly assigned to either a yoga group or an educational film (control) group. Both groups attended two 90-minute classes/week for 8 weeks, followed by a second assessment visit. Those not attending the second assessment were classified as dropouts. Over 60 films covering a range of topics relevant to the study population were evaluated; 15 were selected by consensus of at least 2 researchers and 1 layperson. Each film session followed the same format: an informal greeting period, viewing of the film, and a 15-minute postfilm discussion. To determine acceptability and feasibility of the film class, potential between-group differences in dropout and attendance were examined, and participant feedback given during class and on end-of-study questionnaires were evaluated. The relation between group assignment and dropout was not significant (χ(2) [1, N = 75] = 0.14, p = 0.71). One-way analysis of variance (ANOVA) indicated no significant between-group difference in number of classes attended for the yoga (X = 13.67 ± 3.10) versus film group (13.26 ± 1.97), F(1,63) = 0.39, p = 0.53). Participant feedback regarding the film program was positive. These findings support the feasibility and acceptability of this educational film control. Easy to standardize and tailor to a variety of populations, this film program may offer an attractive alternative to the more traditional educational control.

  20. Effect of lecture instruction on student performance on qualitative questions

    NASA Astrophysics Data System (ADS)

    Heron, Paula R. L.

    2015-06-01

    The impact of lecture instruction on student conceptual understanding in physics has been the subject of research for several decades. Most studies have reported disappointingly small improvements in student performance on conceptual questions despite direct instruction on the relevant topics. These results have spurred a number of attempts to improve learning in physics courses through new curricula and instructional techniques. This paper contributes to the research base through a retrospective analysis of 20 randomly selected qualitative questions on topics in kinematics, dynamics, electrostatics, waves, and physical optics that have been given in introductory calculus-based physics at the University of Washington over a period of 15 years. In some classes, questions were administered after relevant lecture instruction had been completed; in others, it had yet to begin. Simple statistical tests indicate that the average performance of the "after lecture" classes was significantly better than that of the "before lecture" classes for 11 questions, significantly worse for two questions, and indistinguishable for the remaining seven. However, the classes had not been randomly assigned to be tested before or after lecture instruction. Multiple linear regression was therefore conducted with variables (such as class size) that could plausibly lead to systematic differences in performance and thus obscure (or artificially enhance) the effect of lecture instruction. The regression models support the results of the simple tests for all but four questions. In those cases, the effect of lecture instruction was reduced to a nonsignificant level, or increased to a significant, negative level when other variables were considered. Thus the results provide robust evidence that instruction in lecture can increase student ability to give correct answers to conceptual questions but does not necessarily do so; in some cases it can even lead to a decrease.

  1. Psychotropic medication patterns among youth in foster care.

    PubMed

    Zito, Julie M; Safer, Daniel J; Sai, Devadatta; Gardner, James F; Thomas, Diane; Coombes, Phyllis; Dubowski, Melissa; Mendez-Lewis, Maria

    2008-01-01

    Studies have revealed that youth in foster care covered by Medicaid insurance receive psychotropic medication at a rate > 3 times that of Medicaid-insured youth who qualify by low family income. Systematic data on patterns of medication treatment, particularly concomitant drugs, for youth in foster care are limited. The purpose of this work was to describe and quantify patterns of psychotropic monotherapy and concomitant therapy prescribed to a randomly selected, 1-month sample of youth in foster care who had been receiving psychotropic medication. METHODS. Medicaid data were accessed for a July 2004 random sample of 472 medicated youth in foster care aged 0 through 19 years from a southwestern US state. Psychotropic medication treatment data were identified by concomitant pattern, frequency, medication class, subclass, and drug entity and were analyzed in relation to age group; gender; race or ethnicity; International Classification of Diseases, Ninth Revision, psychiatric diagnosis; and physician specialty. Of the foster children who had been dispensed psychotropic medication, 41.3% received > or = 3 different classes of these drugs during July 2004, and 15.9% received > or = 4 different classes. The most frequently used medications were antidepressants (56.8%), attention-deficit/hyperactivity disorder drugs (55.9%), and antipsychotic agents (53.2%). The use of specific psychotropic medication classes varied little by diagnostic grouping. Psychiatrists prescribed 93% of the psychotropic medication dispensed to youth in foster care. The use of > or = 2 drugs within the same psychotropic medication class was noted in 22.2% of those who were given prescribed drugs concomitantly. Concomitant psychotropic medication treatment is frequent for youth in foster care and lacks substantive evidence as to its effectiveness and safety.

  2. Modified Angle's Classification for Primary Dentition

    PubMed Central

    Chandranee, Kaushik Narendra; Chandranee, Narendra Jayantilal; Nagpal, Devendra; Lamba, Gagandeep; Choudhari, Purva; Hotwani, Kavita

    2017-01-01

    Aim: This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Methods: Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3–6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Results: Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Conclusions: Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry. PMID:29326514

  3. Study of relation of continuing medical education to quality of family physicians' care.

    PubMed

    Dunn, E V; Bass, M J; Williams, J I; Borgiel, A E; MacDonald, P; Spasoff, R A

    1988-10-01

    A random sample of 120 physicians in Ontario was studied to assess quality of care in primary care and test an hypothesis that quality of care was related to continuing medical education (CME) activities. The quality-of-care scores were obtained by an in-office audit of a random selection of charts. The scores were global scores for charting, prevention, the use of 13 classes of drugs, and care of a two-year period for 182 different diagnoses. There were no relationships between global quality-of-care scores based on these randomly chosen charts and either the type or quantity of the physicians' CME activities. These activities were reading journals, attending rounds, attending scientific conferences, having informal consultations, using audio and video cassettes, and engaging in self-assessment. The implications of these findings are significant for future research in CME and for planners of present CME programs.

  4. Risk of fractures with selective serotonin-reuptake inhibitors or tricyclic antidepressants.

    PubMed

    Ginzburg, Regina; Rosero, Enma

    2009-01-01

    To evaluate the literature associating the risk of fracture during antidepressant therapy. Literature was identified via MEDLINE (1970-August 2008) using the search terms selective serotonin-reuptake inhibitors, tricyclic antidepressants, antidepressants, and fracture. Reference citations from publications identified were also reviewed. All articles in English identified from the data sources were evaluated. Selective serotonin-reuptake inhibitors (SSRIs) are generally prescribed over other classes of antidepressants because they are considered to be relatively safer. Recent evidence, however, suggests that SSRIs may be associated with an increased risk of fractures. Thirteen clinical studies were identified in the literature search (7 case controls, 5 prospective cohorts, 1 cross-sectional). Most studies compared SSRIs with tricyclic antidepressants (TCAs) and found similar or greater risk of fracture associated with use of an SSRI. This risk appeared to be highest at the beginning of therapy with TCAs and eventually diminished. SSRI risk tended to increase slightly over time. No risk was seen with other classes of antidepressants. However, the number of patients using antidepressants was low. There may be a possible correlation with SSRI or TCA use and risk of fracture. Prospective, randomized controlled trials with sufficient patient samples are needed to verify this finding.

  5. Comparison of temporomandibular joint and ramus morphology between class II and class III cases before and after bi-maxillary osteotomy.

    PubMed

    Iguchi, Ran; Yoshizawa, Kunio; Moroi, Akinori; Tsutsui, Takamitsu; Hotta, Asami; Hiraide, Ryota; Takayama, Akihiro; Tsunoda, Tatsuya; Saito, Yuki; Sato, Momoko; Baba, Nana; Ueki, Koichiro

    2017-12-01

    The purpose of this study was to compare changes in temporomandibular joint (TMJ) and ramus morphology between class II and III cases before and after sagittal split ramus osteotomy (SSRO) and Le Fort I osteotomy. The subjects were 39 patients (78 sides) who underwent bi-maxillary surgery. They consisted of 2 groups (18 class II cases and 21 class III cases), and were selected randomly from among patients who underwent surgery between 2012 and 2016. The TMJ disc tissue and joint effusion were assessed by magnetic resonance imaging (MRI) and the TMJ space, condylar height, ramus height, ramus inclination and condylar square were assessed by computed tomography (CT), pre- and post-operatively. The number of joints with anterior disc displacement in class II was significantly higher than that in class III (p < 0.0001). However, there were no significant differences between the two classes regarding ratio of joint symptoms and ratio of joint effusion pre- and post-operatively. Class II was significantly better than class III regarding reduction ratio of condylar height (p < 0.0001) and square (p = 0.0005). The study findings suggest that condylar morphology could change in both class II and III after bi-maxillary surgery. The findings of the numerical analysis also demonstrated that reduction of condylar volume occurred frequently in class II, although TMJ disc position classification did not change significantly, as previously reported. Copyright © 2017 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

  6. Indicators of satisfaction in clickers-aided EFL class.

    PubMed

    Yu, Zhonggen

    2015-01-01

    How to identify whether students are satisfied with clickers-aided EFL class might be largely a mystery for most researchers since satisfaction is deeply hidden in human psychology which is subtle and intangible. This study, by using bivariate correlation analysis and structural equation modeling, survey scales claimed both valid and internally consistent, and data collected from randomly selected 227 participants, explored the indicators of satisfaction in clickers-aided EFL class, together with gender differences in the indicators. It was concluded that satisfaction was positively correlated with interaction, self-efficacy and self-regulation in clickers-aided EFL class without statistically significant gender differences. Furthermore, interaction, self-efficacy and self-regulation were mutually and significantly correlated. Although indicators of satisfaction might not be limited to these three factors, the findings should be helpful to future researchers who desire to determine whether users are satisfied with the polling technology. Then teachers could decide what teaching style and contents should be adopted. In order to satisfy users of clickers, future lecturing might be designed to promote peer interaction, self-efficacy and self-regulation.

  7. Indicators of satisfaction in clickers-aided EFL class

    PubMed Central

    Yu, Zhonggen

    2015-01-01

    How to identify whether students are satisfied with clickers-aided EFL class might be largely a mystery for most researchers since satisfaction is deeply hidden in human psychology which is subtle and intangible. This study, by using bivariate correlation analysis and structural equation modeling, survey scales claimed both valid and internally consistent, and data collected from randomly selected 227 participants, explored the indicators of satisfaction in clickers-aided EFL class, together with gender differences in the indicators. It was concluded that satisfaction was positively correlated with interaction, self-efficacy and self-regulation in clickers-aided EFL class without statistically significant gender differences. Furthermore, interaction, self-efficacy and self-regulation were mutually and significantly correlated. Although indicators of satisfaction might not be limited to these three factors, the findings should be helpful to future researchers who desire to determine whether users are satisfied with the polling technology. Then teachers could decide what teaching style and contents should be adopted. In order to satisfy users of clickers, future lecturing might be designed to promote peer interaction, self-efficacy and self-regulation. PMID:25999898

  8. Latent Profile Analysis of Schizotypy and Paranormal Belief: Associations with Probabilistic Reasoning Performance

    PubMed Central

    Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew

    2018-01-01

    This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4. PMID:29434562

  9. Latent Profile Analysis of Schizotypy and Paranormal Belief: Associations with Probabilistic Reasoning Performance.

    PubMed

    Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew

    2018-01-01

    This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4.

  10. Distinguishing functional polymorphism from random variation in the sequences of >10,000 HLA-A, -B and -C alleles.

    PubMed

    Robinson, James; Guethlein, Lisbeth A; Cereb, Nezih; Yang, Soo Young; Norman, Paul J; Marsh, Steven G E; Parham, Peter

    2017-06-01

    HLA class I glycoproteins contain the functional sites that bind peptide antigens and engage lymphocyte receptors. Recently, clinical application of sequence-based HLA typing has uncovered an unprecedented number of novel HLA class I alleles. Here we define the nature and extent of the variation in 3,489 HLA-A, 4,356 HLA-B and 3,111 HLA-C alleles. This analysis required development of suites of methods, having general applicability, for comparing and analyzing large numbers of homologous sequences. At least three amino-acid substitutions are present at every position in the polymorphic α1 and α2 domains of HLA-A, -B and -C. A minority of positions have an incidence >1% for the 'second' most frequent nucleotide, comprising 70 positions in HLA-A, 85 in HLA-B and 54 in HLA-C. The majority of these positions have three or four alternative nucleotides. These positions were subject to positive selection and correspond to binding sites for peptides and receptors. Most alleles of HLA class I (>80%) are very rare, often identified in one person or family, and they differ by point mutation from older, more common alleles. These alleles with single nucleotide polymorphisms reflect the germ-line mutation rate. Their frequency predicts the human population harbors 8-9 million HLA class I variants. The common alleles of human populations comprise 42 core alleles, which represent all selected polymorphism, and recombinants that have assorted this polymorphism.

  11. Distinguishing functional polymorphism from random variation in the sequences of >10,000 HLA-A, -B and -C alleles

    PubMed Central

    Cereb, Nezih; Yang, Soo Young; Marsh, Steven G. E.; Parham, Peter

    2017-01-01

    HLA class I glycoproteins contain the functional sites that bind peptide antigens and engage lymphocyte receptors. Recently, clinical application of sequence-based HLA typing has uncovered an unprecedented number of novel HLA class I alleles. Here we define the nature and extent of the variation in 3,489 HLA-A, 4,356 HLA-B and 3,111 HLA-C alleles. This analysis required development of suites of methods, having general applicability, for comparing and analyzing large numbers of homologous sequences. At least three amino-acid substitutions are present at every position in the polymorphic α1 and α2 domains of HLA-A, -B and -C. A minority of positions have an incidence >1% for the ‘second’ most frequent nucleotide, comprising 70 positions in HLA-A, 85 in HLA-B and 54 in HLA-C. The majority of these positions have three or four alternative nucleotides. These positions were subject to positive selection and correspond to binding sites for peptides and receptors. Most alleles of HLA class I (>80%) are very rare, often identified in one person or family, and they differ by point mutation from older, more common alleles. These alleles with single nucleotide polymorphisms reflect the germ-line mutation rate. Their frequency predicts the human population harbors 8–9 million HLA class I variants. The common alleles of human populations comprise 42 core alleles, which represent all selected polymorphism, and recombinants that have assorted this polymorphism. PMID:28650991

  12. Contrasting evolutionary histories of MHC class I and class II loci in grouse—Effects of selection and gene conversion

    USGS Publications Warehouse

    Minias, Piotr; Bateson, Zachary W.; Whittingham, Linda A.; Johnson, Jeff A.; Oyler-McCance, Sara J.; Dunn, Peter O.

    2016-01-01

    Genes of the major histocompatibility complex (MHC) encode receptor molecules that are responsible for recognition of intracellular and extracellular pathogens (class I and class II genes, respectively) in vertebrates. Given the different roles of class I and II MHC genes, one might expect the strength of selection to differ between these two classes. Different selective pressures may also promote different rates of gene conversion at each class. Despite these predictions, surprisingly few studies have looked at differences between class I and II genes in terms of both selection and gene conversion. Here, we investigated the molecular evolution of MHC class I and II genes in five closely related species of prairie grouse (Centrocercus and Tympanuchus) that possess one class I and two class II loci. We found striking differences in the strength of balancing selection acting on MHC class I versus class II genes. More than half of the putative antigen-binding sites (ABS) of class II were under positive or episodic diversifying selection, compared with only 10% at class I. We also found that gene conversion had a stronger role in shaping the evolution of MHC class II than class I. Overall, the combination of strong positive (balancing) selection and frequent gene conversion has maintained higher diversity of MHC class II than class I in prairie grouse. This is one of the first studies clearly demonstrating that macroevolutionary mechanisms can act differently on genes involved in the immune response against intracellular and extracellular pathogens.

  13. Contrasting evolutionary histories of MHC class I and class II loci in grouse—effects of selection and gene conversion

    PubMed Central

    Minias, P; Bateson, Z W; Whittingham, L A; Johnson, J A; Oyler-McCance, S; Dunn, P O

    2016-01-01

    Genes of the major histocompatibility complex (MHC) encode receptor molecules that are responsible for recognition of intracellular and extracellular pathogens (class I and class II genes, respectively) in vertebrates. Given the different roles of class I and II MHC genes, one might expect the strength of selection to differ between these two classes. Different selective pressures may also promote different rates of gene conversion at each class. Despite these predictions, surprisingly few studies have looked at differences between class I and II genes in terms of both selection and gene conversion. Here, we investigated the molecular evolution of MHC class I and II genes in five closely related species of prairie grouse (Centrocercus and Tympanuchus) that possess one class I and two class II loci. We found striking differences in the strength of balancing selection acting on MHC class I versus class II genes. More than half of the putative antigen-binding sites (ABS) of class II were under positive or episodic diversifying selection, compared with only 10% at class I. We also found that gene conversion had a stronger role in shaping the evolution of MHC class II than class I. Overall, the combination of strong positive (balancing) selection and frequent gene conversion has maintained higher diversity of MHC class II than class I in prairie grouse. This is one of the first studies clearly demonstrating that macroevolutionary mechanisms can act differently on genes involved in the immune response against intracellular and extracellular pathogens. PMID:26860199

  14. Test-retest reliability of jump execution variables using mechanography: a comparison of jump protocols.

    PubMed

    Fitzgerald, John S; Johnson, LuAnn; Tomkinson, Grant; Stein, Jesse; Roemmich, James N

    2018-05-01

    Mechanography during the vertical jump may enhance screening and determining mechanistic causes underlying physical performance changes. Utility of jump mechanography for evaluation is limited by scant test-retest reliability data on force-time variables. This study examined the test-retest reliability of eight jump execution variables assessed from mechanography. Thirty-two women (mean±SD: age 20.8 ± 1.3 yr) and 16 men (age 22.1 ± 1.9 yr) attended a familiarization session and two testing sessions, all one week apart. Participants performed two variations of the squat jump with squat depth self-selected and controlled using a goniometer to 80º knee flexion. Test-retest reliability was quantified as the systematic error (using effect size between jumps), random error (using coefficients of variation), and test-retest correlations (using intra-class correlation coefficients). Overall, jump execution variables demonstrated acceptable reliability, evidenced by small systematic errors (mean±95%CI: 0.2 ± 0.07), moderate random errors (mean±95%CI: 17.8 ± 3.7%), and very strong test-retest correlations (range: 0.73-0.97). Differences in random errors between controlled and self-selected protocols were negligible (mean±95%CI: 1.3 ± 2.3%). Jump execution variables demonstrated acceptable reliability, with no meaningful differences between the controlled and self-selected jump protocols. To simplify testing, a self-selected jump protocol can be used to assess force-time variables with negligible impact on measurement error.

  15. Teaching Medical Students to Help Patients Quit Smoking: Outcomes of a 10-School Randomized Controlled Trial.

    PubMed

    Ockene, Judith K; Hayes, Rashelle B; Churchill, Linda C; Crawford, Sybil L; Jolicoeur, Denise G; Murray, David M; Shoben, Abigail B; David, Sean P; Ferguson, Kristi J; Huggett, Kathryn N; Adams, Michael; Okuliar, Catherine A; Gross, Robin L; Bass, Pat F; Greenberg, Ruth B; Leone, Frank T; Okuyemi, Kola S; Rudy, David W; Waugh, Jonathan B; Geller, Alan C

    2016-02-01

    Early in medical education, physicians must develop competencies needed for tobacco dependence treatment. To assess the effect of a multi-modal tobacco dependence treatment curriculum on medical students' counseling skills. A group-randomized controlled trial (2010-2014) included ten U.S. medical schools that were randomized to receive either multi-modal tobacco treatment education (MME) or traditional tobacco treatment education (TE). Students from the classes of 2012 and 2014 at ten medical schools participated. Students from the class of 2012 (N = 1345) completed objective structured clinical examinations (OSCEs), and 50 % (N = 660) were randomly selected for pre-intervention evaluation. A total of 72.9 % of eligible students (N = 1096) from the class of 2014 completed an OSCE and 69.7 % (N = 1047) completed pre and post surveys. The MME included a Web-based course, a role-play classroom demonstration, and a clerkship booster session. Clerkship preceptors in MME schools participated in an academic detailing module and were encouraged to be role models for third-year students. The primary outcome was student tobacco treatment skills using the 5As measured by an objective structured clinical examination (OSCE) scored on a 33-item behavior checklist. Secondary outcomes were student self-reported skills for performing 5As and pharmacotherapy counseling. Although the difference was not statistically significant, MME students completed more tobacco counseling behaviors on the OSCE checklist (mean 8.7 [SE 0.6] vs. mean 8.0 [SE 0.6], p = 0.52) than TE students. Several of the individual Assist and Arrange items were significantly more likely to have been completed by MME students, including suggesting behavioral strategies (11.8 % vs. 4.5 %, p < 0.001) and providing information regarding quitline (21.0 % vs. 3.8 %, p < 0.001). MME students reported higher self-efficacy for Assist, Arrange, and Pharmacotherapy counseling items (ps ≤0.05). Inclusion of only ten schools limits generalizability. Subsequent interventions should incorporate lessons learned from this first randomized controlled trial of a multi-modal longitudinal tobacco treatment curriculum in multiple U.S. medical schools. NIH Trial Registry Number: NCT01905618.

  16. Selection of nursing teaching strategies in mainland China: A questionnaire survey.

    PubMed

    Zhou, HouXiu; Liu, MengJie; Zeng, Jing; Zhu, JingCi

    2016-04-01

    In nursing education, the traditional lecture and direct demonstration teaching method cannot cultivate the various skills that nursing students need. How to choose a more scientific and rational teaching method is a common concern for nursing educators worldwide. To investigate the basis for selecting teaching methods among nursing teachers in mainland China, the factors affecting the selection of different teaching methods, and the application of different teaching methods in theoretical and skill-based nursing courses. Questionnaire survey. Seventy one nursing colleges from 28 provincial-level administrative regions in mainland China. Following the principle of voluntary informed consent, 262 nursing teachers were randomly selected through a nursing education network platform and a conference platform. The questionnaire contents included the basis for and the factors influencing the selection of nursing teaching methods, the participants' common teaching methods, and the teaching experience of the surveyed nursing teachers. The questionnaires were distributed through the network or conference platform, and the data were analyzed by SPSS 17.0 software. The surveyed nursing teachers selected teaching methods mainly based on the characteristics of the teaching content, the characteristics of the students, and their previous teaching experiences. The factors affecting the selection of teaching methods mainly included large class sizes, limited class time, and limited examination formats. The surveyed nursing teachers primarily used lectures to teach theory courses and the direct demonstration method to teach skills courses, and the application frequencies of these two teaching methods were significantly higher than those of other teaching methods (P=0.000). More attention should be paid to the selection of nursing teaching methods. Every teacher should strategically choose teaching methods before each lesson, and nursing education training focused on selecting effective teaching methods should be more extensive. Copyright © 2016. Published by Elsevier Ltd.

  17. VARIABLE SELECTION FOR REGRESSION MODELS WITH MISSING DATA

    PubMed Central

    Garcia, Ramon I.; Ibrahim, Joseph G.; Zhu, Hongtu

    2009-01-01

    We consider the variable selection problem for a class of statistical models with missing data, including missing covariate and/or response data. We investigate the smoothly clipped absolute deviation penalty (SCAD) and adaptive LASSO and propose a unified model selection and estimation procedure for use in the presence of missing data. We develop a computationally attractive algorithm for simultaneously optimizing the penalized likelihood function and estimating the penalty parameters. Particularly, we propose to use a model selection criterion, called the ICQ statistic, for selecting the penalty parameters. We show that the variable selection procedure based on ICQ automatically and consistently selects the important covariates and leads to efficient estimates with oracle properties. The methodology is very general and can be applied to numerous situations involving missing data, from covariates missing at random in arbitrary regression models to nonignorably missing longitudinal responses and/or covariates. Simulations are given to demonstrate the methodology and examine the finite sample performance of the variable selection procedures. Melanoma data from a cancer clinical trial is presented to illustrate the proposed methodology. PMID:20336190

  18. Imbalanced Learning for Functional State Assessment

    NASA Technical Reports Server (NTRS)

    Li, Feng; McKenzie, Frederick; Li, Jiang; Zhang, Guangfan; Xu, Roger; Richey, Carl; Schnell, Tom

    2011-01-01

    This paper presents results of several imbalanced learning techniques applied to operator functional state assessment where the data is highly imbalanced, i.e., some function states (majority classes) have much more training samples than other states (minority classes). Conventional machine learning techniques usually tend to classify all data samples into majority classes and perform poorly for minority classes. In this study, we implemented five imbalanced learning techniques, including random undersampling, random over-sampling, synthetic minority over-sampling technique (SMOTE), borderline-SMOTE and adaptive synthetic sampling (ADASYN) to solve this problem. Experimental results on a benchmark driving lest dataset show thai accuracies for minority classes could be improved dramatically with a cost of slight performance degradations for majority classes,

  19. Mixing rates and limit theorems for random intermittent maps

    NASA Astrophysics Data System (ADS)

    Bahsoun, Wael; Bose, Christopher

    2016-04-01

    We study random transformations built from intermittent maps on the unit interval that share a common neutral fixed point. We focus mainly on random selections of Pomeu-Manneville-type maps {{T}α} using the full parameter range 0<α <∞ , in general. We derive a number of results around a common theme that illustrates in detail how the constituent map that is fastest mixing (i.e. smallest α) combined with details of the randomizing process, determines the asymptotic properties of the random transformation. Our key result (theorem 1.1) establishes sharp estimates on the position of return time intervals for the quenched dynamics. The main applications of this estimate are to limit laws (in particular, CLT and stable laws, depending on the parameters chosen in the range 0<α <1 ) for the associated skew product; these are detailed in theorem 3.2. Since our estimates in theorem 1.1 also hold for 1≤slant α <∞ we study a second class of random transformations derived from piecewise affine Gaspard-Wang maps, prove existence of an infinite (σ-finite) invariant measure and study the corresponding correlation asymptotics. To the best of our knowledge, this latter kind of result is completely new in the setting of random transformations.

  20. Physical activity for osteoarthritis management: a randomized controlled clinical trial evaluating hydrotherapy or Tai Chi classes.

    PubMed

    Fransen, Marlene; Nairn, Lillias; Winstanley, Julie; Lam, Paul; Edmonds, John

    2007-04-15

    To determine whether Tai Chi or hydrotherapy classes for individuals with chronic symptomatic hip or knee osteoarthritis (OA) result in measurable clinical benefits. A randomized controlled trial was conducted among 152 older persons with chronic symptomatic hip or knee OA. Participants were randomly allocated for 12 weeks to hydrotherapy classes (n = 55), Tai Chi classes (n = 56), or a waiting list control group (n = 41). Outcomes were assessed 12 and 24 weeks after randomization and included pain and physical function (Western Ontario and McMaster Universities Osteoarthritis Index), general health status (Medical Outcomes Study Short Form 12 Health Survey [SF-12], version 2), psychological well-being, and physical performance (Up and Go test, 50-foot walk time, timed stair climb). At 12 weeks, compared with controls, participants allocated to hydrotherapy classes demonstrated mean improvements (95% confidence interval) of 6.5 (0.4, 12.7) and 10.5 (3.6, 14.5) for pain and physical function scores (range 0-100), respectively, whereas participants allocated to Tai Chi classes demonstrated improvements of 5.2 (-0.8, 11.1) and 9.7 (2.8, 16.7), respectively. Both class allocations achieved significant improvements in the SF-12 physical component summary score, but only allocation to hydrotherapy achieved significant improvements in the physical performance measures. All significant improvements were sustained at 24 weeks. In this almost exclusively white sample, class attendance was higher for hydrotherapy, with 81% attending at least half of the available 24 classes, compared with 61% for Tai Chi. Access to either hydrotherapy or Tai Chi classes can provide large and sustained improvements in physical function for many older, sedentary individuals with chronic hip or knee OA.

  1. Finite-time scaling at the Anderson transition for vibrations in solids

    NASA Astrophysics Data System (ADS)

    Beltukov, Y. M.; Skipetrov, S. E.

    2017-11-01

    A model in which a three-dimensional elastic medium is represented by a network of identical masses connected by springs of random strengths and allowed to vibrate only along a selected axis of the reference frame exhibits an Anderson localization transition. To study this transition, we assume that the dynamical matrix of the network is given by a product of a sparse random matrix with real, independent, Gaussian-distributed nonzero entries and its transpose. A finite-time scaling analysis of the system's response to an initial excitation allows us to estimate the critical parameters of the localization transition. The critical exponent is found to be ν =1.57 ±0.02 , in agreement with previous studies of the Anderson transition belonging to the three-dimensional orthogonal universality class.

  2. Generation and development of RNA ligase ribozymes with modular architecture through "design and selection".

    PubMed

    Fujita, Yuki; Ishikawa, Junya; Furuta, Hiroyuki; Ikawa, Yoshiya

    2010-08-26

    In vitro selection with long random RNA libraries has been used as a powerful method to generate novel functional RNAs, although it often requires laborious structural analysis of isolated RNA molecules. Rational RNA design is an attractive alternative to avoid this laborious step, but rational design of catalytic modules is still a challenging task. A hybrid strategy of in vitro selection and rational design has been proposed. With this strategy termed "design and selection," new ribozymes can be generated through installation of catalytic modules onto RNA scaffolds with defined 3D structures. This approach, the concept of which was inspired by the modular architecture of naturally occurring ribozymes, allows prediction of the overall architectures of the resulting ribozymes, and the structural modularity of the resulting ribozymes allows modification of their structures and functions. In this review, we summarize the design, generation, properties, and engineering of four classes of ligase ribozyme generated by design and selection.

  3. Effectiveness of Using Computer-Assisted Supplementary Instruction for Teaching the Mole Concept

    NASA Astrophysics Data System (ADS)

    Yalçinalp, Serpil; Geban, Ömer; Özkan, Ilker

    This study examined the effect of computer-assisted instruction (CAI), used as a problem-solving supplement to classroom instruction, on students' understanding of chemical formulas and mole concept, their attitudes toward chemistry subjects, and CAI. The objective was to assess the effectiveness of CAI over recitation hours when both teaching methods were used as a supplement to the traditional chemistry instruction. We randomly selected two classes in a secondary school. Each teaching strategy was randomly assigned to one class. The experimental group received supplementary instruction delivered via CAI, while the control group received similar instruction through recitation hours. The data were analyzed using two-way analysis of variance and t-test. It was found that the students who used the CAI accompanied with lectures scored significantly higher than those who attended recitation hours, in terms of school subject achievement in chemistry and attitudes toward chemistry subjects. In addition, there was a significant improvement in the attitudes of students in the experimental group toward the use of computers in a chemistry course. There was no significant difference between the performances of females versus males in each treatment group.Received: 26 April 1994; Revised: 6 April 1995;

  4. Automatic detection of atrial fibrillation in cardiac vibration signals.

    PubMed

    Brueser, C; Diesel, J; Zink, M D H; Winter, S; Schauerte, P; Leonhardt, S

    2013-01-01

    We present a study on the feasibility of the automatic detection of atrial fibrillation (AF) from cardiac vibration signals (ballistocardiograms/BCGs) recorded by unobtrusive bedmounted sensors. The proposed system is intended as a screening and monitoring tool in home-healthcare applications and not as a replacement for ECG-based methods used in clinical environments. Based on BCG data recorded in a study with 10 AF patients, we evaluate and rank seven popular machine learning algorithms (naive Bayes, linear and quadratic discriminant analysis, support vector machines, random forests as well as bagged and boosted trees) for their performance in separating 30 s long BCG epochs into one of three classes: sinus rhythm, atrial fibrillation, and artifact. For each algorithm, feature subsets of a set of statistical time-frequency-domain and time-domain features were selected based on the mutual information between features and class labels as well as first- and second-order interactions among features. The classifiers were evaluated on a set of 856 epochs by means of 10-fold cross-validation. The best algorithm (random forests) achieved a Matthews correlation coefficient, mean sensitivity, and mean specificity of 0.921, 0.938, and 0.982, respectively.

  5. Estimates of Storage Capacity of Multilayer Perceptron with Threshold Logic Hidden Units.

    PubMed

    Kowalczyk, Adam

    1997-11-01

    We estimate the storage capacity of multilayer perceptron with n inputs, h(1) threshold logic units in the first hidden layer and 1 output. We show that if the network can memorize 50% of all dichotomies of a randomly selected N-tuple of points of R(n) with probability 1, then N

  6. Covariate Selection for Multilevel Models with Missing Data

    PubMed Central

    Marino, Miguel; Buxton, Orfeu M.; Li, Yi

    2017-01-01

    Missing covariate data hampers variable selection in multilevel regression settings. Current variable selection techniques for multiply-imputed data commonly address missingness in the predictors through list-wise deletion and stepwise-selection methods which are problematic. Moreover, most variable selection methods are developed for independent linear regression models and do not accommodate multilevel mixed effects regression models with incomplete covariate data. We develop a novel methodology that is able to perform covariate selection across multiply-imputed data for multilevel random effects models when missing data is present. Specifically, we propose to stack the multiply-imputed data sets from a multiple imputation procedure and to apply a group variable selection procedure through group lasso regularization to assess the overall impact of each predictor on the outcome across the imputed data sets. Simulations confirm the advantageous performance of the proposed method compared with the competing methods. We applied the method to reanalyze the Healthy Directions-Small Business cancer prevention study, which evaluated a behavioral intervention program targeting multiple risk-related behaviors in a working-class, multi-ethnic population. PMID:28239457

  7. Robustness of optimal random searches in fragmented environments

    NASA Astrophysics Data System (ADS)

    Wosniack, M. E.; Santos, M. C.; Raposo, E. P.; Viswanathan, G. M.; da Luz, M. G. E.

    2015-05-01

    The random search problem is a challenging and interdisciplinary topic of research in statistical physics. Realistic searches usually take place in nonuniform heterogeneous distributions of targets, e.g., patchy environments and fragmented habitats in ecological systems. Here we present a comprehensive numerical study of search efficiency in arbitrarily fragmented landscapes with unlimited visits to targets that can only be found within patches. We assume a random walker selecting uniformly distributed turning angles and step lengths from an inverse power-law tailed distribution with exponent μ . Our main finding is that for a large class of fragmented environments the optimal strategy corresponds approximately to the same value μopt≈2 . Moreover, this exponent is indistinguishable from the well-known exact optimal value μopt=2 for the low-density limit of homogeneously distributed revisitable targets. Surprisingly, the best search strategies do not depend (or depend only weakly) on the specific details of the fragmentation. Finally, we discuss the mechanisms behind this observed robustness and comment on the relevance of our results to both the random search theory in general, as well as specifically to the foraging problem in the biological context.

  8. Effects of topology on network evolution

    NASA Astrophysics Data System (ADS)

    Oikonomou, Panos; Cluzel, Philippe

    2006-08-01

    The ubiquity of scale-free topology in nature raises the question of whether this particular network design confers an evolutionary advantage. A series of studies has identified key principles controlling the growth and the dynamics of scale-free networks. Here, we use neuron-based networks of boolean components as a framework for modelling a large class of dynamical behaviours in both natural and artificial systems. Applying a training algorithm, we characterize how networks with distinct topologies evolve towards a pre-established target function through a process of random mutations and selection. We find that homogeneous random networks and scale-free networks exhibit drastically different evolutionary paths. Whereas homogeneous random networks accumulate neutral mutations and evolve by sparse punctuated steps, scale-free networks evolve rapidly and continuously. Remarkably, this latter property is robust to variations of the degree exponent. In contrast, homogeneous random networks require a specific tuning of their connectivity to optimize their ability to evolve. These results highlight an organizing principle that governs the evolution of complex networks and that can improve the design of engineered systems.

  9. Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences

    PubMed Central

    2014-01-01

    Background Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. Results Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. Conclusion The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification. PMID:24418292

  10. The association of the transitions in smoking stages with prevalence of cigarette smoking in the classes and schools: a longitudinal study.

    PubMed

    MohammadPoorasl, Asghar; Nedjat, Saharnaz; Fakhari, Ali; Fotouhi, Akbar

    2014-01-01

    Adolescent tobacco use remains a major public health priority to reduce the prevalence of tobacco use in community. The aim of this study was determining the association of the transitions in smoking stages with prevalence of cigarette smoking in the classes and schools in adolescents of Tabriz City (northwest of Iran). Fifty-six high schools were randomly selected, and 4903 students completed a self-administered questionnaire on cigarette smoking twice with a 12-months interval in 2010 and 2011. Transition from experimenter to regular smoker stage was associated with the prevalence of cigarette smoking in the school. The results have shown the association of student's smoking uptake with the prevalence of cigarette smoking in the school. This highlights the importance of enforcing smoke free policies in schools.

  11. Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows.

    PubMed

    Savegnago, R P; Rosa, G J M; Valente, B D; Herrera, L G G; Carneiro, R L R; Sesana, R C; El Faro, L; Munari, D P

    2013-01-01

    The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  12. Atraumatic restorative treatment (ART): a three-year clinical study in Malawi--comparison of conventional amalgam and ART restorations.

    PubMed

    Kalf-Scholte, Sonja M; van Amerongen, Willem E; Smith, Albert J E; van Haastrecht, Harry J A

    2003-01-01

    This study compares the quality of class I restorations made with the atraumatic restorative treatment (ART) technique and conventional class I amalgam restorations. The study was carried out among secondary school students in Mzuzu, Malawi. First-year students in 1987 who needed at least two class I restorations were selected. Based on a split-mouth design, each participant received both ART and conventional restorations. The 89 pairs of class I cavities were divided randomly into two groups, since two different cermet ionomer cement (CIC) filling materials were used. Impressions of the restorations and subsequent models were made shortly after restoration, after six months, one year, two years, and three years. The quality of the restorations was determined on the models following the US Public Health Service criteria. Bulk fracture, contour, marginal integrity, and surface texture of the restorations were recorded and evaluated separately. Survival rates were determined by the resultant score of all criteria. Though conventional amalgam restorations performed better on all criteria, this difference was significant only for the contour criterion. The survival rates of ART restorations after three years (81.0%) were lower than those of amalgam restorations (90.4%) (P=.067). The quality of ART class I restorations is competitive with that of conventional amalgam restorations.

  13. Automated identification of abnormal metaphase chromosome cells for the detection of chronic myeloid leukemia using microscopic images

    NASA Astrophysics Data System (ADS)

    Wang, Xingwei; Zheng, Bin; Li, Shibo; Mulvihill, John J.; Chen, Xiaodong; Liu, Hong

    2010-07-01

    Karyotyping is an important process to classify chromosomes into standard classes and the results are routinely used by the clinicians to diagnose cancers and genetic diseases. However, visual karyotyping using microscopic images is time-consuming and tedious, which reduces the diagnostic efficiency and accuracy. Although many efforts have been made to develop computerized schemes for automated karyotyping, no schemes can get be performed without substantial human intervention. Instead of developing a method to classify all chromosome classes, we develop an automatic scheme to detect abnormal metaphase cells by identifying a specific class of chromosomes (class 22) and prescreen for suspicious chronic myeloid leukemia (CML). The scheme includes three steps: (1) iteratively segment randomly distributed individual chromosomes, (2) process segmented chromosomes and compute image features to identify the candidates, and (3) apply an adaptive matching template to identify chromosomes of class 22. An image data set of 451 metaphase cells extracted from bone marrow specimens of 30 positive and 30 negative cases for CML is selected to test the scheme's performance. The overall case-based classification accuracy is 93.3% (100% sensitivity and 86.7% specificity). The results demonstrate the feasibility of applying an automated scheme to detect or prescreen the suspicious cancer cases.

  14. The association between school exclusion, delinquency and subtypes of cyber- and F2F-victimizations: identifying and predicting risk profiles and subtypes using latent class analysis.

    PubMed

    Barboza, Gia Elise

    2015-01-01

    This purpose of this paper is to identify risk profiles of youth who are victimized by on- and offline harassment and to explore the consequences of victimization on school outcomes. Latent class analysis is used to explore the overlap and co-occurrence of different clusters of victims and to examine the relationship between class membership and school exclusion and delinquency. Participants were a random sample of youth between the ages of 12 and 18 selected for inclusion to participate in the 2011 National Crime Victimization Survey: School Supplement. The latent class analysis resulted in four categories of victims: approximately 3.1% of students were highly victimized by both bullying and cyberbullying behaviors; 11.6% of youth were classified as being victims of relational bullying, verbal bullying and cyberbullying; a third class of students were victims of relational bullying, verbal bullying and physical bullying but were not cyberbullied (8%); the fourth and final class, characteristic of the majority of students (77.3%), was comprised of non-victims. The inclusion of covariates to the latent class model indicated that gender, grade and race were significant predictors of at least one of the four victim classes. School delinquency measures were included as distal outcomes to test for both overall and pairwise associations between classes. With one exception, the results were indicative of a significant relationship between school delinquency and the victim subtypes. Implications for these findings are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Latent profile analysis of sixth graders based on teacher ratings: Association with school dropout.

    PubMed

    Orpinas, Pamela; Raczynski, Katherine; Peters, Jaclyn Wetherington; Colman, Laura; Bandalos, Deborah

    2015-12-01

    The goal of this study was to identify meaningful groups of sixth graders with common characteristics based on teacher ratings of assets and maladaptive behaviors, describe dropout rates for each group, and examine the validity of these groups using students' self-reports. The sample consisted of racially diverse students (n = 675) attending sixth grade in public schools in Northeast Georgia. The majority of the sample was randomly selected; a smaller group was identified by teachers as high risk for aggression. Based on teacher ratings of externalizing behaviors, internalizing problems, academic skills, leadership, and social assets, latent profile analysis yielded 7 classes that can be displayed along a continuum: Well-Adapted, Average, Average-Social Skills Deficit, Internalizing, Externalizing, Disruptive Behavior with School Problems, and Severe Problems. Dropout rate was lowest for the Well-adapted class (4%) and highest for the Severe Problems class (58%). However, students in the Average-Social Skills Deficit class did not follow the continuum, with a large proportion of students who abandoned high school (29%). The proportion of students identified by teachers as high in aggression consistently increased across the continuum from none in the Well-Adapted class to 84% in the Severe Problems class. Students' self-reports were generally consistent with the latent profile classes. Students in the Well-Adapted class reported low aggression, drug use, and delinquency, and high life satisfaction; self-reports went in the opposite direction for the Disruptive Behaviors with School Problems class. Results highlight the importance of early interventions to improve academic performance, reduce externalizing behaviors, and enhance social assets. (c) 2015 APA, all rights reserved).

  16. [Planar molecular arrangements aid the design of MHC class II binding peptides].

    PubMed

    Cortés, A; Coral, J; McLachlan, C; Benítez, R; Pinilla, L

    2017-01-01

    The coupling between peptides and MHC-II proteins in the human immune system is not well understood. This work presents an evidence-based hypothesis of a guiding intermolecular force present in every human MHC-II protein (HLA-II). Previously, we examined the spatial positions of the fully conserved residues in all HLA-II protein types. In each one, constant planar patterns were revealed. These molecular planes comprise of amino acid groups of the same chemical species (for example, Gly) distributed across the protein structure. Each amino acid plane has a unique direction and this directional element offers spatial selectivity. Constant within all planes, too, is the presence of an aromatic residue possessing electrons in movement, leading the authors to consider that the planes generate electromagnetic fields that could serve as an attractive force in a single direction. Selection and attraction between HLA-II molecules and antigen peptides would, therefore, be non-random, resulting in a coupling mechanism as effective and rapid as is clearly required in the immune response. On the basis of planar projections onto the HLA-II groove, modifications were made by substituting the key residues in the class II-associated invariant chain peptide-a peptide with a universal binding affinity-resulting in eight different modified peptides with affinities greater than that of the unmodified peptide. Accurate and reliable prediction of MHC class II-binding peptides may facilitate the design of universal vaccine-peptides with greatly enhanced binding affinities. The proposed mechanisms of selection, attraction and coupling between HLA-II and antigen peptides are explained further in the paper.

  17. Effect Sizes in Three-Level Cluster-Randomized Experiments

    ERIC Educational Resources Information Center

    Hedges, Larry V.

    2011-01-01

    Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…

  18. Identification and quantification of homologous series of compound in complex mixtures: autocovariance study of GC/MS chromatograms.

    PubMed

    Pietrogrande, Maria Chiara; Zampolli, Maria Grazia; Dondi, Francesco

    2006-04-15

    The paper describes a method for determining homologous classes of compounds in a multicomponent complex chromatogram obtained under programming elution conditions. The method is based on the computation of the autocovariance function of the experimental chromatogram (EACVF). The EACVF plot, if properly interpreted, can be regarded as a "class chromatogram" i.e., a virtual chromatogram formed by peaks whose positions and heights allow identification and quantification of the different homologous series, even if they are embedded in a random complex chromatogram. Theoretical models were developed to describe complex chromatograms displaying random retention pattern, ordered sequences or a combination of them. On the basis of theoretical autocovariance function, the properties of the chromatogram can be experimentally evaluated, under well-defined conditions: in particular, the two components of the chromatogram, ordered and random, can be identified. Moreover, the total number of single components (SCs) and the separated number of the SCs belonging to the random and ordered components can be determined, when the two components display the same concentration. If the mixture contains several homologous series with common frequency and different phase values, the number and identity of the different homologous series as well as the number of SCs belonging to each of them can be evaluated. Moreover, the power of the EACVF method can be magnified by applying it to the single ion monitoring (SIM) signals to selectively detect specific compound classes in order to identify the different homologous series. By this way, a full "decoding" of the complex multicomponent chromatogram is achieved. The method was validated on synthetic mixtures containing known amount of SCs belonging to homologous series of hydrocarbon, alcohols, ketones, and aromatic compounds in addition to other not structurally related SCs. The method was applied to both the total ion monitoring (TIC) and the SIM signals, to describe step by step the essence of the procedure. Moreover, the systematic use of both SIM and TIC can simplify the decoding procedure of complex chromatograms by singling out only specific compound classes or by confirming the identification of the different homologous series. The method was further applied to a sample containing unknown number of compounds and homologous series (a petroleum benzin, bp 140-160 degrees C): the results obtained were meaningful in terms of both the identified number of components and identified homologous series.

  19. Pattern formations and optimal packing.

    PubMed

    Mityushev, Vladimir

    2016-04-01

    Patterns of different symmetries may arise after solution to reaction-diffusion equations. Hexagonal arrays, layers and their perturbations are observed in different models after numerical solution to the corresponding initial-boundary value problems. We demonstrate an intimate connection between pattern formations and optimal random packing on the plane. The main study is based on the following two points. First, the diffusive flux in reaction-diffusion systems is approximated by piecewise linear functions in the framework of structural approximations. This leads to a discrete network approximation of the considered continuous problem. Second, the discrete energy minimization yields optimal random packing of the domains (disks) in the representative cell. Therefore, the general problem of pattern formations based on the reaction-diffusion equations is reduced to the geometric problem of random packing. It is demonstrated that all random packings can be divided onto classes associated with classes of isomorphic graphs obtained from the Delaunay triangulation. The unique optimal solution is constructed in each class of the random packings. If the number of disks per representative cell is finite, the number of classes of isomorphic graphs, hence, the number of optimal packings is also finite. Copyright © 2016 Elsevier Inc. All rights reserved.

  20. Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection.

    PubMed

    Jahandideh, Samad; Srinivasasainagendra, Vinodh; Zhi, Degui

    2012-11-07

    RNA-protein interaction plays an important role in various cellular processes, such as protein synthesis, gene regulation, post-transcriptional gene regulation, alternative splicing, and infections by RNA viruses. In this study, using Gene Ontology Annotated (GOA) and Structural Classification of Proteins (SCOP) databases an automatic procedure was designed to capture structurally solved RNA-binding protein domains in different subclasses. Subsequently, we applied tuned multi-class SVM (TMCSVM), Random Forest (RF), and multi-class ℓ1/ℓq-regularized logistic regression (MCRLR) for analysis and classifying RNA-binding protein domains based on a comprehensive set of sequence and structural features. In this study, we compared prediction accuracy of three different state-of-the-art predictor methods. From our results, TMCSVM outperforms the other methods and suggests the potential of TMCSVM as a useful tool for facilitating the multi-class prediction of RNA-binding protein domains. On the other hand, MCRLR by elucidating importance of features for their contribution in predictive accuracy of RNA-binding protein domains subclasses, helps us to provide some biological insights into the roles of sequences and structures in protein-RNA interactions.

  1. Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data.

    PubMed

    Zhang, Bo; Chen, Zhen; Albert, Paul S

    2012-01-01

    High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, we use latent risk classes to link the 2 modeling components. We characterize complex biomarker-specific differences through biomarker-specific random effects, so that different biomarkers can have different baseline (low-risk) values as well as different between-class differences. The proposed approach also accommodates data features that are common in environmental toxicology and other biomarker exposure data, including a large number of biomarkers, numerous zero values, and complex mean-variance relationship in the biomarkers levels. A Monte Carlo EM (MCEM) algorithm is proposed for parameter estimation. Both the MCEM algorithm and model selection procedures are shown to work well in simulations and applications. In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis.

  2. Amino Acid Residues That Contribute to Substrate Specificity of Class A β-Lactamase SME-1

    PubMed Central

    Majiduddin, Fahd K.; Palzkill, Timothy

    2005-01-01

    Carbapenem antibiotics are used as antibiotics of last resort because they possess a broad spectrum of antimicrobial activity and are not easily hydrolyzed by β-lactamases. Recently, class A enzymes, such as the SME-1, NMC-A, and IMI-1 β-lactamases, have been identified with the capacity to hydrolyze carbapenem antibiotics. Traditional class A β-lactamases, such as TEM-1 and SHV-1, are unable to hydrolyze carbapenem antibiotics and exhibit some differences in sequence from those that are able to hydrolyze carbapenem antibiotics. The positions that differ may contribute to the unique substrate specificity of the class A carbapenemase SME-1. Codons in the SME-1 gene representing residues 104, 105, 132, 167, 237, and 241 were randomized by site-directed mutagenesis, and functional mutants were selected for the ability to hydrolyze imipenem, ampicillin, or cefotaxime. Although several positions are important for hydrolysis of β-lactam antibiotics, no single position was found to uniquely contribute to carbapenem hydrolysis. The results of this study support a model whereby the carbapenemase activity of SME-1 is due to a highly distributed set of interactions that subtly alter the structure of the active-site pocket. PMID:16048956

  3. Amino acid residues that contribute to substrate specificity of class A beta-lactamase SME-1.

    PubMed

    Majiduddin, Fahd K; Palzkill, Timothy

    2005-08-01

    Carbapenem antibiotics are used as antibiotics of last resort because they possess a broad spectrum of antimicrobial activity and are not easily hydrolyzed by beta-lactamases. Recently, class A enzymes, such as the SME-1, NMC-A, and IMI-1 beta-lactamases, have been identified with the capacity to hydrolyze carbapenem antibiotics. Traditional class A beta-lactamases, such as TEM-1 and SHV-1, are unable to hydrolyze carbapenem antibiotics and exhibit some differences in sequence from those that are able to hydrolyze carbapenem antibiotics. The positions that differ may contribute to the unique substrate specificity of the class A carbapenemase SME-1. Codons in the SME-1 gene representing residues 104, 105, 132, 167, 237, and 241 were randomized by site-directed mutagenesis, and functional mutants were selected for the ability to hydrolyze imipenem, ampicillin, or cefotaxime. Although several positions are important for hydrolysis of beta-lactam antibiotics, no single position was found to uniquely contribute to carbapenem hydrolysis. The results of this study support a model whereby the carbapenemase activity of SME-1 is due to a highly distributed set of interactions that subtly alter the structure of the active-site pocket.

  4. A computational proposal for designing structured RNA pools for in vitro selection of RNAs.

    PubMed

    Kim, Namhee; Gan, Hin Hark; Schlick, Tamar

    2007-04-01

    Although in vitro selection technology is a versatile experimental tool for discovering novel synthetic RNA molecules, finding complex RNA molecules is difficult because most RNAs identified from random sequence pools are simple motifs, consistent with recent computational analysis of such sequence pools. Thus, enriching in vitro selection pools with complex structures could increase the probability of discovering novel RNAs. Here we develop an approach for engineering sequence pools that links RNA sequence space regions with corresponding structural distributions via a "mixing matrix" approach combined with a graph theory analysis. We define five classes of mixing matrices motivated by covariance mutations in RNA; these constructs define nucleotide transition rates and are applied to chosen starting sequences to yield specific nonrandom pools. We examine the coverage of sequence space as a function of the mixing matrix and starting sequence via clustering analysis. We show that, in contrast to random sequences, which are associated only with a local region of sequence space, our designed pools, including a structured pool for GTP aptamers, can target specific motifs. It follows that experimental synthesis of designed pools can benefit from using optimized starting sequences, mixing matrices, and pool fractions associated with each of our constructed pools as a guide. Automation of our approach could provide practical tools for pool design applications for in vitro selection of RNAs and related problems.

  5. An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling

    NASA Astrophysics Data System (ADS)

    Moghadamfalahi, Mohammad; Akcakaya, Murat; Nezamfar, Hooman; Sourati, Jamshid; Erdogmus, Deniz

    2017-10-01

    A class of brain computer interfaces (BCIs) employs noninvasive recordings of electroencephalography (EEG) signals to enable users with severe speech and motor impairments to interact with their environment and social network. For example, EEG based BCIs for typing popularly utilize event related potentials (ERPs) for inference. Presentation paradigm design in current ERP-based letter by letter typing BCIs typically query the user with an arbitrary subset characters. However, the typing accuracy and also typing speed can potentially be enhanced with more informed subset selection and flash assignment. In this manuscript, we introduce the active recursive Bayesian state estimation (active-RBSE) framework for inference and sequence optimization. Prior to presentation in each iteration, rather than showing a subset of randomly selected characters, the developed framework optimally selects a subset based on a query function. Selected queries are made adaptively specialized for users during each intent detection. Through a simulation-based study, we assess the effect of active-RBSE on the performance of a language-model assisted typing BCI in terms of typing speed and accuracy. To provide a baseline for comparison, we also utilize standard presentation paradigms namely, row and column matrix presentation paradigm and also random rapid serial visual presentation paradigms. The results show that utilization of active-RBSE can enhance the online performance of the system, both in terms of typing accuracy and speed.

  6. Behavioral and Mental Health Correlates of Youth Stalking Victimization: A Latent Class Approach.

    PubMed

    Reidy, Dennis E; Smith-Darden, Joanne P; Kernsmith, Poco D

    2016-12-01

    Although recognized as a public health problem, little attention has been paid to the problem of stalking among youth. Latent profile analysis was used to identify latent groups of adolescent stalking victims and their behavioral and mental health correlates. A cross-sectional sample of 1,236 youths were randomly selected from 13 schools stratified by community risk level (i.e., low, moderate, and high risk) and gender. Students completed surveys assessing behavioral indicators of stalking victimization, as well as substance use, sexual behavior, dating violence, and psychiatric symptoms. Data were collected in 2013 and data analyses were performed in 2015. Analysis indicated the presence of a non-victim class, a minimal exposure class, and a victim class for boys and girls alike. Approximately 14% of girls and 13% of boys were in the stalking victim class. Adolescents in the victim class reported more symptoms of post-traumatic stress, mood disorder, and hopelessness, as well as more instances of alcohol use, binge drinking, and physical dating violence victimization. Girls in the victim class also reported engaging in sexting behaviors and oral sex with significantly more partners than their non-victim peers. These findings provide valuable knowledge of the prevalence and pertinent health correlates of stalking victimization in adolescence. The data suggest a substantial proportion of adolescents are victims of stalking and are likewise at risk for a number of deleterious health outcomes. As such, this population merits further attention by prevention researchers and practitioners. Published by Elsevier Inc.

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

    Zhang, Lin, E-mail: godyalin@163.com; Singh, Uttam, E-mail: uttamsingh@hri.res.in; Pati, Arun K., E-mail: akpati@hri.res.in

    Compact expressions for the average subentropy and coherence are obtained for random mixed states that are generated via various probability measures. Surprisingly, our results show that the average subentropy of random mixed states approaches the maximum value of the subentropy which is attained for the maximally mixed state as we increase the dimension. In the special case of the random mixed states sampled from the induced measure via partial tracing of random bipartite pure states, we establish the typicality of the relative entropy of coherence for random mixed states invoking the concentration of measure phenomenon. Our results also indicate thatmore » mixed quantum states are less useful compared to pure quantum states in higher dimension when we extract quantum coherence as a resource. This is because of the fact that average coherence of random mixed states is bounded uniformly, however, the average coherence of random pure states increases with the increasing dimension. As an important application, we establish the typicality of relative entropy of entanglement and distillable entanglement for a specific class of random bipartite mixed states. In particular, most of the random states in this specific class have relative entropy of entanglement and distillable entanglement equal to some fixed number (to within an arbitrary small error), thereby hugely reducing the complexity of computation of these entanglement measures for this specific class of mixed states.« less

  8. Perceptibility and the "Choice Experience": User Sensory Perceptions and Experiences Inform Vaginal Prevention Product Design.

    PubMed

    Guthrie, Kate Morrow; Dunsiger, Shira; Vargas, Sara E; Fava, Joseph L; Shaw, Julia G; Rosen, Rochelle K; Kiser, Patrick F; Kojic, E Milu; Friend, David R; Katz, David F

    The development of pericoital (on demand) vaginal HIV prevention technologies remains a global health priority. Clinical trials to date have been challenged by nonadherence, leading to an inability to demonstrate product efficacy. The work here provides new methodology and results to begin to address this limitation. We created validated scales that allow users to characterize sensory perceptions and experiences when using vaginal gel formulations. In this study, we sought to understand the user sensory perceptions and experiences (USPEs) that characterize the preferred product experience for each participant. Two hundred four women evaluated four semisolid vaginal formulations using the USPE scales at four randomly ordered formulation evaluation visits. Women were asked to select their preferred formulation experience for HIV prevention among the four formulations evaluated. The scale scores on the Sex-associated USPE scales (e.g., Initial Penetration and Leakage) for each participant's selected formulation were used in a latent class model analysis. Four classes of preferred formulation experiences were identified. Sociodemographic and sexual history variables did not predict class membership; however, four specific scales were significantly related to class: Initial Penetration, Perceived Wetness, Messiness, and Leakage. The range of preferred user experiences represented by the scale scores creates a potential target range for product development, such that products that elicit scale scores that fall within the preferred range may be more acceptable, or tolerable, to the population under study. It is recommended that similar analyses should be conducted with other semisolid vaginal formulations, and in other cultures, to determine product property and development targets.

  9. Evolutionary dynamics on any population structure

    NASA Astrophysics Data System (ADS)

    Allen, Benjamin; Lippner, Gabor; Chen, Yu-Ting; Fotouhi, Babak; Momeni, Naghmeh; Yau, Shing-Tung; Nowak, Martin A.

    2017-03-01

    Evolution occurs in populations of reproducing individuals. The structure of a population can affect which traits evolve. Understanding evolutionary game dynamics in structured populations remains difficult. Mathematical results are known for special structures in which all individuals have the same number of neighbours. The general case, in which the number of neighbours can vary, has remained open. For arbitrary selection intensity, the problem is in a computational complexity class that suggests there is no efficient algorithm. Whether a simple solution for weak selection exists has remained unanswered. Here we provide a solution for weak selection that applies to any graph or network. Our method relies on calculating the coalescence times of random walks. We evaluate large numbers of diverse population structures for their propensity to favour cooperation. We study how small changes in population structure—graph surgery—affect evolutionary outcomes. We find that cooperation flourishes most in societies that are based on strong pairwise ties.

  10. Prevalence and correlates of physical fitness testing in U.S. schools--2000.

    PubMed

    Morrow, James R; Fulton, Janet E; Brener, Nancy D; Kohl, Harold W

    2008-06-01

    Because of the perceived lack of youth physical fitness and/or concerns for increased obesity, physical education teachers are interested in youth fitness and physical activity levels. Statewide mandates are being developed that require school-based teachers to complete physical fitness testing. Data from the nationally representative School Health Policies and Programs Study 2000 were analyzed to investigate the prevalence of fitness testing and the professional characteristics of fitness test users. Data were collected with teachers of either randomly selected classes in elementary schools and randomly selected required physical education courses in middle/junior high and senior high schools (N = 1,564). The prevalence of fitness test use is 65% across all school levels. Variables associated with physical fitness test usage were professionally oriented. Results showed that teachers in secondary schools (odds ratio [OR] = 2.25, 95% confidence interval [CI] = I.18-4.27), those with degrees in physical education/kinesiology-related disciplines (OR = 2.01, 95% CI = 1.11-3.63), and those who had completed staff development on physical fitness testing (OR = 3.22, 95% CI = 1.86-5.60) were more likely than respondents without these characteristics to engage in physical fitness testing. Results changed little when separate analyses were conducted for classes/courses in districts requiring versus not requiring fitness testing. Financial variables, including fitness-oriented facilities available, metropolitan location, and discretionary expenditures per student, were not associated with fitness test use. Results provided national prevalence of school-based physical fitness testing use in the U. S. and conveyed information about those who currently use physical fitness tests.

  11. Mathematics Literacy on Problem Based Learning with Indonesian Realistic Mathematics Education Approach Assisted E-Learning Edmodo

    NASA Astrophysics Data System (ADS)

    Wardono; Waluya, S. B.; Mariani, Scolastika; Candra D, S.

    2016-02-01

    This study aims to find out that there are differences in mathematical literacy ability in content Change and Relationship class VII Junior High School 19, Semarang by Problem Based Learning (PBL) model with an Indonesian Realistic Mathematics Education (called Pendidikan Matematika Realistik Indonesia or PMRI in Indonesia) approach assisted Elearning Edmodo, PBL with a PMRI approach, and expository; to know whether the group of students with learning PBL models with PMRI approach and assisted E-learning Edmodo can improve mathematics literacy; to know that the quality of learning PBL models with a PMRI approach assisted E-learning Edmodo has a good category; to describe the difficulties of students in working the problems of mathematical literacy ability oriented PISA. This research is a mixed methods study. The population was seventh grade students of Junior High School 19, Semarang Indonesia. Sample selection is done by random sampling so that the selected experimental class 1, class 2 and the control experiment. Data collected by the methods of documentation, tests and interviews. From the results of this study showed average mathematics literacy ability of students in the group PBL models with a PMRI approach assisted E-learning Edmodo better than average mathematics literacy ability of students in the group PBL models with a PMRI approach and better than average mathematics literacy ability of students in the expository models; Mathematics literacy ability in the class using the PBL model with a PMRI approach assisted E-learning Edmodo have increased and the improvement of mathematics literacy ability is higher than the improvement of mathematics literacy ability of class that uses the model of PBL learning with PMRI approach and is higher than the improvement of mathematics literacy ability of class that uses the expository models; The quality of learning using PBL models with a PMRI approach assisted E-learning Edmodo have very good category.

  12. A New Educational Film Control for Use in Studies of Active Mind–Body Therapies: Acceptability and Feasibility

    PubMed Central

    Selfe, Terry Kit; Alexander, Gina K.; Taylor, Ann Gill

    2011-01-01

    Abstract Objectives The study objectives were to ascertain whether a novel educational film class is an acceptable and feasible comparison group for a randomized controlled trial regarding the effects of an active mind–body therapy on cardiovascular disease risk in postmenopausal women. Methods Seventy-five (75) participants attended a baseline assessment visit and were randomly assigned to either a yoga group or an educational film (control) group. Both groups attended two 90-minute classes/week for 8 weeks, followed by a second assessment visit. Those not attending the second assessment were classified as dropouts. Over 60 films covering a range of topics relevant to the study population were evaluated; 15 were selected by consensus of at least 2 researchers and 1 layperson. Each film session followed the same format: an informal greeting period, viewing of the film, and a 15-minute postfilm discussion. To determine acceptability and feasibility of the film class, potential between-group differences in dropout and attendance were examined, and participant feedback given during class and on end-of-study questionnaires were evaluated. Results The relation between group assignment and dropout was not significant (χ2 [1, N = 75] = 0.14, p = 0.71). One-way analysis of variance (ANOVA) indicated no significant between-group difference in number of classes attended for the yoga (X = 13.67 ± 3.10) versus film group (13.26 ± 1.97), F(1,63) = 0.39, p = 0.53). Participant feedback regarding the film program was positive. Conclusions These findings support the feasibility and acceptability of this educational film control. Easy to standardize and tailor to a variety of populations, this film program may offer an attractive alternative to the more traditional educational control. PMID:21554109

  13. Implications of quantum metabolism and natural selection for the origin of cancer cells and tumor progression

    NASA Astrophysics Data System (ADS)

    Davies, Paul; Demetrius, Lloyd A.; Tuszynski, Jack A.

    2012-03-01

    Empirical studies give increased support for the hypothesis that the sporadic form of cancer is an age-related metabolic disease characterized by: (a) metabolic dysregulation with random abnormalities in mitochondrial DNA, and (b) metabolic alteration - the compensatory upregulation of glycolysis to offset mitochondrial impairments. This paper appeals to the theory of Quantum Metabolism and the principles of natural selection to formulate a conceptual framework for a quantitative analysis of the origin and proliferation of the disease. Quantum Metabolism, an analytical theory of energy transduction in cells inspired by the methodology of the quantum theory of solids, elucidates the molecular basis for differences in metabolic rate between normal cells, utilizing predominantly oxidative phosphorylation, and cancer cells utilizing predominantly glycolysis. The principles of natural selection account for the outcome of competition between the two classes of cells. Quantum Metabolism and the principles of natural selection give an ontogenic and evolutionary rationale for cancer proliferation and furnish a framework for effective therapeutic strategies to impede the spread of the disease.

  14. EEG alpha asymmetry as a gender-specific predictor of outcome to acute treatment with different antidepressant medications in the randomized iSPOT-D study.

    PubMed

    Arns, Martijn; Bruder, Gerard; Hegerl, Ulrich; Spooner, Chris; Palmer, Donna M; Etkin, Amit; Fallahpour, Kamran; Gatt, Justine M; Hirshberg, Laurence; Gordon, Evian

    2016-01-01

    To determine whether EEG occipital alpha and frontal alpha asymmetry (FAA) distinguishes outpatients with major depression (MDD) from controls, predicts antidepressant treatment outcome, and to explore the role of gender. In the international Study to Predict Optimized Treatment in Depression (iSPOT-D), a multi-center, randomized, prospective open-label trial, 1008 MDD participants were randomized to escitalopram, sertraline or venlafaxine-extended release. The study also recruited 336 healthy controls. Treatment response was established after eight weeks and resting EEG was measured at baseline (two minutes eyes open and eyes closed). No differences in EEG alpha for occipital and frontal cortex, or for FAA, were found in MDD participants compared to controls. Alpha in the occipital and frontal cortex was not associated with treatment outcome. However, a gender and drug-class interaction effect was found for FAA. Relatively greater right frontal alpha (less cortical activity) in women only was associated with a favorable response to the Selective Serotonin Reuptake Inhibitors escitalopram and sertraline. No such effect was found for venlafaxine-extended release. FAA does not differentiate between MDD and controls, but is associated with antidepressant treatment response and remission in a gender and drug-class specific manner. Future studies investigating EEG alpha measures in depression should a-priori stratify by gender. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  15. Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle.

    PubMed

    Pereira, R J; Bignardi, A B; El Faro, L; Verneque, R S; Vercesi Filho, A E; Albuquerque, L G

    2013-01-01

    Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  16. Growth Modeling with Non-Ignorable Dropout: Alternative Analyses of the STAR*D Antidepressant Trial

    PubMed Central

    Muthén, Bengt; Asparouhov, Tihomir; Hunter, Aimee; Leuchter, Andrew

    2011-01-01

    This paper uses a general latent variable framework to study a series of models for non-ignorable missingness due to dropout. Non-ignorable missing data modeling acknowledges that missingness may depend on not only covariates and observed outcomes at previous time points as with the standard missing at random (MAR) assumption, but also on latent variables such as values that would have been observed (missing outcomes), developmental trends (growth factors), and qualitatively different types of development (latent trajectory classes). These alternative predictors of missing data can be explored in a general latent variable framework using the Mplus program. A flexible new model uses an extended pattern-mixture approach where missingness is a function of latent dropout classes in combination with growth mixture modeling using latent trajectory classes. A new selection model allows not only an influence of the outcomes on missingness, but allows this influence to vary across latent trajectory classes. Recommendations are given for choosing models. The missing data models are applied to longitudinal data from STAR*D, the largest antidepressant clinical trial in the U.S. to date. Despite the importance of this trial, STAR*D growth model analyses using non-ignorable missing data techniques have not been explored until now. The STAR*D data are shown to feature distinct trajectory classes, including a low class corresponding to substantial improvement in depression, a minority class with a U-shaped curve corresponding to transient improvement, and a high class corresponding to no improvement. The analyses provide a new way to assess drug efficiency in the presence of dropout. PMID:21381817

  17. Four minutes of in-class high-intensity interval activity improves selective attention in 9- to 11-year olds.

    PubMed

    Ma, Jasmin K; Le Mare, Lucy; Gurd, Brendon J

    2015-03-01

    The amount of time allocated to physical activity in schools is declining. Time-efficient physical activity solutions that demonstrate their impact on academic achievement-related outcomes are needed to prioritize physical activity within the school curricula. "FUNtervals" are 4-min, high-intensity interval activities that use whole-body actions to complement a storyline. The purpose of this study was to (i) explore whether FUNtervals can improve selective attention, an executive function posited to be essential for learning and academic success; and (ii) examine whether this relationship is predicted by students' classroom off-task behaviour. Seven grade 3-5 classes (n = 88) were exposed to a single-group, repeated cross-over design where each student's selective attention was compared between no-activity and FUNtervals days. In week 1, students were familiarized with the d2 test of attention and FUNterval activities, and baseline off-task behaviour was observed. In both weeks 2 and 3 students completed the d2 test of attention following either a FUNterval break or a no-activity break. The order of these breaks was randomized and counterbalanced between weeks. Neither motor nor passive off-task behaviour predicted changes in selective attention following FUNtervals; however, a weak relationship was observed for verbal off-task behaviour and improvements in d2 test performance. More importantly, students made fewer errors during the d2 test following FUNtervals. In supporting the priority of physical activity inclusion within schools, FUNtervals, a time efficient and easily implemented physical activity break, can improve selective attention in 9- to 11-year olds.

  18. Genetic considerations in human sex-mate selection: partners share human leukocyte antigen but not short-tandem-repeat identity markers.

    PubMed

    Israeli, Moshe; Kristt, Don; Nardi, Yuval; Klein, Tirza

    2014-05-01

    Previous studies support a role for MHC on mating preference, yet it remains unsettled as to whether mating occurs preferentially between individuals sharing human leukocyte antigen (HLA) determinants or not. Investigating sex-mate preferences in the contemporary Israeli population is of further curiosity being a population with distinct genetic characteristics, where multifaceted cultural considerations influence mate selection. Pairs of male-female sex partners were evaluated in three groups. Two groups represented unmarried (n = 1002) or married (n = 308) couples and a control group of fictitious male-female couples. HLA and short-tandem-repeat (STR) genetic identification markers were assessed for the frequency of shared antigens and alleles. Human leukocyte antigen results showed that Class I and/ or Class II single antigen as well as double antigen sharing was more common in sex partners than in control group couples (P < 0.001). Married versus unmarried pairs were not distinguishable. In contrast, STR-DNA markers failed to differentiate between sex-mates and controls (P = 0.78). Sex partnerships shared HLA determinants more frequently than randomly constituted male-female pairs. The observed phenomenon does not reflect a syngenetic background between sex-mates as STR markers were not selectively shared. Thus, sex-mate selection in man may contravene the evolutionary pressure for genetic diversity in regard to HLA. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  19. A machine learning methodology for the selection and classification of spontaneous spinal cord dorsum potentials allows disclosure of structured (non-random) changes in neuronal connectivity induced by nociceptive stimulation

    PubMed Central

    Martin, Mario; Contreras-Hernández, Enrique; Béjar, Javier; Esposito, Gennaro; Chávez, Diógenes; Glusman, Silvio; Cortés, Ulises; Rudomin, Pablo

    2015-01-01

    Previous studies aimed to disclose the functional organization of the neuronal networks involved in the generation of the spontaneous cord dorsum potentials (CDPs) generated in the lumbosacral spinal segments used predetermined templates to select specific classes of spontaneous CDPs. Since this procedure was time consuming and required continuous supervision, it was limited to the analysis of two specific types of CDPs (negative CDPs and negative positive CDPs), thus excluding potentials that may reflect activation of other neuronal networks of presumed functional relevance. We now present a novel procedure based in machine learning that allows the efficient and unbiased selection of a variety of spontaneous CDPs with different shapes and amplitudes. The reliability and performance of the present method is evaluated by analyzing the effects on the probabilities of generation of different classes of spontaneous CDPs induced by the intradermic injection of small amounts of capsaicin in the anesthetized cat, a procedure known to induce a state of central sensitization leading to allodynia and hyperalgesia. The results obtained with the selection method presently described allowed detection of spontaneous CDPs with specific shapes and amplitudes that are assumed to represent the activation of functionally coupled sets of dorsal horn neurones that acquire different, structured configurations in response to nociceptive stimuli. These changes are considered as responses tending to adequate transmission of sensory information to specific functional requirements as part of homeostatic adjustments. PMID:26379540

  20. Latent class instrumental variables: A clinical and biostatistical perspective

    PubMed Central

    Baker, Stuart G.; Kramer, Barnett S.; Lindeman, Karen S.

    2015-01-01

    In some two-arm randomized trials, some participants receive the treatment assigned to the other arm as a result of technical problems, refusal of a treatment invitation, or a choice of treatment in an encouragement design. In some before-and-after studies, the availability of a new treatment changes from one time period to this next. Under assumptions that are often reasonable, the latent class instrumental variable (IV) method estimates the effect of treatment received in the aforementioned scenarios involving all-or-none compliance and all-or-none availability. Key aspects are four initial latent classes (sometimes called principal strata) based on treatment received if in each randomization group or time period, the exclusion restriction assumption (in which randomization group or time period is an instrumental variable), the monotonicity assumption (which drops an implausible latent class from the analysis), and the estimated effect of receiving treatment in one latent class (sometimes called efficacy, the local average treatment effect, or the complier average causal effect). Since its independent formulations in the biostatistics and econometrics literatures, the latent class IV method (which has no well-established name) has gained increasing popularity. We review the latent class IV method from a clinical and biostatistical perspective, focusing on underlying assumptions, methodological extensions, and applications in our fields of obstetrics and cancer research. PMID:26239275

  1. An Exploration of Computer Game-Based Instruction in the “World History” Class in Secondary Education: A Comparative Study in China

    PubMed Central

    Yu, Zhonggen; Yu, Wei Hua; Fan, Xiaohui; Wang, Xiao

    2014-01-01

    So far, many studies on educational games have been carried out in America and Europe. Very few related empirical studies, however, have been conducted in China. This study, combining both quantitative with qualitative research methods, possibly compensated for this regret. The study compared data collected from two randomly selected classes (out of 13 classes) under computer game-based instruction (CGBI) and non-computer game-based instruction (NCGBI), respectively, in a senior high school located in Nanjing, Capital of Jiangsu Province, in China. The participants were 103 students, composed of 52 boys and 51 girls (aged 17-18 years old). The following conclusion was reached: (1) participants under CGBI obtained significantly greater learning achievement than those under NCGBI; (2) participants were significantly more motivated by CGBI compared with NCGBI; (3) there were no significant differences in learning achievement between boys and girls; although (4) boys were significantly more motivated by CGBI than girls. Both disadvantages and advantages were discussed, together with directions for future research. PMID:24816635

  2. An exploration of computer game-based instruction in the "world history" class in secondary education: a comparative study in China.

    PubMed

    Yu, Zhonggen; Yu, Wei Hua; Fan, Xiaohui; Wang, Xiao

    2014-01-01

    So far, many studies on educational games have been carried out in America and Europe. Very few related empirical studies, however, have been conducted in China. This study, combining both quantitative with qualitative research methods, possibly compensated for this regret. The study compared data collected from two randomly selected classes (out of 13 classes) under computer game-based instruction (CGBI) and non-computer game-based instruction (NCGBI), respectively, in a senior high school located in Nanjing, Capital of Jiangsu Province, in China. The participants were 103 students, composed of 52 boys and 51 girls (aged 17-18 years old). The following conclusion was reached: (1) participants under CGBI obtained significantly greater learning achievement than those under NCGBI; (2) participants were significantly more motivated by CGBI compared with NCGBI; (3) there were no significant differences in learning achievement between boys and girls; although (4) boys were significantly more motivated by CGBI than girls. Both disadvantages and advantages were discussed, together with directions for future research.

  3. Evaluation of 107 legumes for renewable sources of energy

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

    Roth, W.B.; Carr, M.E.; Cull, I.M.

    One hundred and seven species of randomly-collected Leguminosae were evaluated for their potential as energy-producing crops. Whole plants, excluding roots, were chemically analyzed, and 11 species were identified as the more promising for future considerations based on a numerical rating system developed at this Center. Of the 11 species, one contained principally rubber (polyisoprene) in the hydrocarbon fraction and 7 contained principally wax. Hydrocarbon fractions of 3 species with less than 0.4% were not examined. The oils of species with at least 3.0% oil were examined by thin layer chromatography (TLC) to determine classes of components and were given amore » saponification treatment to determine yields of unsaponifiable matter and fatty acids. The oil of one species was quantitatively analyzed for classes of compounds by TLC-flame ionization detection. Selected species with ratings greater than 10 are briefly discussed. 16 references, 1 figure, 2 tables.« less

  4. Designing a national soil erosion monitoring network for England and Wales

    NASA Astrophysics Data System (ADS)

    Lark, Murray; Rawlins, Barry; Anderson, Karen; Evans, Martin; Farrow, Luke; Glendell, Miriam; James, Mike; Rickson, Jane; Quine, Timothy; Quinton, John; Brazier, Richard

    2014-05-01

    Although soil erosion is recognised as a significant threat to sustainable land use and may be a priority for action in any forthcoming EU Soil Framework Directive, those responsible for setting national policy with respect to erosion are constrained by a lack of robust, representative, data at large spatial scales. This reflects the process-orientated nature of much soil erosion research. Recognising this limitation, The UK Department for Environment, Food and Rural Affairs (Defra) established a project to pilot a cost-effective framework for monitoring of soil erosion in England and Wales (E&W). The pilot will compare different soil erosion monitoring methods at a site scale and provide statistical information for the final design of the full national monitoring network that will: provide unbiased estimates of the spatial mean of soil erosion rate across E&W (tonnes ha-1 yr-1) for each of three land-use classes - arable and horticultural grassland upland and semi-natural habitats quantify the uncertainty of these estimates with confidence intervals. Probability (design-based) sampling provides most efficient unbiased estimates of spatial means. In this study, a 16 hectare area (a square of 400 x 400 m) positioned at the centre of a 1-km grid cell, selected at random from mapped land use across E&W, provided the sampling support for measurement of erosion rates, with at least 94% of the support area corresponding to the target land use classes. Very small or zero erosion rates likely to be encountered at many sites reduce the sampling efficiency and make it difficult to compare different methods of soil erosion monitoring. Therefore, to increase the proportion of samples with larger erosion rates without biasing our estimates, we increased the inclusion probability density in areas where the erosion rate is likely to be large by using stratified random sampling. First, each sampling domain (land use class in E&W) was divided into strata; e.g. two sub-domains within which, respectively, small or no erosion rates, and moderate or larger erosion rates are expected. Each stratum was then sampled independently and at random. The sample density need not be equal in the two strata, but is known and is accounted for in the estimation of the mean and its standard error. To divide the domains into strata we used information on slope angle, previous interpretation of erosion susceptibility of the soil associations that correspond to the soil map of E&W at 1:250 000 (Soil Survey of England and Wales, 1983), and visual interpretation of evidence of erosion from aerial photography. While each domain could be stratified on the basis of the first two criteria, air photo interpretation across the whole country was not feasible. For this reason we used a two-phase random sampling for stratification (TPRS) design (de Gruijter et al., 2006). First, we formed an initial random sample of 1-km grid cells from the target domain. Second, each cell was then allocated to a stratum on the basis of the three criteria. A subset of the selected cells from each stratum were then selected for field survey at random, with a specified sampling density for each stratum so as to increase the proportion of cells where moderate or larger erosion rates were expected. Once measurements of erosion have been made, an estimate of the spatial mean of the erosion rate over the target domain, its standard error and associated uncertainty can be calculated by an expression which accounts for the estimated proportions of the two strata within the initial random sample. de Gruijter, J.J., Brus, D.J., Biekens, M.F.P. & Knotters, M. 2006. Sampling for Natural Resource Monitoring. Springer, Berlin. Soil Survey of England and Wales. 1983 National Soil Map NATMAP Vector 1:250,000. National Soil Research Institute, Cranfield University.

  5. A class of generalized Ginzburg-Landau equations with random switching

    NASA Astrophysics Data System (ADS)

    Wu, Zheng; Yin, George; Lei, Dongxia

    2018-09-01

    This paper focuses on a class of generalized Ginzburg-Landau equations with random switching. In our formulation, the nonlinear term is allowed to have higher polynomial growth rate than the usual cubic polynomials. The random switching is modeled by a continuous-time Markov chain with a finite state space. First, an explicit solution is obtained. Then properties such as stochastic-ultimate boundedness and permanence of the solution processes are investigated. Finally, two-time-scale models are examined leading to a reduction of complexity.

  6. An observation tool for instructor and student behaviors to measure in-class learner engagement: a validation study

    PubMed Central

    Alimoglu, Mustafa K.; Sarac, Didar B.; Alparslan, Derya; Karakas, Ayse A.; Altintas, Levent

    2014-01-01

    Background Efforts are made to enhance in-class learner engagement because it stimulates and enhances learning. However, it is not easy to quantify learner engagement. This study aimed to develop and validate an observation tool for instructor and student behaviors to determine and compare in-class learner engagement levels in four different class types delivered by the same instructor. Methods Observer pairs observed instructor and student behaviors during lectures in large class (LLC, n=2) with third-year medical students, lectures in small class (LSC, n=6) and case-based teaching sessions (CBT, n=4) with fifth-year students, and problem-based learning (PBL) sessions (~7 hours) with second-year students. The observation tool was a revised form of STROBE, an instrument for recording behaviors of an instructor and four randomly selected students as snapshots for 5-min cycles. Instructor and student behaviors were scored 1–5 on this tool named ‘in-class engagement measure (IEM)’. The IEM scores were parallel to the degree of behavior's contribution to active student engagement, so higher scores were associated with more in-class learner engagement. Additionally, the number of questions asked by the instructor and students were recorded. A total of 203 5-min observations were performed (LLC 20, LSC 85, CBT 50, and PBL 48). Results Interobserver agreement on instructor and student behaviors was 93.7% (κ=0.87) and 80.6% (κ=0.71), respectively. Higher median IEM scores were found in student-centered and problem-oriented methods such as CBT and PBL. A moderate correlation was found between instructor and student behaviors (r=0.689). Conclusions This study provides some evidence for validity of the IEM scores as a measure of student engagement in different class types. PMID:25308966

  7. A class of stochastic optimization problems with one quadratic & several linear objective functions and extended portfolio selection model

    NASA Astrophysics Data System (ADS)

    Xu, Jiuping; Li, Jun

    2002-09-01

    In this paper a class of stochastic multiple-objective programming problems with one quadratic, several linear objective functions and linear constraints has been introduced. The former model is transformed into a deterministic multiple-objective nonlinear programming model by means of the introduction of random variables' expectation. The reference direction approach is used to deal with linear objectives and results in a linear parametric optimization formula with a single linear objective function. This objective function is combined with the quadratic function using the weighted sums. The quadratic problem is transformed into a linear (parametric) complementary problem, the basic formula for the proposed approach. The sufficient and necessary conditions for (properly, weakly) efficient solutions and some construction characteristics of (weakly) efficient solution sets are obtained. An interactive algorithm is proposed based on reference direction and weighted sums. Varying the parameter vector on the right-hand side of the model, the DM can freely search the efficient frontier with the model. An extended portfolio selection model is formed when liquidity is considered as another objective to be optimized besides expectation and risk. The interactive approach is illustrated with a practical example.

  8. Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification.

    PubMed

    Shimoni, Yishai

    2018-02-01

    One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes.

  9. Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification

    PubMed Central

    2018-01-01

    One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. PMID:29470520

  10. Estimation of population mean in the presence of measurement error and non response under stratified random sampling

    PubMed Central

    Shabbir, Javid

    2018-01-01

    In the present paper we propose an improved class of estimators in the presence of measurement error and non-response under stratified random sampling for estimating the finite population mean. The theoretical and numerical studies reveal that the proposed class of estimators performs better than other existing estimators. PMID:29401519

  11. Four-Year Follow-Up of Children in the Leap Randomized Trial: Some Planned and Accidental Findings

    ERIC Educational Resources Information Center

    Strain, Phillip S.

    2017-01-01

    This article reports on a 4-year follow-up study from the Learning Experiences and Alternative Program for Preschoolers and Their Parents (LEAP) randomized trial of early intervention for young children with autism. Overall, participants from LEAP classes were marginally superior to comparison class children on elementary school outcomes specific…

  12. Four-Year Follow-Up of Children in the LEAP Randomized Trial: Some Planned and Accidental Findings

    ERIC Educational Resources Information Center

    Strain, Phillip S.

    2017-01-01

    This article reports on a 4-year follow-up study from the Learning Experiences and Alternative Program for Preschoolers and Their Parents (LEAP) randomized trial of early intervention for young children with autism. Overall, participants from LEAP classes were marginally superior to comparison class children on elementary school outcomes specific…

  13. Behavioral and Mental Health Correlates of Youth Stalking Victimization

    PubMed Central

    Reidy, Dennis E.; Smith-Darden, Joanne P.; Kernsmith, Poco D.

    2018-01-01

    Introduction Although recognized as a public health problem, little attention has been paid to the problem of stalking among youth. Latent profile analysis was used to identify latent groups of adolescent stalking victims and their behavioral and mental health correlates. Methods A cross-sectional sample of 1,236 youths were randomly selected from 13 schools stratified by community risk level (i.e., low, moderate, and high risk) and gender. Students completed surveys assessing behavioral indicators of stalking victimization, as well as substance use, sexual behavior, dating violence, and psychiatric symptoms. Data were collected in 2013 and data analyses were performed in 2015. Results Analysis indicated the presence of a non-victim class, a minimal exposure class, and a victim class for boys and girls alike. Approximately 14% of girls and 13% of boys were in the stalking victim class. Adolescents in the victim class reported more symptoms of post-traumatic stress, mood disorder, and hopelessness, as well as more instances of alcohol use, binge drinking, and physical dating violence victimization. Girls in the victim class also reported engaging in sexting behaviors and oral sex with significantly more partners than their non-victim peers. Conclusions These findings provide valuable knowledge of the prevalence and pertinent health correlates of stalking victimization in adolescence. The data suggest a substantial proportion of adolescents are victims of stalking and are likewise at risk for a number of deleterious health outcomes. As such, this population merits further attention by prevention researchers and practitioners. PMID:27743623

  14. Confirmatory factors analysis of science teacher leadership in the Thailand world-class standard schools

    NASA Astrophysics Data System (ADS)

    Thawinkarn, Dawruwan

    2018-01-01

    This research aims to analyze factors of science teacher leadership in the Thailand World-Class Standard Schools. The research instrument was a five scale rating questionnaire with reliability 0.986. The sample group included 500 science teachers from World-Class Standard Schools who had been selected by using the stratified random sampling technique. Factor analysis of science teacher leadership in the Thailand World-Class Standard Schools was conducted by using M plus for Windows. The results are as follows: The results of confirmatory factor analysis on science teacher leadership in the Thailand World-Class Standard Schools revealed that the model significantly correlated with the empirical data. The consistency index value was x2 = 105.655, df = 88, P-Value = 0.086, TLI = 0.997, CFI = 0.999, RMSEA = 0.022, and SRMR = 0.019. The value of factor loading of science teacher leadership was positive, with statistical significance at the level of 0.01. The value of six factors was between 0.880-0.996. The highest factor loading was the professional learning community, followed by child-centered instruction, participation in development, the role model in teaching, transformational leaders, and self-development with factor loading at 0.996, 0.928, 0.911, 0.907, 0.901, and 0.871, respectively. The reliability of each factor was 99.1%, 86.0%, 83.0%, 82.2%, 81.0%, and 75.8%, respectively.

  15. Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set.

    PubMed

    Zhang, Jinshui; Yuan, Zhoumiqi; Shuai, Guanyuan; Pan, Yaozhong; Zhu, Xiufang

    2017-04-26

    This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM) method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient ( C ) and kernel width ( s ), in mapping homogeneous specific land cover.

  16. Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes.

    PubMed

    Borquis, Rusbel Raul Aspilcueta; Neto, Francisco Ribeiro de Araujo; Baldi, Fernando; Hurtado-Lugo, Naudin; de Camargo, Gregório M F; Muñoz-Berrocal, Milthon; Tonhati, Humberto

    2013-09-01

    In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  17. Randomized Clinical Trial of a Self-Adhering Flowable Composite for Class I Restorations: 2-Year Results.

    PubMed

    Sabbagh, J; Dagher, S; El Osta, N; Souhaid, P

    2017-01-01

    Objectives. To compare the clinical performances of a self-adhering resin composite and a conventional flowable composite with a self-etch bonding system on permanent molars. The influence of using rubber dam versus cotton roll isolation was also investigated. Materials and Methods. Patients aged between 6 and 12 years and presenting at least two permanent molars in need of small class I restorations were selected. Thirty-four pairs of restorations were randomly placed by the same operator. Fifteen patients were treated under rubber dam and nineteen using cotton rolls isolation and saliva ejector. They were evaluated according to the modified USPHS criteria at baseline, 6 months, and 1 and 2 years by two independent evaluators. Results. All patients attended the two-year recall. For all measured variables, there was no significant difference between rubber dam and cotton after 2 years of restoration with Premise Flowable or Vertise Flow ( p value > 0.05). The percentage of restorations scored alpha decreased significantly over time with Premise Flowable and Vertise Flow for marginal adaptation and surface texture as well as marginal discoloration while it did not vary significantly for color matching. After 2 years, Vertise Flow showed a similar behaviour to the Premise Flowable used with a self-adhesive resin system.

  18. A Predictive Model for Toxicity Effects Assessment of Biotransformed Hepatic Drugs Using Iterative Sampling Method.

    PubMed

    Tharwat, Alaa; Moemen, Yasmine S; Hassanien, Aboul Ella

    2016-12-09

    Measuring toxicity is one of the main steps in drug development. Hence, there is a high demand for computational models to predict the toxicity effects of the potential drugs. In this study, we used a dataset, which consists of four toxicity effects:mutagenic, tumorigenic, irritant and reproductive effects. The proposed model consists of three phases. In the first phase, rough set-based methods are used to select the most discriminative features for reducing the classification time and improving the classification performance. Due to the imbalanced class distribution, in the second phase, different sampling methods such as Random Under-Sampling, Random Over-Sampling and Synthetic Minority Oversampling Technique are used to solve the problem of imbalanced datasets. ITerative Sampling (ITS) method is proposed to avoid the limitations of those methods. ITS method has two steps. The first step (sampling step) iteratively modifies the prior distribution of the minority and majority classes. In the second step, a data cleaning method is used to remove the overlapping that is produced from the first step. In the third phase, Bagging classifier is used to classify an unknown drug into toxic or non-toxic. The experimental results proved that the proposed model performed well in classifying the unknown samples according to all toxic effects in the imbalanced datasets.

  19. Importance of implementation level when evaluating the effect of the Hi Five Intervention on infectious illness and illness-related absenteeism.

    PubMed

    Denbæk, Anne Maj; Andersen, Anette; Bast, Lotus Sofie; Bonnesen, Camilla Thørring; Ersbøll, Annette Kjær; Due, Pernille; Johansen, Anette

    2018-05-01

    There is limited research on the importance of implementation when evaluating the effect of hand hygiene interventions in school settings in developed countries. The aim of this study was to examine the association between an implementation index and the effect of the intervention. The Hi Five Intervention was evaluated in a 3-armed cluster randomized controlled trial involving 43 randomly selected Danish schools. Analyses investigating the association between implementation of the Hi Five Intervention and infectious illness days, infectious illness episodes, illness-related absenteeism, and hand hygiene were carried out in a multilevel model (school, class, and child). The level of implementation was associated with hand hygiene and potentially associated with number of infectious illness days and infectious illness episodes among children. This association was not found for illness-related absenteeism. Classes that succeeded in achieving a high level of implementation of the Hi Five Intervention had a lower number of infectious illness days and infectious illness episodes, suggesting that the Hi Five Intervention, if implemented adequately, may be relevant as a tool to decrease infectious illness in a Danish school setting. Copyright © 2018 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

  20. Intra-class correlation estimates for assessment of vitamin A intake in children.

    PubMed

    Agarwal, Girdhar G; Awasthi, Shally; Walter, Stephen D

    2005-03-01

    In many community-based surveys, multi-level sampling is inherent in the design. In the design of these studies, especially to calculate the appropriate sample size, investigators need good estimates of intra-class correlation coefficient (ICC), along with the cluster size, to adjust for variation inflation due to clustering at each level. The present study used data on the assessment of clinical vitamin A deficiency and intake of vitamin A-rich food in children in a district in India. For the survey, 16 households were sampled from 200 villages nested within eight randomly-selected blocks of the district. ICCs and components of variances were estimated from a three-level hierarchical random effects analysis of variance model. Estimates of ICCs and variance components were obtained at village and block levels. Between-cluster variation was evident at each level of clustering. In these estimates, ICCs were inversely related to cluster size, but the design effect could be substantial for large clusters. At the block level, most ICC estimates were below 0.07. At the village level, many ICC estimates ranged from 0.014 to 0.45. These estimates may provide useful information for the design of epidemiological studies in which the sampled (or allocated) units range in size from households to large administrative zones.

  1. Beliefs about the causes of obesity in a national sample of 4th year medical students.

    PubMed

    Phelan, Sean M; Burgess, Diana J; Burke, Sara E; Przedworski, Julia M; Dovidio, John F; Hardeman, Rachel; Morris, Megan; van Ryn, Michelle

    2015-11-01

    Physician knowledge of the complex contributors to obesity varies. We do not know whether today's medical students are graduating with deep understanding of the causes of obesity. Our objective was to assess beliefs about causes of obesity in a national sample of 4th year medical students. We randomly selected 2000 4th year students from a random sample of 50 U.S. medical schools and asked them to rate the importance of several factors as causes of obesity. Of those invited, 1244 (62%) responded. We conducted latent class analysis to identify groups with similar response patterns. Most students demonstrated knowledge that obesity has multiple contributors. Students fell into 1 of 4 classes: (1) more likely to endorse all contributors (28%), (2) more likely to endorse physiological contributors (27%), (3) more likely to endorse behavioral or social contributors (24%), and (4) unlikely to endorse contributors outside of overeating and physical activity (22%). Though students were generally aware of multiple causes, there were 4 distinct patterns of beliefs, with implications for patient care. Targeted interventions may help to improve depth of knowledge about the causes of obesity and lead to more effective care for obese patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  2. Insurees' preferences in hospital choice-A population-based study.

    PubMed

    Schuldt, Johannes; Doktor, Anna; Lichters, Marcel; Vogt, Bodo; Robra, Bernt-Peter

    2017-10-01

    In Germany, the patient himself makes the choice for or against a health service provider. Hospital comparison websites offer him possibilities to inform himself before choosing. However, it remains unclear, how health care consumers use those websites, and there is little information about how preferences in hospital choice differ interpersonally. We conducted a Discrete-Choice-Experiment (DCE) on hospital choice with 1500 randomly selected participants (age 40-70) in three different German cities selecting four attributes for hospital vignettes. The analysis of the study draws on multilevel mixed effects logit regression analyses with the dependent variables: "chance to select a hospital" and "choice confidence". Subsequently, we performed a Latent-Class-Analysis to uncover consumer segments with distinct preferences. 590 of the questionnaires were evaluable. All four attributes of the hospital vignettes have a significant impact on hospital choice. The attribute "complication rate" exerts the highest impact on consumers' decisions and reported choice confidence. Latent-Class-Analysis results in one dominant consumer segment that considered the complication rate the most important decision criterion. Using DCE, we were able to show that the complication rate is an important trusted criterion in hospital choice to a large group of consumers. Our study supports current governmental efforts in Germany to concentrate the provision of specialized health care services. We suggest further national and cross-national research on the topic. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  3. Inference from clustering with application to gene-expression microarrays.

    PubMed

    Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M

    2002-01-01

    There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

  4. Paretian Poisson Processes

    NASA Astrophysics Data System (ADS)

    Eliazar, Iddo; Klafter, Joseph

    2008-05-01

    Many random populations can be modeled as a countable set of points scattered randomly on the positive half-line. The points may represent magnitudes of earthquakes and tornados, masses of stars, market values of public companies, etc. In this article we explore a specific class of random such populations we coin ` Paretian Poisson processes'. This class is elemental in statistical physics—connecting together, in a deep and fundamental way, diverse issues including: the Poisson distribution of the Law of Small Numbers; Paretian tail statistics; the Fréchet distribution of Extreme Value Theory; the one-sided Lévy distribution of the Central Limit Theorem; scale-invariance, renormalization and fractality; resilience to random perturbations.

  5. Deep neural network convolution (NNC) for three-class classification of diffuse lung disease opacities in high-resolution CT (HRCT): consolidation, ground-glass opacity (GGO), and normal opacity

    NASA Astrophysics Data System (ADS)

    Hashimoto, Noriaki; Suzuki, Kenji; Liu, Junchi; Hirano, Yasushi; MacMahon, Heber; Kido, Shoji

    2018-02-01

    Consolidation and ground-glass opacity (GGO) are two major types of opacities associated with diffuse lung diseases. Accurate detection and classification of such opacities are crucially important in the diagnosis of lung diseases, but the process is subjective, and suffers from interobserver variability. Our study purpose was to develop a deep neural network convolution (NNC) system for distinguishing among consolidation, GGO, and normal lung tissue in high-resolution CT (HRCT). We developed ensemble of two deep NNC models, each of which was composed of neural network regression (NNR) with an input layer, a convolution layer, a fully-connected hidden layer, and a fully-connected output layer followed by a thresholding layer. The output layer of each NNC provided a map for the likelihood of being each corresponding lung opacity of interest. The two NNC models in the ensemble were connected in a class-selection layer. We trained our NNC ensemble with pairs of input 2D axial slices and "teaching" probability maps for the corresponding lung opacity, which were obtained by combining three radiologists' annotations. We randomly selected 10 and 40 slices from HRCT scans of 172 patients for each class as a training and test set, respectively. Our NNC ensemble achieved an area under the receiver-operating-characteristic (ROC) curve (AUC) of 0.981 and 0.958 in distinction of consolidation and GGO, respectively, from normal opacity, yielding a classification accuracy of 93.3% among 3 classes. Thus, our deep-NNC-based system for classifying diffuse lung diseases achieved high accuracies for classification of consolidation, GGO, and normal opacity.

  6. U.S. Food Safety and Inspection Service testing for Salmonella in selected raw meat and poultry products in the United States, 1998 through 2003: analysis of set results.

    PubMed

    Naugle, Alecia Larew; Barlow, Kristina E; Eblen, Denise R; Teter, Vanessa; Umholtz, Robert

    2006-11-01

    The U.S. Food Safety and Inspection Service (FSIS) tests sets of samples of selected raw meat and poultry products for Salmonella to ensure that federally inspected establishments meet performance standards defined in the pathogen reduction-hazard analysis and critical control point system (PR-HACCP) final rule. In the present report, sample set results are described and associations between set failure and set and establishment characteristics are identified for 4,607 sample sets collected from 1998 through 2003. Sample sets were obtained from seven product classes: broiler chicken carcasses (n = 1,010), cow and bull carcasses (n = 240), market hog carcasses (n = 560), steer and heifer carcasses (n = 123), ground beef (n = 2,527), ground chicken (n = 31), and ground turkey (n = 116). Of these 4,607 sample sets, 92% (4,255) were collected as part of random testing efforts (A sets), and 93% (4,166) passed. However, the percentage of positive samples relative to the maximum number of positive results allowable in a set increased over time for broilers but decreased or stayed the same for the other product classes. Three factors associated with set failure were identified: establishment size, product class, and year. Set failures were more likely early in the testing program (relative to 2003). Small and very small establishments were more likely to fail than large ones. Set failure was less likely in ground beef than in other product classes. Despite an overall decline in set failures through 2003, these results highlight the need for continued vigilance to reduce Salmonella contamination in broiler chicken and continued implementation of programs designed to assist small and very small establishments with PR-HACCP compliance issues.

  7. Comparison of ADM and Connective Tissue Graft as the Membrane in Class II Furcation Defect Regeneration: A Randomized Clinical Trial

    PubMed Central

    Esfahanian, Vahid; Farhad, Shirin; Sadighi Shamami, Mehrnaz

    2014-01-01

    Background and aims. Furcally-involved teeth present unique challenges to the success of periodontal therapy and influence treatment outcomes. This study aimed to assess to compare use of ADM and connective tissue membrane in class II furcation defect regeneration. Materials and methods. 10 patient with 2 bilaterally class II furcation defects in first and/or second maxilla or man-dibular molar without interproximal furcation involvement, were selected. Four weeks after initial phase of treatment, before and thorough the surgery pocket depth (PD), clinical attachment level to stent (CAL-S), free gingival margin to stent(FGM-S) , crestal bone to stent (Crest-S), horizontal defect depth to stent (HDD-S) and vertical defect depth to stent (VDD-S) and crestal bone to defect depth measured from stent margin. Thereafter, one side randomly treated using connective tissue and DFDBA (study group) and opposite side received ADM and DFDBA (control group). After 6 months, soft and hard tissue parameters measured again in re-entry. Results. Both groups presented improvements after therapies (P & 0.05). No inter-group differences were seen in PD re-duction (P = 0.275), CAL gain (P = 0.156), free gingival margin (P = 0.146), crest of the bone (P = 0.248), reduction in horizontal defects depth (P = 0.139) and reduction in vertical defects depth (P = 0.149). Conclusion. Both treatments modalities have potential of regeneration without any adverse effect on healing process. Connective tissue grafts did not have significant higher bone fill compared to that of ADM. PMID:25093054

  8. Prevalence of attention deficit hyperactivity disorder and comorbid psychiatric and behavioral problems among primary school students in western Saudi Arabia

    PubMed Central

    AlZaben, Faten N.; Sehlo, Mohammad G.; Alghamdi, Waleed A.; Tayeb, Haythum O.; Khalifa, Doaa A.; Mira, Abdulrahman T.; Alshuaibi, Abdulaziz M.; Alguthmi, Mosab A.; Derham, Ahmad A.; Koenig, Harold G.

    2018-01-01

    Objectives: To determine the prevalence of attention deficit hyperactivity disorder (ADHD), subtypes of ADHD, and psychiatric, academic, and behavioral comorbidity in public primary school students in Jeddah, Saudi Arabia. Methods: This is a cross-sectional study. A simple random sample of 6 primary government schools in Jeddah, Saudi Arabia, was identified (3 male, 3 female), and a random sample of classes in each of grades 1-6 were selected. Between July and November 2016, teachers in these classes were asked to complete the Vanderbilt ADHD scale on all students in their classes. Results: A total of 929 students were screened. The overall prevalence of ADHD was 5% (5.3% in girls, 4.7% in boys). The most prevalent subtype of ADHD was combined type (2.7%), followed by hyperactive type (1.2%), and inattentive type (1.1%). The highest prevalence of ADHD overall was in grade 3 (7.1%) and the lowest prevalence in grade 6 (3.4%). Among students with ADHD, prevalence of comorbid psychiatric, academic, and behavioral problems was widespread (56.5% oppositional defiant disorder/conduct disorder, 54.4% impaired academic performance, 44.4% classroom behavioral problems, 41.3% depression/anxiety). Comorbid problems were especially prevalent in combined ADHD subtype and in boys. Conclusions: Attention deficit hyperactivity disorder is common in primary school children in Jeddah, and is associated with widespread psychiatric, academic, and behavioral problems, especially in boys. These findings have implications for the diagnosis and treatment of this serious neurobehavioral disorder. PMID:29332109

  9. Agent Reward Shaping for Alleviating Traffic Congestion

    NASA Technical Reports Server (NTRS)

    Tumer, Kagan; Agogino, Adrian

    2006-01-01

    Traffic congestion problems provide a unique environment to study how multi-agent systems promote desired system level behavior. What is particularly interesting in this class of problems is that no individual action is intrinsically "bad" for the system but that combinations of actions among agents lead to undesirable outcomes, As a consequence, agents need to learn how to coordinate their actions with those of other agents, rather than learn a particular set of "good" actions. This problem is ubiquitous in various traffic problems, including selecting departure times for commuters, routes for airlines, and paths for data routers. In this paper we present a multi-agent approach to two traffic problems, where far each driver, an agent selects the most suitable action using reinforcement learning. The agent rewards are based on concepts from collectives and aim to provide the agents with rewards that are both easy to learn and that if learned, lead to good system level behavior. In the first problem, we study how agents learn the best departure times of drivers in a daily commuting environment and how following those departure times alleviates congestion. In the second problem, we study how agents learn to select desirable routes to improve traffic flow and minimize delays for. all drivers.. In both sets of experiments,. agents using collective-based rewards produced near optimal performance (93-96% of optimal) whereas agents using system rewards (63-68%) barely outperformed random action selection (62-64%) and agents using local rewards (48-72%) performed worse than random in some instances.

  10. Weighted stacking of seismic AVO data using hybrid AB semblance and local similarity

    NASA Astrophysics Data System (ADS)

    Deng, Pan; Chen, Yangkang; Zhang, Yu; Zhou, Hua-Wei

    2016-04-01

    The common-midpoint (CMP) stacking technique plays an important role in enhancing the signal-to-noise ratio (SNR) in seismic data processing and imaging. Weighted stacking is often used to improve the performance of conventional equal-weight stacking in further attenuating random noise and handling the amplitude variations in real seismic data. In this study, we propose to use a hybrid framework of combining AB semblance and a local-similarity-weighted stacking scheme. The objective is to achieve an optimal stacking of the CMP gathers with class II amplitude-variation-with-offset (AVO) polarity-reversal anomaly. The selection of high-quality near-offset reference trace is another innovation of this work because of its better preservation of useful energy. Applications to synthetic and field seismic data demonstrate a great improvement using our method to capture the true locations of weak reflections, distinguish thin-bed tuning artifacts, and effectively attenuate random noise.

  11. A Design for a Multi-Use Object Editor with Connections

    DTIC Science & Technology

    1991-10-01

    Variables of Class Select 14 3.6.2 Methods of Class Select 14 3.6.3 Application States 14 3.7 Class Clipboard 15 3.8 Class Crestore 15 3.9 Conclusions 15 4...this is not directly related to cutting and past- ing between applications. 3.8 CLASS CRESTORE Class crestore holds a connection until all the

  12. Understanding Randomness and its Impact on Student Learning: Lessons Learned from Building the Biology Concept Inventory (BCI)

    PubMed Central

    Garvin-Doxas, Kathy

    2008-01-01

    While researching student assumptions for the development of the Biology Concept Inventory (BCI; http://bioliteracy.net), we found that a wide class of student difficulties in molecular and evolutionary biology appears to be based on deep-seated, and often unaddressed, misconceptions about random processes. Data were based on more than 500 open-ended (primarily) college student responses, submitted online and analyzed through our Ed's Tools system, together with 28 thematic and think-aloud interviews with students, and the responses of students in introductory and advanced courses to questions on the BCI. Students believe that random processes are inefficient, whereas biological systems are very efficient. They are therefore quick to propose their own rational explanations for various processes, from diffusion to evolution. These rational explanations almost always make recourse to a driver, e.g., natural selection in evolution or concentration gradients in molecular biology, with the process taking place only when the driver is present, and ceasing when the driver is absent. For example, most students believe that diffusion only takes place when there is a concentration gradient, and that the mutational processes that change organisms occur only in response to natural selection pressures. An understanding that random processes take place all the time and can give rise to complex and often counterintuitive behaviors is almost totally absent. Even students who have had advanced or college physics, and can discuss diffusion correctly in that context, cannot make the transfer to biological processes, and passing through multiple conventional biology courses appears to have little effect on their underlying beliefs. PMID:18519614

  13. Pharmacotherapy of focal epilepsy in children: a systematic review of approved agents.

    PubMed

    Arya, Ravindra; Glauser, Tracy A

    2013-04-01

    Partial-onset seizures contribute the bulk of seizure burden in childhood epilepsy. The therapeutic decision making involves consideration of factors specific to drug, patient and socioeconomic situation. This paper systematically reviews the available efficacy/effectiveness evidence for various anti-epileptic drugs (AED) as monotherapy and adjunctive therapy for partial-onset seizures in children. Relevant randomized clinical trials (RCTs) were identified by a structured PubMed search, supplemented by an additional hand search of reference lists and authors' files. Eligible studies were reviewed and data extracted into tables. Included RCTs were classified based on accepted published criteria. Only efficacy and effectiveness outcome measures were evaluated since there is little scientifically rigorous comprehensive AED adverse effects data. Oxcarbazepine is the only AED with Class I evidence for efficacy/effectiveness as initial monotherapy for partial-onset seizures in children. Carbamazepine, clobazam, lamotrigine, phenobarbital, phenytoin, topiramate, valproate, vigabatrin and zonisamide have, at best, Class III efficacy/effectiveness evidence for monotherapy of partial-onset seizures in children. For adjunctive therapy, gabapentin, lamotrigine, levetiracetam, oxcarbazepine and topiramate have Class I efficacy/effectiveness evidence for treatment of pediatric partial-onset seizures. This efficacy/effectiveness analysis must not be used in isolation when selecting therapy. AED selection for a specific child needs to integrate a drug's efficacy/effectiveness data with its safety and tolerability profile, pharmacokinetic properties, available formulations, and patient specific characteristics. It is critical that physicians and patients incorporate all these relevant variables when choosing AED therapy.

  14. An evaluation of a body image intervention in adolescent girls delivered in single-sex versus co-educational classroom settings.

    PubMed

    Dunstan, Candice J; Paxton, Susan J; McLean, Siân A

    2017-04-01

    Body dissatisfaction is now recognized as having considerable negative impact on social, psychological, and physical health, particularly in adolescent girls. Consequently, we have developed a six-session co-educational body image intervention (Happy Being Me Co-educational) designed to reduce body dissatisfaction and its risk factors in Grade 7 girls. In addition to evaluating the program's efficacy, we aimed to identify whether girls would benefit equally when it was delivered as a universal intervention to a whole class including both boys and girls (co-educational delivery), or delivered as a selective intervention to girls only (single-sex delivery). Participants were 200 Grade 7 girls from five schools in Melbourne, Australia. Schools were randomly allocated to receive the intervention in single-sex classes (n=74), co-educational classes (n=73), or participate as a no-intervention control (n=53). Girls completed self-report assessments of body dissatisfaction, psychological (internalization of the thin ideal, appearance comparison, and self-esteem) and peer environment (weight-related teasing and appearance conversations) risk factors for body dissatisfaction, and dietary restraint, at baseline, post-intervention, and at 6-month follow-up. Significant improvements in body dissatisfaction and psychological risk factors were observed in the intervention group at post-intervention and these were maintained at follow-up for psychological risk factors. Importantly, no significant differences between universal and selective delivery were observed, suggesting that the intervention is appropriate for dissemination in both modes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Natural science modules with SETS approach to improve students’ critical thinking ability

    NASA Astrophysics Data System (ADS)

    Budi, A. P. S.; Sunarno, W.; Sugiyarto

    2018-05-01

    SETS (Science, Environment, Technology and Society) approach for learning is important to be developed for middle school, since it can improve students’ critical thinking ability. This research aimed to determine feasibility and the effectiveness of Natural Science Module with SETS approach to increase their critical thinking ability. The module development was done by invitation, exploration, explanation, concept fortifying, and assessment. Questionnaire and test performed including pretest and posttest with control group design were used as data collection technique in this research. Two classes were selected randomly as samples and consisted of 32 students in each group. Descriptive data analysis was used to analyze the module feasibility and t-test was used to analyze their critical thinking ability. The results showed that the feasibility of the module development has a very good results based on assessment of the experts, practitioners and peers. Based on the t-test results, there was significant difference between control class and experiment class (0.004), with n-gain score of control and the experiment class respectively 0.270 (low) and 0.470 (medium). It showed that the module was more effective than the textbook. It was able to improve students’ critical thinking ability and appropriate to be used in learning process.

  16. Biosynthetic Potential-Based Strain Prioritization for Natural Product Discovery: A Showcase for Diterpenoid-Producing Actinomycetes

    PubMed Central

    2015-01-01

    Natural products remain the best sources of drugs and drug leads and serve as outstanding small-molecule probes to dissect fundamental biological processes. A great challenge for the natural product community is to discover novel natural products efficiently and cost effectively. Here we report the development of a practical method to survey biosynthetic potential in microorganisms, thereby identifying the most promising strains and prioritizing them for natural product discovery. Central to our approach is the innovative preparation, by a two-tiered PCR method, of a pool of pathway-specific probes, thereby allowing the survey of all variants of the biosynthetic machineries for the targeted class of natural products. The utility of the method was demonstrated by surveying 100 strains, randomly selected from our actinomycete collection, for their biosynthetic potential of four classes of natural products, aromatic polyketides, reduced polyketides, nonribosomal peptides, and diterpenoids, identifying 16 talented strains. One of the talented strains, Streptomyces griseus CB00830, was finally chosen to showcase the discovery of the targeted classes of natural products, resulting in the isolation of three diterpenoids, six nonribosomal peptides and related metabolites, and three polyketides. Variations of this method should be applicable to the discovery of other classes of natural products. PMID:24484381

  17. Latent class instrumental variables: a clinical and biostatistical perspective.

    PubMed

    Baker, Stuart G; Kramer, Barnett S; Lindeman, Karen S

    2016-01-15

    In some two-arm randomized trials, some participants receive the treatment assigned to the other arm as a result of technical problems, refusal of a treatment invitation, or a choice of treatment in an encouragement design. In some before-and-after studies, the availability of a new treatment changes from one time period to this next. Under assumptions that are often reasonable, the latent class instrumental variable (IV) method estimates the effect of treatment received in the aforementioned scenarios involving all-or-none compliance and all-or-none availability. Key aspects are four initial latent classes (sometimes called principal strata) based on treatment received if in each randomization group or time period, the exclusion restriction assumption (in which randomization group or time period is an instrumental variable), the monotonicity assumption (which drops an implausible latent class from the analysis), and the estimated effect of receiving treatment in one latent class (sometimes called efficacy, the local average treatment effect, or the complier average causal effect). Since its independent formulations in the biostatistics and econometrics literatures, the latent class IV method (which has no well-established name) has gained increasing popularity. We review the latent class IV method from a clinical and biostatistical perspective, focusing on underlying assumptions, methodological extensions, and applications in our fields of obstetrics and cancer research. Copyright © 2015 John Wiley & Sons, Ltd.

  18. The effect of using graphic organizers in the teaching of standard biology

    NASA Astrophysics Data System (ADS)

    Pepper, Wade Louis, Jr.

    This study was conducted to determine if the use of graphic organizers in the teaching of standard biology would increase student achievement, involvement and quality of activities. The subjects were 10th grade standard biology students in a large southern inner city high school. The study was conducted over a six-week period in an instructional setting using action research as the investigative format. After calculation of the homogeneity between classes, random selection was used to determine the graphic organizer class and the control class. The graphic organizer class was taught unit material through a variety of instructional methods along with the use of teacher generated graphic organizers. The control class was taught the same unit material using the same instructional methods, but without the use of graphic organizers. Data for the study were gathered from in-class written assignments, teacher-generated tests and text-generated tests, and rubric scores of an out-of-class written assignment and project. Also, data were gathered from student reactions, comments, observations and a teacher's research journal. Results were analyzed using descriptive statistics and qualitative interpretation. By comparing statistical results, it was determined that the use of graphic organizers did not make a statistically significant difference in the understanding of biological concepts and retention of factual information. Furthermore, the use of graphic organizers did not make a significant difference in motivating students to fulfill all class assignments with quality efforts and products. However, based upon student reactions and comments along with observations by the researcher, graphic organizers were viewed by the students as a favorable and helpful instructional tool. In lieu of statistical results, student gains from instructional activities using graphic organizers were positive and merit the continuation of their use as an instructional tool.

  19. What Doesn't Work for Whom? Exploring Heterogeneity in Responsiveness to the Family Check-Up in Early Childhood Using a Mixture Model Approach.

    PubMed

    Pelham, William E; Dishion, Thomas J; Tein, Jenn-Yun; Shaw, Daniel S; Wilson, Melvin N

    2017-11-01

    This study applied latent class analysis to a family-centered prevention trial in early childhood to identify subgroups of families with differential responsiveness to the Family Check-Up (FCU) intervention. The sample included 731 families with 2-year-olds randomized to the FCU or control condition and followed through age 5 with yearly follow-up assessments. A two-step mixture model was used to examine whether specific constellations of family characteristics at age 2 (baseline) were related to intervention response across ages 3, 4, and 5. The first step empirically identified latent classes of families based on several family risk and adjustment variables selected on the basis of previous research. The second step modeled the effect of the FCU on longitudinal change in children's problem behavior in each of the empirically derived latent classes. Results suggested a five-class solution, where a significant intervention effect of moderate to large size was observed in one of the five classes-the class characterized by child neglect, legal problems, and parental mental health issues. Pairwise comparisons revealed that the intervention effect was significantly greater in this class of families than in two other classes that were generally less at risk for the development of child disruptive behavior problems, albeit still low-income. Thus, findings suggest that (a) the FCU is most successful in reducing child problem behavior in more highly distressed, low-income families, and (b) the FCU may have little impact for relatively low-risk, low-income families. Future directions include the development of a brief screening process that can triage low-income families into groups that should be targeted for intervention, redirected to other services, monitored prospectively, or left alone.

  20. Percolation and epidemics in random clustered networks

    NASA Astrophysics Data System (ADS)

    Miller, Joel C.

    2009-08-01

    The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease dynamics. A number of authors have studied percolation or epidemics in clustered networks, but the networks often contain preferential contacts in high degree nodes. We introduce a class of random clustered networks and a class of random unclustered networks with the same preferential mixing. Percolation in the clustered networks reduces the component sizes and increases the epidemic threshold compared to the unclustered networks.

  1. Nonrecurrence and Bell-like inequalities

    NASA Astrophysics Data System (ADS)

    Danforth, Douglas G.

    2017-12-01

    The general class, Λ, of Bell hidden variables is composed of two subclasses ΛR and ΛN such that ΛR⋃ΛN = Λ and ΛR∩ ΛN = {}. The class ΛN is very large and contains random variables whose domain is the continuum, the reals. There are an uncountable infinite number of reals. Every instance of a real random variable is unique. The probability of two instances being equal is zero, exactly zero. ΛN induces sample independence. All correlations are context dependent but not in the usual sense. There is no "spooky action at a distance". Random variables, belonging to ΛN, are independent from one experiment to the next. The existence of the class ΛN makes it impossible to derive any of the standard Bell inequalities used to define quantum entanglement.

  2. Semantic segmentation of 3D textured meshes for urban scene analysis

    NASA Astrophysics Data System (ADS)

    Rouhani, Mohammad; Lafarge, Florent; Alliez, Pierre

    2017-01-01

    Classifying 3D measurement data has become a core problem in photogrammetry and 3D computer vision, since the rise of modern multiview geometry techniques, combined with affordable range sensors. We introduce a Markov Random Field-based approach for segmenting textured meshes generated via multi-view stereo into urban classes of interest. The input mesh is first partitioned into small clusters, referred to as superfacets, from which geometric and photometric features are computed. A random forest is then trained to predict the class of each superfacet as well as its similarity with the neighboring superfacets. Similarity is used to assign the weights of the Markov Random Field pairwise-potential and to account for contextual information between the classes. The experimental results illustrate the efficacy and accuracy of the proposed framework.

  3. The PLUNGE randomized controlled trial: evaluation of a games-based physical activity professional learning program in primary school physical education.

    PubMed

    Miller, Andrew; Christensen, Erin M; Eather, Narelle; Sproule, John; Annis-Brown, Laura; Lubans, David Revalds

    2015-05-01

    To evaluate the efficacy of the Professional Learning for Understanding Games Education (PLUNGE) program on fundamental movement skills (FMS), in-class physical activity and perceived sporting competence. A cluster-randomized controlled trial involving one year six class each from seven primary schools (n=168; mean age=11.2 years, SD=1.0) in the Hunter Region, NSW, Australia. In September (2013) participants were randomized by school into the PLUNGE intervention (n=97 students) or the 7-week wait-list control (n=71) condition. PLUNGE involved the use of Game Centered curriculum delivered via an in-class teacher mentoring program. Students were assessed at baseline and 8-week follow-up for three object control FMS (Test of Gross Motor Development 2), in-class physical activity (pedometer steps/min) and perceived sporting competence (Self-perception Profile for Children). Linear mixed models revealed significant group-by-time intervention effects (all p<0.05) for object control competency (effect size: d=0.9), and in-class pedometer steps/min (d=1.0). No significant intervention effects (p>0.05) were observed for perceived sporting competence. The PLUNGE intervention simultaneously improved object control FMS proficiency and in-class PA in stage three students. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Synopsis of Guidelines for the Clinical Management of Cerebral Cavernous Malformations: Consensus Recommendations Based on Systematic Literature Review by the Angioma Alliance Scientific Advisory Board Clinical Experts Panel

    PubMed Central

    Al-Shahi Salman, Rustam; A. Awad, Issam; Dahlem, Kristen; Flemming, Kelly; Hart, Blaine; Kim, Helen; Jusue-Torres, Ignacio; Kondziolka, Douglas; Lee, Cornelia; Morrison, Leslie; Rigamonti, Daniele; Rebeiz, Tania; Tournier-Lasserve, Elisabeth; Waggoner, Darrel; Whitehead, Kevin

    2017-01-01

    Abstract BACKGROUND: Despite many publications about cerebral cavernous malformations (CCMs), controversy remains regarding diagnostic and management strategies. OBJECTIVE: To develop guidelines for CCM management. METHODS: The Angioma Alliance (www.angioma.org), the patient support group in the United States advocating on behalf of patients and research in CCM, convened a multidisciplinary writing group comprising expert CCM clinicians to help summarize the existing literature related to the clinical care of CCM, focusing on 5 topics: (1) epidemiology and natural history, (2) genetic testing and counseling, (3) diagnostic criteria and radiology standards, (4) neurosurgical considerations, and (5) neurological considerations. The group reviewed literature, rated evidence, developed recommendations, and established consensus, controversies, and knowledge gaps according to a prespecified protocol. RESULTS: Of 1270 publications published between January 1, 1983 and September 31, 2014, we selected 98 based on methodological criteria, and identified 38 additional recent or relevant publications. Topic authors used these publications to summarize current knowledge and arrive at 23 consensus management recommendations, which we rated by class (size of effect) and level (estimate of certainty) according to the American Heart Association/American Stroke Association criteria. No recommendation was level A (because of the absence of randomized controlled trials), 11 (48%) were level B, and 12 (52%) were level C. Recommendations were class I in 8 (35%), class II in 10 (43%), and class III in 5 (22%). CONCLUSION: Current evidence supports recommendations for the management of CCM, but their generally low levels and classes mandate further research to better inform clinical practice and update these recommendations. The complete recommendations document, including the criteria for selecting reference citations, a more detailed justification of the respective recommendations, and a summary of controversies and knowledge gaps, was similarly peer reviewed and is available on line www.angioma.org/CCMGuidelines. PMID:28387823

  5. Intelligent Fault Diagnosis of HVCB with Feature Space Optimization-Based Random Forest

    PubMed Central

    Ma, Suliang; Wu, Jianwen; Wang, Yuhao; Jia, Bowen; Jiang, Yuan

    2018-01-01

    Mechanical faults of high-voltage circuit breakers (HVCBs) always happen over long-term operation, so extracting the fault features and identifying the fault type have become a key issue for ensuring the security and reliability of power supply. Based on wavelet packet decomposition technology and random forest algorithm, an effective identification system was developed in this paper. First, compared with the incomplete description of Shannon entropy, the wavelet packet time-frequency energy rate (WTFER) was adopted as the input vector for the classifier model in the feature selection procedure. Then, a random forest classifier was used to diagnose the HVCB fault, assess the importance of the feature variable and optimize the feature space. Finally, the approach was verified based on actual HVCB vibration signals by considering six typical fault classes. The comparative experiment results show that the classification accuracy of the proposed method with the origin feature space reached 93.33% and reached up to 95.56% with optimized input feature vector of classifier. This indicates that feature optimization procedure is successful, and the proposed diagnosis algorithm has higher efficiency and robustness than traditional methods. PMID:29659548

  6. Impact of a school-based dating violence prevention program among Latino teens: randomized controlled effectiveness trial.

    PubMed

    Jaycox, Lisa H; McCaffrey, Daniel; Eiseman, Beth; Aronoff, Jessica; Shelley, Gene A; Collins, Rebecca L; Marshall, Grant N

    2006-11-01

    Given the high rate of dating violence between teens and associated deleterious outcomes, the need for effective prevention and early intervention programs is clear. Break the Cycle's Ending Violence curriculum, a three-class-session prevention program focused on legal issues, is evaluated here for its impact on Latino/a youth. Tracks within large urban high schools that had at least 80% Latino/a students were randomized to immediate or delayed curriculum. Classrooms were randomly selected within tracks and individual student outcomes were assessed pre- and postintervention and six months later. Students in intervention classrooms showed improved knowledge, less acceptance of female-on-male aggression, and enhanced perception of the helpfulness and likelihood of seeking assistance from a number of sources immediately after the program. Improved knowledge and perceived helpfulness of an attorney were maintained six months later. There were no differences in recent abusive/fearful dating experiences or violence victimization or perpetration. The Ending Violence curriculum has an impact on teen norms, knowledge, and help-seeking proclivities that may aid in early intervention for dating violence among Latino/a students.

  7. Random regression models on Legendre polynomials to estimate genetic parameters for weights from birth to adult age in Canchim cattle.

    PubMed

    Baldi, F; Albuquerque, L G; Alencar, M M

    2010-08-01

    The objective of this work was to estimate covariance functions for direct and maternal genetic effects, animal and maternal permanent environmental effects, and subsequently, to derive relevant genetic parameters for growth traits in Canchim cattle. Data comprised 49,011 weight records on 2435 females from birth to adult age. The model of analysis included fixed effects of contemporary groups (year and month of birth and at weighing) and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were allowed to vary and were modelled by a step function with 1, 4 or 11 classes based on animal's age. The model fitting four classes of residual variances was the best. A total of 12 random regression models from second to seventh order were used to model direct and maternal genetic effects, animal and maternal permanent environmental effects. The model with direct and maternal genetic effects, animal and maternal permanent environmental effects fitted by quadric, cubic, quintic and linear Legendre polynomials, respectively, was the most adequate to describe the covariance structure of the data. Estimates of direct and maternal heritability obtained by multi-trait (seven traits) and random regression models were very similar. Selection for higher weight at any age, especially after weaning, will produce an increase in mature cow weight. The possibility to modify the growth curve in Canchim cattle to obtain animals with rapid growth at early ages and moderate to low mature cow weight is limited.

  8. Implementing Team-Based Learning in Middle School Social Studies Classes

    ERIC Educational Resources Information Center

    Wanzek, Jeanne; Kent, Shawn C.; Vaughn, Sharon; Swanson, Elizabeth A.; Roberts, Greg; Haynes, Martha

    2015-01-01

    The authors examined the effects of team-based learning (TBL) implemented in Grade 8 social studies classes on student content acquisition. Twenty-four classes were randomly assigned to treatment or comparison blocking on teacher. In the treatment classes teachers integrated TBL practices in the content instruction. The authors examined teacher…

  9. Partially Nested Randomized Controlled Trials in Education Research: A Guide to Design and Analysis. NCER 2014-2000

    ERIC Educational Resources Information Center

    Lohr, Sharon; Schochet, Peter Z.; Sanders, Elizabeth

    2014-01-01

    Suppose an education researcher wants to test the impact of a high school drop-out prevention intervention in which at-risk students attend classes to receive intensive summer school instruction. The district will allow the researcher to randomly assign students to the treatment classes or to the control group. Half of the students (the treatment…

  10. ANALYSIS OF SAMPLING TECHNIQUES FOR IMBALANCED DATA: AN N=648 ADNI STUDY

    PubMed Central

    Dubey, Rashmi; Zhou, Jiayu; Wang, Yalin; Thompson, Paul M.; Ye, Jieping

    2013-01-01

    Many neuroimaging applications deal with imbalanced imaging data. For example, in Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, the mild cognitive impairment (MCI) cases eligible for the study are nearly two times the Alzheimer’s disease (AD) patients for structural magnetic resonance imaging (MRI) modality and six times the control cases for proteomics modality. Constructing an accurate classifier from imbalanced data is a challenging task. Traditional classifiers that aim to maximize the overall prediction accuracy tend to classify all data into the majority class. In this paper, we study an ensemble system of feature selection and data sampling for the class imbalance problem. We systematically analyze various sampling techniques by examining the efficacy of different rates and types of undersampling, oversampling, and a combination of over and under sampling approaches. We thoroughly examine six widely used feature selection algorithms to identify significant biomarkers and thereby reduce the complexity of the data. The efficacy of the ensemble techniques is evaluated using two different classifiers including Random Forest and Support Vector Machines based on classification accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity measures. Our extensive experimental results show that for various problem settings in ADNI, (1). a balanced training set obtained with K-Medoids technique based undersampling gives the best overall performance among different data sampling techniques and no sampling approach; and (2). sparse logistic regression with stability selection achieves competitive performance among various feature selection algorithms. Comprehensive experiments with various settings show that our proposed ensemble model of multiple undersampled datasets yields stable and promising results. PMID:24176869

  11. Analysis of sampling techniques for imbalanced data: An n = 648 ADNI study.

    PubMed

    Dubey, Rashmi; Zhou, Jiayu; Wang, Yalin; Thompson, Paul M; Ye, Jieping

    2014-02-15

    Many neuroimaging applications deal with imbalanced imaging data. For example, in Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, the mild cognitive impairment (MCI) cases eligible for the study are nearly two times the Alzheimer's disease (AD) patients for structural magnetic resonance imaging (MRI) modality and six times the control cases for proteomics modality. Constructing an accurate classifier from imbalanced data is a challenging task. Traditional classifiers that aim to maximize the overall prediction accuracy tend to classify all data into the majority class. In this paper, we study an ensemble system of feature selection and data sampling for the class imbalance problem. We systematically analyze various sampling techniques by examining the efficacy of different rates and types of undersampling, oversampling, and a combination of over and undersampling approaches. We thoroughly examine six widely used feature selection algorithms to identify significant biomarkers and thereby reduce the complexity of the data. The efficacy of the ensemble techniques is evaluated using two different classifiers including Random Forest and Support Vector Machines based on classification accuracy, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity measures. Our extensive experimental results show that for various problem settings in ADNI, (1) a balanced training set obtained with K-Medoids technique based undersampling gives the best overall performance among different data sampling techniques and no sampling approach; and (2) sparse logistic regression with stability selection achieves competitive performance among various feature selection algorithms. Comprehensive experiments with various settings show that our proposed ensemble model of multiple undersampled datasets yields stable and promising results. © 2013 Elsevier Inc. All rights reserved.

  12. Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

    PubMed

    Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

    2013-01-01

    DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

  13. Factors affecting unintentional harvesting selectivity in a monomorphic species.

    PubMed

    Bunnefeld, Nils; Baines, David; Newborn, David; Milner-Gulland, E J

    2009-03-01

    1. Changes in the abundance of populations have always perplexed ecologists but long-term studies are revealing new insights into population dynamic processes. Long-term data are often derived from harvest records although many wild populations face high harvesting pressures leading to overharvesting and extinction. Additionally, harvest records used to describe population processes such as fluctuations in abundance and reproductive success often assume a random off-take. 2. Selective harvesting based on phenotypic characteristics occurs in many species (e.g. trophy hunting, fisheries) and has important implications for population dynamics, conservation and management. 3. In species with no marked morphological differences between the age and sex classes, such as the red grouse Lagopus lagopus scoticus during the shooting season, hunters cannot consciously select for a specific sex or age class during the shooting process but harvest records could still give a biased reflection of the population structure because of differences in behaviour between age and sex classes. 4. This study compared age and sex ratios in the bag with those in the population before shooting for red grouse at different points in the shooting season and different densities, which has rarely been tested before. 5. More young than old grouse were shot at large bag sizes and vice versa for small bag sizes than would be expected from the population composition before shooting. The susceptibility of old males to shooting compared to females increased with bag size and was high at the first time the area was shot but decreased with the number of times an area was harvested. 6. These findings stress that the assumption made in many studies that harvest records reflect the age and sex ratio of the population and therefore reflect productivity can be misleading. 7. In this paper, as in the literature, it is also shown that number of grouse shot reflects grouse density and therefore that hunting selectivity might influence population dynamics in a cyclic species. 8. The study is not only relevant for red grouse but applies to systems showing interactions between selective harvesting and wider ecological processes, such as age- and sex-related parasitism and territoriality, which may drive population fluctuations.

  14. The Effects of Class Size in Online College Courses: Experimental Evidence. CEPA Working Paper No. 15-14

    ERIC Educational Resources Information Center

    Bettinger, Eric; Doss, Christopher; Loeb, Susanna; Taylor, Eric

    2015-01-01

    Class size is a first-order consideration in the study of education production and education costs. How larger or smaller classes affect student outcomes is especially relevant to the growth and design of online classes. We study a field experiment in which college students were quasi-randomly assigned to either a large or a small class. All…

  15. The immune system: a weapon of mass destruction invented by evolution to even the odds during the war of the DNAs

    PubMed Central

    2005-01-01

    Summary: Living systems operate under interactive selective pressures. Populations have the ability to anticipate the future by generating a repertoire of elements that cope with new selective pressures. If the repertoire of such elements were transcendental, natural selection could not operate because any one of them would be too rare. This is the problem that vertebrates faced in order to deal with a vast number of pathogens. The solution was to invent an immune system that underwent somatic evolution. This required a random repertoire that was generated somatically and divided the antigenic universe into combinatorials of determinants. As a result, it became virtually impossible for pathogens to escape recognition but the functioning of such a repertoire required two new regulatory mechanisms: 1) a somatic discriminator between Not-To-Be-Ridded (‘Self’) and To-Be-Ridded (‘Non-self’) antigens, and 2) a way to optimize the magnitude and choice of the class of the effector response. The principles governing this dual regulation are analyzed in the light of natural selection. PMID:12190919

  16. Variable selection in subdistribution hazard frailty models with competing risks data

    PubMed Central

    Do Ha, Il; Lee, Minjung; Oh, Seungyoung; Jeong, Jong-Hyeon; Sylvester, Richard; Lee, Youngjo

    2014-01-01

    The proportional subdistribution hazards model (i.e. Fine-Gray model) has been widely used for analyzing univariate competing risks data. Recently, this model has been extended to clustered competing risks data via frailty. To the best of our knowledge, however, there has been no literature on variable selection method for such competing risks frailty models. In this paper, we propose a simple but unified procedure via a penalized h-likelihood (HL) for variable selection of fixed effects in a general class of subdistribution hazard frailty models, in which random effects may be shared or correlated. We consider three penalty functions (LASSO, SCAD and HL) in our variable selection procedure. We show that the proposed method can be easily implemented using a slight modification to existing h-likelihood estimation approaches. Numerical studies demonstrate that the proposed procedure using the HL penalty performs well, providing a higher probability of choosing the true model than LASSO and SCAD methods without losing prediction accuracy. The usefulness of the new method is illustrated using two actual data sets from multi-center clinical trials. PMID:25042872

  17. Neuropharmacology of Poststroke Motor and Speech Recovery.

    PubMed

    Keser, Zafer; Francisco, Gerard E

    2015-11-01

    Almost 7 million adult Americans have had a stroke. There is a growing need for more effective treatment options as add-ons to conventional therapies. This article summarizes the published literature for pharmacologic agents used for the enhancement of motor and speech recovery after stroke. Amphetamine, levodopa, selective serotonin reuptake inhibitors, and piracetam were the most commonly used drugs. Pharmacologic augmentation of stroke motor and speech recovery seems promising but systematic, adequately powered, randomized, and double-blind clinical trials are needed. At this point, the use of these pharmacologic agents is not supported by class I evidence. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. The effect of trade books on the environmental literacy of 11th and 12th graders in aquatic science

    NASA Astrophysics Data System (ADS)

    Lewis, Ann S.

    The purpose of this study was to compare the environmental literacy of 11th and 12th graders who participated in an eighteen-week environmental education program using trade books versus 11 th- and 12th-graders who participated in an eighteen-week, traditional environmental education program without the use of trade books. This study was conducted using a quasi-experimental research technique. Four high school aquatic science classes at two suburban high schools were used in the research. One teacher at each high school taught one control class and one experimental class of aquatic science. In the experimental classes, four trade books were read to the classes during the eighteen-week semester. These four books were selected by the participating teachers before the semester began. The books used were A Home by the Sea, Sea Otter Rescue, There's a Hair in My Dirt, and The Missing Gator of Gumbo Limbo. The instrument used to measure environmental literacy was the Children's Environmental Attitude and Knowledge Scale. This test was given at the beginning of the semester and at the end of the semester. The scores at the end of the semester were analyzed by 2 x 2 mixed model ANOVA with the teacher as the random effect and the condition (trade books) as the fixed effect. The statistical analysis of this study showed that the students in the experimental classes did not score higher than the control classes on the Children's Environmental Attitude and Knowledge Scale or on a subset of "water" questions. Several limitations were placed on this research. These limitations included the following: (1) a small number of classes and a small number of teachers, (2) change from the original plan of using environmental science classes to aquatic science classes, (3) possible indifference of the students, and (4) restrictive teaching strategies of the teachers.

  19. Changes in Body Weight and Psychotropic Drugs: A Systematic Synthesis of the Literature

    PubMed Central

    Dent, Robert; Blackmore, Angelique; Peterson, Joan; Habib, Rami; Kay, Gary Peter; Gervais, Alan; Taylor, Valerie; Wells, George

    2012-01-01

    Introduction Psychotropic medication use is associated with weight gain. While there are studies and reviews comparing weight gain for psychotropics within some classes, clinicians frequently use drugs from different classes to treat psychiatric disorders. Objective To undertake a systematic review of all classes of psychotropics to provide an all encompassing evidence-based tool that would allow clinicians to determine the risks of weight gain in making both intra-class and interclass choices of psychotropics. Methodology and Results We developed a novel hierarchical search strategy that made use of systematic reviews that were already available. When such evidence was not available we went on to evaluate randomly controlled trials, followed by cohort and other clinical trials, narrative reviews, and, where necessary, clinical opinion and anecdotal evidence. The data from the publication with the highest level of evidence based on our hierarchical classification was presented. Recommendations from an expert panel supplemented the evidence used to rank these drugs within their respective classes. Approximately 9500 articles were identified in our literature search of which 666 citations were retrieved. We were able to rank most of the psychotropics based on the available evidence and recommendations from subject matter experts. There were few discrepancies between published evidence and the expert panel in ranking these drugs. Conclusion Potential for weight gain is an important consideration in choice of any psychotropic. This tool will help clinicians select psychotropics on a case-by-case basis in order to minimize the impact of weight gain when making both intra-class and interclass choices. PMID:22719834

  20. 47 CFR 1.1602 - Designation for random selection.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Designation for random selection. 1.1602 Section 1.1602 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1602 Designation for random selection...

  1. 47 CFR 1.1602 - Designation for random selection.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 1 2011-10-01 2011-10-01 false Designation for random selection. 1.1602 Section 1.1602 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1602 Designation for random selection...

  2. Promoting Acceleration of Comprehension and Content through Text in High School Social Studies Classes

    ERIC Educational Resources Information Center

    Wanzek, Jeanne; Swanson, Elizabeth A.; Roberts, Greg; Vaughn, Sharon; Kent, Shawn C.

    2015-01-01

    The purpose of this study was to evaluate the efficacy of Promoting Acceleration of Comprehension and Content Through Text intervention implemented with 11th-grade students enrolled in U.S. History classes. Using a within-teacher randomized design, the study was conducted in 41 classes (23 treatment classes) with 14 teachers providing the…

  3. Class-Size Policy: The STAR Experiment and Related Class-Size Studies. NCPEA Policy Brief. Volume 1, Number 2

    ERIC Educational Resources Information Center

    Achilles, Charles M.

    2012-01-01

    This brief summarizes findings on class size from over 25 years of work on the Tennessee Student Teacher Achievement Ratio (STAR) randomized, longitudinal experiment, and other Class-Size Reduction (CSR) studies throughout the United States, Australia, Hong Kong, Sweden, Great Britain, and elsewhere. The brief concludes with recommendations. The…

  4. Natural Selection on Female Life-History Traits in Relation to Socio-Economic Class in Pre-Industrial Human Populations

    PubMed Central

    Pettay, Jenni E.; Helle, Samuli; Jokela, Jukka; Lummaa, Virpi

    2007-01-01

    Life-history theory predicts that resource scarcity constrains individual optimal reproductive strategies and shapes the evolution of life-history traits. In species where the inherited structure of social class may lead to consistent resource differences among family lines, between-class variation in resource availability should select for divergence in optimal reproductive strategies. Evaluating this prediction requires information on the phenotypic selection and quantitative genetics of life-history trait variation in relation to individual lifetime access to resources. Here, we show using path analysis how resource availability, measured as the wealth class of the family, affected the opportunity and intensity of phenotypic selection on the key life-history traits of women living in pre-industrial Finland during the 1800s and 1900s. We found the highest opportunity for total selection and the strongest selection on earlier age at first reproduction in women of the poorest wealth class, whereas selection favoured older age at reproductive cessation in mothers of the wealthier classes. We also found clear differences in female life-history traits across wealth classes: the poorest women had the lowest age-specific survival throughout their lives, they started reproduction later, delivered fewer offspring during their lifetime, ceased reproduction younger, had poorer offspring survival to adulthood and, hence, had lower fitness compared to the wealthier women. Our results show that the amount of wealth affected the selection pressure on female life-history in a pre-industrial human population. PMID:17622351

  5. [Social self-positioning as indicator of socioeconomic status].

    PubMed

    Fernández, E; Alonso, R M; Quer, A; Borrell, C; Benach, J; Alonso, J; Gómez, G

    2000-01-01

    Self-perceived class results from directly questioning subjects about his or her social class. The aim of this investigation was to analyse self-perceived class in relation to other indicator variables of socioeconomic level. Data from the 1994 Catalan Health Interview Survey, a cross-sectional survey of a representative sample of the non-institutionalised population of Catalonia was used. We conducted a discriminant analysis to compute the degree of right classification when different socioeconomic variables potentially related to self-perceived class were considered. All subjects who directly answered the questionnaire were included (N = 12,245). With the aim of obtaining the discriminant functions in a group of subjects and to validate it in another one, the subjects were divided into two random samples, containing approximately 75% and 25% of subjects (analysis sample, n = 9,248; and validation sample, n = 2,997). The final function for men and women included level of education, social class (based in occupation) and equivalent income. This function correctly classified 40.9% of the subjects in the analysis sample and 39.2% in the validation sample. Two other functions were selected for men and women separately. In men, the function included level of education, professional category, and family income (39.2% of classification in analysis sample and 37.2% in validation sample). In women, the function (level of education, working status, and equivalent income) correctly classified 40.3% of women in analysis sample whereas the percentage was 38.9% in validation sample. The percentages of right classification were higher for the highest and lowest classes. These results show the utility of a simple variable to self-position within the social scale. Self-perceived class is related to education, income, and working determinants.

  6. Classification of conductance traces with recurrent neural networks

    NASA Astrophysics Data System (ADS)

    Lauritzen, Kasper P.; Magyarkuti, András; Balogh, Zoltán; Halbritter, András; Solomon, Gemma C.

    2018-02-01

    We present a new automated method for structural classification of the traces obtained in break junction experiments. Using recurrent neural networks trained on the traces of minimal cross-sectional area in molecular dynamics simulations, we successfully separate the traces into two classes: point contact or nanowire. This is done without any assumptions about the expected features of each class. The trained neural network is applied to experimental break junction conductance traces, and it separates the classes as well as the previously used experimental methods. The effect of using partial conductance traces is explored, and we show that the method performs equally well using full or partial traces (as long as the trace just prior to breaking is included). When only the initial part of the trace is included, the results are still better than random chance. Finally, we show that the neural network classification method can be used to classify experimental conductance traces without using simulated results for training, but instead training the network on a few representative experimental traces. This offers a tool to recognize some characteristic motifs of the traces, which can be hard to find by simple data selection algorithms.

  7. Temporomandibular disorders in growing patients after treatment of class II and III malocclusion with orthopaedic appliances: a systematic review.

    PubMed

    Jiménez-Silva, Antonio; Carnevali-Arellano, Romano; Venegas-Aguilera, Matías; Tobar-Reyes, Julio; Palomino-Montenegro, Hernán

    2018-05-01

    To determine if the use of orthopaedic appliances in growing patients applied to correct Class II and III malocclusion is related to the development of temporomandibular disorders (TMD). A systematic review was conducted between 1960 and July 2017, based on electronic databases: PubMed, Cochrane Library, Embase, Medline, Scopus, EBSCOhost, Scielo, Lilacs and Bireme. Controlled clinical trials (CCTs) and randomized controlled trials (RCTs) were identified. The articles were selected and analyzed by two authors independently. The quality of the evidence was determined according to the guidelines of the Cochrane Risk Bias Assessment Tool and the Cochrane Quality Study Guide. Seven articles were included, four CCTs and three RCTs. The studies were grouped according to malocclusion treatment in (a) class II appliances (n = 4) and (b) class III appliances (n = 3). The quality of evidence was low due to the high risk of bias, independent of the association reported. All studies concluded that the use of orthopaedic appliances would not contribute to the development of TMD. The quality of evidence available is insufficient to establish definitive conclusions, since the studies were very heterogeneous and presented a high risk of bias. However, it is suggested that the use of orthopaedic appliances to correct class II and III malocclusion in growing patients would not be considered as a risk factor for the development of TMD. High-quality RCTs are required to draw any definitive conclusions.

  8. Supervised Detection of Anomalous Light Curves in Massive Astronomical Catalogs

    NASA Astrophysics Data System (ADS)

    Nun, Isadora; Pichara, Karim; Protopapas, Pavlos; Kim, Dae-Won

    2014-09-01

    The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.

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

    Nun, Isadora; Pichara, Karim; Protopapas, Pavlos

    The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each ofmore » the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.« less

  10. 47 CFR 1.1603 - Conduct of random selection.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Conduct of random selection. 1.1603 Section 1.1603 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1603 Conduct of random selection. The...

  11. 47 CFR 1.1603 - Conduct of random selection.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 1 2011-10-01 2011-10-01 false Conduct of random selection. 1.1603 Section 1.1603 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1603 Conduct of random selection. The...

  12. Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

    PubMed Central

    Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

    2009-01-01

    Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependant on each class and on each wrong or partially correct decision. It is based on ν-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers. PMID:19584932

  13. FUSED REACTOR FUELS

    DOEpatents

    Mayer, S.W.

    1962-11-13

    This invention relates to a nuciear reactor fuel composition comprising (1) from about 0.01 to about 50 wt.% based on the total weight of said composition of at least one element selected from the class consisting of uranium, thorium, and plutonium, wherein said eiement is present in the form of at least one component selected from the class consisting of oxides, halides, and salts of oxygenated anions, with components comprising (2) at least one member selected from the class consisting of (a) sulfur, wherein the sulfur is in the form of at least one entity selected irom the class consisting of oxides of sulfur, metal sulfates, metal sulfites, metal halosulfonates, and acids of sulfur, (b) halogen, wherein said halogen is in the form of at least one compound selected from the class of metal halides, metal halosulfonates, and metal halophosphates, (c) phosphorus, wherein said phosphorus is in the form of at least one constituent selected from the class consisting of oxides of phosphorus, metal phosphates, metal phosphites, and metal halophosphates, (d) at least one oxide of a member selected from the class consisting of a metal and a metalloid wherein said oxide is free from an oxide of said element in (1); wherein the amount of at least one member selected from the class consisting of halogen and sulfur is at least about one at.% based on the amount of the sum of said sulfur, halogen, and phosphorus atom in said composition; and wherein the amount of said 2(a), 2(b) and 2(c) components in said composition which are free from said elements of uranium, thorium, arid plutonium, is at least about 60 wt.% based on the combined weight of the components of said composition which are free from said elements of uranium, thorium, and plutonium. (AEC)

  14. Impact of dental pain on daily living of five-year-old Brazilian preschool children: prevalence and associated factors.

    PubMed

    Moure-Leite, F R; Ramos-Jorge, J; Ramos-Jorge, M L; Paiva, S M; Vale, M P; Pordeus, I A

    2011-12-01

    To assess the impact of dental pain on the daily living of 5-year-old preschool children using reports from parents/guardians. A cross-sectional study was carried out involving 549 five-year-old children randomly selected from preschools in the city of Belo Horizonte, Brazil. Data were collected using a previously validated parent-reported questionnaire. The children received dental examinations from a single calibrated examiner. The following outcome variables were selected: age, gender, dental caries, filled teeth, missing teeth, caries involving pulp and social class. Simple and multiple logistic regression analyses were performed on the data. According to parents' reports, 11.1% of children were affected by dental pain in the previous 4 months and of these 72.6% had their daily activities hampered by pain. The majority of these children had difficulty in eating, brushing teeth, sleeping, playing and going to school. The impact of dental pain had a statistically significant association with gender (p=0.001), social class (p=0.009), dental caries (p<0.001), missing teeth (p<0.001), filled teeth (p<0.001) and caries involving pulp (p<0.001). The prevalence of difficulties performing tasks of daily living due to dental pain was relatively high among the children studied.

  15. Pyrosequencing Reveals a Core Community of Anodic Bacterial Biofilms in Bioelectrochemical Systems from China

    PubMed Central

    Xiao, Yong; Zheng, Yue; Wu, Song; Zhang, En-Hua; Chen, Zheng; Liang, Peng; Huang, Xia; Yang, Zhao-Hui; Ng, I-Son; Chen, Bor-Yann; Zhao, Feng

    2015-01-01

    Bioelectrochemical systems (BESs) are promising technologies for energy and product recovery coupled with wastewater treatment, and the core microbial community in electrochemically active biofilm in BESs remains controversy. In the present study, 7 anodic communities from 6 bioelectrochemical systems in 4 labs in southeast, north and south-central of China are explored by 454 pyrosequencing. A total of 251,225 effective sequences are obtained for 7 electrochemically active biofilm samples at 3% cutoff level. While Alpha-, Beta-, and Gamma-proteobacteria are the most abundant classes (averaging 16.0–17.7%), Bacteroidia and Clostridia are the two sub-dominant and commonly shared classes. Six commonly shared genera i.e., Azospira, Azospirillum, Acinetobacter, Bacteroides, Geobacter, Pseudomonas, and Rhodopseudomonas dominate the electrochemically active communities and are defined as core genera. A total of 25 OTUs with average relative abundance >0.5% were selected and designated as core OTUs, and some species relating to these OTUs have been reported electrochemically active. Furthermore, cyclic voltammetry and chronoamperometry tests show that two strains from Acinetobacter guillouiae and Stappia indica, bacteria relate to two core OTUs, are electrochemically active. Using randomly selected bioelectrochemical systems, the study has presented extremely diverse bacterial communities in anodic biofilms, though, we still can suggest some potentially microbes for investigating the electrochemical mechanisms in bioelectrochemical systems. PMID:26733958

  16. Randomly distilling W-class states into general configurations of two-party entanglement

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

    Cui, W.; Chitambar, E.; Lo, H. K.

    2011-11-15

    In this article we obtain results for the task of converting a single N-qubit W-class state (of the form {radical}(x{sub 0})|00...0>+{radical}(x{sub 1})|10...0>+{center_dot}{center_dot}{center_dot}+{radical}(x{sub N})|00...1>) into maximum entanglement shared between two random parties. Previous studies in random distillation have not considered how the particular choice of target pairs affects the transformation, and here we develop a strategy for distilling into general configurations of target pairs. We completely solve the problem of determining the optimal distillation probability for all three-qubit configurations and most four-qubit configurations when x{sub 0}=0. Our proof involves deriving new entanglement monotones defined on the set of four-qubit W-class states.more » As an additional application of our results, we present new upper bounds for converting a generic W-class state into the standard W state |W{sub N}>={radical}((1/N))(|10...0>+{center_dot}{center_dot}{center_dot}+|00...1>).« less

  17. Synthesis and click chemistry of a new class of biodegradable polylactide towards tunable thermo-responsive biomaterials.

    PubMed

    Zhang, Quanxuan; Ren, Hong; Baker, Gregory L

    2015-02-28

    A new class of clickable and biodegradable polylactide was designed and prepared via bulk polymerization of 3,6-dipropargyloxymethyl-1,4-dioxane-2,5-dione ( 1 ) which was synthesized from easily accessible propargyloxylactic acid ( 5 ). A homopolymer of 1 and random copolymer of 1 with l-lactide were obtained as amorphous materials and exhibit low T g of 8.5 and 34 °C, respectively, indicating their promising potentials for biomedical applications. The statistical nature of random copolymers was investigated by DSC analysis and 13 C NMR spectroscopy, which implies the random distribution of terminal alkyne groups along the back bone of copolymers. The efficient click post-modification of this new class of polylactide with alkyl and mPEG azides affords novel hydrophilic biomaterials, which exhibit reversible thermo-responsive properties as evidenced by their tunable LCST ranging from 22 to 69 °C depending on the balance of the incorporated hydrophilic/hydrophobic side chains. These results indicate the generality of this new class of clickable polylactide in preparing novel smart biomaterials in a simple and efficient manner via click chemistry.

  18. Benchmarking protein classification algorithms via supervised cross-validation.

    PubMed

    Kertész-Farkas, Attila; Dhir, Somdutta; Sonego, Paolo; Pacurar, Mircea; Netoteia, Sergiu; Nijveen, Harm; Kuzniar, Arnold; Leunissen, Jack A M; Kocsor, András; Pongor, Sándor

    2008-04-24

    Development and testing of protein classification algorithms are hampered by the fact that the protein universe is characterized by groups vastly different in the number of members, in average protein size, similarity within group, etc. Datasets based on traditional cross-validation (k-fold, leave-one-out, etc.) may not give reliable estimates on how an algorithm will generalize to novel, distantly related subtypes of the known protein classes. Supervised cross-validation, i.e., selection of test and train sets according to the known subtypes within a database has been successfully used earlier in conjunction with the SCOP database. Our goal was to extend this principle to other databases and to design standardized benchmark datasets for protein classification. Hierarchical classification trees of protein categories provide a simple and general framework for designing supervised cross-validation strategies for protein classification. Benchmark datasets can be designed at various levels of the concept hierarchy using a simple graph-theoretic distance. A combination of supervised and random sampling was selected to construct reduced size model datasets, suitable for algorithm comparison. Over 3000 new classification tasks were added to our recently established protein classification benchmark collection that currently includes protein sequence (including protein domains and entire proteins), protein structure and reading frame DNA sequence data. We carried out an extensive evaluation based on various machine-learning algorithms such as nearest neighbor, support vector machines, artificial neural networks, random forests and logistic regression, used in conjunction with comparison algorithms, BLAST, Smith-Waterman, Needleman-Wunsch, as well as 3D comparison methods DALI and PRIDE. The resulting datasets provide lower, and in our opinion more realistic estimates of the classifier performance than do random cross-validation schemes. A combination of supervised and random sampling was used to construct model datasets, suitable for algorithm comparison.

  19. Development of an Independent Global Land Cover Validation Dataset

    NASA Astrophysics Data System (ADS)

    Sulla-Menashe, D. J.; Olofsson, P.; Woodcock, C. E.; Holden, C.; Metcalfe, M.; Friedl, M. A.; Stehman, S. V.; Herold, M.; Giri, C.

    2012-12-01

    Accurate information related to the global distribution and dynamics in global land cover is critical for a large number of global change science questions. A growing number of land cover products have been produced at regional to global scales, but the uncertainty in these products and the relative strengths and weaknesses among available products are poorly characterized. To address this limitation we are compiling a database of high spatial resolution imagery to support international land cover validation studies. Validation sites were selected based on a probability sample, and may therefore be used to estimate statistically defensible accuracy statistics and associated standard errors. Validation site locations were identified using a stratified random design based on 21 strata derived from an intersection of Koppen climate classes and a population density layer. In this way, the two major sources of global variation in land cover (climate and human activity) are explicitly included in the stratification scheme. At each site we are acquiring high spatial resolution (< 1-m) satellite imagery for 5-km x 5-km blocks. The response design uses an object-oriented hierarchical legend that is compatible with the UN FAO Land Cover Classification System. Using this response design, we are classifying each site using a semi-automated algorithm that blends image segmentation with a supervised RandomForest classification algorithm. In the long run, the validation site database is designed to support international efforts to validate land cover products. To illustrate, we use the site database to validate the MODIS Collection 4 Land Cover product, providing a prototype for validating the VIIRS Surface Type Intermediate Product scheduled to start operational production early in 2013. As part of our analysis we evaluate sources of error in coarse resolution products including semantic issues related to the class definitions, mixed pixels, and poor spectral separation between classes.

  20. Prevalence of Sarcopenia and Its Association with Socioeconomic Status among the Elderly in Tehran.

    PubMed

    Dorosty, Ahmadreza; Arero, Godana; Chamar, Maryam; Tavakoli, Sogand

    2016-07-01

    Sarcopenia is a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength. It imposes significant costs on health care systems. Socioeconomic status is also the root cause of healthy challenges among the elderly. Therefore, investigating the association between sarcopenia and socioeconomic status is very important to improve healthy ageing of the elderly. The aim of this study was to investigate the prevalence of sarcopenia and its association with socioeconomic status among the elderly in Tehran. Cross-sectional and case-control studies were conducted from August 2014-July 2015 among 310 men and 334 women elderly (60 and over years old) in Tehran health centers. Randomization, restriction and matching were setting during study design to minimize selection bias. Then study participants were recruited via phone call. Participants' phone numbers were already recorded in a telephone book electronically. When there were two elderly people in the same house, only one person was invited randomly. Association between sarcopenia and socio-economic status was analyzed by SPSS version 22. The overall prevalence of sarcopenia in the elderly was 16.5%. Prevalenceamong the low-income elderly was relatively higher than (20.5%) that among those with middle income status (18.2%) while in the higher income, the proportion of sarcopenia was very low (12.8%). The findings indicated that 339(52.6%) were in low-income status, 304(47.1%) were in middle-income status and 1(.2%) in high-income class. There was a significant association between socioeconomic status and sarcopenia (P-value <0.001). The odd risk of sarcopenia was 0.97 times more likely higher in low socioeconomic class than those who were in middle and high income classes.

  1. Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

    NASA Astrophysics Data System (ADS)

    Zhu, Zhe; Gallant, Alisa L.; Woodcock, Curtis E.; Pengra, Bruce; Olofsson, Pontus; Loveland, Thomas R.; Jin, Suming; Dahal, Devendra; Yang, Limin; Auch, Roger F.

    2016-12-01

    The U.S. Geological Survey's Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the public. This paper describes an approach to optimize the selection of training and auxiliary data for deriving the thematic land cover maps based on all available clear observations from Landsats 4-8. Training data were selected from map products of the U.S. Geological Survey's Land Cover Trends project. The Random Forest classifier was applied for different classification scenarios based on the Continuous Change Detection and Classification (CCDC) algorithm. We found that extracting training data proportionally to the occurrence of land cover classes was superior to an equal distribution of training data per class, and suggest using a total of 20,000 training pixels to classify an area about the size of a Landsat scene. The problem of unbalanced training data was alleviated by extracting a minimum of 600 training pixels and a maximum of 8000 training pixels per class. We additionally explored removing outliers contained within the training data based on their spectral and spatial criteria, but observed no significant improvement in classification results. We also tested the importance of different types of auxiliary data that were available for the conterminous United States, including: (a) five variables used by the National Land Cover Database, (b) three variables from the cloud screening "Function of mask" (Fmask) statistics, and (c) two variables from the change detection results of CCDC. We found that auxiliary variables such as a Digital Elevation Model and its derivatives (aspect, position index, and slope), potential wetland index, water probability, snow probability, and cloud probability improved the accuracy of land cover classification. Compared to the original strategy of the CCDC algorithm (500 pixels per class), the use of the optimal strategy improved the classification accuracies substantially (15-percentage point increase in overall accuracy and 4-percentage point increase in minimum accuracy).

  2. [Factors contributing to smoking among students in Ouagadougou (Burkina Faso)].

    PubMed

    Koueta, F; Dao, L; Yé, D; Koura, M; Sawadogo, A

    2009-03-01

    Smoking is of great concern to the international community because of the sharp increase in tobacco consumption among adolescents. We conducted a transverse descriptive study on 23 to 27 May 2006, on a sample of 500 smoking students randomly selected from secondary schools in the city of Ouagadougou, to identify their motivation with the aim of prevention. The main factors encouraging smoking among students were: *Economic conditions: 64% came from a favourable economic environment with daily pocket money (100%) and a means of travel (74.8%). *Difficulties with their studies: 57.2% of smoking students had repeated at least one class and half had a class average lower than 10/20. *A smoking environment: 72% of smokers lived away from their parents, 46% of students had smoked in imitation of their colleagues. School was the preferred place for the consumption of cigarettes (67.9%). *The influence of the media: 80.8% were drawn into smoking by the influence of advertising. Prevention programmes must take all these factors into account.

  3. Hydrogen as a New Class of Radioprotective Agent

    PubMed Central

    Qian, Liren; Shen, Jianliang; Chuai, Yunhai; Cai, Jianming

    2013-01-01

    It is well known that most of the ionizing radiation-induced damage is caused by hydroxyl radicals (·OH) follows radiolysis of H2O. Molecular hydrogen (H2) has antioxidant activities by selectively reducing ·OH and peroxynitrite(ONOO-). We firstly hypothesized and demonstrated the radioprotective effect of H2 in vitro and in vivo, which was also repeated on different experimental animal models by different departments. A randomized, placebo-controlled study showed that consumption of hydrogen-rich water reduces the biological reaction to radiation-induced oxidative stress without compromising anti-tumor effects. These encouraging results suggested that H2 represents a potentially novel preventative strategy for radiation-induced oxidative injuries. H2 is explosive. Therefore, administration of hydrogen-rich solution (physiological saline/pure water/other solutions saturated with H2) may be more practical in daily life and more suitable for daily consumption. This review focuses on major scientific and clinical advances of hydrogen-rich solution/H2 as a new class of radioprotective agent. PMID:24155664

  4. [The reliability of a questionnaire regarding Colombian children's physical activity].

    PubMed

    Herazo-Beltrán, Aliz Y; Domínguez-Anaya, Regina

    2012-10-01

    Reporting the Physical Activity Questionnaire for school children's (PAQ-C) test-retest reliability and internal consistency. This was a descriptive study of 100 school-aged children aged 9 to 11 years old attending a school in Cartagena, Colombia. The sample was randomly selected. The PAQ-C was given twice, one week apart, after the informed consent forms had been signing by the children's parents and school officials. Cronbach's alpha coefficient of reliability was used for assessing internal consistency and an intra-class correlation coefficient for test-retest reliability SPSS (version 17.0) was used for statistical analysis. The questionnaire scored 0.73 internal consistencies during the first measurement and 0.78 on the second; intra-class correlation coefficient was 0.60. There were differences between boys and girls regarding both measurements. The PAQ-C had acceptable internal consistency and test-retest reliability, thereby making it useful for measuring children's self-reported physical activity and a valuable tool for population studies in Colombia.

  5. Effectiveness of Student Learning during Experimental Work in Primary School.

    PubMed

    Logar, Ana; Peklaj, Cirila; Ferk Savec, Vesna

    2017-09-01

    The aim of the research was to optimize the effectiveness of student learning based on experimental work in chemistry classes in Slovenian primary schools. To obtain evidence about how experimental work is implemented during regular chemistry classes, experimental work was videotaped during 19 units of chemistry lessons at 12 Slovenian primary schools from the pool of randomly selected schools. Altogether 332 eight-grade students were involved in the investigation, with an average age of 14.2 years. Students were videotaped during chemistry lessons, and their worksheets were collected afterward. The 12 chemistry teachers, who conducted lessons in these schools, were interviewed before the lessons; their teaching plans were also collected. The collected data was analyzed using qualitative methods. The results indicate that many teachers in Slovenian primary schools are not fully aware of the potential of experimental work integrated into chemistry lessons for the development of students' experimental competence. Further research of the value of different kinds of training to support teachers for the use of experimental work in chemistry teaching is needed.

  6. Results from the Biology Concept Inventory (BCI), and what they mean for biogeoscience literacy.

    NASA Astrophysics Data System (ADS)

    Garvin-Doxas, K.; Klymkowsky, M.

    2008-12-01

    While researching the Biology Concept Inventory (BCI) we found that a wide class of student difficulties in genetics and molecular biology can be traced to deep-seated misconceptions about random processes and molecular interactions. Students believe that random processes are inefficient, while biological systems are very efficient, and are therefore quick to propose their own rational explanations for various processes (from diffusion to evolution). These rational explanations almost always make recourse to a driver (natural selection in genetics, or density gradients in molecular biology) with the process only taking place when the driver is present. The concept of underlying random processes that are taking place all the time giving rise to emergent behaviour is almost totally absent. Even students who have advanced or college physics, and can discuss diffusion correctly in that context, cannot make the transfer to biological processes. Furthermore, their understanding of molecular interactions is purely geometric, with a lock-and-key model (rather than an energy minimization model) that does not allow for the survival of slight variations of the "correct" molecule. Together with the dominant misconception about random processes, this results in a strong conceptual barrier in understanding evolutionary processes, and can frustrate the success of education programs.

  7. Evolution of major histocompatibility complex class I and class II genes in the brown bear

    PubMed Central

    2012-01-01

    Background Major histocompatibility complex (MHC) proteins constitute an essential component of the vertebrate immune response, and are coded by the most polymorphic of the vertebrate genes. Here, we investigated sequence variation and evolution of MHC class I and class II DRB, DQA and DQB genes in the brown bear Ursus arctos to characterise the level of polymorphism, estimate the strength of positive selection acting on them, and assess the extent of gene orthology and trans-species polymorphism in Ursidae. Results We found 37 MHC class I, 16 MHC class II DRB, four DQB and two DQA alleles. We confirmed the expression of several loci: three MHC class I, two DRB, two DQB and one DQA. MHC class I also contained two clusters of non-expressed sequences. MHC class I and DRB allele frequencies differed between northern and southern populations of the Scandinavian brown bear. The rate of nonsynonymous substitutions (dN) exceeded the rate of synonymous substitutions (dS) at putative antigen binding sites of DRB and DQB loci and, marginally significantly, at MHC class I loci. Models of codon evolution supported positive selection at DRB and MHC class I loci. Both MHC class I and MHC class II sequences showed orthology to gene clusters found in the giant panda Ailuropoda melanoleuca. Conclusions Historical positive selection has acted on MHC class I, class II DRB and DQB, but not on the DQA locus. The signal of historical positive selection on the DRB locus was particularly strong, which may be a general feature of caniforms. The presence of MHC class I pseudogenes may indicate faster gene turnover in this class through the birth-and-death process. South–north population structure at MHC loci probably reflects origin of the populations from separate glacial refugia. PMID:23031405

  8. Evolution of major histocompatibility complex class I and class II genes in the brown bear.

    PubMed

    Kuduk, Katarzyna; Babik, Wiesław; Bojarska, Katarzyna; Sliwińska, Ewa B; Kindberg, Jonas; Taberlet, Pierre; Swenson, Jon E; Radwan, Jacek

    2012-10-02

    Major histocompatibility complex (MHC) proteins constitute an essential component of the vertebrate immune response, and are coded by the most polymorphic of the vertebrate genes. Here, we investigated sequence variation and evolution of MHC class I and class II DRB, DQA and DQB genes in the brown bear Ursus arctos to characterise the level of polymorphism, estimate the strength of positive selection acting on them, and assess the extent of gene orthology and trans-species polymorphism in Ursidae. We found 37 MHC class I, 16 MHC class II DRB, four DQB and two DQA alleles. We confirmed the expression of several loci: three MHC class I, two DRB, two DQB and one DQA. MHC class I also contained two clusters of non-expressed sequences. MHC class I and DRB allele frequencies differed between northern and southern populations of the Scandinavian brown bear. The rate of nonsynonymous substitutions (dN) exceeded the rate of synonymous substitutions (dS) at putative antigen binding sites of DRB and DQB loci and, marginally significantly, at MHC class I loci. Models of codon evolution supported positive selection at DRB and MHC class I loci. Both MHC class I and MHC class II sequences showed orthology to gene clusters found in the giant panda Ailuropoda melanoleuca. Historical positive selection has acted on MHC class I, class II DRB and DQB, but not on the DQA locus. The signal of historical positive selection on the DRB locus was particularly strong, which may be a general feature of caniforms. The presence of MHC class I pseudogenes may indicate faster gene turnover in this class through the birth-and-death process. South-north population structure at MHC loci probably reflects origin of the populations from separate glacial refugia.

  9. Dirty two-band superconductivity with interband pairing order

    NASA Astrophysics Data System (ADS)

    Asano, Yasuhiro; Sasaki, Akihiro; Golubov, Alexander A.

    2018-04-01

    We study theoretically the effects of random nonmagnetic impurities on the superconducting transition temperature T c in a two-band superconductor characterized by an equal-time s-wave interband pairing order parameter. Because of the two-band degree of freedom, it is possible to define a spin-triplet s-wave pairing order parameter as well as a spin-singlet s-wave order parameter. The former belongs to odd-band-parity symmetry class, whereas the latter belongs to even-band-parity symmetry class. In a spin-singlet superconductor, T c is insensitive to the impurity concentration when we estimate the self-energy due to the random impurity potential within the Born approximation. On the other hand in a spin-triplet superconductor, T c decreases with the increase of the impurity concentration. We conclude that Cooper pairs belonging to odd-band-parity symmetry class are fragile under the random impurity potential even though they have s-wave pairing symmetry.

  10. 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.

  11. Earthquake Hazard Class Mapping by Parcel in Las Vegas Valley

    NASA Astrophysics Data System (ADS)

    Pancha, A.; Pullammanappallil, S.; Louie, J. N.; Hellmer, W. K.

    2011-12-01

    Clark County, Nevada completed the very first effort in the United States to map earthquake hazard class systematically through an entire urban area. The map is used in development and disaster response planning, in addition to its direct use for building code implementation and enforcement. The County contracted with the Nevada System of Higher Education to classify about 500 square miles including urban Las Vegas Valley, and exurban areas considered for future development. The Parcel Map includes over 10,000 surface-wave array measurements accomplished over three years using Optim's SeisOpt° ReMi measurement and processing techniques adapted for large scale data. These array measurements classify individual parcels on the NEHRP hazard scale. Parallel "blind" tests were conducted at 93 randomly selected sites. The rms difference between the Vs30 values yielded by the blind data and analyses and the Parcel Map analyses is 4.92%. Only six of the blind-test sites showed a difference with a magnitude greater than 10%. We describe a "C+" Class for sites with Class B average velocities but soft surface soil. The measured Parcel Map shows a clearly definable C+ to C boundary on the west side of the Valley. The C to D boundary is much more complex. Using the parcel map in computing shaking in the Valley for scenario earthquakes is crucial for obtaining realistic predictions of ground motions.

  12. Drug selection in French university hospitals: analysis of formularies for nine competitive pharmacological classes.

    PubMed

    Gallini, Adeline; Juillard-Condat, Blandine; Saux, Marie-Claude; Taboulet, Florence

    2011-11-01

    To give a panorama of the selectivity and agreement of French university hospitals' drug formularies (HDF) for nine competitive classes. All university hospitals were asked to send their HDF and selection criteria as of January 2009 for nine competitive pharmacological classes (proton pump inhibitors, serotonin antagonists, low molecular weight heparins, erythropoietins, angiotensin converting enzyme inhibitors, angiotensin II receptor antagonists, statins, α-adrenoreceptor antagonists and selective serotonin re-uptake inhibitors). Selectivity of HDF was estimated by the percentage of drug entities selected by the hospital within the pharmacological class. Agreement between hospitals was assessed with modified kappa coefficients for multi-raters. Twenty-one out of the 29 hospitals agreed to participate. These hospitals selected between 34% and 63% of the drug entities available for the nine classes, which represented 18 to 35 agents. Regarding the nature of chosen drug entities, the overall level of agreement was 'fair' and varied with pharmacological classes. Selection criteria were sent by only 12 hospitals. The technical component was the most important element in all hospitals. The weight of the economic component varied between 20% and 40% in the tender's grade. Large variations were seen in the number and nature of drugs selected by university hospitals which can be attributable to two successive decision-making processes (evaluation by the Drug and Therapeutics Committee followed by the purchasing process). © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

  13. Do Comments on Mathematics Homework Affect Student Achievement?

    ERIC Educational Resources Information Center

    Austin, Joe Dan

    1976-01-01

    Students in nine classes were randomly assigned to treatment groups receiving (1) written comments on their homework papers or (2) no comments. In two of the classes, the students receiving comments showed achievement superior to that of the others. In the remainder of the classes there was no difference. (SD)

  14. Extrapolating Weak Selection in Evolutionary Games

    PubMed Central

    Wu, Bin; García, Julián; Hauert, Christoph; Traulsen, Arne

    2013-01-01

    In evolutionary games, reproductive success is determined by payoffs. Weak selection means that even large differences in game outcomes translate into small fitness differences. Many results have been derived using weak selection approximations, in which perturbation analysis facilitates the derivation of analytical results. Here, we ask whether results derived under weak selection are also qualitatively valid for intermediate and strong selection. By “qualitatively valid” we mean that the ranking of strategies induced by an evolutionary process does not change when the intensity of selection increases. For two-strategy games, we show that the ranking obtained under weak selection cannot be carried over to higher selection intensity if the number of players exceeds two. For games with three (or more) strategies, previous examples for multiplayer games have shown that the ranking of strategies can change with the intensity of selection. In particular, rank changes imply that the most abundant strategy at one intensity of selection can become the least abundant for another. We show that this applies already to pairwise interactions for a broad class of evolutionary processes. Even when both weak and strong selection limits lead to consistent predictions, rank changes can occur for intermediate intensities of selection. To analyze how common such games are, we show numerically that for randomly drawn two-player games with three or more strategies, rank changes frequently occur and their likelihood increases rapidly with the number of strategies . In particular, rank changes are almost certain for , which jeopardizes the predictive power of results derived for weak selection. PMID:24339769

  15. Schizophrenia with prominent catatonic features ('catatonic schizophrenia') III. Latent class analysis of the catatonic syndrome.

    PubMed

    Ungvari, Gabor S; Goggins, William; Leung, Siu-Kau; Lee, Edwin; Gerevich, Jozsef

    2009-02-01

    No reports have yet been published on catatonia using latent class analysis (LCA). This study applied LCA to a large, diagnostically homogenous sample of patients with chronic schizophrenia who also presented with catatonic symptoms. A random sample of 225 Chinese inpatients with DSM-IV schizophrenia was selected from the long-stay wards of a psychiatric hospital. Their psychopathology, extrapyramidal motor status and level of functioning were evaluated with standardized rating scales. Catatonia was rated using a modified version of the Bush-Francis Catatonia Rating Scale. LCA was then applied to the 178 patients who presented with at least one catatonic sign. In LCA a four-class solution was found to fit best the statistical model. Classes 1, 2, 3 and 4 constituted 18%, 39.4%, 20.1% and 22.5% of the whole catatonic sample, respectively. Class 1 included patients with symptoms of 'automatic' phenomena (automatic obedience, Mitgehen, waxy flexibility). Class 2 comprised patients with 'repetitive/echo' phenomena (perseveration, stereotypy, verbigeration, mannerisms and grimacing). Class 3 contained patients with symptoms of 'withdrawal' (immobility, mutism, posturing, staring and withdrawal). Class 4 consisted of 'agitated/resistive' patients, who displayed symptoms of excitement, impulsivity, negativism and combativeness. The symptom composition of these 4 classes was nearly identical with that of the four factors identified by factor analysis in the same cohort of subjects in an earlier study. In multivariate regression analysis, the 'withdrawn' class was associated with higher scores on the Scale of Assessment of Negative Symptoms and lower and higher scores for negative and positive items respectively on the Nurses' Observation Scale for Inpatient Evaluation's (NOSIE). The 'automatic' class was associated with lower values on the Simpson-Angus Extrapyramidal Side Effects Scale, and the 'repetitive/echo' class with higher scores on the NOSIE positive items. These results provide preliminary support for the notion that chronic schizophrenia patients with catatonic features can be classified into 4 distinct syndromal groups on the basis of their motor symptoms. Identifying distinct catatonic syndromes would help to find their biological substrates and to develop specific therapeutic measures.

  16. Effects of online games on student performance in undergraduate physics

    NASA Astrophysics Data System (ADS)

    Sadiq, Irfan

    The present state of physics teaching and learning is a reflection of the difficulty of the subject matter which has resulted in students' low motivation toward physics as well as lack of meaningful and deeper learning experiences. In light of an overall decline in interest in physics, an investigation of alternate teaching and learning methods and tools was appropriate. The research posed the following question: To what extent do online games about kinematics and two-dimensional motion impact student performance in undergraduate general physics as measured by a unit posttest? Two intact classes of 20 students each were randomly assigned to either the experimental group or the control group. Only the experimental group received the treatment of using online games. The duration of topics covered in the game content was identical to the lecture on kinematics and two-dimensional motion. Instructors for the experimental group incorporated online games in their regular classroom teaching, whereas those in the control group continued with their previously used curriculum without games. This study was conducted in three weekly sessions. Although students were not selected using random sampling, existing classes were randomly assigned to either the experimental group or the control group. There were 20 students in the experimental group and 20 students in the control group. The independent samples t test was conducted to compare the means of two independently sampled experimental and control groups. Analysis of covariance (ANCOVA) was used to determine if the two groups were significantly different with regard to their general physics performance on the posttest while controlling for the pretest scores. Analysis of posttest and pretest scores revealed that game-based learning did not significantly impact student performance.

  17. Effect of coenzyme Q10 supplementation on heart failure: a meta-analysis123

    PubMed Central

    Thompson-Paul, Angela M; Bazzano, Lydia A

    2013-01-01

    Background: Coenzyme Q10 (CoQ10; also called ubiquinone) is an antioxidant that has been postulated to improve functional status in congestive heart failure (CHF). Several randomized controlled trials have examined the effects of CoQ10 on CHF with inconclusive results. Objective: The objective of this meta-analysis was to evaluate the impact of CoQ10 supplementation on the ejection fraction (EF) and New York Heart Association (NYHA) functional classification in patients with CHF. Design: A systematic review of the literature was conducted by using databases including MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, and manual examination of references from selected studies. Studies included were randomized controlled trials of CoQ10 supplementation that reported the EF or NYHA functional class as a primary outcome. Information on participant characteristics, trial design and duration, treatment, dose, control, EF, and NYHA classification were extracted by using a standardized protocol. Results: Supplementation with CoQ10 resulted in a pooled mean net change of 3.67% (95% CI: 1.60%, 5.74%) in the EF and −0.30 (95% CI: −0.66, 0.06) in the NYHA functional class. Subgroup analyses showed significant improvement in EF for crossover trials, trials with treatment duration ≤12 wk in length, studies published before 1994, and studies with a dose ≤100 mg CoQ10/d and in patients with less severe CHF. These subgroup analyses should be interpreted cautiously because of the small number of studies and patients included in each subgroup. Conclusions: Pooled analyses of available randomized controlled trials suggest that CoQ10 may improve the EF in patients with CHF. Additional well-designed studies that include more diverse populations are needed. PMID:23221577

  18. Towards User-Friendly Spelling with an Auditory Brain-Computer Interface: The CharStreamer Paradigm

    PubMed Central

    Höhne, Johannes; Tangermann, Michael

    2014-01-01

    Realizing the decoding of brain signals into control commands, brain-computer interfaces (BCI) aim to establish an alternative communication pathway for locked-in patients. In contrast to most visual BCI approaches which use event-related potentials (ERP) of the electroencephalogram, auditory BCI systems are challenged with ERP responses, which are less class-discriminant between attended and unattended stimuli. Furthermore, these auditory approaches have more complex interfaces which imposes a substantial workload on their users. Aiming for a maximally user-friendly spelling interface, this study introduces a novel auditory paradigm: “CharStreamer”. The speller can be used with an instruction as simple as “please attend to what you want to spell”. The stimuli of CharStreamer comprise 30 spoken sounds of letters and actions. As each of them is represented by the sound of itself and not by an artificial substitute, it can be selected in a one-step procedure. The mental mapping effort (sound stimuli to actions) is thus minimized. Usability is further accounted for by an alphabetical stimulus presentation: contrary to random presentation orders, the user can foresee the presentation time of the target letter sound. Healthy, normal hearing users (n = 10) of the CharStreamer paradigm displayed ERP responses that systematically differed between target and non-target sounds. Class-discriminant features, however, varied individually from the typical N1-P2 complex and P3 ERP components found in control conditions with random sequences. To fully exploit the sequential presentation structure of CharStreamer, novel data analysis approaches and classification methods were introduced. The results of online spelling tests showed that a competitive spelling speed can be achieved with CharStreamer. With respect to user rating, it clearly outperforms a control setup with random presentation sequences. PMID:24886978

  19. Gene transfer preferentially selects MHC class I positive tumour cells and enhances tumour immunogenicity.

    PubMed

    Hacker, Ulrich T; Schildhauer, Ines; Barroso, Margarita Céspedes; Kofler, David M; Gerner, Franz M; Mysliwietz, Josef; Buening, Hildegard; Hallek, Michael; King, Susan B S

    2006-05-01

    The modulated expression of MHC class I on tumour tissue is well documented. Although the effect of MHC class I expression on the tumorigenicity and immunogenicity of MHC class I negative tumour cell lines has been rigorously studied, less is known about the validity of gene transfer and selection in cell lines with a mixed MHC class I phenotype. To address this issue we identified a C26 cell subline that consists of distinct populations of MHC class I (H-2D/K) positive and negative cells. Transient transfection experiments using liposome-based transfer showed a lower transgene expression in MHC class I negative cells. In addition, MHC class I negative cells were more sensitive to antibiotic selection. This led to the generation of fully MHC class I positive cell lines. In contrast to C26 cells, all transfectants were rejected in vivo and induced protection against the parental tumour cells in rechallenge experiments. Tumour cell specificity of the immune response was demonstrated in in vitro cytokine secretion and cytotoxicity assays. Transfectants expressing CD40 ligand and hygromycin phosphotransferase were not more immunogenic than cells expressing hygromycin resistance alone. We suggest that the MHC class I positive phenotype of the C26 transfectants had a bearing on their immunogenicity, because selected MHC class I positive cells were more immunogenic than parental C26 cells and could induce specific anti-tumour immune responses. These data demonstrate that the generation of tumour cell transfectants can lead to the selection of subpopulations that show an altered phenotype compared to the parental cell line and display altered immunogenicity independent of selection marker genes or other immune modulatory genes. Our results show the importance of monitoring gene transfer in the whole tumour cell population, especially for the evaluation of in vivo therapies targeted to heterogeneous tumour cell populations.

  20. Class Size Effects on Literacy Skills and Literacy Interest in First Grade: A Large-Scale Investigation

    ERIC Educational Resources Information Center

    Ecalle, Jean; Magnan, Annie; Gibert, Fabienne

    2006-01-01

    This article examines the impact of class size on literacy skills and on literacy interest in beginning readers from zones with specific educational needs in France. The data came from an experiment involving first graders in which teachers and pupils were randomly assigned to the different class types (small classes of 10-12 pupils vs. regular…

  1. Selective Predation of a Stalking Predator on Ungulate Prey

    PubMed Central

    Heurich, Marco; Zeis, Klara; Küchenhoff, Helmut; Müller, Jörg; Belotti, Elisa; Bufka, Luděk; Woelfing, Benno

    2016-01-01

    Prey selection is a key factor shaping animal populations and evolutionary dynamics. An optimal forager should target prey that offers the highest benefits in terms of energy content at the lowest costs. Predators are therefore expected to select for prey of optimal size. Stalking predators do not pursue their prey long, which may lead to a more random choice of prey individuals. Due to difficulties in assessing the composition of available prey populations, data on prey selection of stalking carnivores are still scarce. We show how the stalking predator Eurasian lynx (Lynx lynx) selects prey individuals based on species identity, age, sex and individual behaviour. To address the difficulties in assessing prey population structure, we confirm inferred selection patterns by using two independent data sets: (1) data of 387 documented kills of radio-collared lynx were compared to the prey population structure retrieved from systematic camera trapping using Manly’s standardized selection ratio alpha and (2) data on 120 radio-collared roe deer were analysed using a Cox proportional hazards model. Among the larger red deer prey, lynx selected against adult males—the largest and potentially most dangerous prey individuals. In roe deer lynx preyed selectively on males and did not select for a specific age class. Activity during high risk periods reduced the risk of falling victim to a lynx attack. Our results suggest that the stalking predator lynx actively selects for size, while prey behaviour induces selection by encounter and stalking success rates. PMID:27548478

  2. Changing health behaviors to improve health outcomes after angioplasty: a randomized trial of net present value versus future value risk communication.

    PubMed

    Charlson, M E; Peterson, J C; Boutin-Foster, C; Briggs, W M; Ogedegbe, G G; McCulloch, C E; Hollenberg, J; Wong, C; Allegrante, J P

    2008-10-01

    Patients who have undergone angioplasty experience difficulty modifying at-risk behaviors for subsequent cardiac events. The purpose of this study was to test whether an innovative approach to framing of risk, based on 'net present value' economic theory, would be more effective in behavioral intervention than the standard 'future value approach' in reducing cardiovascular morbidity and mortality following angioplasty. At baseline, all patients completed a health assessment, received an individualized risk profile and selected risk factors for modification. The intervention randomized patients into two varying methods for illustrating positive effects of behavior change. For the experimental group, each selected risk factor was assigned a numeric biologic age (the net present value) that approximated the relative potential to improve current health status and quality of life when modifying that risk factor. In the control group, risk reduction was framed as the value of preventing future health problems. Ninety-four percent of patients completed 2-year follow-up. There was no difference between the rates of death, stroke, myocardial infarction, Class II-IV angina or severe ischemia (on non-invasive testing) between the net present value group and the future value group. Our results show that a net present risk communication intervention did not result in significant differences in health outcomes.

  3. Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach

    PubMed Central

    Kudisthalert, Wasu

    2018-01-01

    Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets–Maximum Unbiased Validation Dataset–which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6. PMID:29652912

  4. Feature Selection Has a Large Impact on One-Class Classification Accuracy for MicroRNAs in Plants.

    PubMed

    Yousef, Malik; Saçar Demirci, Müşerref Duygu; Khalifa, Waleed; Allmer, Jens

    2016-01-01

    MicroRNAs (miRNAs) are short RNA sequences involved in posttranscriptional gene regulation. Their experimental analysis is complicated and, therefore, needs to be supplemented with computational miRNA detection. Currently computational miRNA detection is mainly performed using machine learning and in particular two-class classification. For machine learning, the miRNAs need to be parametrized and more than 700 features have been described. Positive training examples for machine learning are readily available, but negative data is hard to come by. Therefore, it seems prerogative to use one-class classification instead of two-class classification. Previously, we were able to almost reach two-class classification accuracy using one-class classifiers. In this work, we employ feature selection procedures in conjunction with one-class classification and show that there is up to 36% difference in accuracy among these feature selection methods. The best feature set allowed the training of a one-class classifier which achieved an average accuracy of ~95.6% thereby outperforming previous two-class-based plant miRNA detection approaches by about 0.5%. We believe that this can be improved upon in the future by rigorous filtering of the positive training examples and by improving current feature clustering algorithms to better target pre-miRNA feature selection.

  5. [Relationship between cyberbullying and the suicide related psychological behavior among middle and high school students in Anhui Province].

    PubMed

    Wang, Gengfu; Fang, Yu; Jiang, Liu; Zhou, Guiyang; Yuan, Shanshan; Wang, Xiuxiu; Su, Puyu

    2015-11-01

    To examine the prevalence rate of cyberbullying in middle and high school students in Anhui Province and explore the relationship between cyberbullying and suicide related psychological behavior. A total of 5726 middle and high school students from the 7th to the 12th grades in three regular middle schools and three regular high schools recruited from three cities in the Anhui Province (Tongling, Chuzhou, and Fuyang). Tongling, Chuzhou, and Fuyang are in the south, middle and north of Anhui, respectively. Each city was selected one regular middle school and one regular high school, and 8 classes were selected form each grade from each school. A stratified cluster random sampling method was used to randomly select 5726 participants among the six schools. Self-reports on cyberbullying and suicide related psychological behavior were collected. Among these 5726 adolescents, 46.8% of them involved in cyberbullying. Among them, 3.2% were bullies, 23.8% were victims, and 19.8% were both. Prevalence rates of suicide idea, suicide plan, suicide preparation, suicide implementation were 19.3%, 6.9%, 4.7% and 1.8%, respectively. Cyberbullying involvement, as victims, bullies or bully-victims, increased the risk of four kinds of suicide related psychological behavior (suicide idea, suicide plan, suicide preparation, suicide implementation) (P < 0.05). Cyberbullying has become a common occurrence in middle and high school students. Additionally, cyberbullying is closely related to suicide related psychological behavior among middle and high school students.

  6. The impact of Islamic religious education on anxiety level in primipara mothers.

    PubMed

    Mokhtaryan, Tahereh; Yazdanpanahi, Zahra; Akbarzadeh, Marzieh; Amooee, Sedigheh; Zare, Najaf

    2016-01-01

    Anxiety is among the most common pregnancy complications. This study was conducted to examine the impact of religious teaching on anxiety in primiparous mothers referring to the selected perinatal clinics of Tehran University of Medical Sciences in 2013. This randomized clinical trial was conducted on the pregnant women in 20-28 weeks of gestation referring to the selected clinics of Tehran University of Medical Sciences from July 2013 to June 2014. The subjects were selected through simple random sampling and divided into religious education and control groups. To assess the individuals, a demographic questionnaire, an anxiety trait State-Trait Anxiety Inventory and a religious knowledge and attitude trait (pre- test and post-test and 1 or 2 months after the test) were filled in by the two groups. Training classes (religious knowledge and attitude trait) for the cases were held in 6 weeks, and the sessions lasted for 1½ h. The knowledge and attitude scores showed significant differences in the controls and cases after the intervention ( P = 0.001) and 2 months after the study ( P = 0.001). According to the results of independent t -test, a significant difference was found in the state anxiety score ( P = 0.002) and personal score ( P = 0.0197) between the two groups before the intervention; however, the results were strongly significant different after the intervention and 2 months after the study ( P ≤ 0.001). The improvement in the mothers' knowledge and attitude in religious subjects will reduce anxiety in primiparas.

  7. Selfish Spermatogonial Selection: Evidence from an Immunohistochemical Screen in Testes of Elderly Men

    PubMed Central

    Turner, Gareth D. H.; Dudka-Ruszkowska, Wioleta; Taylor, Stephen; Meyts, Ewa Rajpert-De; Goriely, Anne; Wilkie, Andrew O. M.

    2012-01-01

    The dominant congenital disorders Apert syndrome, achondroplasia and multiple endocrine neoplasia–caused by specific missense mutations in the FGFR2, FGFR3 and RET proteins respectively–represent classical examples of paternal age-effect mutation, a class that arises at particularly high frequencies in the sperm of older men. Previous analyses of DNA from randomly selected cadaveric testes showed that the levels of the corresponding FGFR2, FGFR3 and RET mutations exhibit very uneven spatial distributions, with localised hotspots surrounded by large mutation-negative areas. These studies imply that normal testes are mosaic for clusters of mutant cells: these clusters are predicted to have altered growth and signalling properties leading to their clonal expansion (selfish spermatogonial selection), but DNA extraction eliminates the possibility to study such processes at a tissue level. Using a panel of antibodies optimised for the detection of spermatocytic seminoma, a rare tumour of spermatogonial origin, we demonstrate that putative clonal events are frequent within normal testes of elderly men (mean age: 73.3 yrs) and can be classed into two broad categories. We found numerous small (less than 200 cells) cellular aggregations with distinct immunohistochemical characteristics, localised to a portion of the seminiferous tubule, which are of uncertain significance. However more infrequently we identified additional regions where entire seminiferous tubules had a circumferentially altered immunohistochemical appearance that extended through multiple serial sections that were physically contiguous (up to 1 mm in length), and exhibited enhanced staining for antibodies both to FGFR3 and a marker of downstream signal activation, pAKT. These findings support the concept that populations of spermatogonia in individual seminiferous tubules in the testes of older men are clonal mosaics with regard to their signalling properties and activation, thus fulfilling one of the specific predictions of selfish spermatogonial selection. PMID:22879958

  8. Fukunaga-Koontz transform based dimensionality reduction for hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Ochilov, S.; Alam, M. S.; Bal, A.

    2006-05-01

    Fukunaga-Koontz Transform based technique offers some attractive properties for desired class oriented dimensionality reduction in hyperspectral imagery. In FKT, feature selection is performed by transforming into a new space where feature classes have complimentary eigenvectors. Dimensionality reduction technique based on these complimentary eigenvector analysis can be described under two classes, desired class and background clutter, such that each basis function best represent one class while carrying the least amount of information from the second class. By selecting a few eigenvectors which are most relevant to desired class, one can reduce the dimension of hyperspectral cube. Since the FKT based technique reduces data size, it provides significant advantages for near real time detection applications in hyperspectral imagery. Furthermore, the eigenvector selection approach significantly reduces computation burden via the dimensionality reduction processes. The performance of the proposed dimensionality reduction algorithm has been tested using real-world hyperspectral dataset.

  9. Evolving optimised decision rules for intrusion detection using particle swarm paradigm

    NASA Astrophysics Data System (ADS)

    Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

    2012-12-01

    The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

  10. Construction, Characterization, and Preliminary BAC-End Sequence Analysis of a Bacterial Artificial Chromosome Library of the Tea Plant (Camellia sinensis)

    PubMed Central

    Lin, Jinke; Kudrna, Dave; Wing, Rod A.

    2011-01-01

    We describe the construction and characterization of a publicly available BAC library for the tea plant, Camellia sinensis. Using modified methods, the library was constructed with the aim of developing public molecular resources to advance tea plant genomics research. The library consists of a total of 401,280 clones with an average insert size of 135 kb, providing an approximate coverage of 13.5 haploid genome equivalents. No empty vector clones were observed in a random sampling of 576 BAC clones. Further analysis of 182 BAC-end sequences from randomly selected clones revealed a GC content of 40.35% and low chloroplast and mitochondrial contamination. Repetitive sequence analyses indicated that LTR retrotransposons were the most predominant sequence class (86.93%–87.24%), followed by DNA retrotransposons (11.16%–11.69%). Additionally, we found 25 simple sequence repeats (SSRs) that could potentially be used as genetic markers. PMID:21234344

  11. Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

    NASA Technical Reports Server (NTRS)

    Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

    2016-01-01

    Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

  12. Learning planar Ising models

    DOE PAGES

    Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael; ...

    2016-12-01

    Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less

  13. Learning planar Ising models

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

    Johnson, Jason K.; Oyen, Diane Adele; Chertkov, Michael

    Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However, exact inference is intractable in general graphical models, which suggests the problem of seeking the best approximation to a collection of random variables within some tractable family of graphical models. In this paper, we focus on the class of planar Ising models, for which exact inference is tractable using techniques of statistical physics. Based on these techniques and recent methods for planarity testing and planar embedding, we propose a greedy algorithm for learning the bestmore » planar Ising model to approximate an arbitrary collection of binary random variables (possibly from sample data). Given the set of all pairwise correlations among variables, we select a planar graph and optimal planar Ising model defined on this graph to best approximate that set of correlations. Finally, we demonstrate our method in simulations and for two applications: modeling senate voting records and identifying geo-chemical depth trends from Mars rover data.« less

  14. Columnar organization of orientation domains in V1

    NASA Astrophysics Data System (ADS)

    Liedtke, Joscha; Wolf, Fred

    In the primary visual cortex (V1) of primates and carnivores, the functional architecture of basic stimulus selectivities appears similar across cortical layers (Hubel & Wiesel, 1962) justifying the use of two-dimensional cortical models and disregarding organization in the third dimension. Here we show theoretically that already small deviations from an exact columnar organization lead to non-trivial three-dimensional functional structures. We extend two-dimensional random field models (Schnabel et al., 2007) to a three-dimensional cortex by keeping a typical scale in each layer and introducing a correlation length in the third, columnar dimension. We examine in detail the three-dimensional functional architecture for different cortical geometries with different columnar correlation lengths. We find that (i) topological defect lines are generally curved and (ii) for large cortical curvatures closed loops and reconnecting topological defect lines appear. This theory extends the class of random field models by introducing a columnar dimension and provides a systematic statistical assessment of the three-dimensional functional architecture of V1 (see also (Tanaka et al., 2011)).

  15. The Influence of Small Class Size, Duration, Intensity, and Heterogeneity on Head Start Fade

    ERIC Educational Resources Information Center

    Huss, Christopher D.

    2010-01-01

    The researcher conducted a nonexperimental study to investigate and analyze the influence of reduced class sizes, intensity (all day and every day), duration (five years), and heterogeneity (random class assignment) on the Head Start Fade effect. The researcher employed retrospective data analysis using a longitudinal explanatory design on data…

  16. Canine retraction and anchorage loss: self-ligating versus conventional brackets in a randomized split-mouth study.

    PubMed

    da Costa Monini, André; Júnior, Luiz Gonzaga Gandini; Martins, Renato Parsekian; Vianna, Alexandre Protásio

    2014-09-01

    To evaluate the velocity of canine retraction, anchorage loss and changes on canine and first molar inclinations using self-ligating and conventional brackets. Twenty-five adults with Class I malocclusion and a treatment plan involving extractions of four first premolars were selected for this randomized split-mouth control trial. Patients had either conventional or self-ligating brackets bonded to maxillary canines randomly. Retraction was accomplished using 100-g nickel-titanium closed coil springs, which were reactivated every 4 weeks. Oblique radiographs were taken before and after canine retraction was completed, and the cephalograms were superimposed on stable structures of the maxilla. Cephalometric points were digitized twice by a blinded operator for error control, and the following landmarks were collected: canine cusp and apex horizontal changes, molar cusp and apex horizontal changes, and angulation changes in canines and molars. The blinded data, which were normally distributed, were analyzed through paired t-tests for group differences. No differences were found between the two groups for all variables tested. Both brackets showed the same velocity of canine retraction and loss of anteroposterior anchorage of the molars. No changes were found between brackets regarding the inclination of canines and first molars.

  17. Determination of trace elements in bovine semen samples by inductively coupled plasma mass spectrometry and data mining techniques for identification of bovine class.

    PubMed

    Aguiar, G F M; Batista, B L; Rodrigues, J L; Silva, L R S; Campiglia, A D; Barbosa, R M; Barbosa, F

    2012-12-01

    The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  18. Differentiation of functional constipation and constipation predominant irritable bowel syndrome based on Rome III criteria: a population-based study.

    PubMed

    Koloski, N A; Jones, M; Young, M; Talley, N J

    2015-05-01

    While the Rome III classification recognises functional constipation (FC) and constipation predominant IBS (IBS-C) as distinct disorders, recent evidence has suggested that these disorders are difficult to separate in clinical practice. To identify whether clinical and lifestyle factors differentiate Rome III-defined IBS-C from FC based on gastrointestinal symptoms and lifestyle characteristics. 3260 people randomly selected from the Australian population returned a postal survey. FC and IBS-C were defined according to Rome III. The first model used logistic regression to differentiate IBS-C from FC based on lifestyle, quality-of-life and psychological characteristics. The second approach was data-driven employing latent class analysis (LCA) to identify naturally occurring clusters in the data considering all symptoms involved in the Rome III criteria for IBS-C and FC. We found n = 206 (6.5%; 95% CI 5.7-7.4%) people met strict Rome III FC whereas n = 109 (3.5%; 95% CI 2.8-4.1%) met strict Rome III IBS-C. The case-control approach indicated that FC patients reported an older age at onset of constipation, were less likely to exercise, had higher mental QoL and less health care seeking than IBS-C. LCA yielded one latent class that was predominantly (75%) FC, while the other class was approximately half IBS-C and half FC. The FC-dominated latent class had clearly lower levels of symptoms used to classify IBS (pain-related symptoms) and was more likely to be male (P = 0.046) but was otherwise similar in distribution of lifestyle factors to the mixed class. The latent class analysis approach suggests a differentiation based more on symptom severity rather than the Rome III view. © 2015 John Wiley & Sons Ltd.

  19. Emerging Vaccine Therapy Approaches for Prostate Cancer

    PubMed Central

    Sonpavde, Guru; Slawin, Kevin M; Spencer, David M; Levitt, Jonathan M

    2010-01-01

    Prostate cancer vaccines attempt to induce clinically relevant, cancer-specific systemic immune responses in patients with prostate cancer and represent a new class of targeted, nontoxic therapies. With a growing array of vaccine technologies in preclinical or clinical development, autologous antigen-presenting cell vaccines loaded with the antigen, prostate acid phosphatase, and poxvirus vaccines targeting prostate-specific antigen have recently demonstrated a significant survival benefit in randomized trials of patients with metastatic castration-resistant prostate cancer, whereas others have failed to demonstrate any benefit. The combination of vaccines with chemotherapy, radiotherapy, and other biologic agents is also being evaluated. Efforts to optimize vaccine approaches and select ideal patient populations need to continue to build on these early successes. PMID:20428291

  20. Improved Sparse Multi-Class SVM and Its Application for Gene Selection in Cancer Classification

    PubMed Central

    Huang, Lingkang; Zhang, Hao Helen; Zeng, Zhao-Bang; Bushel, Pierre R.

    2013-01-01

    Background Microarray techniques provide promising tools for cancer diagnosis using gene expression profiles. However, molecular diagnosis based on high-throughput platforms presents great challenges due to the overwhelming number of variables versus the small sample size and the complex nature of multi-type tumors. Support vector machines (SVMs) have shown superior performance in cancer classification due to their ability to handle high dimensional low sample size data. The multi-class SVM algorithm of Crammer and Singer provides a natural framework for multi-class learning. Despite its effective performance, the procedure utilizes all variables without selection. In this paper, we propose to improve the procedure by imposing shrinkage penalties in learning to enforce solution sparsity. Results The original multi-class SVM of Crammer and Singer is effective for multi-class classification but does not conduct variable selection. We improved the method by introducing soft-thresholding type penalties to incorporate variable selection into multi-class classification for high dimensional data. The new methods were applied to simulated data and two cancer gene expression data sets. The results demonstrate that the new methods can select a small number of genes for building accurate multi-class classification rules. Furthermore, the important genes selected by the methods overlap significantly, suggesting general agreement among different variable selection schemes. Conclusions High accuracy and sparsity make the new methods attractive for cancer diagnostics with gene expression data and defining targets of therapeutic intervention. Availability: The source MATLAB code are available from http://math.arizona.edu/~hzhang/software.html. PMID:23966761

  1. Detecting long-duration cloud contamination in hyper-temporal NDVI imagery

    NASA Astrophysics Data System (ADS)

    Ali, Amjad; de Bie, C. A. J. M.; Skidmore, A. K.

    2013-10-01

    Cloud contamination impacts on the quality of hyper-temporal NDVI imagery and its subsequent interpretation. Short-duration cloud impacts are easily removed by using quality flags and an upper envelope filter, but long-duration cloud contamination of NDVI imagery remains. In this paper, an approach that goes beyond the use of quality flags and upper envelope filtering is tested to detect when and where long-duration clouds are responsible for unreliable NDVI readings, so that a user can flag those data as missing. The study is based on MODIS Terra and the combined Terra-Aqua 16-day NDVI product for the south of Ghana, where persistent cloud cover occurs throughout the year. The combined product could be assumed to have less cloud contamination, since it is based on two images per day. Short-duration cloud effects were removed from the two products through using the adaptive Savitzky-Golay filter. Then for each 'cleaned' product an unsupervised classified map was prepared using the ISODATA algorithm, and, by class, plots were prepared to depict changes over time of the means and the standard deviations in NDVI values. By comparing plots of similar classes, long-duration cloud contamination appeared to display a decline in mean NDVI below the lower limit 95% confidence interval with a coinciding increase in standard deviation above the upper limit 95% confidence interval. Regression analysis was carried out per NDVI class in two randomly selected groups in order to statistically test standard deviation values related to long-duration cloud contamination. A decline in seasonal NDVI values (growing season) were below the lower limit of 95% confidence interval as well as a concurrent increase in standard deviation values above the upper limit of the 95% confidence interval were noted in 34 NDVI classes. The regression analysis results showed that differences in NDVI class values between the Terra and the Terra-Aqua imagery were significantly correlated (p < 0.05) with the corresponding standard deviation values of the Terra imagery in case of all NDVI classes of two selected NDVI groups. The method successfully detects long-duration cloud contamination that results in unreliable NDVI values. The approach offers scientists interested in time series analysis a method of masking by area (class) the periods when pre-cleaned NDVI values remain affected by clouds. The approach requires no additional data for execution purposes but involves unsupervised classification of the imagery to carry out the evaluation of class-specific mean NDVI and standard deviation values over time.

  2. The Effect of Teaching Model ‘Learning Cycles 5E’ toward Students’ Achievement in Learning Mathematic at X Years Class SMA Negeri 1 Banuhampu 2013/2014 Academic Year

    NASA Astrophysics Data System (ADS)

    Yeni, N.; Suryabayu, E. P.; Handayani, T.

    2017-02-01

    Based on the survey showed that mathematics teacher still dominated in teaching and learning process. The process of learning is centered on the teacher while the students only work based on instructions provided by the teacher without any creativity and activities that stimulate students to explore their potential. Realized the problem above the writer interested in finding the solution by applying teaching model ‘Learning Cycles 5E’. The purpose of his research is to know whether teaching model ‘Learning Cycles 5E’ is better than conventional teaching in teaching mathematic. The type of the research is quasi experiment by Randomized Control test Group Only Design. The population in this research were all X years class students. The sample is chosen randomly after doing normality, homogeneity test and average level of students’ achievement. As the sample of this research was X.7’s class as experiment class used teaching model learning cycles 5E and X.8’s class as control class used conventional teaching. The result showed us that the students achievement in the class that used teaching model ‘Learning Cycles 5E’ is better than the class which did not use the model.

  3. Effects of random study checks and guided notes study cards on middle school special education students' notetaking accuracy and science vocabulary quiz scores

    NASA Astrophysics Data System (ADS)

    Wood, Charles L.

    Federal legislation mandates that all students with disabilities have meaningful access to the general education curriculum and that students with and without disabilities be held equally accountable to the same academic standards (IDEIA, 2004; NCLB, 2001). Many students with disabilities, however, perform poorly in academic content courses, especially at the middle and secondary school levels. Previous research has reported increased notetaking accuracy and quiz scores over lecture content when students completed guided notes compared to taking their own notes. This study evaluated the effects of a pre-quiz review procedure and specially formatted guided notes on middle school special education students' learning of science vocabulary. This study compared the effects of three experimental conditions. (a) Own Notes (ON), (b) Own Notes+Random Study Checks (ON+RSC), and (c) Guided Notes Study Cards+Random Study Checks (GNSC+RSC) on each student's accuracy of notes, next-day quiz scores, and review quiz scores. Each session, the teacher presented 12 science vocabulary terms and definitions during a lecture and students took notes. The students were given 5 minutes to study their notes at the end of each session and were reminded to study their notes at home and in study hall period. In the ON condition students took notes on a sheet of paper with numbered lines from 1 to 12. Just before each next-day quiz in the ON+RSC condition students used write-on response cards to answer two teacher-posed questions over randomly selected vocabulary terms from the previous day's lecture. If the answer on a randomly selected student's response card was correct, that student earned a lottery ticket for inexpensive prizes and a quiz bonus point for herself and each classmate. In the GNSC+RSC condition students took notes on specially formatted guided notes that after the lecture they cut into a set of flashcards that could used for study. The students' mean notetaking accuracy was 75% during ON, 89% during ON+RSC, and 99.5% during GNSC+RSC. The class mean scores on next-day quizzes during ON, ON+RSC, and GNSC+RSC was 39%, 68%, and 90%, respectively. The class mean score on review quizzes following ON, ON+RSC, and GNSC+RSC was 2.1, 5.3, and 7.8 (maximum score, 10), respectively. Results for five of the seven students provide convincing evidence of functional relationships between ON+RSC and higher quiz scores compared to ON and between GNSC+RSC and higher quiz scores compared to ON+RSC. Students', teachers', and parents' opinions regarding the RSC and GNSC procedures were highly favorable.

  4. Progressive Elaboration and Cross-Validation of a Latent Class Typology of Adolescent Alcohol Involvement in a National Sample

    PubMed Central

    Donovan, John E.; Chung, Tammy

    2015-01-01

    Objective: Most studies of adolescent drinking focus on single alcohol use behaviors (e.g., high-volume drinking, drunkenness) and ignore the patterning of adolescents’ involvement across multiple alcohol behaviors. The present latent class analyses (LCAs) examined a procedure for empirically determining multiple cut points on the alcohol use behaviors in order to establish a typology of adolescent alcohol involvement. Method: LCA was carried out on six alcohol use behavior indicators collected from 6,504 7th through 12th graders who participated in Wave I of the National Longitudinal Study of Adolescent Health (AddHealth). To move beyond dichotomous indicators, a “progressive elaboration” strategy was used, starting with six dichotomous indicators and then evaluating a series of models testing additional cut points on the ordinal indicators at progressively higher points for one indicator at a time. Analyses were performed on one random half-sample, and confirmatory LCAs were performed on the second random half-sample and in the Wave II data. Results: The final model consisted of four latent classes (never or non–current drinkers, low-intake drinkers, non–problem drinkers, and problem drinkers). Confirmatory LCAs in the second random half-sample from Wave I and in Wave II support this four-class solution. The means on the four latent classes were also generally ordered on an array of measures reflecting psychosocial risk for problem behavior. Conclusions: These analyses suggest that there may be four different classes or types of alcohol involvement among adolescents, and, more importantly, they illustrate the utility of the progressive elaboration strategy for moving beyond dichotomous indicators in latent class models. PMID:25978828

  5. Limited MHC class I intron 2 repertoire variation in bonobos.

    PubMed

    de Groot, Natasja G; Heijmans, Corrine M C; Helsen, Philippe; Otting, Nel; Pereboom, Zjef; Stevens, Jeroen M G; Bontrop, Ronald E

    2017-10-01

    Common chimpanzees (Pan troglodytes) experienced a selective sweep, probably caused by a SIV-like virus, which targeted their MHC class I repertoire. Based on MHC class I intron 2 data analyses, this selective sweep took place about 2-3 million years ago. As a consequence, common chimpanzees have a skewed MHC class I repertoire that is enriched for allotypes that are able to recognise conserved regions of the SIV proteome. The bonobo (Pan paniscus) shared an ancestor with common chimpanzees approximately 1.5 to 2 million years ago. To investigate whether the signature of this selective sweep is also detectable in bonobos, the MHC class I gene repertoire of two bonobo panels comprising in total 29 animals was investigated by Sanger sequencing. We identified 14 Papa-A, 20 Papa-B and 11 Papa-C alleles, of which eight, five and eight alleles, respectively, have not been reported previously. Within this pool of MHC class I variation, we recovered only 2 Papa-A, 3 Papa-B and 6 Papa-C intron 2 sequences. As compared to humans, bonobos appear to have an even more diminished MHC class I intron 2 lineage repertoire than common chimpanzees. This supports the notion that the selective sweep may have predated the speciation of common chimpanzees and bonobos. The further reduction of the MHC class I intron 2 lineage repertoire observed in bonobos as compared to the common chimpanzee may be explained by a founding effect or other subsequent selective processes.

  6. Qigong or Yoga Versus No Intervention in Older Adults With Chronic Low Back Pain-A Randomized Controlled Trial.

    PubMed

    Teut, Michael; Knilli, Judith; Daus, Dorothea; Roll, Stephanie; Witt, Claudia M

    2016-07-01

    The aim of this study was to assess the effectiveness of the reduction of chronic lower back pain in older adults using either yoga classes or qigong classes compared with no intervention. Older adults (65 years of age and older) with chronic low back pain were enrolled in and randomly allocated to: 1) yoga (24 classes, 45 minutes each, during 3 months), 2) qigong (12 classes, 90 minutes each, during 3 months), or 3) a control group who received no additional intervention. The pain intensity item of the Functional Rating Index after 3 months was used as primary outcome parameter. A total of 176 patients were randomized (n = 61 yoga, n = 58 qigong, n = 57 control; mean age 73 ± 5.6 years, 89% female). The mean adjusted pain intensity after 3 months was 1.71 for the yoga group (95% confidence interval [CI], 1.54-1.89), 1.67 for the qigong group (95% CI, 1.45-1.89), and 1.89 for no intervention (95% CI, 1.67-2.11). No statistically significant group differences were observed. Possible explanations for this lack of pain relief might include the ineffectiveness of interventions, inappropriate outcomes, or differences in pain perception and processing in older adults. The aim of this study was to assess the effectiveness of the reduction of chronic lower back pain in older adults using either yoga classes or qigong classes compared with no intervention. This 3-armed randomized trial with 176 older adults showed that yoga and qigong were not superior to no treatment in reducing pain and increasing quality of life. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

  7. Model selection for anomaly detection

    NASA Astrophysics Data System (ADS)

    Burnaev, E.; Erofeev, P.; Smolyakov, D.

    2015-12-01

    Anomaly detection based on one-class classification algorithms is broadly used in many applied domains like image processing (e.g. detection of whether a patient is "cancerous" or "healthy" from mammography image), network intrusion detection, etc. Performance of an anomaly detection algorithm crucially depends on a kernel, used to measure similarity in a feature space. The standard approaches (e.g. cross-validation) for kernel selection, used in two-class classification problems, can not be used directly due to the specific nature of a data (absence of a second, abnormal, class data). In this paper we generalize several kernel selection methods from binary-class case to the case of one-class classification and perform extensive comparison of these approaches using both synthetic and real-world data.

  8. Ensemble-type numerical uncertainty information from single model integrations

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

    Rauser, Florian, E-mail: florian.rauser@mpimet.mpg.de; Marotzke, Jochem; Korn, Peter

    2015-07-01

    We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of themore » influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.« less

  9. Researching Sex Bias in the Classroom.

    ERIC Educational Resources Information Center

    Donlan, Dan

    This paper outlines five methods of research on sex bias in the classroom: one-time survey, one class/one treatment, two class/two treatment, one class/random assignment to treatment, and analysis of differentiated effect. It shows how each method could be used in attempting to measure the effect of a unit on Norma Klein's "Mom, the Wolfman and…

  10. Class Size Effects on Student Achievement: Heterogeneity across Abilities and Fields

    ERIC Educational Resources Information Center

    De Paola, Maria; Ponzo, Michela; Scoppa, Vincenzo

    2013-01-01

    In this paper, we analyze class size effects on college students exploiting data from a project offering special remedial courses in mathematics and language skills to freshmen enrolled at an Italian medium-sized public university. To estimate the effects of class size, we exploit the fact that students and teachers are virtually randomly assigned…

  11. Peer Assessment Enhances Student Learning: The Results of a Matched Randomized Crossover Experiment in a College Statistics Class.

    PubMed

    Sun, Dennis L; Harris, Naftali; Walther, Guenther; Baiocchi, Michael

    2015-01-01

    Feedback has a powerful influence on learning, but it is also expensive to provide. In large classes it may even be impossible for instructors to provide individualized feedback. Peer assessment is one way to provide personalized feedback that scales to large classes. Besides these obvious logistical benefits, it has been conjectured that students also learn from the practice of peer assessment. However, this has never been conclusively demonstrated. Using an online educational platform that we developed, we conducted an in-class matched-set, randomized crossover experiment with high power to detect small effects. We establish that peer assessment causes a small but significant gain in student achievement. Our study also demonstrates the potential of web-based platforms to facilitate the design of high-quality experiments to identify small effects that were previously not detectable.

  12. Random regression analyses using B-spline functions to model growth of Nellore cattle.

    PubMed

    Boligon, A A; Mercadante, M E Z; Lôbo, R B; Baldi, F; Albuquerque, L G

    2012-02-01

    The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

  13. Accuracy assessment of NLCD 2006 land cover and impervious surface

    USGS Publications Warehouse

    Wickham, James D.; Stehman, Stephen V.; Gass, Leila; Dewitz, Jon; Fry, Joyce A.; Wade, Timothy G.

    2013-01-01

    Release of NLCD 2006 provides the first wall-to-wall land-cover change database for the conterminous United States from Landsat Thematic Mapper (TM) data. Accuracy assessment of NLCD 2006 focused on four primary products: 2001 land cover, 2006 land cover, land-cover change between 2001 and 2006, and impervious surface change between 2001 and 2006. The accuracy assessment was conducted by selecting a stratified random sample of pixels with the reference classification interpreted from multi-temporal high resolution digital imagery. The NLCD Level II (16 classes) overall accuracies for the 2001 and 2006 land cover were 79% and 78%, respectively, with Level II user's accuracies exceeding 80% for water, high density urban, all upland forest classes, shrubland, and cropland for both dates. Level I (8 classes) accuracies were 85% for NLCD 2001 and 84% for NLCD 2006. The high overall and user's accuracies for the individual dates translated into high user's accuracies for the 2001–2006 change reporting themes water gain and loss, forest loss, urban gain, and the no-change reporting themes for water, urban, forest, and agriculture. The main factor limiting higher accuracies for the change reporting themes appeared to be difficulty in distinguishing the context of grass. We discuss the need for more research on land-cover change accuracy assessment.

  14. Comparing the performance of meta-classifiers—a case study on selected imbalanced data sets relevant for prediction of liver toxicity

    NASA Astrophysics Data System (ADS)

    Jain, Sankalp; Kotsampasakou, Eleni; Ecker, Gerhard F.

    2018-05-01

    Cheminformatics datasets used in classification problems, especially those related to biological or physicochemical properties, are often imbalanced. This presents a major challenge in development of in silico prediction models, as the traditional machine learning algorithms are known to work best on balanced datasets. The class imbalance introduces a bias in the performance of these algorithms due to their preference towards the majority class. Here, we present a comparison of the performance of seven different meta-classifiers for their ability to handle imbalanced datasets, whereby Random Forest is used as base-classifier. Four different datasets that are directly (cholestasis) or indirectly (via inhibition of organic anion transporting polypeptide 1B1 and 1B3) related to liver toxicity were chosen for this purpose. The imbalance ratio in these datasets ranges between 4:1 and 20:1 for negative and positive classes, respectively. Three different sets of molecular descriptors for model development were used, and their performance was assessed in 10-fold cross-validation and on an independent validation set. Stratified bagging, MetaCost and CostSensitiveClassifier were found to be the best performing among all the methods. While MetaCost and CostSensitiveClassifier provided better sensitivity values, Stratified Bagging resulted in high balanced accuracies.

  15. Risk factors for human-directed canine aggression in a referral level clinical population.

    PubMed

    Lord, M; Casey, R A; Loftus, B A; Blackwell, E J

    2017-07-07

    Risk factors for human-directed aggression were investigated using retrospective analysis of data from a referral-level clinical behaviour population in the UK. A sample of 200 cases involving human-directed canine aggression and 200 control cases involving no instance of human-directed aggression were selected at random from a population of 746 cases. The final model suggested that clinical cases with human-directed aggression were significantly younger than those presenting with other undesired behaviours (P=0.008) and that male dogs were 1.4 times more likely to be aggressive towards human beings than female dogs (P=0.019). Dogs were 1.7 times more likely to be aggressive towards people if they had attended more than five puppy classes than if they had never attended puppy class (P=0.015) and that dogs were 2.8 times more likely to be aggressive towards human beings if there was another dog between 0 months and 24 months of age in the home (P=0.004). These factors only account for 7 per cent to 10 per cent of the variance between the human-directed aggression population and the control population, but factors such as attendance at puppy classes and numbers of dogs in the household suggest the need for longitudinal studies to investigate temporal relationships.

  16. Comparing the performance of meta-classifiers—a case study on selected imbalanced data sets relevant for prediction of liver toxicity

    NASA Astrophysics Data System (ADS)

    Jain, Sankalp; Kotsampasakou, Eleni; Ecker, Gerhard F.

    2018-04-01

    Cheminformatics datasets used in classification problems, especially those related to biological or physicochemical properties, are often imbalanced. This presents a major challenge in development of in silico prediction models, as the traditional machine learning algorithms are known to work best on balanced datasets. The class imbalance introduces a bias in the performance of these algorithms due to their preference towards the majority class. Here, we present a comparison of the performance of seven different meta-classifiers for their ability to handle imbalanced datasets, whereby Random Forest is used as base-classifier. Four different datasets that are directly (cholestasis) or indirectly (via inhibition of organic anion transporting polypeptide 1B1 and 1B3) related to liver toxicity were chosen for this purpose. The imbalance ratio in these datasets ranges between 4:1 and 20:1 for negative and positive classes, respectively. Three different sets of molecular descriptors for model development were used, and their performance was assessed in 10-fold cross-validation and on an independent validation set. Stratified bagging, MetaCost and CostSensitiveClassifier were found to be the best performing among all the methods. While MetaCost and CostSensitiveClassifier provided better sensitivity values, Stratified Bagging resulted in high balanced accuracies.

  17. Monte Carlo Techniques for Nuclear Systems - Theory Lectures

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

    Brown, Forrest B.

    These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. Thesemore » lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations. Beginning MCNP users are encouraged to review LA-UR-09-00380, "Criticality Calculations with MCNP: A Primer (3nd Edition)" (available at http:// mcnp.lanl.gov under "Reference Collection") prior to the class. No Monte Carlo class can be complete without having students write their own simple Monte Carlo routines for basic random sampling, use of the random number generator, and simplified particle transport simulation.« less

  18. Prevalence of tobacco use among students aged 13-15 years in Health Ministers' Council/Gulf Cooperation Council Member States, 2001-2004.

    PubMed

    Moh'd Al-Mulla, Ahmad; Abdou Helmy, Sahar; Al-Lawati, Jawad; Al Nasser, Sami; Ali Abdel Rahman, Salah; Almutawa, Ayesha; Abi Saab, Bassam; Al-Bedah, Abdullah Mohammed; Al-Rabeah, Abdullah Mohamed; Ali Bahaj, Ahmed; El-Awa, Fatimah; Warren, Charles W; Jones, Nathan R; Asma, Samira

    2008-06-01

    This article examines differences and similarities in adolescent tobacco use among Member States of the Health Ministers' Council for the Gulf Cooperation Council (HMC/GCC) using Global Youth Tobacco Survey (GYTS) data. Nationally representative samples of students in grades associated with ages 13-15 in Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, United Arab Emirates, and Yemen. Schools were selected proportional to enrollment size, classes were randomly selected within participating schools, and all students in selected classes were eligible to participate. GYTS results confirmed that boys are significantly more likely than girls to smoke cigarettes or use shisha (water pipe). Students had higher rates of tobacco use than adults in Bahrain, Oman, and United Arab Emirates. For boys and girls, shisha use was higher than cigarette smoking in almost all countries. Susceptibility to initiate smoking among never smokers was higher than current cigarette smoking in all countries. Exposure to secondhand smoke in public places was greater than 30%, direct protobacco advertising exposure was greater than 70% on billboards and in newspapers, and more than 10% of students were influenced by indirect advertising. Finally, less than half of the students were taught in school about the dangers of tobacco use in the past year. For boys and girls, high prevalence of cigarette smoking, high prevalence of shisha use, and high susceptibility of never smokers to initiate smoking in the next year are troubling indicators for the future of chronic disease and tobacco-related mortality in the Member States of the HMC/GCC.

  19. Tobacco use by youth: a surveillance report from the Global Youth Tobacco Survey project.

    PubMed Central

    Warren, C. W.; Riley, L.; Asma, S.; Eriksen, M. P.; Green, L.; Blanton, C.; Loo, C.; Batchelor, S.; Yach, D.

    2000-01-01

    The Global Youth Tobacco Survey (GYTS) project was developed by the World Health Organization and the US Centers for Disease Control and Prevention to track tobacco use among youth in countries across the world, using a common methodology and core questionnaire. The GYTS is school based and employs a two-stage sample design to produce representative data on smoking among students aged 13-15 years. The first stage consists of a probabilistic selection of schools, and the second consists of a random selection of classes from the participating schools. All students in the selected classes are eligible for the survey. In 1999, the GYTS was conducted in 13 countries and is currently in progress in over 30 countries. This report describes data from 12 countries: Barbados, China, Costa Rica, Fiji, Jordan, Poland, the Russian Federation (Moscow), South Africa, Sri Lanka, Ukraine (Kiev), Venezuela, and Zimbabwe. The findings show that tobacco use in the surveyed age group ranged from a high of 33% to a low of 10%. While the majority of current smokers wanted to stop smoking, very few were able to attend a cessation programme. In most countries the majority of young people reported seeing advertisements for cigarettes in media outlets, but anti-tobacco advertising was rare. The majority of young people reported being taught in school about the dangers of smoking. Environmental tobacco smoke exposure was very high in all countries. These results show that the GYTS surveillance system is enhancing the capacity of countries to design, implement, and evaluate tobacco prevention and control programmes. PMID:10994259

  20. Modified signal-to-noise: a new simple and practical gene filtering approach based on the concept of projective adaptive resonance theory (PART) filtering method.

    PubMed

    Takahashi, Hiro; Honda, Hiroyuki

    2006-07-01

    Considering the recent advances in and the benefits of DNA microarray technologies, many gene filtering approaches have been employed for the diagnosis and prognosis of diseases. In our previous study, we developed a new filtering method, namely, the projective adaptive resonance theory (PART) filtering method. This method was effective in subclass discrimination. In the PART algorithm, the genes with a low variance in gene expression in either class, not both classes, were selected as important genes for modeling. Based on this concept, we developed novel simple filtering methods such as modified signal-to-noise (S2N') in the present study. The discrimination model constructed using these methods showed higher accuracy with higher reproducibility as compared with many conventional filtering methods, including the t-test, S2N, NSC and SAM. The reproducibility of prediction was evaluated based on the correlation between the sets of U-test p-values on randomly divided datasets. With respect to leukemia, lymphoma and breast cancer, the correlation was high; a difference of >0.13 was obtained by the constructed model by using <50 genes selected by S2N'. Improvement was higher in the smaller genes and such higher correlation was observed when t-test, NSC and SAM were used. These results suggest that these modified methods, such as S2N', have high potential to function as new methods for marker gene selection in cancer diagnosis using DNA microarray data. Software is available upon request.

  1. Church-based social marketing to motivate older adults to take balance classes for fall prevention: cluster randomized controlled trial.

    PubMed

    DiGuiseppi, Carolyn G; Thoreson, Sallie R; Clark, Lauren; Goss, Cynthia W; Marosits, Mark J; Currie, Dustin W; Lezotte, Dennis C

    2014-10-01

    Determine whether a church-based social marketing program increases older adults' participation in balance classes for fall prevention. In 2009-10, 51 churches (7101 total members aged ≥ 60) in Colorado, U.S.A. were randomized to receive no intervention or a social marketing program. The program highlighted benefits of class participation (staying independent, building relationships), reduced potential barriers (providing convenient, subsidized classes), and communicated marketing messages through church leaders, trained "messengers," printed materials and church-based communication channels. Between-group differences in balance class enrollment and marketing message recall among congregants were compared using Wilcoxon Two-Sample Test and regression models. Compared to 25 control churches, 26 churches receiving the social marketing program had a higher median proportion (9.8% vs. 0.3%; p<0.001) and mean number (7.0 vs. 0.5; IRR=11.2 [95%CI: 7.5, 16.8]) of older adult congregants who joined balance classes. Intervention church members were also more likely to recall information about preventing falls with balance classes (AOR=6.2; 95% CI: 2.6, 14.8) and availability of classes locally (AOR=7.7; 95% CI: 2.6, 22.9). Church-based social marketing effectively disseminated messages about preventing falls through balance classes and, by emphasizing benefits and reducing barriers and costs of participation, successfully motivated older adults to enroll in the classes. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Severe chronic heart failure in patients considered for heart transplantation in Poland.

    PubMed

    Korewicki, Jerzy; Leszek, Przemysław; Zieliński, Tomasz; Rywik, Tomasz; Piotrowski, Walerian; Kurjata, Paweł; Kozar-Kamińska, Katarzyna; Kodziszewska, Katarzyna

    2012-01-01

    Based on the results of clinical trials, the prognosis for patients with severe heart failure (HF) has improved over the last 20 years. However, clinical trials do not reflect 'real life' due to patient selection. Thus, the aim of the POLKARD-HF registry was the analysis of survival of patients with refractory HF referred for orthotopic heart transplantation (OHT). Between 1 November 2003 and 31 October 2007, 983 patients with severe HF, referred for OHT in Poland, were included into the registry. All patients underwent routine clinical and hemodynamic evaluation, with NT-proBNP and hsCRP assessment. Death or an emergency OHT were assumed as the endpoints. The average observation period was 601 days. Kaplan-Meier curves with log-rank and univariate together with multifactor Cox regression model the stepwise variable selection method were used to determine the predictive value of analyzed variables. Among the 983 patients, the probability of surviving for one year was approximately 80%, for two years 70%, and for three years 67%. Etiology of the HF did not significantly influence the prognosis. The patients in NYHA class IV had a three-fold higher risk of death or emergency OHT. The univariate/multifactor Cox regression analysis revealed that NYHA IV class (HR 2.578, p < 0.0001), HFSS score (HR 2.572, p < 0.0001) and NT-proBNP plasma level (HR 1.600, p = 0.0200), proved to influence survival without death or emergency OHT. Despite optimal treatment, the prognosis for patients with refractory HF is still not good. NYHA class IV, NT-proBNP and HFSS score can help define the highest risk group. The results are consistent with the prognosis of patients enrolled into the randomized trials.

  3. Economic considerations and patients' preferences affect treatment selection for patients with rheumatoid arthritis: a discrete choice experiment among European rheumatologists.

    PubMed

    Hifinger, M; Hiligsmann, M; Ramiro, S; Watson, V; Severens, J L; Fautrel, B; Uhlig, T; van Vollenhoven, R; Jacques, P; Detert, J; Canas da Silva, J; Scirè, C A; Berghea, F; Carmona, L; Péntek, M; Keat, A; Boonen, A

    2017-01-01

    To compare the value that rheumatologists across Europe attach to patients' preferences and economic aspects when choosing treatments for patients with rheumatoid arthritis. In a discrete choice experiment, European rheumatologists chose between two hypothetical drug treatments for a patient with moderate disease activity. Treatments differed in five attributes: efficacy (improvement and achieved state on disease activity), safety (probability of serious adverse events), patient's preference (level of agreement), medication costs and cost-effectiveness (incremental cost-effectiveness ratio (ICER)). A Bayesian efficient design defined 14 choice sets, and a random parameter logit model was used to estimate relative preferences for rheumatologists across countries. Cluster analyses and latent class models were applied to understand preference patterns across countries and among individual rheumatologists. Responses of 559 rheumatologists from 12 European countries were included in the analysis (49% females, mean age 48 years). In all countries, efficacy dominated treatment decisions followed by economic considerations and patients' preferences. Across countries, rheumatologists avoided selecting a treatment that patients disliked. Latent class models revealed four respondent profiles: one traded off all attributes except safety, and the remaining three classes disregarded ICER. Among individual rheumatologists, 57% disregarded ICER and these were more likely from Italy, Romania, Portugal or France, whereas 43% disregarded uncommon/rare side effects and were more likely from Belgium, Germany, Hungary, the Netherlands, Norway, Spain, Sweden or UK. Overall, European rheumatologists are willing to trade between treatment efficacy, patients' treatment preferences and economic considerations. However, the degree of trade-off differs between countries and among individuals. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  4. Variation in the suppression or enhancement of responses related to drug habits as a function of stimulus classes and competing response categories.

    PubMed

    Haertzen, C A; Ross, F E

    1980-08-01

    Male prisoners who were opiate addicts (N = 47) were given three Process Association Tests of Addiction containing stimuli which evoked responses characteristic of three levels of drug habits: beginning and ending stage of addiction, intermediate stage of addiction, and an advanced level of addiction. Each test required subjects to associate 278 word stimuli with one of five options which were randomly selected from among 20 options covering the stages of addiction, steps in drug taking, and drug effects. The purpose of the study was to determine whether responses to particular options suppressed or enhanced responses to other options. A strong interaction was found between the classes of stimuli and the response options which produced suppression or enhancement. This interaction made it possible to develop a suppression scale to measure the effect of each class of stimulus. Popular responses most frequently suppressed responses of other options. Thus, when the stimuli were clean, responses of "to be clean" and "to live a normal life," which are sensitive indicators of the beginning or ending stages of addiction , suppressed responses of other stages. The response of "to be high," a prime indicator of an intermediate habit, suppressed responses of other options when the stimuli were drug names. Responses of "to be hooked" and "to fix," which are specific indicators of a strong habit, and "to be high," which is a nonspecific indicator of a strong habit, suppressed responses of many other options. In the development of new association tests the analysis of suppression could provide a basis for selectively varying option groupings in order to increase or decrease the frequently of certain responses.

  5. The effect of class imbalance on case selection for case-based classifiers: An empirical study in the context of medical decision support

    PubMed Central

    Malof, Jordan M.; Mazurowski, Maciej A.; Tourassi, Georgia D.

    2013-01-01

    Case selection is a useful approach for increasing the efficiency and performance of case-based classifiers. Multiple techniques have been designed to perform case selection. This paper empirically investigates how class imbalance in the available set of training cases can impact the performance of the resulting classifier as well as properties of the selected set. In this study, the experiments are performed using a dataset for the problem of detecting breast masses in screening mammograms. The classification problem was binary and we used a k-nearest neighbor classifier. The classifier’s performance was evaluated using the Receiver Operating Characteristic (ROC) area under the curve (AUC) measure. The experimental results indicate that although class imbalance reduces the performance of the derived classifier and the effectiveness of selection at improving overall classifier performance, case selection can still be beneficial, regardless of the level of class imbalance. PMID:21820273

  6. Attentional Requirements for the Selection of Words from Different Grammatical Categories

    ERIC Educational Resources Information Center

    Ayora, Pauline; Janssen, Niels; Dell'Acqua, Roberto; Alario, F.-Xavier

    2009-01-01

    Two grammatical classes are commonly distinguished in psycholinguistic research. The open-class includes content words such as nouns, whereas the closed-class includes function words such as determiners. A standing issue is to identify whether these words are retrieved through similar or distinct selection mechanisms. We report a comparative…

  7. Choice: 36 band feature selection software with applications to multispectral pattern recognition

    NASA Technical Reports Server (NTRS)

    Jones, W. C.

    1973-01-01

    Feature selection software was developed at the Earth Resources Laboratory that is capable of inputting up to 36 channels and selecting channel subsets according to several criteria based on divergence. One of the criterion used is compatible with the table look-up classifier requirements. The software indicates which channel subset best separates (based on average divergence) each class from all other classes. The software employs an exhaustive search technique, and computer time is not prohibitive. A typical task to select the best 4 of 22 channels for 12 classes takes 9 minutes on a Univac 1108 computer.

  8. Universality Classes of Interaction Structures for NK Fitness Landscapes

    NASA Astrophysics Data System (ADS)

    Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim

    2018-07-01

    Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.

  9. Universality Classes of Interaction Structures for NK Fitness Landscapes

    NASA Astrophysics Data System (ADS)

    Hwang, Sungmin; Schmiegelt, Benjamin; Ferretti, Luca; Krug, Joachim

    2018-02-01

    Kauffman's NK-model is a paradigmatic example of a class of stochastic models of genotypic fitness landscapes that aim to capture generic features of epistatic interactions in multilocus systems. Genotypes are represented as sequences of L binary loci. The fitness assigned to a genotype is a sum of contributions, each of which is a random function defined on a subset of k ≤ L loci. These subsets or neighborhoods determine the genetic interactions of the model. Whereas earlier work on the NK model suggested that most of its properties are robust with regard to the choice of neighborhoods, recent work has revealed an important and sometimes counter-intuitive influence of the interaction structure on the properties of NK fitness landscapes. Here we review these developments and present new results concerning the number of local fitness maxima and the statistics of selectively accessible (that is, fitness-monotonic) mutational pathways. In particular, we develop a unified framework for computing the exponential growth rate of the expected number of local fitness maxima as a function of L, and identify two different universality classes of interaction structures that display different asymptotics of this quantity for large k. Moreover, we show that the probability that the fitness landscape can be traversed along an accessible path decreases exponentially in L for a large class of interaction structures that we characterize as locally bounded. Finally, we discuss the impact of the NK interaction structures on the dynamics of evolution using adaptive walk models.

  10. Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection.

    PubMed

    Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

    2017-01-01

    Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.

  11. Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection

    PubMed Central

    Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

    2017-01-01

    Objectives Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Methods Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Results Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. Conclusion The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports. PMID:28166263

  12. A Novel Feature Optimization for Wearable Human-Computer Interfaces Using Surface Electromyography Sensors

    PubMed Central

    Zhang, Xiong; Zhao, Yacong; Zhang, Yu; Zhong, Xuefei; Fan, Zhaowen

    2018-01-01

    The novel human-computer interface (HCI) using bioelectrical signals as input is a valuable tool to improve the lives of people with disabilities. In this paper, surface electromyography (sEMG) signals induced by four classes of wrist movements were acquired from four sites on the lower arm with our designed system. Forty-two features were extracted from the time, frequency and time-frequency domains. Optimal channels were determined from single-channel classification performance rank. The optimal-feature selection was according to a modified entropy criteria (EC) and Fisher discrimination (FD) criteria. The feature selection results were evaluated by four different classifiers, and compared with other conventional feature subsets. In online tests, the wearable system acquired real-time sEMG signals. The selected features and trained classifier model were used to control a telecar through four different paradigms in a designed environment with simple obstacles. Performance was evaluated based on travel time (TT) and recognition rate (RR). The results of hardware evaluation verified the feasibility of our acquisition systems, and ensured signal quality. Single-channel analysis results indicated that the channel located on the extensor carpi ulnaris (ECU) performed best with mean classification accuracy of 97.45% for all movement’s pairs. Channels placed on ECU and the extensor carpi radialis (ECR) were selected according to the accuracy rank. Experimental results showed that the proposed FD method was better than other feature selection methods and single-type features. The combination of FD and random forest (RF) performed best in offline analysis, with 96.77% multi-class RR. Online results illustrated that the state-machine paradigm with a 125 ms window had the highest maneuverability and was closest to real-life control. Subjects could accomplish online sessions by three sEMG-based paradigms, with average times of 46.02, 49.06 and 48.08 s, respectively. These experiments validate the feasibility of proposed real-time wearable HCI system and algorithms, providing a potential assistive device interface for persons with disabilities. PMID:29543737

  13. Automatic threshold selection for multi-class open set recognition

    NASA Astrophysics Data System (ADS)

    Scherreik, Matthew; Rigling, Brian

    2017-05-01

    Multi-class open set recognition is the problem of supervised classification with additional unknown classes encountered after a model has been trained. An open set classifer often has two core components. The first component is a base classifier which estimates the most likely class of a given example. The second component consists of open set logic which estimates if the example is truly a member of the candidate class. Such a system is operated in a feed-forward fashion. That is, a candidate label is first estimated by the base classifier, and the true membership of the example to the candidate class is estimated afterward. Previous works have developed an iterative threshold selection algorithm for rejecting examples from classes which were not present at training time. In those studies, a Platt-calibrated SVM was used as the base classifier, and the thresholds were applied to class posterior probabilities for rejection. In this work, we investigate the effectiveness of other base classifiers when paired with the threshold selection algorithm and compare their performance with the original SVM solution.

  14. DEVELOPMENT OF A CLASS-SELECTIVE ENZYME IMMUNOASSAY FOR URINARY PHENOLIC GLUCURONIDES. (R825433)

    EPA Science Inventory

    Class-selective immunoassays for the measurement of glucuronides in human urine can aid evaluation of human exposure to complex mixtures of xenobiotics. Therefore, an enzyme immunoassay (EIA) for the group-selective detection of phenolic The Practice Pattern of Percutaneous Coronary Intervention in Korea: Based on Year 2014 Cohort of Korean Percutaneous Coronary Intervention (K-PCI) Registry.

    PubMed

    Gwon, Hyeon-Cheol; Jeon, Dong Woon; Kang, Hyun-Jae; Jang, Jae-Sik; Park, Duk-Woo; Shin, Dong-Ho; Moon, Keon-Woong; Kim, Jung-Sun; Kim, Juhan; Bae, Jang-Whan; Hur, Seung-Ho; Kim, Byung Ok; Choi, Donghoon; Han, Kyoo-Rok; Kim, Hyo-Soo

    2017-05-01

    Appropriate use criteria (AUC) was developed to improve the quality of percutaneous coronary intervention (PCI). However, these criteria should consider the current practice pattern in the country where they are being applied. The algorithm for the Korean PCI practice pattern (KP3) was developed by modifying the United States-derived AUC in expert consensus meetings. KP3 class A was defined as any strategy with evidence from randomized trials that was more conservative for PCI than medical therapy or coronary artery bypass graft (CABG). Class C was defined as any strategy with less evidence from randomized trials and more aggressive for PCI than medical therapy or CABG. Class B was defined as a strategy that was partly class A and partly class C. We applied the KP3 classification system to the Korean PCI registry. The KP3 class A was noted in 67.7% of patients, class B in 28.8%, and class C in 3.5%. The median proportion of class C cases per center was 2.0%. The distribution of KP3 classes varied significantly depending on clinical and angiographic characteristics. The proportion of KP3 class C cases per center was not significantly dependent on PCI volume, but rather on the percentage of ACS cases in each center. We report the current PCI practice pattern by applying the new KP3 classification in a nationwide PCI registry. The results should be interpreted carefully with due regard for the complex relationships between the determining variables and the healthcare system in Korea.

  15. Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models.

    PubMed

    Aspilcueta-Borquis, Rúsbel R; Araujo Neto, Francisco R; Baldi, Fernando; Santos, Daniel J A; Albuquerque, Lucia G; Tonhati, Humberto

    2012-08-01

    The test-day yields of milk, fat and protein were analysed from 1433 first lactations of buffaloes of the Murrah breed, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, born between 1985 and 2007. For the test-day yields, 10 monthly classes of lactation days were considered. The contemporary groups were defined as the herd-year-month of the test day. Random additive genetic, permanent environmental and residual effects were included in the model. The fixed effects considered were the contemporary group, number of milkings (1 or 2 milkings), linear and quadratic effects of the covariable cow age at calving and the mean lactation curve of the population (modelled by third-order Legendre orthogonal polynomials). The random additive genetic and permanent environmental effects were estimated by means of regression on third- to sixth-order Legendre orthogonal polynomials. The residual variances were modelled with a homogenous structure and various heterogeneous classes. According to the likelihood-ratio test, the best model for milk and fat production was that with four residual variance classes, while a third-order Legendre polynomial was best for the additive genetic effect for milk and fat yield, a fourth-order polynomial was best for the permanent environmental effect for milk production and a fifth-order polynomial was best for fat production. For protein yield, the best model was that with three residual variance classes and third- and fourth-order Legendre polynomials were best for the additive genetic and permanent environmental effects, respectively. The heritability estimates for the characteristics analysed were moderate, varying from 0·16±0·05 to 0·29±0·05 for milk yield, 0·20±0·05 to 0·30±0·08 for fat yield and 0·18±0·06 to 0·27±0·08 for protein yield. The estimates of the genetic correlations between the tests varied from 0·18±0·120 to 0·99±0·002; from 0·44±0·080 to 0·99±0·004; and from 0·41±0·080 to 0·99±0·004, for milk, fat and protein production, respectively, indicating that whatever the selection criterion used, indirect genetic gains can be expected throughout the lactation curve.

  16. The Impact of a Classroom-Based Guidance Program on Student Performance in Community College Math Classes

    ERIC Educational Resources Information Center

    Butcher, Kristin F.; Visher, Mary G.

    2013-01-01

    Passing through remedial and required math classes poses a significant barrier to success for many community college students. This study uses random assignment to investigate the impact of a "light-touch" intervention, where an individual visited math classes a few times during the semester, for a few minutes each time, to inform…

  17. Smart in Mathematics? Exploring the Effects of In-Class-Level Differentiation Using SMARTboard on Math Proficiency

    ERIC Educational Resources Information Center

    Cabus, Sofie J.; Haelermans, Carla; Franken, Sonja

    2017-01-01

    This paper explored the effects of in-class-level differentiation by making innovative use of an interactive whiteboard (SMARTboard) on math proficiency. Therefore, this paper evaluates the use of SMARTboard in class, in combination with teacher training, using a randomized field experiment among 199 pre-vocational students in seventh grade in the…

  18. Dancing for Parkinson Disease: A Randomized Trial of Irish Set Dancing Compared With Usual Care.

    PubMed

    Shanahan, Joanne; Morris, Meg E; Bhriain, Orfhlaith Ni; Volpe, Daniele; Lynch, Tim; Clifford, Amanda M

    2017-09-01

    To examine the feasibility of a randomized controlled study design and to explore the benefits of a set dancing intervention compared with usual care. Randomized controlled design, with participants randomized to Irish set dance classes or a usual care group. Community based. Individuals with idiopathic Parkinson disease (PD) (N=90). The dance group attended a 1.5-hour dancing class each week for 10 weeks and undertook a home dance program for 20 minutes, 3 times per week. The usual care group continued with their usual care and daily activities. The primary outcome was feasibility, determined by recruitment rates, success of randomization and allocation procedures, attrition, adherence, safety, willingness of participants to be randomized, resource availability, and cost. Secondary outcomes were motor function (motor section of the Unified Parkinson's Disease Rating Scale), quality of life (Parkinson's Disease Questionnaire-39), functional endurance (6-min walk test), and balance (mini-BESTest). Ninety participants were randomized (45 per group). There were no adverse effects or resource constraints. Although adherence to the dancing program was 93.5%, there was >40% attrition in each group. Postintervention, the dance group had greater nonsignificant gains in quality of life than the usual care group. There was a meaningful deterioration in endurance in the usual care group. There were no meaningful changes in other outcomes. The exit questionnaire showed participants enjoyed the classes and would like to continue participation. For people with mild to moderately severe PD, set dancing is feasible and enjoyable and may improve quality of life. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  19. Spatial Analysis of “Crazy Quilts”, a Class of Potentially Random Aesthetic Artefacts

    PubMed Central

    Westphal-Fitch, Gesche; Fitch, W. Tecumseh

    2013-01-01

    Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. “Crazy quilts” represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures. PMID:24066095

  1. Spatial analysis of "crazy quilts", a class of potentially random aesthetic artefacts.

    PubMed

    Westphal-Fitch, Gesche; Fitch, W Tecumseh

    2013-01-01

    Human artefacts in general are highly structured and often display ordering principles such as translational, reflectional or rotational symmetry. In contrast, human artefacts that are intended to appear random and non symmetrical are very rare. Furthermore, many studies show that humans find it extremely difficult to recognize or reproduce truly random patterns or sequences. Here, we attempt to model two-dimensional decorative spatial patterns produced by humans that show no obvious order. "Crazy quilts" represent a historically important style of quilt making that became popular in the 1870s, and lasted about 50 years. Crazy quilts are unusual because unlike most human artefacts, they are specifically intended to appear haphazard and unstructured. We evaluate the degree to which this intention was achieved by using statistical techniques of spatial point pattern analysis to compare crazy quilts with regular quilts from the same region and era and to evaluate the fit of various random distributions to these two quilt classes. We found that the two quilt categories exhibit fundamentally different spatial characteristics: The patch areas of crazy quilts derive from a continuous random distribution, while area distributions of regular quilts consist of Gaussian mixtures. These Gaussian mixtures derive from regular pattern motifs that are repeated and we suggest that such a mixture is a distinctive signature of human-made visual patterns. In contrast, the distribution found in crazy quilts is shared with many other naturally occurring spatial patterns. Centroids of patches in the two quilt classes are spaced differently and in general, crazy quilts but not regular quilts are well-fitted by a random Strauss process. These results indicate that, within the constraints of the quilt format, Victorian quilters indeed achieved their goal of generating random structures.

  2. TRANSFER OF AVERSIVE RESPONDENT ELICITATION IN ACCORDANCE WITH EQUIVALENCE RELATIONS

    PubMed Central

    Valverde, Miguel RodrÍguez; Luciano, Carmen; Barnes-Holmes, Dermot

    2009-01-01

    The present study investigates the transfer of aversively conditioned respondent elicitation through equivalence classes, using skin conductance as the measure of conditioning. The first experiment is an attempt to replicate Experiment 1 in Dougher, Augustson, Markham, Greenway, and Wulfert (1994), with different temporal parameters in the aversive conditioning procedure employed. Match-to-sample procedures were used to teach 17 participants two 4-member equivalence classes. Then, one member of one class was paired with electric shock and one member of the other class was presented without shock. The remaining stimuli from each class were presented in transfer tests. Unlike the findings in the original study, transfer of conditioning was not achieved. In Experiment 2, similar procedures were used with 30 participants, although several modifications were introduced (formation of five-member classes, direct conditioning with several elements of each class, random sequences of stimulus presentation in transfer tests, reversal in aversive conditioning contingencies). More than 80% of participants who had shown differential conditioning also showed the transfer of function effect. Moreover, this effect was replicated within subjects for 3 participants. This is the first demonstration of the transfer of aversive respondent elicitation through stimulus equivalence classes with the presentation of transfer test trials in random order. The latter prevents the possibility that transfer effects are an artefact of transfer test presentation order. PMID:20119523

  3. Selective class IIa histone deacetylase inhibition via a nonchelating zinc-binding group.

    PubMed

    Lobera, Mercedes; Madauss, Kevin P; Pohlhaus, Denise T; Wright, Quentin G; Trocha, Mark; Schmidt, Darby R; Baloglu, Erkan; Trump, Ryan P; Head, Martha S; Hofmann, Glenn A; Murray-Thompson, Monique; Schwartz, Benjamin; Chakravorty, Subhas; Wu, Zining; Mander, Palwinder K; Kruidenier, Laurens; Reid, Robert A; Burkhart, William; Turunen, Brandon J; Rong, James X; Wagner, Craig; Moyer, Mary B; Wells, Carrow; Hong, Xuan; Moore, John T; Williams, Jon D; Soler, Dulce; Ghosh, Shomir; Nolan, Michael A

    2013-05-01

    In contrast to studies on class I histone deacetylase (HDAC) inhibitors, the elucidation of the molecular mechanisms and therapeutic potential of class IIa HDACs (HDAC4, HDAC5, HDAC7 and HDAC9) is impaired by the lack of potent and selective chemical probes. Here we report the discovery of inhibitors that fill this void with an unprecedented metal-binding group, trifluoromethyloxadiazole (TFMO), which circumvents the selectivity and pharmacologic liabilities of hydroxamates. We confirm direct metal binding of the TFMO through crystallographic approaches and use chemoproteomics to demonstrate the superior selectivity of the TFMO series relative to a hydroxamate-substituted analog. We further apply these tool compounds to reveal gene regulation dependent on the catalytic active site of class IIa HDACs. The discovery of these inhibitors challenges the design process for targeting metalloenzymes through a chelating metal-binding group and suggests therapeutic potential for class IIa HDAC enzyme blockers distinct in mechanism and application compared to current HDAC inhibitors.

  4. Parental attitudes towards measles vaccination in the canton of Aargau, Switzerland: a latent class analysis.

    PubMed

    Weiss, Carine; Schröpfer, Daniel; Merten, Sonja

    2016-08-11

    Despite the successes of routine national childhood vaccination programmes, measles remains a public health concern. The purpose of this paper is to investigate how patterns of parental attitudes are linked to the decision-making process for or against MMR vaccination. This exploratory study was designed to identify distinct patterns of attitudes towards or against measles vaccination through Latent Class Analysis (LCA) in a sub-sample of mothers living in the canton of Aargau in Switzerland. Parents of young children below 36 months of age were randomly selected through parents' counsellors' registries. Among other questions, respondents were asked to state their agreement in response to 14 belief statements regarding measles vaccination on a 5-point Likert scale. To identify groups of parents showing distinct patterns of attitudes and beliefs regarding measles vaccination, we used Latent Class Analysis (LCA). The LCA showed three classes of parents with different attitudes and believes towards measles vaccination: The biggest group (class 1) are those having positive attitudes towards immunisation, followed by the second biggest group (class 2) which is characterised by having fearful attitudes and by showing uncertainty about immunisation. The third group (class 3) shows distinct patterns of critical attitudes against immunisation. Within this group over 90 % agree or totally agree that immunisation is an artificial intrusion into the natural immune system and therefore want to vaccinate their children only if necessary. We find that parents in the Canton Aargau who hesitate to vaccinate their children against measles, mumps and rubella show distinct opinions and attitudes. Health professionals should be aware of these perceptions to tailor their messages accordingly and positively influence these parents to vaccinate their children. Special attention needs to be given to those parents who are planning to vaccinate their children but are not following the national guidelines.

  5. Use of Systematic Methods to Improve Disease Identification in Administrative Data: The Case of Severe Sepsis.

    PubMed

    Shahraz, Saeid; Lagu, Tara; Ritter, Grant A; Liu, Xiadong; Tompkins, Christopher

    2017-03-01

    Selection of International Classification of Diseases (ICD)-based coded information for complex conditions such as severe sepsis is a subjective process and the results are sensitive to the codes selected. We use an innovative data exploration method to guide ICD-based case selection for severe sepsis. Using the Nationwide Inpatient Sample, we applied Latent Class Analysis (LCA) to determine if medical coders follow any uniform and sensible coding for observations with severe sepsis. We examined whether ICD-9 codes specific to sepsis (038.xx for septicemia, a subset of 995.9 codes representing Systemic Inflammatory Response syndrome, and 785.52 for septic shock) could all be members of the same latent class. Hospitalizations coded with sepsis-specific codes could be assigned to a latent class of their own. This class constituted 22.8% of all potential sepsis observations. The probability of an observation with any sepsis-specific codes being assigned to the residual class was near 0. The chance of an observation in the residual class having a sepsis-specific code as the principal diagnosis was close to 0. Validity of sepsis class assignment is supported by empirical results, which indicated that in-hospital deaths in the sepsis-specific class were around 4 times as likely as that in the residual class. The conventional methods of defining severe sepsis cases in observational data substantially misclassify sepsis cases. We suggest a methodology that helps reliable selection of ICD codes for conditions that require complex coding.

  6. Two spatial light modulator system for laboratory simulation of random beam propagation in random media.

    PubMed

    Wang, Fei; Toselli, Italo; Korotkova, Olga

    2016-02-10

    An optical system consisting of a laser source and two independent consecutive phase-only spatial light modulators (SLMs) is shown to accurately simulate a generated random beam (first SLM) after interaction with a stationary random medium (second SLM). To illustrate the range of possibilities, a recently introduced class of random optical frames is examined on propagation in free space and several weak turbulent channels with Kolmogorov and non-Kolmogorov statistics.

  7. Advancements in automated tissue segmentation pipeline for contrast-enhanced CT scans of adult and pediatric patients

    NASA Astrophysics Data System (ADS)

    Somasundaram, Elanchezhian; Kaufman, Robert; Brady, Samuel

    2017-03-01

    The development of a random forests machine learning technique is presented for fully-automated neck, chest, abdomen, and pelvis tissue segmentation of CT images using Trainable WEKA (Waikato Environment for Knowledge Analysis) Segmentation (TWS) plugin of FIJI (ImageJ, NIH). The use of a single classifier model to segment six tissue classes (lung, fat, muscle, solid organ, blood/contrast agent, bone) in the CT images is studied. An automated unbiased scheme to sample pixels from the training images and generate a balanced training dataset over the seven classes is also developed. Two independent training datasets are generated from a pool of 4 adult (>55 kg) and 3 pediatric patients (<=55 kg) with 7 manually contoured slices for each patient. Classifier training investigated 28 image filters comprising a total of 272 features. Highly correlated and insignificant features are eliminated using Correlated Feature Subset (CFS) selection with Best First Search (BFS) algorithms in WEKA. The 2 training models (from the 2 training datasets) had 74 and 71 input training features, respectively. The study also investigated the effect of varying the number of trees (25, 50, 100, and 200) in the random forest algorithm. The performance of the 2 classifier models are evaluated on inter-patient intra-slice, intrapatient inter-slice and inter-patient inter-slice test datasets. The Dice similarity coefficients (DSC) and confusion matrices are used to understand the performance of the classifiers across the tissue segments. The effect of number of features in the training input on the performance of the classifiers for tissue classes with less than optimal DSC values is also studied. The average DSC values for the two training models on the inter-patient intra-slice test data are: 0.98, 0.89, 0.87, 0.79, 0.68, and 0.84, for lung, fat, muscle, solid organ, blood/contrast agent, and bone, respectively. The study demonstrated that a robust segmentation accuracy for lung, muscle and fat tissue classes. For solid-organ, blood/contrast and bone, the performance of the segmentation pipeline improved significantly by using the advanced capabilities of WEKA. However, further improvements are needed to reduce the noise in the segmentation.

  8. Defining an essence of structure determining residue contacts in proteins.

    PubMed

    Sathyapriya, R; Duarte, Jose M; Stehr, Henning; Filippis, Ioannis; Lappe, Michael

    2009-12-01

    The network of native non-covalent residue contacts determines the three-dimensional structure of a protein. However, not all contacts are of equal structural significance, and little knowledge exists about a minimal, yet sufficient, subset required to define the global features of a protein. Characterisation of this "structural essence" has remained elusive so far: no algorithmic strategy has been devised to-date that could outperform a random selection in terms of 3D reconstruction accuracy (measured as the Ca RMSD). It is not only of theoretical interest (i.e., for design of advanced statistical potentials) to identify the number and nature of essential native contacts-such a subset of spatial constraints is very useful in a number of novel experimental methods (like EPR) which rely heavily on constraint-based protein modelling. To derive accurate three-dimensional models from distance constraints, we implemented a reconstruction pipeline using distance geometry. We selected a test-set of 12 protein structures from the four major SCOP fold classes and performed our reconstruction analysis. As a reference set, series of random subsets (ranging from 10% to 90% of native contacts) are generated for each protein, and the reconstruction accuracy is computed for each subset. We have developed a rational strategy, termed "cone-peeling" that combines sequence features and network descriptors to select minimal subsets that outperform the reference sets. We present, for the first time, a rational strategy to derive a structural essence of residue contacts and provide an estimate of the size of this minimal subset. Our algorithm computes sparse subsets capable of determining the tertiary structure at approximately 4.8 A Ca RMSD with as little as 8% of the native contacts (Ca-Ca and Cb-Cb). At the same time, a randomly chosen subset of native contacts needs about twice as many contacts to reach the same level of accuracy. This "structural essence" opens new avenues in the fields of structure prediction, empirical potentials and docking.

  9. Defining an Essence of Structure Determining Residue Contacts in Proteins

    PubMed Central

    Sathyapriya, R.; Duarte, Jose M.; Stehr, Henning; Filippis, Ioannis; Lappe, Michael

    2009-01-01

    The network of native non-covalent residue contacts determines the three-dimensional structure of a protein. However, not all contacts are of equal structural significance, and little knowledge exists about a minimal, yet sufficient, subset required to define the global features of a protein. Characterisation of this “structural essence” has remained elusive so far: no algorithmic strategy has been devised to-date that could outperform a random selection in terms of 3D reconstruction accuracy (measured as the Ca RMSD). It is not only of theoretical interest (i.e., for design of advanced statistical potentials) to identify the number and nature of essential native contacts—such a subset of spatial constraints is very useful in a number of novel experimental methods (like EPR) which rely heavily on constraint-based protein modelling. To derive accurate three-dimensional models from distance constraints, we implemented a reconstruction pipeline using distance geometry. We selected a test-set of 12 protein structures from the four major SCOP fold classes and performed our reconstruction analysis. As a reference set, series of random subsets (ranging from 10% to 90% of native contacts) are generated for each protein, and the reconstruction accuracy is computed for each subset. We have developed a rational strategy, termed “cone-peeling” that combines sequence features and network descriptors to select minimal subsets that outperform the reference sets. We present, for the first time, a rational strategy to derive a structural essence of residue contacts and provide an estimate of the size of this minimal subset. Our algorithm computes sparse subsets capable of determining the tertiary structure at approximately 4.8 Å Ca RMSD with as little as 8% of the native contacts (Ca-Ca and Cb-Cb). At the same time, a randomly chosen subset of native contacts needs about twice as many contacts to reach the same level of accuracy. This “structural essence” opens new avenues in the fields of structure prediction, empirical potentials and docking. PMID:19997489

  10. On the Asymmetric Zero-Range in the Rarefaction Fan

    NASA Astrophysics Data System (ADS)

    Gonçalves, Patrícia

    2014-02-01

    We consider one-dimensional asymmetric zero-range processes starting from a step decreasing profile leading, in the hydrodynamic limit, to the rarefaction fan of the associated hydrodynamic equation. Under that initial condition, and for totally asymmetric jumps, we show that the weighted sum of joint probabilities for second class particles sharing the same site is convergent and we compute its limit. For partially asymmetric jumps, we derive the Law of Large Numbers for a second class particle, under the initial configuration in which all positive sites are empty, all negative sites are occupied with infinitely many first class particles and there is a single second class particle at the origin. Moreover, we prove that among the infinite characteristics emanating from the position of the second class particle it picks randomly one of them. The randomness is given in terms of the weak solution of the hydrodynamic equation, through some sort of renormalization function. By coupling the constant-rate totally asymmetric zero-range with the totally asymmetric simple exclusion, we derive limiting laws for more general initial conditions.

  11. [Representations of the body: with the word one group of adolescents from popular classes].

    PubMed

    Braga, Patrícia Déa; Molina, Maria del Carmen Bisi; de Figueiredo, Túlio Alberto Martins

    2010-01-01

    In view of the great body aesthetic concern demonstrated by a group of adolescents from popular classes, this study had the purpose of getting to know and analyze the social representations of the body. It investigated the qualitative approach carried out with adolescent workers from the Centro Salesiano do Menor, in Vitória, Espírito Santo State. A random sample was selected from a group of 334 individuals. Eight girls and seven boys were approached by means of non-structured interview. From the analysis of their speeches, a categorization was performed and the theory of the Social Representations was used for discussion. The results pointed out that body perception, for boys as well as for girls, are focused on the ideas of proportionality, normality and perfection. Regarding the consequences of not having an ideal body, both stated situations such as: exclusion, illnesses, unhappiness and even death. In-depth knowledge on opinion, thoughts and feelings of the adolescents relative to the body, may contribute to subside interventions in this group, extending significantly the scope of professional performance in the health sector.

  12. Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

    PubMed

    Hager, Rebecca; Tsiatis, Anastasios A; Davidian, Marie

    2018-05-18

    Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment options at each decision point, and thus formalizes this process. An optimal regime is one leading to the most beneficial outcome on average if used to select treatment for the patient population. We propose a method for estimation of an optimal regime involving two decision points when the outcome of interest is a censored survival time, which is based on maximizing a locally efficient, doubly robust, augmented inverse probability weighted estimator for average outcome over a class of regimes. By casting this optimization as a classification problem, we exploit well-studied classification techniques such as support vector machines to characterize the class of regimes and facilitate implementation via a backward iterative algorithm. Simulation studies of performance and application of the method to data from a sequential, multiple assignment randomized clinical trial in acute leukemia are presented. © 2018, The International Biometric Society.

  13. The effects of shade on performance, carcass classes and behaviour of heat-stressed feedlot cattle at the finisher phase.

    PubMed

    Blaine, K L; Nsahlai, Ignatius Verla

    2011-03-01

    The study aimed to determine the impact of shade on the performance, carcass class and behaviour using 146 crossbred steers and bulls during the finishing phase on a commercial feedlot in February. Treatments were (1) shade and (2) no shade. Average daily gain (ADG), DMI, and feed efficiency were measured, and hot carcass weight (HCW) and grades were collected at slaughter. The proportion of animals within a pen engaged in various behavioural activities (standing, lying, feeding and panting) was recorded. Five randomly selected individual animals per treatment were monitored every 2 min between 0700 and 1600 hours to determine the time spent on each of the above activities. Shade improved the final body weight (P < 0.0001), ADG (P = 0.079), and HCW by 8.33 kg (P < 0.05). Shade increased (P < 0.05) the feeding activity but decreased (P < 0.05) panting behaviour. Shade conferred an economic benefit of R2.03 head(-1)week(-1), and thus would reduce heat stress and increase the feedlot profitability.

  14. On the number of Bose-selected modes in driven-dissipative ideal Bose gases

    NASA Astrophysics Data System (ADS)

    Schnell, Alexander; Ketzmerick, Roland; Eckardt, André

    2018-03-01

    In an ideal Bose gas that is driven into a steady state far from thermal equilibrium, a generalized form of Bose condensation can occur. Namely, the single-particle states unambiguously separate into two groups: the group of Bose-selected states, whose occupations increase linearly with the total particle number, and the group of all other states whose occupations saturate [Phys. Rev. Lett. 111, 240405 (2013), 10.1103/PhysRevLett.111.240405]. However, so far very little is known about how the number of Bose-selected states depends on the properties of the system and its coupling to the environment. The answer to this question is crucial since systems hosting a single, a few, or an extensive number of Bose-selected states will show rather different behavior. While in the former two scenarios each selected mode acquires a macroscopic occupation, corresponding to (fragmented) Bose condensation, the latter case rather bears resemblance to a high-temperature state of matter. In this paper, we systematically investigate the number of Bose-selected states, considering different classes of the rate matrices that characterize the driven-dissipative ideal Bose gases in the limit of weak system-bath coupling. These include rate matrices with continuum limit, rate matrices of chaotic driven systems, random rate matrices, and rate matrices resulting from thermal baths that couple to a few observables only.

  15. On the number of Bose-selected modes in driven-dissipative ideal Bose gases.

    PubMed

    Schnell, Alexander; Ketzmerick, Roland; Eckardt, André

    2018-03-01

    In an ideal Bose gas that is driven into a steady state far from thermal equilibrium, a generalized form of Bose condensation can occur. Namely, the single-particle states unambiguously separate into two groups: the group of Bose-selected states, whose occupations increase linearly with the total particle number, and the group of all other states whose occupations saturate [Phys. Rev. Lett. 111, 240405 (2013)PRLTAO0031-900710.1103/PhysRevLett.111.240405]. However, so far very little is known about how the number of Bose-selected states depends on the properties of the system and its coupling to the environment. The answer to this question is crucial since systems hosting a single, a few, or an extensive number of Bose-selected states will show rather different behavior. While in the former two scenarios each selected mode acquires a macroscopic occupation, corresponding to (fragmented) Bose condensation, the latter case rather bears resemblance to a high-temperature state of matter. In this paper, we systematically investigate the number of Bose-selected states, considering different classes of the rate matrices that characterize the driven-dissipative ideal Bose gases in the limit of weak system-bath coupling. These include rate matrices with continuum limit, rate matrices of chaotic driven systems, random rate matrices, and rate matrices resulting from thermal baths that couple to a few observables only.

  16. Maximizing lipocalin prediction through balanced and diversified training set and decision fusion.

    PubMed

    Nath, Abhigyan; Subbiah, Karthikeyan

    2015-12-01

    Lipocalins are short in sequence length and perform several important biological functions. These proteins are having less than 20% sequence similarity among paralogs. Experimentally identifying them is an expensive and time consuming process. The computational methods based on the sequence similarity for allocating putative members to this family are also far elusive due to the low sequence similarity existing among the members of this family. Consequently, the machine learning methods become a viable alternative for their prediction by using the underlying sequence/structurally derived features as the input. Ideally, any machine learning based prediction method must be trained with all possible variations in the input feature vector (all the sub-class input patterns) to achieve perfect learning. A near perfect learning can be achieved by training the model with diverse types of input instances belonging to the different regions of the entire input space. Furthermore, the prediction performance can be improved through balancing the training set as the imbalanced data sets will tend to produce the prediction bias towards majority class and its sub-classes. This paper is aimed to achieve (i) the high generalization ability without any classification bias through the diversified and balanced training sets as well as (ii) enhanced the prediction accuracy by combining the results of individual classifiers with an appropriate fusion scheme. Instead of creating the training set randomly, we have first used the unsupervised Kmeans clustering algorithm to create diversified clusters of input patterns and created the diversified and balanced training set by selecting an equal number of patterns from each of these clusters. Finally, probability based classifier fusion scheme was applied on boosted random forest algorithm (which produced greater sensitivity) and K nearest neighbour algorithm (which produced greater specificity) to achieve the enhanced predictive performance than that of individual base classifiers. The performance of the learned models trained on Kmeans preprocessed training set is far better than the randomly generated training sets. The proposed method achieved a sensitivity of 90.6%, specificity of 91.4% and accuracy of 91.0% on the first test set and sensitivity of 92.9%, specificity of 96.2% and accuracy of 94.7% on the second blind test set. These results have established that diversifying training set improves the performance of predictive models through superior generalization ability and balancing the training set improves prediction accuracy. For smaller data sets, unsupervised Kmeans based sampling can be an effective technique to increase generalization than that of the usual random splitting method. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. COMPARISON OF RANDOM AND SYSTEMATIC SITE SELECTION FOR ASSESSING ATTAINMENT OF AQUATIC LIFE USES IN SEGMENTS OF THE OHIO RIVER

    EPA Science Inventory

    This report is a description of field work and data analysis results comparing a design comparable to systematic site selection with one based on random selection of sites. The report is expected to validate the use of random site selection in the bioassessment program for the O...

  18. Adaptive random walks on the class of Web graphs

    NASA Astrophysics Data System (ADS)

    Tadić, B.

    2001-09-01

    We study random walk with adaptive move strategies on a class of directed graphs with variable wiring diagram. The graphs are grown from the evolution rules compatible with the dynamics of the world-wide Web [B. Tadić, Physica A 293, 273 (2001)], and are characterized by a pair of power-law distributions of out- and in-degree for each value of the parameter β, which measures the degree of rewiring in the graph. The walker adapts its move strategy according to locally available information both on out-degree of the visited node and in-degree of target node. A standard random walk, on the other hand, uses the out-degree only. We compute the distribution of connected subgraphs visited by an ensemble of walkers, the average access time and survival probability of the walks. We discuss these properties of the walk dynamics relative to the changes in the global graph structure when the control parameter β is varied. For β≥ 3, corresponding to the world-wide Web, the access time of the walk to a given level of hierarchy on the graph is much shorter compared to the standard random walk on the same graph. By reducing the amount of rewiring towards rigidity limit β↦βc≲ 0.1, corresponding to the range of naturally occurring biochemical networks, the survival probability of adaptive and standard random walk become increasingly similar. The adaptive random walk can be used as an efficient message-passing algorithm on this class of graphs for large degree of rewiring.

  19. Find a Diabetes Prevention Program Near You

    MedlinePlus

    ... throughout the country. Find an In-person Class Select From List Find a class near you by ... some locations. Search by ZIP ZIP Code: Distance: Select Location Location: Find an Online Program Online programs ...

  20. Validation of World Health Organization Assessment Schedule 2.0 in specialized somatic rehabilitation services in Norway.

    PubMed

    Moen, Vegard Pihl; Drageset, Jorunn; Eide, Geir Egil; Klokkerud, Mari; Gjesdal, Sturla

    2017-02-01

    The World Health Organization Disability Assessment Schedule (WHODAS) 2.0 is a generic instrument to assess disability covering six domains. The purpose of this study was to investigate the potential of the instrument for monitoring disability in specialized somatic rehabilitation by testing reliability, construct validity and responsiveness of WHODAS 2.0, Norwegian version, among patients with various health conditions. For taxonomy, terminology and definitions, the Consensus-based Standards for the Selection of Health Measurement Instruments were followed. Reproducibility was investigated by the intra-class correlation coefficient (ICC) in a randomly selected sample. Internal consistency was assessed by Cronbach's alpha. Construct validity was evaluated by correlations between WHODAS 2.0 and the Medical Outcomes Study 36-item Short Form, and fit of the hypothesized structure using confirmatory factor analysis (CFA). Responsiveness was evaluated in another randomly selected sample by testing a priori formulated hypotheses. Nine hundred seventy patients were included in the study. Reproducibility and responsiveness were evaluated in 53 and 104 patients, respectively. The ICC for the WHODAS 2.0 domains ranged from 0.63 to 0.84 and was 0.87 for total score. Cronbach's alpha for domains ranged from 0.75 to 0.94 and was 0.93 for total score. For construct validity, 6 of 12 expected correlations were confirmed and CFA did not achieve satisfactory fit indices. For responsiveness, 3 of 8 hypotheses were confirmed. The Norwegian version of WHODAS 2.0 showed moderate to satisfactory reliability and moderate validity in rehabilitation patients. However, the present study indicated possible limitations in terms of responsiveness.

  1. Potent and Specific Inhibition of Glycosidases by Small Artificial Binding Proteins (Affitins)

    PubMed Central

    Mechaly, Ariel E.; Obal, Gonzalo; Béhar, Ghislaine; Mouratou, Barbara; Oppezzo, Pablo; Alzari, Pedro M.; Pecorari, Frédéric

    2014-01-01

    Glycosidases are associated with various human diseases. The development of efficient and specific inhibitors may provide powerful tools to modulate their activity. However, achieving high selectivity is a major challenge given that glycosidases with different functions can have similar enzymatic mechanisms and active-site architectures. As an alternative approach to small-chemical compounds, proteinaceous inhibitors might provide a better specificity by involving a larger surface area of interaction. We report here the design and characterization of proteinaceous inhibitors that specifically target endoglycosidases representative of the two major mechanistic classes; retaining and inverting glycosidases. These inhibitors consist of artificial affinity proteins, Affitins, selected against the thermophilic CelD from Clostridium thermocellum and lysozyme from hen egg. They were obtained from libraries of Sac7d variants, which involve either the randomization of a surface or the randomization of a surface and an artificially-extended loop. Glycosidase binders exhibited affinities in the nanomolar range with no cross-recognition, with efficient inhibition of lysozyme (Ki = 45 nM) and CelD (Ki = 95 and 111 nM), high expression yields in Escherichia coli, solubility, and thermal stabilities up to 81.1°C. The crystal structures of glycosidase-Affitin complexes validate our library designs. We observed that Affitins prevented substrate access by two modes of binding; covering or penetrating the catalytic site via the extended loop. In addition, Affitins formed salt-bridges with residues essential for enzymatic activity. These results lead us to propose the use of Affitins as versatile selective glycosidase inhibitors and, potentially, as enzymatic inhibitors in general. PMID:24823716

  2. Potent and specific inhibition of glycosidases by small artificial binding proteins (affitins).

    PubMed

    Correa, Agustín; Pacheco, Sabino; Mechaly, Ariel E; Obal, Gonzalo; Béhar, Ghislaine; Mouratou, Barbara; Oppezzo, Pablo; Alzari, Pedro M; Pecorari, Frédéric

    2014-01-01

    Glycosidases are associated with various human diseases. The development of efficient and specific inhibitors may provide powerful tools to modulate their activity. However, achieving high selectivity is a major challenge given that glycosidases with different functions can have similar enzymatic mechanisms and active-site architectures. As an alternative approach to small-chemical compounds, proteinaceous inhibitors might provide a better specificity by involving a larger surface area of interaction. We report here the design and characterization of proteinaceous inhibitors that specifically target endoglycosidases representative of the two major mechanistic classes; retaining and inverting glycosidases. These inhibitors consist of artificial affinity proteins, Affitins, selected against the thermophilic CelD from Clostridium thermocellum and lysozyme from hen egg. They were obtained from libraries of Sac7d variants, which involve either the randomization of a surface or the randomization of a surface and an artificially-extended loop. Glycosidase binders exhibited affinities in the nanomolar range with no cross-recognition, with efficient inhibition of lysozyme (Ki = 45 nM) and CelD (Ki = 95 and 111 nM), high expression yields in Escherichia coli, solubility, and thermal stabilities up to 81.1°C. The crystal structures of glycosidase-Affitin complexes validate our library designs. We observed that Affitins prevented substrate access by two modes of binding; covering or penetrating the catalytic site via the extended loop. In addition, Affitins formed salt-bridges with residues essential for enzymatic activity. These results lead us to propose the use of Affitins as versatile selective glycosidase inhibitors and, potentially, as enzymatic inhibitors in general.

  3. Central nervous system medications and falls risk in men aged 60-75 years: the Study on Male Osteoporosis and Aging (SOMA).

    PubMed

    Masud, Tahir; Frost, Morten; Ryg, Jesper; Matzen, Lars; Ibsen, Marlene; Abrahamsen, Bo; Brixen, Kim

    2013-01-01

    drugs acting on the central nervous system (CNS) increase falls risk. Most data on CNS drugs and falls are in women/mixed-sex populations. This study assessed the relationship between CNS drugs and falls in men aged 60-75 years. a questionnaire was sent to randomly selected Danish men aged 60-75 years. Cross-sectional data on CNS drugs and falls in the previous year were available for 4,696 men. Logistic regression investigated the relationship between falls and CNS drugs. the median age was 66.3 (IQR = 63.1-70.0) years; 21.7% were fallers. The following were associated with fallers (OR; 95% CI): opiates (2.4; 1.5-3.7), other analgesics (1.7; 1.4-2.1), antiepileptics (2.8; 1.5-5.1), antidepressants (2.8; 1.9-4.1) and anxiolytics/hypnotics (1.5; 0.9-2.6). Effects of opiates interacted strongly and significantly with age, with a marked association with falls in the older half of the subjects only. No significant associations were found between antipsychotics and fallers. Selective serotonin reuptake inhibitors and tricyclics were significantly associated with fallers (3.1; 2.0-5.0 and 2.2; 1.0-4.7, respectively). several CNS drug classes are associated with an approximately 2-3-fold increase risk of falls in men aged 60-75 years randomly selected from the population. Further longitudinal data are now required to confirm and further investigate the role of CNS drugs in falls causation in men.

  4. Student control ideology and the science classroom environment in urban secondary schools of sudan

    NASA Astrophysics Data System (ADS)

    Harty, Harold; Hassan, Hassan A.

    An examination was made concerning the relationships between Sudanese secondary science teachers' pupil control ideology and their students' perceptions/observations of the psychosocial environment of their science classrooms. One hundred secondary science teachers were classified as possessing humanistic (N = 20) or custodial (N = 20) control ideologies. A class (N = 40) of students was randomly selected for every teacher in both groups. The findings revealed that no significant relationships existed between the control ideologies of the teachers and their students' perceptions/observations of the classroom environment. Custodialism in control ideology was significantly related to the classroom environment psychosocial aspect of low support. Discussion and implications of the findings have been approached from both Sudanese and American perspectives.

  5. Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

    NASA Astrophysics Data System (ADS)

    Polan, Daniel F.; Brady, Samuel L.; Kaufman, Robert A.

    2016-09-01

    There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 n , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21 patient image sections, were analyzed. The automated algorithm produced segmentation of seven material classes with a median DSC of 0.86  ±  0.03 for pediatric patient protocols, and 0.85  ±  0.04 for adult patient protocols. Additionally, 100 randomly selected patient examinations were segmented and analyzed, and a mean sensitivity of 0.91 (range: 0.82-0.98), specificity of 0.89 (range: 0.70-0.98), and accuracy of 0.90 (range: 0.76-0.98) were demonstrated. In this study, we demonstrate that this fully automated segmentation tool was able to produce fast and accurate segmentation of the neck and trunk of the body over a wide range of patient habitus and scan parameters.

  6. No Randomization? No Problem: Experimental Control and Random Assignment in Single Case Research

    ERIC Educational Resources Information Center

    Ledford, Jennifer R.

    2018-01-01

    Randomization of large number of participants to different treatment groups is often not a feasible or preferable way to answer questions of immediate interest to professional practice. Single case designs (SCDs) are a class of research designs that are experimental in nature but require only a few participants, all of whom receive the…

  7. Cardiac HDAC6 Catalytic Activity is Induced in Response to Chronic Hypertension

    PubMed Central

    Lemon, Douglas D.; Horn, Todd R.; Cavasin, Maria A.; Jeong, Mark Y.; Haubold, Kurt W.; Long, Carlin S.; Irwin, David C.; McCune, Sylvia A.; Chung, Eunhee; Leinwand, Leslie A.; McKinsey, Timothy A.

    2011-01-01

    Small molecule histone deacetylase (HDAC) inhibitors block adverse cardiac remodeling in animal models of heart failure. The efficacious compounds target class I, class IIb and, to a lesser extent, class IIa HDACs. It is hypothesized that a selective inhibitor of a specific HDAC class (or an isoform within that class) will provide a favorable therapeutic window for the treatment of heart failure, although the optimal selectivity profile for such a compound remains unknown. Genetic studies have suggested that class I HDACs promote pathological cardiac remodeling, while class IIa HDACs are protective. In contrast, nothing is known about the function or regulation of class IIb HDACs in the heart. We developed assays to quantify catalytic activity of distinct HDAC classes in left and right ventricular cardiac tissue from animal models of hypertensive heart disease. Class I and IIa HDAC activity was elevated in some but not all diseased tissues. In contrast, catalytic activity of the class IIb HDAC, HDAC6, was consistently increased in stressed myocardium, but not in a model of physiologic hypertrophy. HDAC6 catalytic activity was also induced by diverse extracellular stimuli in cultured cardiac myocytes and fibroblasts. These findings suggest an unforeseen role for HDAC6 in the heart, and highlight the need for pre-clinical evaluation of HDAC6-selective inhibitors to determine whether this HDAC isoform is pathological or protective in the setting of cardiovascular disease. PMID:21539845

  8. Measurements of experimental precision for trials with cowpea (Vigna unguiculata L. Walp.) genotypes.

    PubMed

    Teodoro, P E; Torres, F E; Santos, A D; Corrêa, A M; Nascimento, M; Barroso, L M A; Ceccon, G

    2016-05-09

    The aim of this study was to evaluate the suitability of statistics as experimental precision degree measures for trials with cowpea (Vigna unguiculata L. Walp.) genotypes. Cowpea genotype yields were evaluated in 29 trials conducted in Brazil between 2005 and 2012. The genotypes were evaluated with a randomized block design with four replications. Ten statistics that were estimated for each trial were compared using descriptive statistics, Pearson correlations, and path analysis. According to the class limits established, selective accuracy and F-test values for genotype, heritability, and the coefficient of determination adequately estimated the degree of experimental precision. Using these statistics, 86.21% of the trials had adequate experimental precision. Selective accuracy and the F-test values for genotype, heritability, and the coefficient of determination were directly related to each other, and were more suitable than the coefficient of variation and the least significant difference (by the Tukey test) to evaluate experimental precision in trials with cowpea genotypes.

  9. Fast Human Detection for Intelligent Monitoring Using Surveillance Visible Sensors

    PubMed Central

    Ko, Byoung Chul; Jeong, Mira; Nam, JaeYeal

    2014-01-01

    Human detection using visible surveillance sensors is an important and challenging work for intruder detection and safety management. The biggest barrier of real-time human detection is the computational time required for dense image scaling and scanning windows extracted from an entire image. This paper proposes fast human detection by selecting optimal levels of image scale using each level's adaptive region-of-interest (ROI). To estimate the image-scaling level, we generate a Hough windows map (HWM) and select a few optimal image scales based on the strength of the HWM and the divide-and-conquer algorithm. Furthermore, adaptive ROIs are arranged per image scale to provide a different search area. We employ a cascade random forests classifier to separate candidate windows into human and nonhuman classes. The proposed algorithm has been successfully applied to real-world surveillance video sequences, and its detection accuracy and computational speed show a better performance than those of other related methods. PMID:25393782

  10. How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space.

    PubMed

    Koutsoukas, Alexios; Paricharak, Shardul; Galloway, Warren R J D; Spring, David R; Ijzerman, Adriaan P; Glen, Robert C; Marcus, David; Bender, Andreas

    2014-01-27

    Chemical diversity is a widely applied approach to select structurally diverse subsets of molecules, often with the objective of maximizing the number of hits in biological screening. While many methods exist in the area, few systematic comparisons using current descriptors in particular with the objective of assessing diversity in bioactivity space have been published, and this shortage is what the current study is aiming to address. In this work, 13 widely used molecular descriptors were compared, including fingerprint-based descriptors (ECFP4, FCFP4, MACCS keys), pharmacophore-based descriptors (TAT, TAD, TGT, TGD, GpiDAPH3), shape-based descriptors (rapid overlay of chemical structures (ROCS) and principal moments of inertia (PMI)), a connectivity-matrix-based descriptor (BCUT), physicochemical-property-based descriptors (prop2D), and a more recently introduced molecular descriptor type (namely, "Bayes Affinity Fingerprints"). We assessed both the similar behavior of the descriptors in assessing the diversity of chemical libraries, and their ability to select compounds from libraries that are diverse in bioactivity space, which is a property of much practical relevance in screening library design. This is particularly evident, given that many future targets to be screened are not known in advance, but that the library should still maximize the likelihood of containing bioactive matter also for future screening campaigns. Overall, our results showed that descriptors based on atom topology (i.e., fingerprint-based descriptors and pharmacophore-based descriptors) correlate well in rank-ordering compounds, both within and between descriptor types. On the other hand, shape-based descriptors such as ROCS and PMI showed weak correlation with the other descriptors utilized in this study, demonstrating significantly different behavior. We then applied eight of the molecular descriptors compared in this study to sample a diverse subset of sample compounds (4%) from an initial population of 2587 compounds, covering the 25 largest human activity classes from ChEMBL and measured the coverage of activity classes by the subsets. Here, it was found that "Bayes Affinity Fingerprints" achieved an average coverage of 92% of activity classes. Using the descriptors ECFP4, GpiDAPH3, TGT, and random sampling, 91%, 84%, 84%, and 84% of the activity classes were represented in the selected compounds respectively, followed by BCUT, prop2D, MACCS, and PMI (in order of decreasing performance). In addition, we were able to show that there is no visible correlation between compound diversity in PMI space and in bioactivity space, despite frequent utilization of PMI plots to this end. To summarize, in this work, we assessed which descriptors select compounds with high coverage of bioactivity space, and can hence be used for diverse compound selection for biological screening. In cases where multiple descriptors are to be used for diversity selection, this work describes which descriptors behave complementarily, and can hence be used jointly to focus on different aspects of diversity in chemical space.

  11. Automatic learning-based beam angle selection for thoracic IMRT

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

    Amit, Guy; Marshall, Andrea; Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca

    Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationallymore » efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume coverage and organ at risk sparing and were superior over plans produced with fixed sets of common beam angles. The great majority of the automatic plans (93%) were approved as clinically acceptable by three radiation therapy specialists. Conclusions: The results demonstrated the feasibility of utilizing a learning-based approach for automatic selection of beam angles in thoracic IMRT planning. The proposed method may assist in reducing the manual planning workload, while sustaining plan quality.« less

  12. Housing as a Determinant of Tongan Children’s Health: Innovative Methodology Using Wearable Cameras

    PubMed Central

    Robinson, Andrew; Puloka, Viliami; Smith, Moira; Stanley, James; Signal, Louise

    2017-01-01

    Housing is a significant determinant of health, particularly in developing countries such as Tonga. Currently, very little is known about the quality of the housing in Tonga, as is the case with many developing countries, nor about the interaction between children and the home environment. This study aimed to identify the nature and extent of health risk factors and behaviours in Tongan houses from a child’s perspective. An innovative methodology was used, Kids’Cam Tonga. Seventy-two Class 6 children (10 to 13-year-olds) were randomly selected from 12 randomly selected schools in Tongatapu, the main island. Each participating child wore a wearable camera on lanyards around their neck. The device automatically took wide-angled, 136° images of the child’s perspective every seven seconds. The children were instructed to wear the camera all day from Friday morning to Sunday evening, inclusive. The analysis showed that the majority of Tongan children in the study live in houses that have structural deficiencies and hazards, including water damage (42%), mould (36%), and electrical (89%) and burn risk factors (28%). The findings suggest that improvements to the housing stock may reduce the associated health burden and increase buildings’ resilience to natural hazards. A collaborative approach between communities, community leaders, government and non-governmental organisations (NGOs) is urgently needed. This research methodology may be of value to other developing countries. PMID:28976919

  13. Mediation and spillover effects in group-randomized trials: a case study of the 4Rs educational intervention

    PubMed Central

    VanderWeele, Tyler J.; Hong, Guanglei; Jones, Stephanie M.; Brown, Joshua L.

    2013-01-01

    Peer influence and social interactions can give rise to spillover effects in which the exposure of one individual may affect outcomes of other individuals. Even if the intervention under study occurs at the group or cluster level as in group-randomized trials, spillover effects can occur when the mediator of interest is measured at a lower level than the treatment. Evaluators who choose groups rather than individuals as experimental units in a randomized trial often anticipate that the desirable changes in targeted social behaviors will be reinforced through interference among individuals in a group exposed to the same treatment. In an empirical evaluation of the effect of a school-wide intervention on reducing individual students’ depressive symptoms, schools in matched pairs were randomly assigned to the 4Rs intervention or the control condition. Class quality was hypothesized as an important mediator assessed at the classroom level. We reason that the quality of one classroom may affect outcomes of children in another classroom because children interact not simply with their classmates but also with those from other classes in the hallways or on the playground. In investigating the role of class quality as a mediator, failure to account for such spillover effects of one classroom on the outcomes of children in other classrooms can potentially result in bias and problems with interpretation. Using a counterfactual conceptualization of direct, indirect and spillover effects, we provide a framework that can accommodate issues of mediation and spillover effects in group randomized trials. We show that the total effect can be decomposed into a natural direct effect, a within-classroom mediated effect and a spillover mediated effect. We give identification conditions for each of the causal effects of interest and provide results on the consequences of ignoring “interference” or “spillover effects” when they are in fact present. Our modeling approach disentangles these effects. The analysis examines whether the 4Rs intervention has an effect on children's depressive symptoms through changing the quality of other classes as well as through changing the quality of a child's own class. PMID:23997375

  14. Social System of River City High School Senior Class: Socio-economic Status (SES).

    ERIC Educational Resources Information Center

    Daly, Richard F.

    The goal of this study was to investigate the relationship between an adolescent's socioeconomic status (SES) and selected variables of the sub-subsystems of the River City High School senior class social system during the 1974-75 academic year. Variables for study were selected from each of the three sub-subsystems of the senior class social…

  15. Randomizing Roaches: Exploring the "Bugs" of Randomization in Experimental Design

    ERIC Educational Resources Information Center

    Wagler, Amy; Wagler, Ron

    2014-01-01

    Understanding the roles of random selection and random assignment in experimental design is a central learning objective in most introductory statistics courses. This article describes an activity, appropriate for a high school or introductory statistics course, designed to teach the concepts, values and pitfalls of random selection and assignment…

  16. Change in Affect and Needs Satisfaction for Amotivated Students within the Sport Education Model

    ERIC Educational Resources Information Center

    Perlman, Dana

    2010-01-01

    The purpose of this study is to examine the influence of the Sport Education Model ("SEM") on amotivated students affect and needs satisfaction. 78 amotivated students from an original pool of 1,176 students enrolled in one of 32 physical education classes. Classes were randomly assigned to either the "SEM" (N = 16)or traditional class (N = 16).…

  17. Randomized Phase II Trial of High-Dose Melatonin and Radiation Therapy for RPA Class 2 Patients With Brain Metastases (RTOG 0119)

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

    Berk, Lawrence; Berkey, Brian; Rich, Tyvin

    Purpose: To determine if high-dose melatonin for Radiation Therapy Oncology Group (RTOG) recursive partitioning analysis (RPA) Class 2 patients with brain metastases improved survival over historical controls, and to determine if the time of day melatonin was given affected its toxicity or efficacy. RTOG 0119 was a phase II randomized trial for this group of patients. Methods and Materials: RTOG RPA Class 2 patients with brain metastases were randomized to 20 mg of melatonin, given either in the morning (8-9 AM) or in the evening (8-9 PM). All patients received radiation therapy (30 Gy in 10 fractions) in the afternoon.more » Melatonin was continued until neurologic deterioration or death. The primary endpoint was overall survival time. Neurologic deterioration, as reflected by the Mini-Mental Status Examination, was also measured. Results: Neither of the randomized groups had survival distributions that differed significantly from the historic controls of patients treated with whole-brain radiotherapy. The median survivals of the morning and evening melatonin treatments were 3.4 and 2.8 months, while the RTOG historical control survival was 4.1 months. Conclusions: High-dose melatonin did not show any beneficial effect in this group of patients.« less

  18. Interactive lesion segmentation on dynamic contrast enhanced breast MRI using a Markov model

    NASA Astrophysics Data System (ADS)

    Wu, Qiu; Salganicoff, Marcos; Krishnan, Arun; Fussell, Donald S.; Markey, Mia K.

    2006-03-01

    The purpose of this study is to develop a method for segmenting lesions on Dynamic Contrast-Enhanced (DCE) breast MRI. DCE breast MRI, in which the breast is imaged before, during, and after the administration of a contrast agent, enables a truly 3D examination of breast tissues. This functional angiogenic imaging technique provides noninvasive assessment of microcirculatory characteristics of tissues in addition to traditional anatomical structure information. Since morphological features and kinetic curves from segmented lesions are to be used for diagnosis and treatment decisions, lesion segmentation is a key pre-processing step for classification. In our study, the ROI is defined by a bounding box containing the enhancement region in the subtraction image, which is generated by subtracting the pre-contrast image from 1st post-contrast image. A maximum a posteriori (MAP) estimate of the class membership (lesion vs. non-lesion) for each voxel is obtained using the Iterative Conditional Mode (ICM) method. The prior distribution of the class membership is modeled as a multi-level logistic model, a Markov Random Field model in which the class membership of each voxel is assumed to depend upon its nearest neighbors only. The likelihood distribution is assumed to be Gaussian. The parameters of each Gaussian distribution are estimated from a dozen voxels manually selected as representative of the class. The experimental segmentation results demonstrate anatomically plausible breast tissue segmentation and the predicted class membership of voxels from the interactive segmentation algorithm agrees with the manual classifications made by inspection of the kinetic enhancement curves. The proposed method is advantageous in that it is efficient, flexible, and robust.

  19. Sociodemographic variations in obesity among Ghanaian adults.

    PubMed

    Amoah, Albert G B

    2003-12-01

    To determine the sociodemographic associations of obesity in Ghana. A cross-sectional descriptive study was conducted on a sample of 6300 adults aged 25 years and over who were selected by random cluster sampling. Two urban (high-class and low-class suburbs) and a rural community in Accra, Ghana. In total, 4731 (1857 males, 2874 females) subjects participated. Demographic data were obtained by a questionnaire and height and weight were determined with subjects in light clothing and without shoes. The overall crude prevalence of overweight and obesity was 23.4 and 14.1%, respectively. The rates of overweight (27.1 vs. 17.5%) and obesity (20.2 vs. 4.6%) were higher in females than males. Obesity increased with age up to 64 years. There were more overweight and obesity in the urban high-class residents compared with the low-class residents and in urban than rural subjects. Overweight and obesity were highest among the Akan and Ga tribes and relatively low among Ewes. Subjects with tertiary education had the highest prevalence of obesity (18.8%) compared with less literate and illiterate subjects (12.5-13.8%). Subjects whose jobs were of a sedentary nature had higher levels of obesity (15%) than subjects whose jobs involved heavy physical activity (10%). Subjects who did not engage in leisure-time physical activity were more obese than those who had three or more sessions of leisure-time physical activity per week (15.3 vs. 13.5%). Overweight and obesity are common among residents in the Accra area. Older age, female gender, urban, high-class residence, sedentary occupation and tertiary education were associated with higher levels of obesity. Policies and programmes that promote healthy lifestyles may prove beneficial.

  20. An AUC-based permutation variable importance measure for random forests

    PubMed Central

    2013-01-01

    Background The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. Results We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. Conclusions The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html. PMID:23560875

  1. An AUC-based permutation variable importance measure for random forests.

    PubMed

    Janitza, Silke; Strobl, Carolin; Boulesteix, Anne-Laure

    2013-04-05

    The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html.

  2. Discriminative least squares regression for multiclass classification and feature selection.

    PubMed

    Xiang, Shiming; Nie, Feiping; Meng, Gaofeng; Pan, Chunhong; Zhang, Changshui

    2012-11-01

    This paper presents a framework of discriminative least squares regression (LSR) for multiclass classification and feature selection. The core idea is to enlarge the distance between different classes under the conceptual framework of LSR. First, a technique called ε-dragging is introduced to force the regression targets of different classes moving along opposite directions such that the distances between classes can be enlarged. Then, the ε-draggings are integrated into the LSR model for multiclass classification. Our learning framework, referred to as discriminative LSR, has a compact model form, where there is no need to train two-class machines that are independent of each other. With its compact form, this model can be naturally extended for feature selection. This goal is achieved in terms of L2,1 norm of matrix, generating a sparse learning model for feature selection. The model for multiclass classification and its extension for feature selection are finally solved elegantly and efficiently. Experimental evaluation over a range of benchmark datasets indicates the validity of our method.

  3. Systematic, Evidence-Based Review of Exercise, Physical Activity, and Physical Fitness Effects on Cognition in Persons with Multiple Sclerosis.

    PubMed

    Sandroff, Brian M; Motl, Robert W; Scudder, Mark R; DeLuca, John

    2016-09-01

    Cognitive dysfunction is highly prevalent, disabling, and poorly-managed in persons with multiple sclerosis (MS). Recent evidence suggests that exercise might have beneficial effects on cognition in this population. The current systematic, evidence-based review examined the existing literature on exercise, physical activity, and physical fitness effects on cognition in MS to accurately describe the current status of the field, offer recommendations for clinicians, and identify study-specific and participant-specific characteristics for providing future direction for ongoing MS research. We performed an open-dated search of Medline, PsychInfo, and CINAHL in December 2015. The search strategy involved using the terms 'exercise' OR 'physical activity' OR 'physical fitness' OR 'aerobic' OR 'resistance' OR 'balance' OR 'walking' OR 'yoga' OR 'training' OR 'rehabilitation' AND 'multiple sclerosis'. Articles were eliminated from the systematic review if it was a review article, theoretical paper, or textbook chapter; did not involve persons with MS; involved only persons with pediatric-onset MS; did not involve neuropsychological outcomes; did not include empirical data to evaluate outcomes; involved pharmacological interventions; or was not available in English. The selected articles were first classified as examining exercise, physical activity, or physical fitness, and were then randomly assigned to 2 independent reviewers who rated each article for level of evidence based on American Academy of Neurology criteria. Reviewers further completed a table to characterize important elements of each study (i.e., intervention characteristics), the cognitive domain(s) that were targeted, participant-specific characteristics, outcome measures, and study results. The present review resulted in 26 studies on the effects of exercise, physical activity, and physical fitness on cognition in persons with MS. This included 1 Class I study, 3 Class II studies, 8 Class III studies, and 14 Class IV studies. Of the 26 total studies, 6 were randomized controlled trials. Overall, there is conflicting evidence for the effects of exercise on cognition in MS, and overall positive, but not definitive evidence for the effects of physical activity and physical fitness, respectively, on cognition in this population. Collectively, there is insufficient well-designed research to definitively conclude that exercise, physical activity, and physical fitness are effective for improving cognition in MS. This is based, in part, on methodological issues of Class I and II studies, such as inclusion of cognition as a secondary outcome (35 % of reviewed studies), poorly-developed exercise interventions, and paucity of research that included cognitively-impaired MS samples. However, promising evidence from Class III and Class IV studies may be useful for informing the development of better intervention research.

  4. Selection and Trans-Species Polymorphism of Major Histocompatibility Complex Class II Genes in the Order Crocodylia

    PubMed Central

    Jaratlerdsiri, Weerachai; Isberg, Sally R.; Higgins, Damien P.; Miles, Lee G.; Gongora, Jaime

    2014-01-01

    Major Histocompatibility Complex (MHC) class II genes encode for molecules that aid in the presentation of antigens to helper T cells. MHC characterisation within and between major vertebrate taxa has shed light on the evolutionary mechanisms shaping the diversity within this genomic region, though little characterisation has been performed within the Order Crocodylia. Here we investigate the extent and effect of selective pressures and trans-species polymorphism on MHC class II α and β evolution among 20 extant species of Crocodylia. Selection detection analyses showed that diversifying selection influenced MHC class II β diversity, whilst diversity within MHC class II α is the result of strong purifying selection. Comparison of translated sequences between species revealed the presence of twelve trans-species polymorphisms, some of which appear to be specific to the genera Crocodylus and Caiman. Phylogenetic reconstruction clustered MHC class II α sequences into two major clades representing the families Crocodilidae and Alligatoridae. However, no further subdivision within these clades was evident and, based on the observation that most MHC class II α sequences shared the same trans-species polymorphisms, it is possible that they correspond to the same gene lineage across species. In contrast, phylogenetic analyses of MHC class II β sequences showed a mixture of subclades containing sequences from Crocodilidae and/or Alligatoridae, illustrating orthologous relationships among those genes. Interestingly, two of the subclades containing sequences from both Crocodilidae and Alligatoridae shared specific trans-species polymorphisms, suggesting that they may belong to ancient lineages pre-dating the divergence of these two families from the common ancestor 85–90 million years ago. The results presented herein provide an immunogenetic resource that may be used to further assess MHC diversity and functionality in Crocodylia. PMID:24503938

  5. Balancing selection and genetic drift at major histocompatibility complex class II genes in isolated populations of golden snub-nosed monkey (Rhinopithecus roxellana)

    PubMed Central

    2012-01-01

    Background Small, isolated populations often experience loss of genetic variation due to random genetic drift. Unlike neutral or nearly neutral markers (such as mitochondrial genes or microsatellites), major histocompatibility complex (MHC) genes in these populations may retain high levels of polymorphism due to balancing selection. The relative roles of balancing selection and genetic drift in either small isolated or bottlenecked populations remain controversial. In this study, we examined the mechanisms maintaining polymorphisms of MHC genes in small isolated populations of the endangered golden snub-nosed monkey (Rhinopithecus roxellana) by comparing genetic variation found in MHC and microsatellite loci. There are few studies of this kind conducted on highly endangered primate species. Results Two MHC genes were sequenced and sixteen microsatellite loci were genotyped from samples representing three isolated populations. We isolated nine DQA1 alleles and sixteen DQB1 alleles and validated expression of the alleles. Lowest genetic variation for both MHC and microsatellites was found in the Shennongjia (SNJ) population. Historical balancing selection was revealed at both the DQA1 and DQB1 loci, as revealed by excess non-synonymous substitutions at antigen binding sites (ABS) and maximum-likelihood-based random-site models. Patterns of microsatellite variation revealed population structure. FST outlier analysis showed that population differentiation at the two MHC loci was similar to the microsatellite loci. Conclusions MHC genes and microsatellite loci showed the same allelic richness pattern with the lowest genetic variation occurring in SNJ, suggesting that genetic drift played a prominent role in these isolated populations. As MHC genes are subject to selective pressures, the maintenance of genetic variation is of particular interest in small, long-isolated populations. The results of this study may contribute to captive breeding and translocation programs for endangered species. PMID:23083308

  6. 20 CFR 404.1210 - Optionally excluded services.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... Section 404.1210 Employees' Benefits SOCIAL SECURITY ADMINISTRATION FEDERAL OLD-AGE, SURVIVORS AND... selectively by coverage groups. They are: (a) Services in any class or classes of elective positions; (b) Services in any class or classes of part-time positions; (c) Services in any class or classes of positions...

  7. A stratified two-stage sampling design for digital soil mapping in a Mediterranean basin

    NASA Astrophysics Data System (ADS)

    Blaschek, Michael; Duttmann, Rainer

    2015-04-01

    The quality of environmental modelling results often depends on reliable soil information. In order to obtain soil data in an efficient manner, several sampling strategies are at hand depending on the level of prior knowledge and the overall objective of the planned survey. This study focuses on the collection of soil samples considering available continuous secondary information in an undulating, 16 km²-sized river catchment near Ussana in southern Sardinia (Italy). A design-based, stratified, two-stage sampling design has been applied aiming at the spatial prediction of soil property values at individual locations. The stratification based on quantiles from density functions of two land-surface parameters - topographic wetness index and potential incoming solar radiation - derived from a digital elevation model. Combined with four main geological units, the applied procedure led to 30 different classes in the given test site. Up to six polygons of each available class were selected randomly excluding those areas smaller than 1ha to avoid incorrect location of the points in the field. Further exclusion rules were applied before polygon selection masking out roads and buildings using a 20m buffer. The selection procedure was repeated ten times and the set of polygons with the best geographical spread were chosen. Finally, exact point locations were selected randomly from inside the chosen polygon features. A second selection based on the same stratification and following the same methodology (selecting one polygon instead of six) was made in order to create an appropriate validation set. Supplementary samples were obtained during a second survey focusing on polygons that have either not been considered during the first phase at all or were not adequately represented with respect to feature size. In total, both field campaigns produced an interpolation set of 156 samples and a validation set of 41 points. The selection of sample point locations has been done using ESRI software (ArcGIS) extended by Hawth's Tools and later on its replacement the Geospatial Modelling Environment (GME). 88% of all desired points could actually be reached in the field and have been successfully sampled. Our results indicate that the sampled calibration and validation sets are representative for each other and could be successfully used as interpolation data for spatial prediction purposes. With respect to soil textural fractions, for instance, equal multivariate means and variance homogeneity were found for the two datasets as evidenced by significant (P > 0.05) Hotelling T²-test (2.3 with df1 = 3, df2 = 193) and Bartlett's test statistics (6.4 with df = 6). The multivariate prediction of clay, silt and sand content using a neural network residual cokriging approach reached an explained variance level of 56%, 47% and 63%. Thus, the presented case study is a successful example of considering readily available continuous information on soil forming factors such as geology and relief as stratifying variables for designing sampling schemes in digital soil mapping projects.

  8. Comparing spatial regression to random forests for large ...

    EPA Pesticide Factsheets

    Environmental data may be “large” due to number of records, number of covariates, or both. Random forests has a reputation for good predictive performance when using many covariates, whereas spatial regression, when using reduced rank methods, has a reputation for good predictive performance when using many records. In this study, we compare these two techniques using a data set containing the macroinvertebrate multimetric index (MMI) at 1859 stream sites with over 200 landscape covariates. Our primary goal is predicting MMI at over 1.1 million perennial stream reaches across the USA. For spatial regression modeling, we develop two new methods to accommodate large data: (1) a procedure that estimates optimal Box-Cox transformations to linearize covariate relationships; and (2) a computationally efficient covariate selection routine that takes into account spatial autocorrelation. We show that our new methods lead to cross-validated performance similar to random forests, but that there is an advantage for spatial regression when quantifying the uncertainty of the predictions. Simulations are used to clarify advantages for each method. This research investigates different approaches for modeling and mapping national stream condition. We use MMI data from the EPA's National Rivers and Streams Assessment and predictors from StreamCat (Hill et al., 2015). Previous studies have focused on modeling the MMI condition classes (i.e., good, fair, and po

  9. Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database.

    PubMed

    Dimitriadis, S I; Liparas, Dimitris; Tsolaki, Magda N

    2018-05-15

    In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the main scope being its use in daily practice. However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from a single modality, namely MRI. Based on preprocessed MRI images from the organizers of a neuroimaging challenge, 3 we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate among HC, MCI, cMCI and AD. We explored the efficacy of a novel scheme that includes multiple feature selections via Random Forest from subsets of the whole set of features (e.g. whole set, left/right hemisphere etc.), Random Forest classification using a fusion approach and ensemble classification via majority voting. From the ADNI database, 60 HC, 60 MCI, 60 cMCI and 60 CE were used as a training set with known labels. An extra dataset of 160 subjects (HC: 40, MCI: 40, cMCI: 40 and AD: 40) was used as an external blind validation dataset to evaluate the proposed machine learning scheme. In the second blind dataset, we succeeded in a four-class classification of 61.9% by combining MRI-based features with a Random Forest-based Ensemble Strategy. We achieved the best classification accuracy of all teams that participated in this neuroimaging competition. The results demonstrate the effectiveness of the proposed scheme to simultaneously discriminate among four groups using morphological MRI features for the very first time in the literature. Hence, the proposed machine learning scheme can be used to define single and multi-modal biomarkers for AD. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Types, frequencies, and burden of nonspecific adverse events of drugs: analysis of randomized placebo-controlled clinical trials.

    PubMed

    Mahr, Alfred; Golmard, Clara; Pham, Emilie; Iordache, Laura; Deville, Laure; Faure, Pierre

    2017-07-01

    Scarce studies analyzing adverse event (AE) data from randomized placebo-controlled clinical trials (RPCCTs) of selected illnesses suggested that a substantial proportion of collected AEs are unrelated to the drug taken. This study analyzed the nonspecific AEs occurring with active-drug exposure in RPCCTs for a large range of medical conditions. Randomized placebo-controlled clinical trials published in five prominent medical journals during 2006-2012 were searched. Only trials that evaluated orally or parenterally administered active drugs versus placebo in a head-to-head setting were selected. For AEs reported from ≥10 RPCCTs, Pearson's correlation coefficients (r) were calculated to determine the relationship between AE rates in placebo and active-drug recipients. Random-effects meta-analyses were used to compute proportions of nonspecific AEs, which were truncated at a maximum of 100%, in active-drug recipients. We included 231 trials addressing various medical domains or healthy participants. For the 88 analyzed AE variables, AE rates for placebo and active-drug recipients were in general strongly correlated (r > 0.50) or very strongly correlated (r > 0.80). The pooled proportions of nonspecific AEs for the active-drug recipients were 96.8% (95%CI: 95.5-98.1) for any AEs, 100% (97.9-100) for serious AEs, and 77.7% (72.7-83.2) for drug-related AEs. Results were similar for individual medical domains and healthy participants. The pooled proportion of nonspecificity of 82 system organ class and individual AE types ranged from 38% to 100%. The large proportion of nonspecific AEs reported in active-drug recipients of RPCCTs, including serious and drug-related AEs, highlights the limitations of clinical trial data to determine the tolerability of drugs. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  11. Fingerprinting of HLA class I genes for improved selection of unrelated bone marrow donors.

    PubMed

    Martinelli, G; Farabegoli, P; Buzzi, M; Panzica, G; Zaccaria, A; Bandini, G; Calori, E; Testoni, N; Rosti, G; Conte, R; Remiddi, C; Salvucci, M; De Vivo, A; Tura, S

    1996-02-01

    The degree of matching of HLA genes between the selected donor and recipient is an important aspect of the selection of unrelated donors for allogeneic bone marrow transplantation (UBMT). The most sensitive methods currently used are serological typing of HLA class I genes, mixed lymphocyte culture (MLC), IEF and molecular genotyping of HLA class II genes by direct sequencing of PCR products. Serological typing of class I antigenes (A, B and C) fails to detect minor differences demonstrated by direct sequencing of DNA polymorphic regions. Molecular genotyping of HLA class I genes by DNA analysis is costly and work-intensive. To improve compatibility between donor and recipient, we have set up a new rapid and non-radioisotopic application of the 'fingerprinting PCR' technique for the analysis of the polymorphic second exon of the HLA class I A, B and C genes. This technique is based on the formation of specific patterns (PCR fingerprints) of homoduplexes and heteroduplexes between heterologous amplified DNA sequences. After an electrophoretic run on non-denaturing polyacrylamide gel, different HLA class I types give allele-specific banding patterns. HLA class I matching is performed, after the gel has been soaked in ethidium bromide or silver-stained, by visual comparison of patients' fingerprints with those of donors. Identity can be confirmed by mixing donor and recipient DNAs in an amplification cross-match. To assess the technique, 10 normal samples, 22 related allogeneic bone marrow transplanted pairs and 10 unrelated HLA-A and HLA-B serologically matched patient-donor pairs were analysed for HLA class I polymorphic regions. In all the related pairs and in 1/10 unrelated pairs, matched donor-recipient patterns were identified. This new application of PCR fingerprinting may confirm the HLA class I serological selection of unrelated marrow donors.

  12. Uniform Recovery Bounds for Structured Random Matrices in Corrupted Compressed Sensing

    NASA Astrophysics Data System (ADS)

    Zhang, Peng; Gan, Lu; Ling, Cong; Sun, Sumei

    2018-04-01

    We study the problem of recovering an $s$-sparse signal $\\mathbf{x}^{\\star}\\in\\mathbb{C}^n$ from corrupted measurements $\\mathbf{y} = \\mathbf{A}\\mathbf{x}^{\\star}+\\mathbf{z}^{\\star}+\\mathbf{w}$, where $\\mathbf{z}^{\\star}\\in\\mathbb{C}^m$ is a $k$-sparse corruption vector whose nonzero entries may be arbitrarily large and $\\mathbf{w}\\in\\mathbb{C}^m$ is a dense noise with bounded energy. The aim is to exactly and stably recover the sparse signal with tractable optimization programs. In this paper, we prove the uniform recovery guarantee of this problem for two classes of structured sensing matrices. The first class can be expressed as the product of a unit-norm tight frame (UTF), a random diagonal matrix and a bounded columnwise orthonormal matrix (e.g., partial random circulant matrix). When the UTF is bounded (i.e. $\\mu(\\mathbf{U})\\sim1/\\sqrt{m}$), we prove that with high probability, one can recover an $s$-sparse signal exactly and stably by $l_1$ minimization programs even if the measurements are corrupted by a sparse vector, provided $m = \\mathcal{O}(s \\log^2 s \\log^2 n)$ and the sparsity level $k$ of the corruption is a constant fraction of the total number of measurements. The second class considers randomly sub-sampled orthogonal matrix (e.g., random Fourier matrix). We prove the uniform recovery guarantee provided that the corruption is sparse on certain sparsifying domain. Numerous simulation results are also presented to verify and complement the theoretical results.

  13. Strategic Resource Use for Learning: A Self-Administered Intervention That Guides Self-Reflection on Effective Resource Use Enhances Academic Performance.

    PubMed

    Chen, Patricia; Chavez, Omar; Ong, Desmond C; Gunderson, Brenda

    2017-06-01

    Many educational policies provide learners with more resources (e.g., new learning activities, study materials, or technologies), but less often do they address whether students are using these resources effectively. We hypothesized that making students more self-reflective about how they should approach their learning with the resources available to them would improve their class performance. We designed a novel Strategic Resource Use intervention that students could self-administer online and tested its effects in two cohorts of a college-level introductory statistics class. Before each exam, students randomly assigned to the treatment condition strategized about which academic resources they would use for studying, why each resource would be useful, and how they would use their resources. Students randomly assigned to the treatment condition reported being more self-reflective about their learning throughout the class, used their resources more effectively, and outperformed students in the control condition by an average of one third of a letter grade in the class.

  14. TNO/Centaurs grouping tested with asteroid data sets

    NASA Astrophysics Data System (ADS)

    Fulchignoni, M.; Birlan, M.; Barucci, M. A.

    2001-11-01

    Recently, we have discussed the possible subdivision in few groups of a sample of 22 TNO and Centaurs for which the BVRIJ photometry were available (Barucci et al., 2001, A&A, 371,1150). We obtained this results using the multivariate statistics adopted to define the current asteroid taxonomy, namely the Principal Components Analysis and the G-mode method (Tholen & Barucci, 1989, in ASTEROIDS II). How these methods work with a very small statistical sample as the TNO/Centaurs one? Theoretically, the number of degrees of freedom of the sample is correct. In fact it is 88 in our case and have to be larger then 50 to cope with the requirements of the G-mode. Does the random sampling of the small number of members of a large population contain enough information to reveal some structure in the population? We extracted several samples of 22 asteroids out of a data-base of 86 objects of known taxonomic type for which BVRIJ photometry is available from ECAS (Zellner et al. 1985, ICARUS 61, 355), SMASS II (S.W. Bus, 1999, PhD Thesis, MIT), and the Bell et al. Atlas of the asteroid infrared spectra. The objects constituting the first sample were selected in order to give a good representation of the major asteroid taxonomic classes (at least three samples each class): C,S,D,A, and G. Both methods were able to distinguish all these groups confirming the validity of the adopted methods. The S class is hard to individuate as a consequence of the choice of I and J variables, which imply a lack of information on the absorption band at 1 micron. The other samples were obtained by random choice of the objects. Not all the major groups were well represented (less than three samples per groups), but the general trend of the asteroid taxonomy has been always obtained. We conclude that the quoted grouping of TNO/Centaurs is representative of some physico-chemical structure of the outer solar system small body population.

  15. Application of random effects to the study of resource selection by animals

    USGS Publications Warehouse

    Gillies, C.S.; Hebblewhite, M.; Nielsen, S.E.; Krawchuk, M.A.; Aldridge, Cameron L.; Frair, J.L.; Saher, D.J.; Stevens, C.E.; Jerde, C.L.

    2006-01-01

    1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence.2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability.3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed.4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects.5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection.6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

  16. Application of random effects to the study of resource selection by animals.

    PubMed

    Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

    2006-07-01

    1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

  17. FAST TRACK COMMUNICATION: Freezing and extreme-value statistics in a random energy model with logarithmically correlated potential

    NASA Astrophysics Data System (ADS)

    Fyodorov, Yan V.; Bouchaud, Jean-Philippe

    2008-09-01

    We investigate some implications of the freezing scenario proposed by Carpentier and Le Doussal (CLD) for a random energy model (REM) with logarithmically correlated random potential. We introduce a particular (circular) variant of the model, and show that the integer moments of the partition function in the high-temperature phase are given by the well-known Dyson Coulomb gas integrals. The CLD freezing scenario allows one to use those moments for extracting the distribution of the free energy in both high- and low-temperature phases. In particular, it yields the full distribution of the minimal value in the potential sequence. This provides an explicit new class of extreme-value statistics for strongly correlated variables, manifestly different from the standard Gumbel class.

  18. Evolution by selection, recombination, and gene duplication in MHC class I genes of two Rhacophoridae species

    PubMed Central

    2013-01-01

    Background Comparison of major histocompatibility complex (MHC) genes across vertebrate species can reveal molecular mechanisms underlying the evolution of adaptive immunity-related proteins. As the first terrestrial tetrapods, amphibians deserve special attention because of their exposure to probably increased spectrum of microorganisms compared with ancestral aquatic fishes. Knowledge regarding the evolutionary patterns and mechanisms associated with amphibian MHC genes remains limited. The goal of the present study was to isolate MHC class I genes from two Rhacophoridae species (Rhacophorus omeimontis and Polypedates megacephalus) and examine their evolution. Results We identified 27 MHC class I alleles spanning the region from exon 2 to 4 in 38 tree frogs. The available evidence suggests that these 27 sequences all belong to classical MHC class I (MHC Ia) genes. Although several anuran species only display one MHC class Ia locus, at least two or three loci were observed in P. megacephalus and R. omeimontis, indicating that the number of MHC class Ia loci varies among anuran species. Recombination events, which mainly involve the entire exons, played an important role in shaping the genetic diversity of the 27 MHC class Ia alleles. In addition, signals of positive selection were found in Rhacophoridae MHC class Ia genes. Amino acid sites strongly suggested by program to be under positive selection basically accorded with the putative antigen binding sites deduced from crystal structure of human HLA. Phylogenetic relationships among MHC class I alleles revealed the presence of trans-species polymorphisms. Conclusions In the two Rhacophoridae species (1) there are two or three MHC class Ia loci; (2) recombination mainly occurs between the entire exons of MHC class Ia genes; (3) balancing selection, gene duplication and recombination all contribute to the diversity of MHC class Ia genes. These findings broaden our knowledge on the evolution of amphibian MHC systems. PMID:23734729

  19. Combined impact of negative lifestyle factors on cardiovascular risk in children: a randomized prospective study.

    PubMed

    Meyer, Ursina; Schindler, Christian; Bloesch, Tamara; Schmocker, Eliane; Zahner, Lukas; Puder, Jardena J; Kriemler, Susi

    2014-12-01

    Negative lifestyle factors are known to be associated with increased cardiovascular risk (CVR) in children, but research on their combined impact on a general population of children is sparse. Therefore, we aimed to quantify the combined impact of easily assessable negative lifestyle factors on the CVR scores of randomly selected children after 4 years. Of the 540 randomly selected 6- to 13-year-old children, 502 children participated in a baseline health assessment, and 64% were assessed again after 4 years. Measures included anthropometry, fasting blood samples, and a health assessment questionnaire. Participants scored one point for each negative lifestyle factor at baseline: overweight; physical inactivity; high media consumption; little outdoor time; skipping breakfast; and having a parent who has ever smoked, is inactive, or overweight. A CVR score at follow-up was constructed by averaging sex- and age-related z-scores of waist circumference, blood pressure, glucose, inverted high-density lipoprotein, and triglycerides. The age-, sex-, pubertal stage-, and social class-adjusted probabilities (95% confidence interval) for being in the highest CVR score tertile at follow-up for children who had at most one (n = 48), two (n = 64), three (n = 56), four (n = 41), or five or more (n = 14) risky lifestyle factors were 15.4% (8.9-25.3), 24.3% (17.4-32.8), 36.0% (28.6-44.2), 49.8% (38.6-61.0), and 63.5% (47.2-77.2), respectively. Even in childhood, an accumulation of negative lifestyle factors is associated with higher CVR scores after 4 years. These negative lifestyle factors are easy to assess in clinical practice and allow early detection and prevention of CVR in childhood. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  20. Peers and Academic Achievement: A Longitudinal Study on Selection and Socialization Effects of In-Class Friends

    ERIC Educational Resources Information Center

    Fortuin, Janna; van Geel, Mitch; Vedder, Paul

    2016-01-01

    The present study was conducted to analyze whether in-class friends influence each other's grades, and whether adolescents tend to select friends that are similar to them in terms of academic achievement. During 1 academic year, 542 eighth-grade students (M age = 13.3 years) reported on 3 different occasions on their in-class friendship networks.…

  1. The effect of class size in grades K-3 on adult earnings, employment, and disability status: evidence from a multi-center randomized controlled trial.

    PubMed

    Wilde, Elizabeth Ty; Finn, Jeremy; Johnson, Gretchen; Muennig, Peter

    2011-11-01

    Early education interventions have been forwarded as a means for reducing social disparities in income and health in adulthood. We explore whether a successful early education intervention, which occurred between 1985 and 1989, improved the employment rates, earnings and health of blacks relative to whites through 2008. We used data from Project STAR (Student Teacher Achievement Ratio), a four-year multi-center randomized controlled trial of reduced class sizes in Tennessee involving 11,601 students. Students were initially randomized within 79 schools to classes with 22-25 or 13-17 students. We linked subject records to Social Security Administration (SSA) earnings and disability data collected between 1997 and 2008-when the majority of subjects were between the ages of 18 and 28. We focused our analysis on annual, rather than cumulative, measures of earnings and employment because educational attainment after high school might reduce earnings through age 23. We considered three or more years of statistically significant positive (or negative) annual impacts to be a meaningful effect. Project STAR improved cognition and high school graduation rates. These benefits were primarily realized among low-income and minority students. These early education benefits did not translate into reduced disability claims in adulthood for treated subjects. However, exposure to small class size increased employment for blacks, and increased earnings for black males (p<0.05). Exposure to small classes also led to an increase in earnings for white males. However, white females exposed to small classes experienced a net decline in earnings and employment across the later years of follow up (p<0.05), offsetting any gains by white males. Exposure to small class size in grades K-3 appears to improve earnings and employment for black males and earnings for white males, while reducing employment and earnings among white females.

  2. Game-Based Learning as a Vehicle to Teach First Aid Content: A Randomized Experiment

    ERIC Educational Resources Information Center

    Charlier, Nathalie; De Fraine, Bieke

    2013-01-01

    Background: Knowledge of first aid (FA), which constitutes lifesaving treatments for injuries or illnesses, is important for every individual. In this study, we have set up a group-randomized controlled trial to assess the effectiveness of a board game for learning FA. Methods: Four class groups (120 students) were randomly assigned to 2…

  3. Rational Design Synthesis and Evaluation of New Selective Inhibitors of Microbial Class II (Zinc Dependent) Fructose Bis-phosphate Aldolases

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

    R Daher; M Coincon; M Fonvielle

    2011-12-31

    We report the synthesis and biochemical evaluation of several selective inhibitors of class II (zinc dependent) fructose bis-phosphate aldolases (Fba). The products were designed as transition-state analogues of the catalyzed reaction, structurally related to the substrate fructose bis-phosphate (or sedoheptulose bis-phosphate) and based on an N-substituted hydroxamic acid, as a chelator of the zinc ion present in active site. The compounds synthesized were tested on class II Fbas from various pathogenic microorganisms and, by comparison, on a mammalian class I Fba. The best inhibitor shows Ki against class II Fbas from various pathogens in the nM range, with very highmore » selectivity (up to 105). Structural analyses of inhibitors in complex with aldolases rationalize and corroborate the enzymatic kinetics results. These inhibitors represent lead compounds for the preparation of new synthetic antibiotics, notably for tuberculosis prophylaxis.« less

  4. Comparisons of Selected Student and Teacher Variables in All-Girls and Coeducational Physical Education Environments

    ERIC Educational Resources Information Center

    Derry, Julie A.; Phillips, D. Allen

    2004-01-01

    The purpose of this study was to investigate selected student and teacher variables and compare the differences between these variables for female students and female teachers in coeducation and single-sex physical education classes. Eighteen female teachers and intact classes were selected; 9 teachers from coeducation and 9 teachers from…

  5. Gaia eclipsing binary and multiple systems. Supervised classification and self-organizing maps

    NASA Astrophysics Data System (ADS)

    Süveges, M.; Barblan, F.; Lecoeur-Taïbi, I.; Prša, A.; Holl, B.; Eyer, L.; Kochoska, A.; Mowlavi, N.; Rimoldini, L.

    2017-07-01

    Context. Large surveys producing tera- and petabyte-scale databases require machine-learning and knowledge discovery methods to deal with the overwhelming quantity of data and the difficulties of extracting concise, meaningful information with reliable assessment of its uncertainty. This study investigates the potential of a few machine-learning methods for the automated analysis of eclipsing binaries in the data of such surveys. Aims: We aim to aid the extraction of samples of eclipsing binaries from such databases and to provide basic information about the objects. We intend to estimate class labels according to two different, well-known classification systems, one based on the light curve morphology (EA/EB/EW classes) and the other based on the physical characteristics of the binary system (system morphology classes; detached through overcontact systems). Furthermore, we explore low-dimensional surfaces along which the light curves of eclipsing binaries are concentrated, and consider their use in the characterization of the binary systems and in the exploration of biases of the full unknown Gaia data with respect to the training sets. Methods: We have explored the performance of principal component analysis (PCA), linear discriminant analysis (LDA), Random Forest classification and self-organizing maps (SOM) for the above aims. We pre-processed the photometric time series by combining a double Gaussian profile fit and a constrained smoothing spline, in order to de-noise and interpolate the observed light curves. We achieved further denoising, and selected the most important variability elements from the light curves using PCA. Supervised classification was performed using Random Forest and LDA based on the PC decomposition, while SOM gives a continuous 2-dimensional manifold of the light curves arranged by a few important features. We estimated the uncertainty of the supervised methods due to the specific finite training set using ensembles of models constructed on randomized training sets. Results: We obtain excellent results (about 5% global error rate) with classification into light curve morphology classes on the Hipparcos data. The classification into system morphology classes using the Catalog and Atlas of Eclipsing binaries (CALEB) has a higher error rate (about 10.5%), most importantly due to the (sometimes strong) similarity of the photometric light curves originating from physically different systems. When trained on CALEB and then applied to Kepler-detected eclipsing binaries subsampled according to Gaia observing times, LDA and SOM provide tractable, easy-to-visualize subspaces of the full (functional) space of light curves that summarize the most important phenomenological elements of the individual light curves. The sequence of light curves ordered by their first linear discriminant coefficient is compared to results obtained using local linear embedding. The SOM method proves able to find a 2-dimensional embedded surface in the space of the light curves which separates the system morphology classes in its different regions, and also identifies a few other phenomena, such as the asymmetry of the light curves due to spots, eccentric systems, and systems with a single eclipse. Furthermore, when data from other surveys are projected to the same SOM surface, the resulting map yields a good overview of the general biases and distortions due to differences in time sampling or population.

  6. A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.

    PubMed

    Fernández, Alberto; Carmona, Cristobal José; José Del Jesus, María; Herrera, Francisco

    2017-09-01

    Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.

  7. A randomized study of two methods of teaching perineal massage: effects on practice rates, episiotomy rates, and lacerations.

    PubMed

    Mynaugh, P A

    1991-09-01

    This study examined the effects of two methods of teaching perineal massage on the rates of practice of perineal massage, of episiotomy, and of lacerations in primiparas at birth. Couples in 20 randomly selected sections of four prenatal class series received routine printed and verbal instruction and a 12-minute video demonstration of perineal massage, or only the routine printed and verbal instruction. Women reported their practice rates in daily diary records, which were mailed to the researcher weekly. Hospital records provided delivery data. Of the 83 women, 23 (28%) practiced perineal massage: 16 (35.6%) in the experimental group, 7 (18.4%) controls. Even though the rate of practice almost doubled among experimental group women, the videotape instruction method was statistically nonsignificant. Episiotomy and laceration rates were not affected by teaching method. More severe lacerations occurred among the experimental group; however, the control group had almost four times as many severe (21%) as minor (5.3%) lacerations. The experimental group had twice as many severe (28.9%) as minor (13.3%) lacerations. These results were also nonsignificant.

  8. Comparison of in vivo 3D cone-beam computed tomography tooth volume measurement protocols.

    PubMed

    Forst, Darren; Nijjar, Simrit; Flores-Mir, Carlos; Carey, Jason; Secanell, Marc; Lagravere, Manuel

    2014-12-23

    The objective of this study is to analyze a set of previously developed and proposed image segmentation protocols for precision in both intra- and inter-rater reliability for in vivo tooth volume measurements using cone-beam computed tomography (CBCT) images. Six 3D volume segmentation procedures were proposed and tested for intra- and inter-rater reliability to quantify maxillary first molar volumes. Ten randomly selected maxillary first molars were measured in vivo in random order three times with 10 days separation between measurements. Intra- and inter-rater agreement for all segmentation procedures was attained using intra-class correlation coefficient (ICC). The highest precision was for automated thresholding with manual refinements. A tooth volume measurement protocol for CBCT images employing automated segmentation with manual human refinement on a 2D slice-by-slice basis in all three planes of space possessed excellent intra- and inter-rater reliability. Three-dimensional volume measurements of the entire tooth structure are more precise than 3D volume measurements of only the dental roots apical to the cemento-enamel junction (CEJ).

  9. Neonatal Seizure Detection Using Deep Convolutional Neural Networks.

    PubMed

    Ansari, Amir H; Cherian, Perumpillichira J; Caicedo, Alexander; Naulaers, Gunnar; De Vos, Maarten; Van Huffel, Sabine

    2018-04-02

    Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not be optimal. The main goal of the present paper is using deep convolutional neural networks (CNNs) and random forest to automatically optimize feature selection and classification. The input of the proposed classifier is raw multi-channel EEG and the output is the class label: seizure/nonseizure. By training this network, the required features are optimized, while fitting a nonlinear classifier on the features. After training the network with EEG recordings of 26 neonates, five end layers performing the classification were replaced with a random forest classifier in order to improve the performance. This resulted in a false alarm rate of 0.9 per hour and seizure detection rate of 77% using a test set of EEG recordings of 22 neonates that also included dubious seizures. The newly proposed CNN classifier outperformed three data-driven feature-based approaches and performed similar to a previously developed heuristic method.

  10. Amino acid sequence requirements at residues 69 and 238 for the SME-1 beta-lactamase to confer resistance to beta-lactam antibiotics.

    PubMed

    Majiduddin, Fahd K; Palzkill, Timothy

    2003-03-01

    Carbapenem antibiotics have been used to counteract resistant strains of bacteria harboring beta-lactamases and extended-spectrum beta-lactamases. Four enzymes from the class A group of beta-lactamases, NMC-A, IMI-1, SME-1, and KPC-1, efficiently hydrolyze carbapenem antibiotics. Sequence comparisons and structural information indicate that cysteines at amino acid residues 69 and 238, which are conserved in all four of these enzymes, form a disulfide bond that is unique to these beta-lactamases. To test whether this disulfide bond is required for catalytic activity, the codons for residues Cys69 and Cys238 were randomized individually and simultaneously by PCR-based mutagenesis to create random replacement libraries for these positions. Mutants that were able to confer resistance to ampicillin, imipenem, or cefotaxime were selected from these libraries. The results indicate that positions Cys69 and Cys238 are critical for hydrolysis of all of the antibiotics tested, suggesting that the disulfide bond is generally required for this enzyme to catalyze the hydrolysis of beta-lactam antibiotics.

  11. Amino Acid Sequence Requirements at Residues 69 and 238 for the SME-1 β-Lactamase To Confer Resistance to β-Lactam Antibiotics

    PubMed Central

    Majiduddin, Fahd K.; Palzkill, Timothy

    2003-01-01

    Carbapenem antibiotics have been used to counteract resistant strains of bacteria harboring β-lactamases and extended-spectrum β-lactamases. Four enzymes from the class A group of β-lactamases, NMC-A, IMI-1, SME-1, and KPC-1, efficiently hydrolyze carbapenem antibiotics. Sequence comparisons and structural information indicate that cysteines at amino acid residues 69 and 238, which are conserved in all four of these enzymes, form a disulfide bond that is unique to these β-lactamases. To test whether this disulfide bond is required for catalytic activity, the codons for residues Cys69 and Cys238 were randomized individually and simultaneously by PCR-based mutagenesis to create random replacement libraries for these positions. Mutants that were able to confer resistance to ampicillin, imipenem, or cefotaxime were selected from these libraries. The results indicate that positions Cys69 and Cys238 are critical for hydrolysis of all of the antibiotics tested, suggesting that the disulfide bond is generally required for this enzyme to catalyze the hydrolysis of β-lactam antibiotics. PMID:12604542

  12. The Effect of Fermi Questions in the Development of Science Processes Skills in Physics among Jordanian Ninth Graders

    ERIC Educational Resources Information Center

    Barahmeh, Haytham Mousa; Hamad, Adwan Mohammad Bani; Barahmeh, Nabeel Mousa

    2017-01-01

    This study aimed at exploring the effect of Fermi question on the development of science process skills in the physics subject at ninth Grade students. The sample of the study consisted of (2) classes for males and (2) classes for females, which were randomly divided into (2) groups: An experimental group of (41) students divided into a class of…

  13. The Effects of Cardio-Syntactic Analysis Instruction on Writing Scores in a 11th Grade High School Classroom

    ERIC Educational Resources Information Center

    Kariuki, Patrick N.; Blair, Paul W.

    2015-01-01

    The purpose of this research was to determine the effects of Cardio-Syntactic Analysis instruction on writing scores in an 11th grade English class. The sample consisted of 35 students enrolled in an Honor's English 11 class at Volunteer high School, in Church Hill, TN. The class was randomly assigned into an experimental group of 17 students and…

  14. Do Science and Technology Teachers and Pre-Service Primary Teachers Have Different Thoughts about Concept Maps in Science and Technology Lessons?

    ERIC Educational Resources Information Center

    Karakuyu, Yunus

    2011-01-01

    The purpose of this study is to determine the thoughts of primary science and technology teachers, primary class teachers, pre-service primary class teachers and pre-service primary science and technology teachers' about concept maps. This scale applied the use of basic and random method on the chosen 125 4th and 5th grade primary class teachers…

  15. ANALYSIS OF SELECTED CHEMICAL GROUPS BY LIQUID CHROMATOGRAPHY/MASS SPECTROMETRY

    EPA Science Inventory

    The use of the moving-belt liquid chromatographic interface in combination with mass spectrometry was evaluated for determining detection limits of selected members of various chemical classes. mong the chemical classes examined were benzidines, nitrosoamines, anilines, nitroarom...

  16. Gum chewing affects academic performance in adolescents

    USDA-ARS?s Scientific Manuscript database

    Chewing gum may have an impact on improved memory during specific tasks of recognition and sustained attention. Research objective was to determine the effect of gum chewing on standardized test scores and math class grades of eighth grade students. Four math classes, 108 students, were randomized i...

  17. A Feature and Algorithm Selection Method for Improving the Prediction of Protein Structural Class.

    PubMed

    Ni, Qianwu; Chen, Lei

    2017-01-01

    Correct prediction of protein structural class is beneficial to investigation on protein functions, regulations and interactions. In recent years, several computational methods have been proposed in this regard. However, based on various features, it is still a great challenge to select proper classification algorithm and extract essential features to participate in classification. In this study, a feature and algorithm selection method was presented for improving the accuracy of protein structural class prediction. The amino acid compositions and physiochemical features were adopted to represent features and thirty-eight machine learning algorithms collected in Weka were employed. All features were first analyzed by a feature selection method, minimum redundancy maximum relevance (mRMR), producing a feature list. Then, several feature sets were constructed by adding features in the list one by one. For each feature set, thirtyeight algorithms were executed on a dataset, in which proteins were represented by features in the set. The predicted classes yielded by these algorithms and true class of each protein were collected to construct a dataset, which were analyzed by mRMR method, yielding an algorithm list. From the algorithm list, the algorithm was taken one by one to build an ensemble prediction model. Finally, we selected the ensemble prediction model with the best performance as the optimal ensemble prediction model. Experimental results indicate that the constructed model is much superior to models using single algorithm and other models that only adopt feature selection procedure or algorithm selection procedure. The feature selection procedure or algorithm selection procedure are really helpful for building an ensemble prediction model that can yield a better performance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. Are schoolteachers able to teach first aid to children younger than 6 years? A comparative study

    PubMed Central

    Ammirati, Christine; Gagnayre, Rémi; Amsallem, Carole; Némitz, Bernard; Gignon, Maxime

    2014-01-01

    Objectives This study was designed to assess the knowledge acquired by very young children (<6 years) trained by their own teachers at nursery school. This comparative study assessed the effect of training before the age of 6 years compared with a group of age-matched untrained children. Setting Some schoolteachers were trained by emergency medical teams to perform basic first aid. Participants Eighteen classes comprising 315 pupils were randomly selected: nine classes of trained pupils (cohort C1) and nine classes of untrained pupils (cohort C2). Primary and secondary outcome measures The test involved observing and describing three pictures and using the phone to call the medical emergency centre. Assessment of each child was based on nine criteria, and was performed by the teacher 2 months after completion of first aid training. Results This study concerned 285 pupils: 140 trained and 145 untrained. The majority of trained pupils gave the expected answers for all criteria and reacted appropriately by assessing the situation and alerting emergency services (55.7−89.3% according to the questions). Comparison of the two groups revealed a significantly greater ability of trained pupils to describe an emergency situation (p<0.005) and raise the alert (p<0.0001). Conclusions This study shows the ability of very young children to assimilate basic skills as taught by their own schoolteachers. PMID:25239292

  19. Effect of three surface sealants on marginal sealing of Class V composite resin restorations.

    PubMed

    Ramos, R P; Chimello, D T; Chinelatti, M A; Dibb, R G; Mondelli, J

    2000-01-01

    This study evaluated in vitro the effectiveness of three different surface sealants (Fortify, Protect-it! and Optiguard) on the marginal sealing of Class V light-activated composite resin restorations (Prodigy). For this purpose, 20 sound noncarious human premolars extracted within a six-month period were selected. Class V cavities with the occlusal margin in enamel and cervical margin in cementum were prepared in both buccal and lingual surfaces. The teeth, randomly assigned in four groups with 10 cavities in each group, were restored with composite resin after applying an adhesive system (Optibond FL). After the finishing and polishing procedures, the restorations were covered with a specific surface sealant, except for the control samples, which were not sealed. After placing restorations, the specimens were thermocycled and immersed in a 50% silver nitrate solution (tracer agent) for eight hours, sectioned longitudinally and analyzed for leakage using an optical microscope in a blind study with three examiners. The marginal microleakage was evaluated at the occlusal and cervical interfaces and compared among the four groups using the Kruskall-Wallis and the Wilcoxon Tests. There was better sealing at the occlusal margin, and in this region, there were no statistically significant differences among the materials (p > 0.05). In the cervical region, Fortify and Protect-it! showed improved results over the Control Group, and Optiguard showed similar results to the Control Group (without sealing).

  20. [Spatial variation of soil properties and quality evaluation for arable Ustic Cambosols in central Henan Province].

    PubMed

    Zhang, Xue-Lei; Feng, Wan-Wan; Zhong, Guo-Min

    2011-01-01

    A GIS-based 500 m x 500 m soil sampling point arrangement was set on 248 points at Wenshu Town of Yuzhou County in central Henan Province, where the typical Ustic Cambosols locates. By using soil digital data, the spatial database was established, from which, all the needed latitude and longitude data of the sampling points were produced for the field GPS guide. Soil samples (0-20 cm) were collected from 202 points, of which, bulk density measurement were conducted for randomly selected 34 points, and the ten soil property items used as the factors for soil quality assessment, including organic matter, available K, available P, pH, total N, total P, soil texture, cation exchange capacity (CEC), slowly available K, and bulk density, were analyzed for the other points. The soil property items were checked by statistic tools, and then, classified with standard criteria at home and abroad. The factor weight was given by analytic hierarchy process (AHP) method, and the spatial variation of the major 10 soil properties as well as the soil quality classes and their occupied areas were worked out by Kriging interpolation maps. The results showed that the arable Ustic Cambosols in study area was of good quality soil, over 95% of which ranked in good and medium classes and only less than 5% were in poor class.

  1. Best antihypertensive strategies to improve blood pressure control in Latin America: position of the Latin American Society of Hypertension.

    PubMed

    Coca, Antonio; López-Jaramillo, Patricio; Thomopoulos, Costas; Zanchetti, Alberto

    2018-02-01

    : Evidence from randomized trials has shown that effective treatment with blood pressure (BP)-lowering medications reduces the risk of cardiovascular morbidity and mortality in patients with hypertension. Therefore, hypertension control and prevention of subsequent morbidity and mortality should be achievable for all patients worldwide. However, many people in Latin America remain undiagnosed, untreated or have inadequately controlled BP, even where this is access to health systems. Barriers to hypertension control in low-income countries include difficulties in transportation to health services; inappropriate opening hours; difficulties in making clinic appointments; inaccessible healthcare facilities, lack of insurance and high treatment costs. After a review of the best recent available evidence on the efficacy and tolerability of antihypertensive drugs and strategies, the Latin American Society of Hypertension experts conclude that all major classes of BP-lowering drugs be available to hypertensive patients, because all have been shown to reduce major cardiovascular outcomes compared with placebo, and have shown to be associated with a comparable risk of major cardiovascular events and mortality when compared between classes. Within each class, no evidence whatsoever is available to show that one compound is more effective than another in outcome prevention. Therefore, the selection of individual drugs may be based mainly on the capacity of Latin American governments to obtain the lowest prices of the different molecules manufactured by companies with high production quality standards.

  2. Object-based random forest classification of Landsat ETM+ and WorldView-2 satellite imagery for mapping lowland native grassland communities in Tasmania, Australia

    NASA Astrophysics Data System (ADS)

    Melville, Bethany; Lucieer, Arko; Aryal, Jagannath

    2018-04-01

    This paper presents a random forest classification approach for identifying and mapping three types of lowland native grassland communities found in the Tasmanian Midlands region. Due to the high conservation priority assigned to these communities, there has been an increasing need to identify appropriate datasets that can be used to derive accurate and frequently updateable maps of community extent. Therefore, this paper proposes a method employing repeat classification and statistical significance testing as a means of identifying the most appropriate dataset for mapping these communities. Two datasets were acquired and analysed; a Landsat ETM+ scene, and a WorldView-2 scene, both from 2010. Training and validation data were randomly subset using a k-fold (k = 50) approach from a pre-existing field dataset. Poa labillardierei, Themeda triandra and lowland native grassland complex communities were identified in addition to dry woodland and agriculture. For each subset of randomly allocated points, a random forest model was trained based on each dataset, and then used to classify the corresponding imagery. Validation was performed using the reciprocal points from the independent subset that had not been used to train the model. Final training and classification accuracies were reported as per class means for each satellite dataset. Analysis of Variance (ANOVA) was undertaken to determine whether classification accuracy differed between the two datasets, as well as between classifications. Results showed mean class accuracies between 54% and 87%. Class accuracy only differed significantly between datasets for the dry woodland and Themeda grassland classes, with the WorldView-2 dataset showing higher mean classification accuracies. The results of this study indicate that remote sensing is a viable method for the identification of lowland native grassland communities in the Tasmanian Midlands, and that repeat classification and statistical significant testing can be used to identify optimal datasets for vegetation community mapping.

  3. A Perron-Frobenius type of theorem for quantum operations

    NASA Astrophysics Data System (ADS)

    Lagro, Matthew

    Quantum random walks are a generalization of classical Markovian random walks to a quantum mechanical or quantum computing setting. Quantum walks have promising applications but are complicated by quantum decoherence. We prove that the long-time limiting behavior of the class of quantum operations which are the convex combination of norm one operators is governed by the eigenvectors with norm one eigenvalues which are shared by the operators. This class includes all operations formed by a coherent operation with positive probability of orthogonal measurement at each step. We also prove that any operation that has range contained in a low enough dimension subspace of the space of density operators has limiting behavior isomorphic to an associated Markov chain. A particular class of such operations are coherent operations followed by an orthogonal measurement. Applications of the convergence theorems to quantum walks are given.

  4. Systematic Review for the 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.

    PubMed

    Reboussin, David M; Allen, Norrina B; Griswold, Michael E; Guallar, Eliseo; Hong, Yuling; Lackland, Daniel T; Miller, Edgar Pete R; Polonsky, Tamar; Thompson-Paul, Angela M; Vupputuri, Suma

    2018-06-01

    To review the literature systematically and perform meta-analyses to address these questions: 1) Is there evidence that self-measured blood pressure (BP) without other augmentation is superior to office-based measurement of BP for achieving better BP control or for preventing adverse clinical outcomes that are related to elevated BP? 2) What is the optimal target for BP lowering during antihypertensive therapy in adults? 3) In adults with hypertension, how do various antihypertensive drug classes differ in their benefits and harms compared with each other as first-line therapy? Electronic literature searches were performed by Doctor Evidence, a global medical evidence software and services company, across PubMed and EMBASE from 1966 to 2015 using key words and relevant subject headings for randomized controlled trials that met eligibility criteria defined for each question. We performed analyses using traditional frequentist statistical and Bayesian approaches, including random-effects Bayesian network meta-analyses. Our results suggest that: 1) There is a modest but significant improvement in systolic BP in randomized controlled trials of self-measured BP versus usual care at 6 but not 12 months, and for selected patients and their providers self-measured BP may be a helpful adjunct to routine office care. 2) systolic BP lowering to a target of <130 mm Hg may reduce the risk of several important outcomes including risk of myocardial infarction, stroke, heart failure, and major cardiovascular events. No class of medications (ie, angiotensin-converting enzyme inhibitors, angiotensin-receptor blockers, calcium channel blockers, or beta blockers) was significantly better than thiazides and thiazide-like diuretics as a first-line therapy for any outcome. © 2017 by the American College of Cardiology Foundation and the American Heart Association, Inc.

  5. Analysis of rice purchase decision on rice consumer in Bandung city

    NASA Astrophysics Data System (ADS)

    Kusno, K.; Imannurdin, A.; Syamsiyah, N.; Djuwendah, E.

    2018-03-01

    This study was conducted at three kinds of purchase location which were traditional market, rice kiosk, and supermarket in Bandung City, with survey data of 108 respondents which were selected by systematic random sampling. The aim of this study is to (1) identify consumer characteristics, (2) identify which atribute is considered by consumer in buying rice, and (3) analyze the relationship between purchase decision and income class. Data were analyzed by descriptive analysis and Chi Square test. The results showed most consumers in the traditional market were middle-educated and lower middle-income, at the rice kiosk, the consumer were generally middle-educated and middle-income, and in the supermarkets, the majority were high-educated and upper middle-income consumers. “Kepulenan” be the first priority of most consumers, but for the lower-middle class, the main priority was price. Thus, in case of scarcity and rice price increase, the government should immediately arrange market operations which targeting to lower-middle class consumers. There was a significant relationship between (1) the quality of rice consumed, (2) the frequency of rice purchase per month, and (3) attitudes toward rice price increase; each with the income class. Although the price of rice increase, consumers of middle and upper-middle were remain loyal to the quality of rice they consumed. This indicates rice market in Bandung city is an ideal market for premium rice so that traders and producers are expected to maintain the quality of rice, such as keep using superior seeds and applying good cultivation based on Good Agricultural Practice (GAP) rules.

  6. Two randomized trials provide no consistent evidence for nonmusical cognitive benefits of brief preschool music enrichment.

    PubMed

    Mehr, Samuel A; Schachner, Adena; Katz, Rachel C; Spelke, Elizabeth S

    2013-01-01

    Young children regularly engage in musical activities, but the effects of early music education on children's cognitive development are unknown. While some studies have found associations between musical training in childhood and later nonmusical cognitive outcomes, few randomized controlled trials (RCTs) have been employed to assess causal effects of music lessons on child cognition and no clear pattern of results has emerged. We conducted two RCTs with preschool children investigating the cognitive effects of a brief series of music classes, as compared to a similar but non-musical form of arts instruction (visual arts classes, Experiment 1) or to a no-treatment control (Experiment 2). Consistent with typical preschool arts enrichment programs, parents attended classes with their children, participating in a variety of developmentally appropriate arts activities. After six weeks of class, we assessed children's skills in four distinct cognitive areas in which older arts-trained students have been reported to excel: spatial-navigational reasoning, visual form analysis, numerical discrimination, and receptive vocabulary. We initially found that children from the music class showed greater spatial-navigational ability than did children from the visual arts class, while children from the visual arts class showed greater visual form analysis ability than children from the music class (Experiment 1). However, a partial replication attempt comparing music training to a no-treatment control failed to confirm these findings (Experiment 2), and the combined results of the two experiments were negative: overall, children provided with music classes performed no better than those with visual arts or no classes on any assessment. Our findings underscore the need for replication in RCTs, and suggest caution in interpreting the positive findings from past studies of cognitive effects of music instruction.

  7. Two Randomized Trials Provide No Consistent Evidence for Nonmusical Cognitive Benefits of Brief Preschool Music Enrichment

    PubMed Central

    Mehr, Samuel A.; Schachner, Adena; Katz, Rachel C.; Spelke, Elizabeth S.

    2013-01-01

    Young children regularly engage in musical activities, but the effects of early music education on children's cognitive development are unknown. While some studies have found associations between musical training in childhood and later nonmusical cognitive outcomes, few randomized controlled trials (RCTs) have been employed to assess causal effects of music lessons on child cognition and no clear pattern of results has emerged. We conducted two RCTs with preschool children investigating the cognitive effects of a brief series of music classes, as compared to a similar but non-musical form of arts instruction (visual arts classes, Experiment 1) or to a no-treatment control (Experiment 2). Consistent with typical preschool arts enrichment programs, parents attended classes with their children, participating in a variety of developmentally appropriate arts activities. After six weeks of class, we assessed children's skills in four distinct cognitive areas in which older arts-trained students have been reported to excel: spatial-navigational reasoning, visual form analysis, numerical discrimination, and receptive vocabulary. We initially found that children from the music class showed greater spatial-navigational ability than did children from the visual arts class, while children from the visual arts class showed greater visual form analysis ability than children from the music class (Experiment 1). However, a partial replication attempt comparing music training to a no-treatment control failed to confirm these findings (Experiment 2), and the combined results of the two experiments were negative: overall, children provided with music classes performed no better than those with visual arts or no classes on any assessment. Our findings underscore the need for replication in RCTs, and suggest caution in interpreting the positive findings from past studies of cognitive effects of music instruction. PMID:24349171

  8. Raloxifene for women with Alzheimer disease: A randomized controlled pilot trial.

    PubMed

    Henderson, Victor W; Ala, Tom; Sainani, Kristin L; Bernstein, Allan L; Stephenson, B Sue; Rosen, Allyson C; Farlow, Martin R

    2015-12-01

    To determine whether raloxifene, a selective estrogen receptor modulator, improves cognitive function compared with placebo in women with Alzheimer disease (AD) and to provide an estimate of cognitive effect. This pilot study was conducted as a randomized, double-blind, placebo-controlled trial, with a planned treatment of 12 months. Women with late-onset AD of mild to moderate severity were randomly allocated to high-dose (120 mg) oral raloxifene or identical placebo provided once daily. The primary outcome compared between treatment groups at 12 months was change in the Alzheimer's Disease Assessment Scale, cognitive subscale (ADAS-cog). Forty-two women randomized to raloxifene or placebo were included in intent-to-treat analyses (mean age 76 years, range 68-84), and 39 women contributed 12-month outcomes. ADAS-cog change scores at 12 months did not differ significantly between treatment groups (standardized difference 0.03, 95% confidence interval -0.39 to 0.44, 2-tailed p = 0.89). Raloxifene and placebo groups did not differ significantly on secondary analyses of dementia rating, activities of daily living, behavior, or a global cognition composite score. Caregiver burden and caregiver distress were similar in both groups. Results on the primary outcome showed no cognitive benefits in the raloxifene-treated group. This study provides Class I evidence that for women with AD, raloxifene does not have a significant cognitive effect. The study lacked the precision to exclude a small effect. © 2015 American Academy of Neurology.

  9. Object-Oriented Approach to Integrating Database Semantics. Volume 4.

    DTIC Science & Technology

    1987-12-01

    schemata for; 1. Object Classification Shema -- Entities 2. Object Structure and Relationship Schema -- Relations 3. Operation Classification and... relationships are represented in a database is non- intuitive for naive users. *It is difficult to access and combine information in multiple databases. In this...from the CURRENT-.CLASSES table. Choosing a selected item do-selects it. Choose 0 to exit. 1. STUDENTS 2. CUR~RENT-..CLASSES 3. MANAGMNT -.CLASS

  10. Endogenous Sensory Discrimination and Selection by a Fast Brain Switch for a High Transfer Rate Brain-Computer Interface.

    PubMed

    Xu, Ren; Jiang, Ning; Dosen, Strahinja; Lin, Chuang; Mrachacz-Kersting, Natalie; Dremstrup, Kim; Farina, Dario

    2016-08-01

    In this study, we present a novel multi-class brain-computer interface (BCI) for communication and control. In this system, the information processing is shared by the algorithm (computer) and the user (human). Specifically, an electro-tactile cycle was presented to the user, providing the choice (class) by delivering timely sensory input. The user discriminated these choices by his/her endogenous sensory ability and selected the desired choice with an intuitive motor task. This selection was detected by a fast brain switch based on real-time detection of movement-related cortical potentials from scalp EEG. We demonstrated the feasibility of such a system with a four-class BCI, yielding a true positive rate of  ∼ 80% and  ∼ 70%, and an information transfer rate of  ∼ 7 bits/min and  ∼ 5 bits/min, for the movement and imagination selection command, respectively. Furthermore, when the system was extended to eight classes, the throughput of the system was improved, demonstrating the capability of accommodating a large number of classes. Combining the endogenous sensory discrimination with the fast brain switch, the proposed system could be an effective, multi-class, gaze-independent BCI system for communication and control applications.

  11. Pharmacotherapy of Hypertension in Chronic Dialysis Patients

    PubMed Central

    Georgianos, Panagiotis I.

    2016-01-01

    Among patients on dialysis, hypertension is highly prevalent and contributes to the high burden of cardiovascular morbidity and mortality. Strict volume control via sodium restriction and probing of dry weight are first-line approaches for the treatment of hypertension in this population; however, antihypertensive drug therapy is often needed to control BP. Few trials compare head-to-head the superiority of one antihypertensive drug class over another with respect to improving BP control or altering cardiovascular outcomes; accordingly, selection of the appropriate antihypertensive regimen should be individualized. To individualize therapy, consideration should be given to intra- and interdialytic pharmacokinetics, effect on cardiovascular reflexes, ability to treat comorbid illnesses, and adverse effect profile. β-Blockers followed by dihydropyridine calcium-channel blockers are our first- and second-line choices for antihypertensive drug use. Angiotensin–converting enzyme inhibitors and angiotensin receptor blockers seem to be reasonable third–line choices, because the evidence base to support their use in patients on dialysis is sparse. Add-on therapy with mineralocorticoid receptor antagonists in specific subgroups of patients on dialysis (i.e., those with severe congestive heart failure) seems to be another promising option in anticipation of the ongoing trials evaluating their efficacy and safety. Adequately powered, multicenter, randomized trials evaluating hard cardiovascular end points are urgently warranted to elucidate the comparative effectiveness of antihypertensive drug classes in patients on dialysis. In this review, we provide an overview of the randomized evidence on pharmacotherapy of hypertension in patients on dialysis, and we conclude with suggestions for future research to address critical gaps in this important area. PMID:27797886

  12. What variables are important in predicting bovine viral diarrhea virus? A random forest approach.

    PubMed

    Machado, Gustavo; Mendoza, Mariana Recamonde; Corbellini, Luis Gustavo

    2015-07-24

    Bovine viral diarrhea virus (BVDV) causes one of the most economically important diseases in cattle, and the virus is found worldwide. A better understanding of the disease associated factors is a crucial step towards the definition of strategies for control and eradication. In this study we trained a random forest (RF) prediction model and performed variable importance analysis to identify factors associated with BVDV occurrence. In addition, we assessed the influence of features selection on RF performance and evaluated its predictive power relative to other popular classifiers and to logistic regression. We found that RF classification model resulted in an average error rate of 32.03% for the negative class (negative for BVDV) and 36.78% for the positive class (positive for BVDV).The RF model presented area under the ROC curve equal to 0.702. Variable importance analysis revealed that important predictors of BVDV occurrence were: a) who inseminates the animals, b) number of neighboring farms that have cattle and c) rectal palpation performed routinely. Our results suggest that the use of machine learning algorithms, especially RF, is a promising methodology for the analysis of cross-sectional studies, presenting a satisfactory predictive power and the ability to identify predictors that represent potential risk factors for BVDV investigation. We examined classical predictors and found some new and hard to control practices that may lead to the spread of this disease within and among farms, mainly regarding poor or neglected reproduction management, which should be considered for disease control and eradication.

  13. Protocol of GLUcose COntrol Safety and Efficacy in type 2 DIabetes, a NETwork meta-analysis: GLUCOSE DINET protocol-Rational and design.

    PubMed

    Grenet, Guillaume; Lajoinie, Audrey; Ribault, Shams; Nguyen, Gia Bao; Linet, Thomas; Metge, Augustin; Cornu, Catherine; Cucherat, Michel; Moulin, Philippe; Gueyffier, François

    2017-06-01

    The aim of this study was to propose a ranking of the currently available antidiabetic drugs, regarding vascular clinical outcomes, in patients with type 2 diabetes, through a network meta-analysis approach. Randomized clinical trials, regardless of the blinding design, testing contemporary antidiabetic drugs, and considering clinically relevant outcomes in patients with type 2 diabetes mellitus will be included. The primary outcomes of this analysis will be overall mortality, cardiovascular mortality, and major cardiovascular events. Diabetic microangiopathy will be a secondary outcome. Adverse events, hypoglycemia, weight evolution, bariatric surgery, and discontinuation of the treatment will also be recorded. Each drug will be analyzed according to its therapeutic class: biguanide, alpha-glucosidase inhibitors, sulfonylureas, glitazones, glinides, insulin, DPP-4 inhibitors, GLP-1 analogs, and gliflozins. The treatment effect of each drug class will be compared using pairwise meta-analysis and a Bayesian random model network meta-analysis. Sensitivity analyses will be conducted according to the quality of the studies and the glycemic control. The report will follow the PRISMA checklist for network meta-analysis. Results of the search strategy and of the study selection will be presented in a PRISMA compliant flowchart. The treatment effects will be summarized with odds ratio (OR) estimates and their 95% credible intervals. A ranking of the drugs will be proposed. Our network meta-analysis should allow a clinically relevant ranking of the contemporary antidiabetic drugs. © 2016 Société Française de Pharmacologie et de Thérapeutique.

  14. Texture analysis based on the Hermite transform for image classification and segmentation

    NASA Astrophysics Data System (ADS)

    Estudillo-Romero, Alfonso; Escalante-Ramirez, Boris; Savage-Carmona, Jesus

    2012-06-01

    Texture analysis has become an important task in image processing because it is used as a preprocessing stage in different research areas including medical image analysis, industrial inspection, segmentation of remote sensed imaginary, multimedia indexing and retrieval. In order to extract visual texture features a texture image analysis technique is presented based on the Hermite transform. Psychovisual evidence suggests that the Gaussian derivatives fit the receptive field profiles of mammalian visual systems. The Hermite transform describes locally basic texture features in terms of Gaussian derivatives. Multiresolution combined with several analysis orders provides detection of patterns that characterizes every texture class. The analysis of the local maximum energy direction and steering of the transformation coefficients increase the method robustness against the texture orientation. This method presents an advantage over classical filter bank design because in the latter a fixed number of orientations for the analysis has to be selected. During the training stage, a subset of the Hermite analysis filters is chosen in order to improve the inter-class separability, reduce dimensionality of the feature vectors and computational cost during the classification stage. We exhaustively evaluated the correct classification rate of real randomly selected training and testing texture subsets using several kinds of common used texture features. A comparison between different distance measurements is also presented. Results of the unsupervised real texture segmentation using this approach and comparison with previous approaches showed the benefits of our proposal.

  15. Influence of polluted SY River on child growth and sex hormones.

    PubMed

    Tang, Chun Yu; Li, An Qi; Guan, Yong Bo; Li, Yan; Cheng, Xue Min; Li, Ping; Li, Shi Qun; Luo, Yi Xin; Huang, Qi; Chen, Hong Yang; Cui, Liu Xin

    2012-06-01

    To investigate the influence of the polluted SY River on children's growth and sex hormones, and provide scientific data for assessment of the polluted status of the SY River. The study areas were selected randomly from the SY River Basin. Lead (Pb), mercury (Hg), arsenic (As), phthalates (DEP, DBP, DMP, DEHP), and bisphenol A (BPA) were measured both in the river water and in the drinking water. School children were selected by cluster sampling (n=154). Physical development indexes (height, weight, bust-circumference, and skinfold thickness) and sex hormones [testosterone (T) and estradiol (E2)] were measured for all the children. The contents of Pb and Hg exceeded Class V standards of surface water quality in each section of the river and other indicators exceeded Class III. Compared to the control area, the concentrations of Pb, Hg, As, BPA, DEP, and DBP in the drinking water were significantly higher than in the polluted area (P<0.05). Children from the control area had significantly lower E2 and T than children from the polluted area (P<0.05). Among anthropometric results, only skinfold thickness had statistically significant difference between the two groups (P<0.05), while the other indexes showed no significant differences between the two groups (P>0.05). The drinking water has been polluted by the SY River and affected serum sex hormone levels of children living in the polluted area. Copyright © 2012 The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier B.V. All rights reserved.

  16. Application of a deep-learning method to the forecast of daily solar flare occurrence using Convolution Neural Network

    NASA Astrophysics Data System (ADS)

    Shin, Seulki; Moon, Yong-Jae; Chu, Hyoungseok

    2017-08-01

    As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT 195Å, and 304Å from January 1996 to December 2010, and output ones are yes or no of flare occurrence. We select training dataset from Jan 1996 to Dec 2000 and from Jan 2003 to Dec 2008. Testing dataset is chosen from Jan 2001 to Dec 2002 and from Jan 2009 to Dec 2010 in order to consider the solar cycle effect. In training dataset, we randomly select one fifth of training data for validation dataset to avoid the overfitting problem. Our model successfully forecasts the flare occurrence with about 0.90 probability of detection (POD) for common flares (C-, M-, and X-class). While POD of major flares (M- and X-class) forecasting is 0.96, false alarm rate (FAR) also scores relatively high(0.60). We also present several statistical parameters such as critical success index (CSI) and true skill statistics (TSS). Our model can immediately be applied to automatic forecasting service when image data are available.

  17. Designing Authentic Learning Tasks for Online Library Instruction

    ERIC Educational Resources Information Center

    Finch, Jannette L.; Jefferson, Renee N.

    2013-01-01

    This empirical study explores whether authentic tasks designed specifically for deliberately grouped students have an effect on student perception of teaching presence and student cognitive gains. In one library research class offered in an express session online, the instructor grouped students randomly. In a second online library research class,…

  18. Open-closed-loop iterative learning control for a class of nonlinear systems with random data dropouts

    NASA Astrophysics Data System (ADS)

    Cheng, X. Y.; Wang, H. B.; Jia, Y. L.; Dong, YH

    2018-05-01

    In this paper, an open-closed-loop iterative learning control (ILC) algorithm is constructed for a class of nonlinear systems subjecting to random data dropouts. The ILC algorithm is implemented by a networked control system (NCS), where only the off-line data is transmitted by network while the real-time data is delivered in the point-to-point way. Thus, there are two controllers rather than one in the control system, which makes better use of the saved and current information and thereby improves the performance achieved by open-loop control alone. During the transfer of off-line data between the nonlinear plant and the remote controller data dropout occurs randomly and the data dropout rate is modeled as a binary Bernoulli random variable. Both measurement and control data dropouts are taken into consideration simultaneously. The convergence criterion is derived based on rigorous analysis. Finally, the simulation results verify the effectiveness of the proposed method.

  19. Classes of Split-Plot Response Surface Designs for Equivalent Estimation

    NASA Technical Reports Server (NTRS)

    Parker, Peter A.; Kowalski, Scott M.; Vining, G. Geoffrey

    2006-01-01

    When planning an experimental investigation, we are frequently faced with factors that are difficult or time consuming to manipulate, thereby making complete randomization impractical. A split-plot structure differentiates between the experimental units associated with these hard-to-change factors and others that are relatively easy-to-change and provides an efficient strategy that integrates the restrictions imposed by the experimental apparatus. Several industrial and scientific examples are presented to illustrate design considerations encountered in the restricted randomization context. In this paper, we propose classes of split-plot response designs that provide an intuitive and natural extension from the completely randomized context. For these designs, the ordinary least squares estimates of the model are equivalent to the generalized least squares estimates. This property provides best linear unbiased estimators and simplifies model estimation. The design conditions that allow for equivalent estimation are presented enabling design construction strategies to transform completely randomized Box-Behnken, equiradial, and small composite designs into a split-plot structure.

  20. Mutation Accumulation, Soft Selection and the Middle-Class Neighborhood

    PubMed Central

    Moorad, Jacob A.; Hall, David W.

    2009-01-01

    The “middle-class neighborhood” is a breeding design intended to allow new mutations to accumulate by lessening the effects of purifying selection through the elimination of among-line fitness variation. We show that this design effectively applies soft selection to the experimental population, potentially causing biased estimates of mutational effects if social effects contribute to fitness. PMID:19448272

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