Dance Class Structure Affects Youth Physical Activity and Sedentary Behavior: A Study of Seven Dance Types

ERIC Educational Resources Information Center

Lopez Castillo, Maria A.; Carlson, Jordan A.; Cain, Kelli L.; Bonilla, Edith A.; Chuang, Emmeline; Elder, John P.; Sallis, James F.

2015-01-01

Purpose: The study aims were to determine: (a) how class structure varies by dance type, (b) how moderate-to-vigorous physical activity (MVPA) and sedentary behavior vary by dance class segments, and (c) how class structure relates to total MVPA in dance classes. Method: Participants were 291 boys and girls ages 5 to 18 years old enrolled in 58…

Effectiveness of different tutorial recitation teaching methods and its implications for TA training

NASA Astrophysics Data System (ADS)

Endorf, Robert

2008-04-01

We present results from a comparative study of student understanding for students who attended recitation classes that used different teaching methods. The purpose of the study was to evaluate which teaching methods would be the most effective for recitation classes associated with large lectures in introductory physics courses. Student volunteers from our introductory calculus-based physics course at the University of Cincinnati attended a special recitation class that was taught using one of four different teaching methods. A total of 272 students were divided into approximately equal groups for each method. Students in each class were taught the same topic, ``Changes in Energy and Momentum,'' from ``Tutorials in Introductory Physics'' by Lillian McDermott, Peter Shaffer and the Physics Education Group at the University of Washington. The different teaching methods varied in the amount of student and teacher engagement. Student understanding was evaluated through pretests and posttests. Our results demonstrate the importance of the instructor's role in teaching recitation classes. The most effective teaching method was for students working in cooperative learning groups with the instructors questioning the groups using Socratic dialogue. In addition, we investigated student preferences of modes of instruction through an open-ended survey. Our results provide guidance and evidence for the teaching methods which should be emphasized in training course instructors.

The 21st century skills with model eliciting activities on linear program

NASA Astrophysics Data System (ADS)

Handajani, Septriana; Pratiwi, Hasih; Mardiyana

2018-04-01

Human resources in the 21st century are required to master various forms of skills, including critical thinking skills and problem solving. The teaching of the 21st century is a teaching that integrates literacy skills, knowledge, skills, attitudes, and mastery of ICT. This study aims to determine whether there are differences in the effect of applying Model Elliciting Activities (MEAs) that integrates 21st century skills, namely 4C and conventional learning to learning outcomes. This research was conducted at Vocational High School in the odd semester of 2017 and uses the experimental method. The experimental class is treated MEAs that integrates 4C skills and the control class is given conventional learning. Methods of data collection in this study using the method of documentation and test methods. The data analysis uses Z-test. Data obtained from experiment class and control class. The result of this study showed there are differences in the effect of applying MEAs that integrates 4C skills and conventional learning to learning outcomes. Classes with MEAs that integrates 4C skills give better learning outcomes than the ones in conventional learning classes. This happens because MEAs that integrates 4C skills can improved creativity skills, communication skills, collaboration skills, and problem-solving skills.

Elementary School Children's Reasoning about Social Class: A Mixed-Methods Study

ERIC Educational Resources Information Center

Mistry, Rashmita S.; Brown, Christia S.; White, Elizabeth S.; Chow, Kirby A.; Gillen-O'Neel, Cari

2015-01-01

The current study examined children's identification and reasoning about their subjective social status (SSS), their beliefs about social class groups (i.e., the poor, middle class, and rich), and the associations between the two. Study participants were 117 10- to 12-year-old children of diverse racial, ethnic, and socioeconomic backgrounds…

Opinions of the Class Teachers towards "Privacy" and Its Violation

ERIC Educational Resources Information Center

Kiral, Bilgen; Karaman Kepenekci, Yasemin

2017-01-01

Purpose: The aim of this study is to reveal the opinions of teachers in terms of the right to privacy at school, both in the class and individually, and the violation of this right. Research Methods: Data was collected using a qualitative interview method. 21 teachers from state schools and 15 from two private schools, in total 36 class teachers,…

Home Advantage: Social Class and Parental Intervention in Elementary Education.

ERIC Educational Resources Information Center

Lareau, Annette

Social class influences parent involvement in schooling. This book uses the case study method to compare family-school relationships in a working-class elementary school with those in an upper middle-class school, focusing on one first grade class in each school, and within the two schools, on 12 families, over the course of their children's first…

Film Study: "Nothing But a Man."

ERIC Educational Resources Information Center

Manchel, Frank

1967-01-01

To examine new approaches to film study, "Nothing But a Man," which portrays the difficulties encountered by a young Negro in the South, was taught experimentally in three 11th-grade English classes at Cheshire High School, Connecticut. A different method of approaching the movie was used in each class to determine effective teaching methods for…

A Comparative Study on the Effectiveness of Two Song-Teaching Methods: Holistic vs. Phrase-by-Phrase

ERIC Educational Resources Information Center

Persellin, Diane; Bateman, Laura

2009-01-01

The purpose of our study was to compare the effectiveness of two song-teaching methods: holistic and phrase-by-phrase. Thirty-two first-grade children (n = 32) from two music classes in an urban elementary school were taught two folksongs. The first class (n = 16) was taught one song through the phrase-by-phrase method and another song through the…

Student Achievement in Large-Lecture Remedial Math Classes

ERIC Educational Resources Information Center

Monte, Brent M.

2011-01-01

Due to the increase in students seeking remedial math classes at the community college level, coupled with declining revenues to the community colleges and a lack of classroom availability, the need to consider increasing class size has become a relevant and timely issue. This study is a mixed-method, quasi-experimental study testing effects of…

Liquid-Based Medium Used to Prepare Cytological Breast Nipple Fluid Improves the Quality of Cellular Samples Automatic Collection

PubMed Central

Zonta, Marco Antonio; Velame, Fernanda; Gema, Samara; Filassi, Jose Roberto; Longatto-Filho, Adhemar

2014-01-01

Background Breast cancer is the second cause of death in women worldwide. The spontaneous breast nipple discharge may contain cells that can be analyzed for malignancy. Halo® Mamo Cyto Test (HMCT) was recently developed as an automated system indicated to aspirate cells from the breast ducts. The objective of this study was to standardize the methodology of sampling and sample preparation of nipple discharge obtained by the automated method Halo breast test and perform cytological evaluation in samples preserved in liquid medium (SurePath™). Methods We analyzed 564 nipple fluid samples, from women between 20 and 85 years old, without history of breast disease and neoplasia, no pregnancy, and without gynecologic medical history, collected by HMCT method and preserved in two different vials with solutions for transport. Results From 306 nipple fluid samples from method 1, 199 (65%) were classified as unsatisfactory (class 0), 104 (34%) samples were classified as benign findings (class II), and three (1%) were classified as undetermined to neoplastic cells (class III). From 258 samples analyzed in method 2, 127 (49%) were classified as class 0, 124 (48%) were classified as class II, and seven (2%) were classified as class III. Conclusion Our study suggests an improvement in the quality and quantity of cellular samples when the association of the two methodologies is performed, Halo breast test and the method in liquid medium. PMID:29147397

Counting to 20: Online Implementation of a Face-to-Face, Elementary Mathematics Methods Problem-Solving Activity

ERIC Educational Resources Information Center

Schwartz, Catherine Stein

2012-01-01

This study describes implementation of the same problem-solving activity in both online and face-to-face environments. The activity, done in the first class period or first module of a K-2 mathematics methods course, was initially used in a face-to-face class and then adapted later for use in an online class. While the task was originally designed…

Assets as a Socioeconomic Status Index: Categorical Principal Components Analysis vs. Latent Class Analysis.

PubMed

Sartipi, Majid; Nedjat, Saharnaz; Mansournia, Mohammad Ali; Baigi, Vali; Fotouhi, Akbar

2016-11-01

Some variables like Socioeconomic Status (SES) cannot be directly measured, instead, so-called 'latent variables' are measured indirectly through calculating tangible items. There are different methods for measuring latent variables such as data reduction methods e.g. Principal Components Analysis (PCA) and Latent Class Analysis (LCA). The purpose of our study was to measure assets index- as a representative of SES- through two methods of Non-Linear PCA (NLPCA) and LCA, and to compare them for choosing the most appropriate model. This was a cross sectional study in which 1995 respondents filled the questionnaires about their assets in Tehran. The data were analyzed by SPSS 19 (CATPCA command) and SAS 9.2 (PROC LCA command) to estimate their socioeconomic status. The results were compared based on the Intra-class Correlation Coefficient (ICC). The 6 derived classes from LCA based on BIC, were highly consistent with the 6 classes from CATPCA (Categorical PCA) (ICC = 0.87, 95%CI: 0.86 - 0.88). There is no gold standard to measure SES. Therefore, it is not possible to definitely say that a specific method is better than another one. LCA is a complicated method that presents detailed information about latent variables and required one assumption (local independency), while NLPCA is a simple method, which requires more assumptions. Generally, NLPCA seems to be an acceptable method of analysis because of its simplicity and high agreement with LCA.

A Large-Scale Blended and Flipped Class: Class Design and Investigation of Factors Influencing Students' Intention to Learn

ERIC Educational Resources Information Center

Zhang, Yulei; Dang, Yan; Amer, Beverly

2016-01-01

This paper reports a study of a large-scale blended and flipped class and has two major parts. First, it presents the design of the class, i.e., a coordinated and multisection undergraduate introduction-to-computer-information-systems course. The detailed design of various teaching methods used in the class is presented, including a digital…

Incorporating Meaningful Gamification in a Blended Learning Research Methods Class: Examining Student Learning, Engagement, and Affective Outcomes

ERIC Educational Resources Information Center

Tan, Meng; Hew, Khe Foon

2016-01-01

In this study, we investigated how the use of meaningful gamification affects student learning, engagement, and affective outcomes in a short, 3-day blended learning research methods class using a combination of experimental and qualitative research methods. Twenty-two postgraduates were randomly split into two groups taught by the same…

"It All depends...": Middle School Teachers Evaluate Single-Sex Classes

ERIC Educational Resources Information Center

Spielhagen, Frances R.

2011-01-01

This mixed-methods study explored the effectiveness of single-sex classes according to key stakeholders in this educational reform--the teachers who choose or are hired to teach in single-sex classes and schools. Specifically, this study examined the on-the-ground experiences of middle school teachers as they attempted to implement a relatively…

Landsat D Thematic Mapper image dimensionality reduction and geometric correction accuracy

NASA Technical Reports Server (NTRS)

Ford, G. E.

1986-01-01

To characterize and quantify the performance of the Landsat thematic mapper (TM), techniques for dimensionality reduction by linear transformation have been studied and evaluated and the accuracy of the correction of geometric errors in TM images analyzed. Theoretical evaluations and comparisons for existing methods for the design of linear transformation for dimensionality reduction are presented. These methods include the discrete Karhunen Loeve (KL) expansion, Multiple Discriminant Analysis (MDA), Thematic Mapper (TM)-Tasseled Cap Linear Transformation and Singular Value Decomposition (SVD). A unified approach to these design problems is presented in which each method involves optimizing an objective function with respect to the linear transformation matrix. From these studies, four modified methods are proposed. They are referred to as the Space Variant Linear Transformation, the KL Transform-MDA hybrid method, and the First and Second Version of the Weighted MDA method. The modifications involve the assignment of weights to classes to achieve improvements in the class conditional probability of error for classes with high weights. Experimental evaluations of the existing and proposed methods have been performed using the six reflective bands of the TM data. It is shown that in terms of probability of classification error and the percentage of the cumulative eigenvalues, the six reflective bands of the TM data require only a three dimensional feature space. It is shown experimentally as well that for the proposed methods, the classes with high weights have improvements in class conditional probability of error estimates as expected.

Prediction of future uniform milk prices in Florida federal milk marketing order 6 from milk futures markets.

PubMed

De Vries, A; Feleke, S

2008-12-01

This study assessed the accuracy of 3 methods that predict the uniform milk price in Federal Milk Marketing Order 6 (Florida). Predictions were made for 1 to 12 mo into the future. Data were from January 2003 to May 2007. The CURRENT method assumed that future uniform milk prices were equal to the last announced uniform milk price. The F+BASIS and F+UTIL methods were based on the milk futures markets because the futures prices reflect the market's expectation of the class III and class IV cash prices that are announced monthly by USDA. The F+BASIS method added an exponentially weighted moving average of the difference between the class III cash price and the historical uniform milk price (also known as basis) to the class III futures price. The F+UTIL method used the class III and class IV futures prices, the most recently announced butter price, and historical utilizations to predict the skim milk prices, butterfat prices, and utilizations in all 4 classes. Predictions of future utilizations were made with a Holt-Winters smoothing method. Federal Milk Marketing Order 6 had high class I utilization (85 +/- 4.8%). Mean and standard deviation of the class III and class IV cash prices were $13.39 +/- 2.40/cwt (1 cwt = 45.36 kg) and $12.06 +/- 1.80/cwt, respectively. The actual uniform price in Tampa, Florida, was $16.62 +/- 2.16/cwt. The basis was $3.23 +/- 1.23/cwt. The F+BASIS and F+UTIL predictions were generally too low during the period considered because the class III cash prices were greater than the corresponding class III futures prices. For the 1- to 6-mo-ahead predictions, the root of the mean squared prediction errors from the F+BASIS method were $1.12, $1.20, $1.55, $1.91, $2.16, and $2.34/cwt, respectively. The root of the mean squared prediction errors ranged from $2.50 to $2.73/cwt for predictions up to 12 mo ahead. Results from the F+UTIL method were similar. The accuracies of the F+BASIS and F+UTIL methods for all 12 fore-cast horizons were not significantly different. Application of the modified Mariano-Diebold tests showed that no method included all the information contained in the other methods. In conclusion, both F+BASIS and F+UTIL methods tended to more accurately predict the future uniform milk prices than the CURRENT method, but prediction errors could be substantial even a few months into the future. The majority of the prediction error was caused by the inefficiency of the futures markets to predict the class III cash prices.

Comparison of Two Small-Group Learning Methods in 12th-Grade Physics Classes Focusing on Intrinsic Motivation and Academic Performance

ERIC Educational Resources Information Center

Berger, Roland; Hanze, Martin

2009-01-01

Twelfth-grade physics classes with 344 students participated in a quasi-experimental study comparing two small-group learning settings. In the jigsaw classroom, in contrast to the cyclical rotation method, teaching expectancy as well as resource interdependence is established. The study is based on the self-determination theory of motivation,…

Additional Evidence on the Relationship between Class Size and Student Performance

ERIC Educational Resources Information Center

Arias, J. J.; Walker, Douglas M.

2004-01-01

Much of the economic education literature suggests that the principles of economics class size does not significantly affect student performance. However, study methods have varied in terms of the aggregation level (student or class), the measure of performance (TUCE or course letter grade), and the class size measure (e.g., students who completed…

Partial least squares density modeling (PLS-DM) - a new class-modeling strategy applied to the authentication of olives in brine by near-infrared spectroscopy.

PubMed

Oliveri, Paolo; López, M Isabel; Casolino, M Chiara; Ruisánchez, Itziar; Callao, M Pilar; Medini, Luca; Lanteri, Silvia

2014-12-03

A new class-modeling method, referred to as partial least squares density modeling (PLS-DM), is presented. The method is based on partial least squares (PLS), using a distance-based sample density measurement as the response variable. Potential function probability density is subsequently calculated on PLS scores and used, jointly with residual Q statistics, to develop efficient class models. The influence of adjustable model parameters on the resulting performances has been critically studied by means of cross-validation and application of the Pareto optimality criterion. The method has been applied to verify the authenticity of olives in brine from cultivar Taggiasca, based on near-infrared (NIR) spectra recorded on homogenized solid samples. Two independent test sets were used for model validation. The final optimal model was characterized by high efficiency and equilibrate balance between sensitivity and specificity values, if compared with those obtained by application of well-established class-modeling methods, such as soft independent modeling of class analogy (SIMCA) and unequal dispersed classes (UNEQ). Copyright © 2014 Elsevier B.V. All rights reserved.

Feasibility of Active Machine Learning for Multiclass Compound Classification.

PubMed

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

2016-01-25

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

The Effect of Special Teaching Methods Class on the Level of Teachers' Self-Efficacy Perception of Pre-Service Teacher

ERIC Educational Resources Information Center

Gökdag Baltaoglu, Meltem

2015-01-01

The purpose of this study is to evaluate the change in the level of teachers' self-efficacy perception of primary school Social Studies pre-service teachers who take the special teaching methods class. Single group pretest-posttest model from pre-experimental patterns was applied in the research. The study group of the research consisted of 59…

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

PubMed Central

Tsai, Yu-Shuen; Aguan, Kripamoy; Pal, Nikhil R.; Chung, I-Fang

2011-01-01

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases. PMID:21909426

A critical assessment of transmethylation procedures for n-3 long-chain polyunsaturated fatty acid quantification of lipid classes.

PubMed

Sehl, Anthony; Couëdelo, Leslie; Fonseca, Laurence; Vaysse, Carole; Cansell, Maud

2018-06-15

Lipid transmethylation methods described in the literature are not always evaluated with care so to insure that the methods are effective, especially on food matrix or biological samples containing polyunsaturated fatty acid (PUFA). The aim of the present study was to select a method suitable for all lipid species rich in long chain n-3 PUFA. Three published methods were adapted and applied on individual lipid classes. Lipid (trans)methylation efficiency was characterized in terms of reaction yield and gas chromatography (GC) analysis. The acid-catalyzed method was unable to convert triglycerides and sterol esters, while the method using an incubation at a moderate temperature was ineffective on phospholipids and sterol esters. On the whole only the method using sodium methoxide and sulfuric acid was effective on lipid classes taken individually or in a complex medium. This study highlighted the use of an appropriate (trans)methylation method for insuring an accurate fatty acid composition. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison of peer-tutoring learning model through problem-solving approach and traditional learning model on the cognitive ability of grade 10 students at SMKN 13 Bandung on the topic of Stoichiometry

NASA Astrophysics Data System (ADS)

Hayat, A. Z.; Wahyu, W.; Kurnia

2018-05-01

This study aims to find out the improvement of cognitive ability of students on the implementation of cooperative learning model of peer-tutoring by using problem-solving approach. The research method used is mix method of Sequential Explanatory strategy and pretest post-test non-equivalent control group design. The participants involved in this study were 68 grade 10 students of Vocational High School in Bandung that consisted of 34 samples of experimental class and 34 samples of control class. The instruments used include written test and questionnaires. The improvement of cognitive ability of students was calculated using the N- gain formula. Differences of two average scores were calculated using t-test at significant level of α = 0.05. The result of study shows that the improvement of cognitive ability in experimental class was significantly different compared to the improvement in the control class at significant level of α = 0.05. The improvement of cognitive ability in experimental class is higher than in control class.

WebMail versus WebApp: Comparing Problem-Based Learning Methods in a Business Research Methods Course

ERIC Educational Resources Information Center

Williams van Rooij, Shahron

2007-01-01

This study examined the impact of two Problem-Based Learning (PBL) approaches on knowledge transfer, problem-solving self-efficacy, and perceived learning gains among four intact classes of adult learners engaged in a group project in an online undergraduate business research methods course. With two of the classes using a text-only PBL workbook…

Estimating the Richness of a Population When the Maximum Number of Classes Is Fixed: A Nonparametric Solution to an Archaeological Problem

PubMed Central

Eren, Metin I.; Chao, Anne; Hwang, Wen-Han; Colwell, Robert K.

2012-01-01

Background Estimating assemblage species or class richness from samples remains a challenging, but essential, goal. Though a variety of statistical tools for estimating species or class richness have been developed, they are all singly-bounded: assuming only a lower bound of species or classes. Nevertheless there are numerous situations, particularly in the cultural realm, where the maximum number of classes is fixed. For this reason, a new method is needed to estimate richness when both upper and lower bounds are known. Methodology/Principal Findings Here, we introduce a new method for estimating class richness: doubly-bounded confidence intervals (both lower and upper bounds are known). We specifically illustrate our new method using the Chao1 estimator, rarefaction, and extrapolation, although any estimator of asymptotic richness can be used in our method. Using a case study of Clovis stone tools from the North American Lower Great Lakes region, we demonstrate that singly-bounded richness estimators can yield confidence intervals with upper bound estimates larger than the possible maximum number of classes, while our new method provides estimates that make empirical sense. Conclusions/Significance Application of the new method for constructing doubly-bound richness estimates of Clovis stone tools permitted conclusions to be drawn that were not otherwise possible with singly-bounded richness estimates, namely, that Lower Great Lakes Clovis Paleoindians utilized a settlement pattern that was probably more logistical in nature than residential. However, our new method is not limited to archaeological applications. It can be applied to any set of data for which there is a fixed maximum number of classes, whether that be site occupancy models, commercial products (e.g. athletic shoes), or census information (e.g. nationality, religion, age, race). PMID:22666316

The Relationship between Professional Preparation and Class Structure on Health Instruction in the Secondary Classroom

ERIC Educational Resources Information Center

Hammig, Bart; Ogletree, Roberta; Wycoff-Horn, Marcie R.

2011-01-01

Background: The aim of the present study was to examine the impact of professional preparation and class structure on health content delivery and time spent delivering content among required health education classes in the United States. Methods: Data from the classroom-level file of the 2006 School Health Policies and Programs Study were…

Social Gender in the Pictures Drawn by Students about Physical Education Class

ERIC Educational Resources Information Center

Temel, Cenk; Güllü, Mehmet

2016-01-01

The current study aimed to analyze the social gender perception in physical education classes in Turkey through the pictures drawn by students about the physical education class. The document analysis technique, which is a qualitative research method, was used in the study. In the light of this aim, the pictures drawn by a total of 394 students…

The Effectiveness of Single-Gender Eighth-Grade English, History, Mathematics and Science Classes

ERIC Educational Resources Information Center

Roth, Douglas Jeffrey

2009-01-01

Purpose, scope, and method of study. The purpose of this study was to compare the effectiveness of eighth-grade single-gender classes with coed classes across subject area, gender, at-risk status, and socioeconomic status (SES). The sample was drawn from one school, DeSoto West Junior High School, where enrollment averages 80% African American,…

LEARNING EFFICIENCY AS A FUNCTION OF DEPICTION, VERBALIZATION, GRADE AND SOCIAL CLASS.

ERIC Educational Resources Information Center

ROHWER, WILLIAM D., JR.; AND OTHERS

LEARNING EFFICIENCY AS A FUNCTION OF DEPICTION, VERBALIZATION, GRADE LEVEL, AND SOCIAL CLASS WAS EXPLORED BY ASKING 384 KINDERGARTEN, FIRST-, THIRD-, AND SIXTH-GRADE CHILDREN FROM BOTH MIDDLE-CLASS AND LOWER-CLASS AREAS TO LEARN A LIST OF 24 PAIRED ASSOCIATES. ALL PAIRS WERE PRESENTED PICTORIALLY BY A STUDY-TEST METHOD FOR TWO LEARNING TRIALS. THE…

Cooperative learning in third graders' jigsaw groups for mathematics and science with and without questioning training.

PubMed

Souvignier, Elmar; Kronenberger, Julia

2007-12-01

There is much support for using cooperative methods, since important instructional aspects, such as elaboration of new information, can easily be realized by methods like 'jigsaw'. However, the impact of providing students with additional help like a questioning training and potential limitations of the method concerning the (minimum) age of the students have rarely been investigated. The study investigated the effects of cooperative methods at elementary school level. Three conditions of instruction were compared: jigsaw, jigsaw with a supplementary questioning training and teacher-guided instruction. Nine third grade classes from three schools with 208 students participated in the study. In each school, all the three instructional conditions were realized in three different classes. All classes studied three units on geometry and one unit on astronomy using the assigned instructional method. Each learning unit comprised six lessons. For each unit, an achievement test was administered as pre-test, post-test and delayed test. In the math units, no differences between the three conditions could be detected. In the astronomy unit, students benefited more from teacher-guided instruction. Differential analyses revealed that 'experts' learned more than students in teacher-guided instruction, whereas 'novices' were outperformed by the students in the control classes. Even third graders used the jigsaw method with satisfactory learning results. The modest impact of the questioning training and the low learning gains of the cooperative classes in the astronomy unit as well as high discrepancies between learning outcomes of experts and novices show that explicit instruction of explaining skills in combination with well-structured material are key issues in using the jigsaw method with younger students.

A Repeated Trajectory Class Model for Intensive Longitudinal Categorical Outcome

PubMed Central

Lin, Haiqun; Han, Ling; Peduzzi, Peter N.; Murphy, Terrence E.; Gill, Thomas M.; Allore, Heather G.

2014-01-01

This paper presents a novel repeated latent class model for a longitudinal response that is frequently measured as in our prospective study of older adults with monthly data on activities of daily living (ADL) for more than ten years. The proposed method is especially useful when the longitudinal response is measured much more frequently than other relevant covariates. The repeated trajectory classes represent distinct temporal patterns of the longitudinal response wherein an individual’s membership in the trajectory classes may renew or change over time. Within a trajectory class, the longitudinal response is modeled by a class-specific generalized linear mixed model. Effectively, an individual may remain in a trajectory class or switch to another as the class membership predictors are updated periodically over time. The identification of a common set of trajectory classes allows changes among the temporal patterns to be distinguished from local fluctuations in the response. An informative event such as death is jointly modeled by class-specific probability of the event through shared random effects. We do not impose the conditional independence assumption given the classes. The method is illustrated by analyzing the change over time in ADL trajectory class among 754 older adults with 70500 person-months of follow-up in the Precipitating Events Project. We also investigate the impact of jointly modeling the class-specific probability of the event on the parameter estimates in a simulation study. The primary contribution of our paper is the periodic updating of trajectory classes for a longitudinal categorical response without assuming conditional independence. PMID:24519416

Peer Instruction in introductory physics: A method to bring about positive changes in students' attitudes and beliefs

NASA Astrophysics Data System (ADS)

Zhang, Ping; Ding, Lin; Mazur, Eric

2017-06-01

This paper analyzes pre-post matched gains in the epistemological views of science students taking the introductory physics course at Beijing Normal University (BNU) in China. In this study we examined the attitudes and beliefs of science majors (n =441 ) in four classes, one taught using traditional (lecture) teaching methods, and the other three taught with Peer Instruction (PI). In two of the PI classes, student peer groups were constantly changing throughout the semester, while in the other PI class student groups remained fixed for the duration of the semester. The results of the pre- and post-test using the Colorado Learning Attitudes about Science Survey showed that students in traditional lecture settings became significantly more novicelike in their beliefs about physics and learning physics over the course of a semester, a result consistent with what was reported in the literature. However, all three of the classes taught using the PI method improved student attitudes and beliefs about physics and learning physics. In the PI class with fixed peer groups, students exhibited a greater positive shift in attitudes and beliefs than in the other PI class with changing peer groups. The study also looked at gender differences in student learning attitudes. Gender results revealed that female science majors in the PI classes achieved a greater positive shift in attitudes and beliefs after instruction than did male students.

Student Evaluation of Instruction: Comparison between In-Class and Online Methods

ERIC Educational Resources Information Center

Capa-Aydin, Yesim

2016-01-01

This study compares student evaluations of instruction that were collected in-class with those gathered through an online survey. The two modes of administration were compared with respect to response rate, psychometric characteristics and mean ratings through different statistical analyses. Findings indicated that in-class evaluations produced a…

Instructor Presence for Web-Based Classes

ERIC Educational Resources Information Center

Lear, Janet L.; Isernhagen, Jody C.; LaCost, Barbara A.; King, James W.

2009-01-01

Is instructor presence important in an online distance education class? Yes, said the students of this mixed methods research study. Students (n=241) enrolled in 31 Web-based sections of classes at four Midwestern post-secondary institutions in two different states were surveyed. The survey instrument included both the Rovai Classroom Community…

Confidence Wagering during Mathematics and Science Testing

ERIC Educational Resources Information Center

Jack, Brady Michael; Liu, Chia-Ju; Chiu, Hoan-Lin; Shymansky, James A.

2009-01-01

This proposal presents the results of a case study involving five 8th grade Taiwanese classes, two mathematics and three science classes. These classes used a new method of testing called confidence wagering. This paper advocates the position that confidence wagering can predict the accuracy of a student's test answer selection during…

Informal Learning: A Lived Experience in a University Musicianship Class

ERIC Educational Resources Information Center

Mok, Annie O.

2017-01-01

This study investigates how a class of university music students who engaged in a "lived" experience of informal learning adopted methods and strategies to complete a self-learning "aural copying" performance assignment in a musicianship class in Hong Kong. Data were collected from observations of the performances and the…

The Effect of Process Intervention on the Attitudes and Learning in a College Freshman Composition Class.

ERIC Educational Resources Information Center

Wahlberg, William Auman

This study was designed to explore one method of intervening in the process of a conventional academic classroom to affect student attitude and improve the learning climate. Two college freshman composition classes of 22 students each provided the subjects for the study. Each class was taught by the same instructor for three hours a week; one…

A Comparative Analysis of Method Books for Class Jazz Instruction

ERIC Educational Resources Information Center

Watson, Kevin E.

2017-01-01

The purpose of this study was to analyze and compare instructional topics and teaching approaches included in selected class method books for jazz pedagogy through content analysis methodology. Frequency counts for the number of pages devoted to each defined instructional content category were compiled and percentages of pages allotted to each…

School Principals' Opinions on In-Class Inspections

ERIC Educational Resources Information Center

Kayikci, Kemal; Sahin, Ahmet; Canturk, Gokhan

2016-01-01

The aim of this research is to determine school principals' opinions on the in-class inspections carried out by inspectors of the Ministry of National Education of Turkey (MEB). The study was modeled as a convergent parallel design, one of the mixed methods which combined qualitative and quantitative methods. For data collection, the researchers…

QUALITY ASSURANCE STUDY OF MARINE LIPID CLASS DETERMINATION USING CHROMAROD/IATROSCAN( REG. TRADEMARK) THIN-LAYER CHROMATOGRAPHY-FLAME IONIZATION DETECTOR

EPA Science Inventory

An Iatroscan thin-layer chromatorgraphy-flame ionization detector has been utilized to quantify lipid classes in marine samples. This method was evaluated relative to established quality assurance (QA) procedures used for the gas chromatographic analysis of PCBs. A method for ext...

PRELIMINARY COMPARATIVE STUDY OF METHODS TO EXTRACT VIRUS FROM RAW AND PROCESSED SEWAGE SLUDGES

EPA Science Inventory

Two simple virus extraction techniques were compared to an EPA standard method for detection of human enteric viruses in raw sewage sludge and class A biosolids. The techniques were used to detect both indigenous and seeded virus from a plant that distributes class A material pr...

[Microinvasive dental treatment in pre-school children].

PubMed

Korolenkova, M V

The aim of the study was to assess the efficiency of atraumatic restorative treatment (ART) with cavity preparation by means of dental endo motor. ART method was applied in 94 children (50 females and 44 males, 301 teeth treated) aged 21-96 months. Wireless dental endo motor (Endo Mate TC2, NSK, Japan) was used for cavity preparation. The cavities (102 (33.9%) class I, 156 (51.8%) class V, 20 (6.6%) class II, 18 (6%) class III and 5 (1.7%) class IV) were then filled with glass-ionomer cement (Fuji IX, GC, Japan). Success rate was assessed 3, 6, 12 and 18 months after treatment. Overall ART procedure success rate (good marginal fit, no occlusal wearing or restoration fractures) at 18-month follow up was 88.7% (267 fillings out of 301) with the highest survival in class I (96.1%) and class V (96.2%) restoration and poorest in class II (50%), class III (44.4%) and class IV (20%) restorations. Cavity preparation with wireless dental endo motor was well tolerated even by infants (12 children were younger than 24 months), as it is noiseless and significantly faster than conventional manual preparation. ART method with the use of dental endo motor showed good success rate and proved to be highly efficient in small and apprehensive children. The method, however, should be avoided in class III and IV cavities as the success rate is poor mostly because of restoration fractures.

Effectiveness of different tutorial recitation teaching methods and its implications for TA training

NASA Astrophysics Data System (ADS)

Koenig, Kathleen M.; Endorf, Robert J.; Braun, Gregory A.

2007-06-01

We present results from a comparative study of student understanding for students who attended recitation classes that used different teaching methods. Student volunteers from our introductory calculus-based physics course attended a special recitation class that was taught using one of four different teaching methods. A total of 272 students were divided into approximately equal groups for each method. Students in each class were taught the same topic, “Changes in Energy and Momentum,” from Tutorials in Introductory Physics. The different teaching methods varied in the amount of student and teacher engagement. Student understanding was evaluated through pre- and post-tests. Our results demonstrate the importance of the instructor’s role in teaching recitation classes. The most effective teaching method was for students working in cooperative learning groups with the instructors questioning the groups using Socratic dialogue. In addition, we investigated student preferences for modes of instruction through an open-ended survey. Our results provide guidance and evidence for the teaching methods that should be emphasized in training course instructors.

Effective Teaching in Elementary Social Studies.

ERIC Educational Resources Information Center

Savage, Tom V.; Armstrong, David G.

This book is designed for use in elementary social studies methods classes, as a source for discussion in advanced curriculum classes, and as a personal reference for elementary social studies teachers. This book has four major divisions with each division offering a list of lesson ideas. Part 1, "Contexts for the Social Studies," includes: (1)…

Impact of Class Lecture Webcasting on Attendance and Learning

ERIC Educational Resources Information Center

Traphagan, Tomoko; Kucsera, John V.; Kishi, Kyoko

2010-01-01

The present study investigated the impact of class lecture webcasts on students' attendance and learning. The research design employed four data collection methods in two class sections--one with webcast access and another without--of the same course taught by the same instructors. Results indicated the following four major findings. (1) The…

SCALE(ing)-UP Teaching: A Case Study of Student Motivation in an Undergraduate Course

ERIC Educational Resources Information Center

Chittum, Jessica R.; McConnell, Kathryne Drezek; Sible, Jill

2017-01-01

Teaching large classes is increasingly common; thus, demand for effective large-class pedagogy is rising. One method, titled "SCALE-UP" (Student-Centered Active Learning Environment for Undergraduate Programs), is intended for large classes and involves collaborative, active learning in a technology-rich and student-centered environment.…

The job content questionnaire in various occupational contexts: applying a latent class model

PubMed Central

Santos, Kionna Oliveira Bernardes; de Araújo, Tânia Maria; Karasek, Robert

2017-01-01

Objective To evaluate Job Content Questionnaire(JCQ) performance using the latent class model. Methods We analysed cross-sectional studies conducted in Brazil and examined three occupational categories: petroleum industry workers (n=489), teachers (n=4392) and primary healthcare workers (3078)and 1552 urban workers from a representative sample of the city of Feira de Santana in Bahia, Brazil. An appropriate number of latent classes was extracted and described each occupational category using latent class analysis, a multivariate method that evaluates constructs and takes into account the latent characteristics underlying the structure of measurement scales. The conditional probabilities of workers belonging to each class were then analysed graphically. Results Initially, the latent class analysis extracted four classes corresponding to the four job types (active, passive, low strain and high strain) proposed by the Job-Strain model (JSM) and operationalised by the JCQ. However, after taking into consideration the adequacy criteria to evaluate the number of extracted classes, three classes (active, low strain and high strain) were extracted from the studies of urban workers and teachers and four classes (active, passive, low strain and high strain) from the study of primary healthcare and petroleum industry workers. Conclusion The four job types proposed by the JSM were identified among primary healthcare and petroleum industry workers—groups with relatively high levels of skill discretion and decision authority. Three job types were identified for teachers and urban workers; however, passive job situations were not found within these groups. The latent class analysis enabled us to describe the conditional standard responses of the job types proposed by the model, particularly in relation to active jobs and high and low strain situations. PMID:28515185

Using Flexible Busing to Meet Average Class Size Targets

ERIC Educational Resources Information Center

Felt, Andrew J.; Koelemay, Ryan; Richter, Alexander

2008-01-01

This article describes a method of flexible redistricting for K-12 public school districts that allows students from the same geographical region to be bused to different schools, with the goal of meeting average class size (ACS) target ranges. Results of a case study on a geographically large school district comparing this method to a traditional…

Writing Our Way into Shared Understanding: Collaborative Autobiographical Writing in the Qualitative Methods Class

ERIC Educational Resources Information Center

Lapadat, Judith C.

2009-01-01

From her experience as an instructor, the author finds that it is valuable to engage graduate students in conducting a study within their qualitative methods course. In this article, the author discusses how she used a collaborative autobiographical research approach. Class members generate autobiographical writing to be shared with the group, and…

Combining multiple decisions: applications to bioinformatics

NASA Astrophysics Data System (ADS)

Yukinawa, N.; Takenouchi, T.; Oba, S.; Ishii, S.

2008-01-01

Multi-class classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. This article reviews two recent approaches to multi-class classification by combining multiple binary classifiers, which are formulated based on a unified framework of error-correcting output coding (ECOC). The first approach is to construct a multi-class classifier in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. In the second approach, misclassification of each binary classifier is formulated as a bit inversion error with a probabilistic model by making an analogy to the context of information transmission theory. Experimental studies using various real-world datasets including cancer classification problems reveal that both of the new methods are superior or comparable to other multi-class classification methods.

Pregnancy Intention and Contraceptive Use among Women by Class of Obesity: Results from the 2006-2010 and 2011-2013 National Survey of Family Growth.

PubMed

Nguyen, Brian T; Elia, Jennifer L; Ha, Cathrine Y; Kaneshiro, Bliss E

Conflicting research findings on the association of obesity and pregnancy intention may be due to their collective definition of obesity at a body mass index of 30 kg/m 2 or greater. However, obese women with a BMI of 40 kg/m 2 or greater may be both behaviorally and clinically different from obese women with a lower BMI. This study reexamines this relationship, stratifying by class of obesity; the study also explores variations in contraceptive use by class of obesity given their potential contribution to the incidence of unintended or unwanted pregnancy. This study combined data from the 2006 through 2010 and 2011 through 2013 US National Survey of Family Growth. Pregnancy intention (intended, mistimed, unwanted) and current contraceptive use (no method, barrier, pill/patch/ring/injection, long-acting reversible contraceptive, sterilization) were compared across body mass index categories: normal (18.5-24.9 kg/m kg/m 2 ), overweight (25.0-29.9), obese class 1 (30.0-34.9 kg/m 2 ), class 2 (35.0-39.9 kg/m 2 ), and class 3 (≥40 kg/m 2 , severe obesity). Weighted multinomial logistic regressions were refined to determine independent associations of body mass index class and pregnancy intention, as well as contraceptive method, controlling for demographic, socioeconomic, and reproductive factors. Body mass index data were available for 9,848 nonpregnant, sexually active women who reported not wanting to become pregnant. Women with class 3 obesity had significantly greater odds of mistimed (adjusted odd ratio [aOR], 1.67; 95% confidence interval [CI], 1.02-2.75) or unwanted (aOR, 1.96; 95% CI, 1.15-3.32) pregnancy compared with normal weight women. Women with class 2 or 3 obesity were more likely to not be using contraception (aOR, 1.53-1.62; 95% CI, 1.04-2.29). Although women with class 2 obesity were more likely to be using long-acting reversible contraceptive methods and sterilization over short-acting hormonal methods (aOR, 1.67; 95% CI, 1.08-2.57; aOR, 2.05; 95% CI,1.44-2.91), this association was not observed among women with class 3 obesity. Women with class 3 obesity are at greater risk of unintended pregnancy and are less likely to be using contraception than normal weight women. Whether these findings are related to patient and/or provider barriers that are not as visible among women with class 1 and class 2 obesity warrants further investigation. Copyright © 2017 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

Analysis of the Possibilities for Discussing Questions of Global Justice in Geography Classes on the Use of Methods of Empirical Social Research When Analyzing the Teaching of Geography in Class

ERIC Educational Resources Information Center

Applis, Stefan

2015-01-01

This study examines students' orientations with regard to questions on the implementation of justice in production structures of the global textile industry. The students worked with the Mystery Method from the Thinking Through Geography approach by David Leat and with Lawrence Kohlberg's Method of Dilemma Discussion. During this process, the…

The impact of podcasting on the learning and satisfaction of undergraduate nursing students.

PubMed

Vogt, Marjorie; Schaffner, Barbara; Ribar, Alicia; Chavez, Ruth

2010-01-01

Nursing education has evolved from traditional pedagogical models to current methods using technology for knowledge acquisition. Podcasting is one example of teaching methodology used in higher education. Studies demonstrate positive student satisfaction with podcasting, but there is limited data related to knowledge acquisition. The purpose of this study was to examine the impact of podcasting on nursing student learning and satisfaction. Two classes of junior baccalaureate nursing students had scores on selected exam questions compared. The 2007 class (n=63) had select content presented in traditional lecture format where the 2008 class (n=57) had the same content presented via podcast. Both methods used the same faculty and exam questions. The 2008 class completed a satisfaction survey. Results indicated no significant difference in correct responses on exam questions. Exam scores were better with the first podcast, equal for the second, and worse with the third podcast. Students were overall satisfied with the podcasting experience and commented positively on its portability and flexibility. This study contributes to the knowledge base of podcasting effectiveness and raises the question of evaluation of new teaching methodologies. Must an increase in learning occur for new methods to be considered effective, or is positive student satisfaction adequate to encourage the adoption of new technology methods?

Flow cytometry beads rather than the antihuman globulin method should be used to detect HLA Class I IgG antibody (PRA) in cadaveric renal regraft candidates.

PubMed

Bryan, Christopher F; McDonald, Scott B; Baier, Karen A; Luger, Alan M; Aeder, Mark I; Murillo, Daniel; Muruve, Nicolas A; Nelson, Paul W; Shield, Charles F; Warady, Bradley A

2002-01-01

HLA Class I antibody screening can be performed by flow cytometry using a mixture of 30 distinct bead populations each coated with the Class I antigen phenotype derived from different cell lines. In this study we compared the efficacy of Class I antibody screens done by flow cytometry beads with the antihuman globulin (AHG) method for patients awaiting cadaveric renal retransplantation. Class I panel reactive antibody (PRA) screening by flow cytometric beads of 21 regraft serum samples that had all been found to be negative by AHG DTT Class I PRA, revealed that 57.1% (12 of 21) had a flow Class I PRA of > or = 10%. Furthermore, when five regraft sera with an intermediate PRA were screened (mean AHG DTT PRA = 33.2 +/- 13%) the mean flow Class I PRA almost doubled (mean flow PRA = 72.4 +/- 10.2%) (p < 0.01). When active UNOS waiting list regraft candidates, after several months of screening the Class I PRA by flow beads, were divided into the three PRA categories based on their peak flow Class I PRA value (0-20%, 21-79% and > or = 80%), the incidence of a positive flow cross-match was 0%, 72% and 85% and the incidence of retransplantation was 60%, 22% and 10%, in each of these groups, respectively. These data provided our histocompatibility laboratory with the rationale to stop performing the AHG PRA and perform only the flow Class I PRA method for regraft candidates.

A Convergent Parallel Mixed-Methods Study of Controversial Issues in Social Studies Classes: A Clash of Ideologies

ERIC Educational Resources Information Center

Demir, Selcuk Besir; Pismek, Nuray

2018-01-01

In today's educational landscape, social studies classes are characterized by controversial issues (CIs) that teachers handle differently using various ideologies. These CIs have become more and more popular, particularly in heterogeneous communities. The actual classroom practices for teaching social studies courses are unclear in the context of…

Implementing Communication Strategy Instruction in the ESL Oral Classroom: What Do Low-Proficiency Learners Tell Us?

ERIC Educational Resources Information Center

Lam, Wendy Y. K.

2010-01-01

This article reports findings from a strategy intervention study involving a treatment class (N=20) and a comparison class (N=20) in an ESL oral setting. Oral communication strategies were taught to the treatment class. A data-collection method comprising stimulated recall interviews that aimed to investigate respectively the learning process…

Combined Patterns of Risk for Problem and Obesogenic Behaviors in Adolescents: A Latent Class Analysis Approach

ERIC Educational Resources Information Center

Fleary, Sasha A.

2017-01-01

Background: Several studies have used latent class analyses to explore obesogenic behaviors and substance use in adolescents independently. We explored a variety of health risks jointly to identify distinct patterns of risk behaviors among adolescents. Methods: Latent class models were estimated using Youth Risk Behavior Surveillance System…

Major histocompatibility complex (MHC) class I and II alleles which confer susceptibility or protection in the Morphea in Adults and Children (MAC) cohort

PubMed Central

Jacobe, Heidi; Ahn, Chul; Arnett, Frank; Reveille, John D.

2014-01-01

Objective To determine human leukocyte antigen class I (HLA-class I) and II (HLA-class II) alleles associated with morphea (localized scleroderma) in the Morphea in Adults and Children (MAC) cohort by a nested case–control association study. Methods Morphea patients were included from MAC cohort and matched controls from the NIH/NIAMS Scleroderma Family Registry and DNA Repository and Division of Rheumatology at the University of Texas Health Science Center at Houston. HLA- Class II genotyping and SSCP typing was performed of HLA-A, -B, -C alleles. Associations between HLA-Class I and II alleles and morphea as well as its subphenotypes were determined. Results There were 211 cases available for HLA-class I typing with 726 matched controls and 158 cases available for HLA Class-II typing with 1108 matched controls. The strongest associations were found with DRB1*04:04 (OR 2.3, 95% CI 1.4–4.0 P=0.002) and HLA-B*37 conferred the highest OR among Class I alleles (3.3, 95% CI 1.6–6.9, P= 0.0016). Comparison with risk alleles in systemic sclerosis determined using the same methods and control population revealed one common allele (DRB*04:04). Conclusion Results of the present study demonstrate specific HLA Class I and II alleles are associated with morphea and likely generalized and linear subtypes. The associated morphea alleles are different than in scleroderma, implicating morphea is also immunogenetically distinct. Risk alleles in morphea are also associated with conditions such as rheumatoid arthritis (RA) and other autoimmune conditions. Population based studies indicate patients with RA have increased risk of morphea, implicating a common susceptibility allele. PMID:25223600

Evaluation of metabolites extraction strategies for identifying different brain regions and their relationship with alcohol preference and gender difference using NMR metabolomics.

PubMed

Wang, Jie; Zeng, Hao-Long; Du, Hongying; Liu, Zeyuan; Cheng, Ji; Liu, Taotao; Hu, Ting; Kamal, Ghulam Mustafa; Li, Xihai; Liu, Huili; Xu, Fuqiang

2018-03-01

Metabolomics generate a profile of small molecules from cellular/tissue metabolism, which could directly reflect the mechanisms of complex networks of biochemical reactions. Traditional metabolomics methods, such as OPLS-DA, PLS-DA are mainly used for binary class discrimination. Multiple groups are always involved in the biological system, especially for brain research. Multiple brain regions are involved in the neuronal study of brain metabolic dysfunctions such as alcoholism, Alzheimer's disease, etc. In the current study, 10 different brain regions were utilized for comparative studies between alcohol preferring and non-preferring rats, male and female rats respectively. As many classes are involved (ten different regions and four types of animals), traditional metabolomics methods are no longer efficient for showing differentiation. Here, a novel strategy based on the decision tree algorithm was employed for successfully constructing different classification models to screen out the major characteristics of ten brain regions at the same time. Subsequently, this method was also utilized to select the major effective brain regions related to alcohol preference and gender difference. Compared with the traditional multivariate statistical methods, the decision tree could construct acceptable and understandable classification models for multi-class data analysis. Therefore, the current technology could also be applied to other general metabolomics studies involving multi class data. Copyright © 2017 Elsevier B.V. All rights reserved.

An Analysis of the Design and Implementation of Elementary Science Methods Class Instruction in Colleges and Universities in Arkansas

ERIC Educational Resources Information Center

Lee, Carole K.

2010-01-01

This study aims to understand the design and implementation of elementary methods classes focused in science instruction by teacher educators in the colleges and universities in the state of Arkansas. All 18 institutions with an Early Childhood Education program approved by the Arkansas Department of Education were reviewed with interviews, site…

Do Teachers Make Decisions Like Firefighters? Applying Naturalistic Decision-Making Methods to Teachers' In-Class Decision Making in Mathematics

ERIC Educational Resources Information Center

Jazby, Dan

2014-01-01

Research into human decision making (DM) processes from outside of education paint a different picture of DM than current DM models in education. This pilot study assesses the use of critical decision method (CDM)--developed from observations of firefighters' DM -- in the context of primary mathematics teachers' in-class DM. Preliminary results…

Une nouvelle méthode de cartographie de la région d'Oran (Algérie) à l'aide de la télédétection multispectrale

NASA Astrophysics Data System (ADS)

Laoufi, Fatiha; Belbachir, Ahmed-Hafid; Benabadji, Noureddine; Zanoun, Abdelouahab

2011-10-01

We have mapped the region of Oran, Algeria, using multispectral remote sensing with different resolutions. For the identification of objects on the ground using their spectral signatures, two methods were applied to images from SPOT, LANDSAT, IRS-1 C and ASTER. The first one is called Base Rule method (BR method) and is based on a set of rules that must be met at each pixel in the different bands reflectance calibrated and henceforth it is assigned to a given class. The construction of these rules is based on the spectral profiles of popular classes in the scene studied. The second one is called Spectral Angle Mapper method (SAM method) and is based on the direct calculation of the spectral angle between the target vector representing the spectral profile of the desired class and the pixel vector whose components are numbered accounts in the different bands of the calibrated image reflectance. This new method was performed using PCSATWIN software developed by our own laboratory LAAR. After collecting a library of spectral signatures with multiple libraries, a detailed study of the principles and physical processes that can influence the spectral signature has been conducted. The final goal is to establish the range of variation of a spectral profile of a well-defined class and therefore to get precise bases for spectral rules. From the results we have obtained, we find that the supervised classification of these pixels by BR method derived from spectral signatures reduces the uncertainty associated with identifying objects by enhancing significantly the percentage of correct classification with very distinct classes.

Argumentation in Science Class: Its Planning, Practice, and Effect on Student Motivation

ERIC Educational Resources Information Center

Taneja, Anju

2016-01-01

Studies have shown an association between argumentative discourse in science class, better understanding of science concepts, and improved academic performance. However, there is lack of research on how argumentation can increase student motivation. This mixed methods concurrent nested study uses Bandura's construct of motivation and concepts of…

Detection of 224 candidate structured RNAs by comparative analysis of specific subsets of intergenic regions

PubMed Central

Lünse, Christina E.; Corbino, Keith A.; Ames, Tyler D.; Nelson, James W.; Roth, Adam; Perkins, Kevin R.; Sherlock, Madeline E.

2017-01-01

Abstract The discovery of structured non-coding RNAs (ncRNAs) in bacteria can reveal new facets of biology and biochemistry. Comparative genomics analyses executed by powerful computer algorithms have successfully been used to uncover many novel bacterial ncRNA classes in recent years. However, this general search strategy favors the discovery of more common ncRNA classes, whereas progressively rarer classes are correspondingly more difficult to identify. In the current study, we confront this problem by devising several methods to select subsets of intergenic regions that can concentrate these rare RNA classes, thereby increasing the probability that comparative sequence analysis approaches will reveal their existence. By implementing these methods, we discovered 224 novel ncRNA classes, which include ROOL RNA, an RNA class averaging 581 nt and present in multiple phyla, several highly conserved and widespread ncRNA classes with properties that suggest sophisticated biochemical functions and a multitude of putative cis-regulatory RNA classes involved in a variety of biological processes. We expect that further research on these newly found RNA classes will reveal additional aspects of novel biology, and allow for greater insights into the biochemistry performed by ncRNAs. PMID:28977401

Isotopic composition of atmospheric moisture from pan water evaporation measurements.

PubMed

Devi, Pooja; Jain, Ashok Kumar; Rao, M Someshwer; Kumar, Bhishm

2015-01-01

A continuous and reliable time series data of the stable isotopic composition of atmospheric moisture is an important requirement for the wider applicability of isotope mass balance methods in atmospheric and water balance studies. This requires routine sampling of atmospheric moisture by an appropriate technique and analysis of moisture for its isotopic composition. We have, therefore, used a much simpler method based on an isotope mass balance approach to derive the isotopic composition of atmospheric moisture using a class-A drying evaporation pan. We have carried out the study by collecting water samples from a class-A drying evaporation pan and also by collecting atmospheric moisture using the cryogenic trap method at the National Institute of Hydrology, Roorkee, India, during a pre-monsoon period. We compared the isotopic composition of atmospheric moisture obtained by using the class-A drying evaporation pan method with the cryogenic trap method. The results obtained from the evaporation pan water compare well with the cryogenic based method. Thus, the study establishes a cost-effective means of maintaining time series data of the isotopic composition of atmospheric moisture at meteorological observatories. The conclusions drawn in the present study are based on experiments conducted at Roorkee, India, and may be examined at other regions for its general applicability.

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

Acceptability and characteristics of 124 human bioequivalence studies with active substances classified according to the Biopharmaceutic Classification System

PubMed Central

Ramirez, Elena; Laosa, Olga; Guerra, Pedro; Duque, Blanca; Mosquera, Beatriz; Borobia, Alberto M; Lei, Suhua H; Carcas, Antonio J; Frias, Jesus

2010-01-01

AIM The aim of this study was to evaluate the acceptability of 124 bioequivalence (BE) studies with 80 active substances categorized according to the Biopharmaceutics Classification System (BCS) in order to establish if there were different probabilities of proving BE between the different BCS classes. METHODS We evaluated the differences between pharmaceutical products with active substances from different BCS classes in terms of acceptability, number of subjects in the study (n), the point estimates, and intra- and inter-subject coefficients of variation data from BE studies with generic products. RESULTS Out of 124 BE studies 89 (71.77%) were performed with pharmaceutical products containing active substances classified by the BCS. In all BCS classes there were non-bioequivalent pharmaceutical products: 4 out of 26 (15.38%) in class 1, 14 out of 28 (50%) in class 2, 3 out of 22 (13.63%) in class 3 and 1 out of 13 (7.69%) in class 4. When we removed those pharmaceutical products in which intra-subject variability was higher than predicted (2 in class 1 active substances, 9 in class 2 and 2 in class 3) there were still non-BE pharmaceutical products in classes 1, 2 and 3. CONCLUSIONS Comparisons between pharmaceutical products with active substances from the four BCS classes have not allowed us to define differential characteristics of each class in terms of n, inter and intra-subject variability for Cmax or AUC. Despite the usually employed test dissolution methodology proposed as quality control, pharmaceutical products with active substances from the four classes of BCS showed non-BE studies. PMID:21039763

Factors affecting the relationship between quantitative polymerase chain reaction (qPCR) and culture-based enumeration of Enterococcus in environmental waters.

PubMed

Raith, M R; Ebentier, D L; Cao, Y; Griffith, J F; Weisberg, S B

2014-03-01

To determine the extent to which discrepancies between qPCR and culture-based results in beach water quality monitoring can be attributed to: (i) within-method variability, (ii) between-method difference within each method class (qPCR or culture) and (iii) between-class difference. We analysed 306 samples using two culture-based (EPA1600 and Enterolert) and two qPCR (Taqman and Scorpion) methods, each in duplicate. Both qPCR methods correlated with EPA1600, but regression analyses indicated approximately 0·8 log10 unit overestimation by qPCR compared to culture methods. Differences between methods within a class were less than half of this and were minimal for between-replicate within a method. Using the 104 Enterococcus per 100 ml management decision threshold, Taqman qPCR indicated the same decisions as EPA1600 for 87% of the samples, but indicated beach posting for unhealthful water when EPA1600 did not for 12% of the samples. After accounting for within-method and within-class variability, 8% of the samples exhibited true between-class discrepancy where both qPCR methods indicated beach posting while both culture methods did not. Measurement target difference (DNA vs growth) accounted for the majority of the qPCR-vs-culture discrepancy, but its influence on monitoring application is outweighed by frequent incorrect posting with culture methods due to incubation time delay. This is the first study to quantify the frequency with which culture-vs-qPCR discrepancies can be attributed to target difference - vs - method variability. © 2013 The Society for Applied Microbiology.

The Relationship between Attention Levels and Class Participation of First-Year Students in Classroom Teaching Departments

ERIC Educational Resources Information Center

Sezer, Adem; Inel, Yusuf; Seçkin, Ahmet Çagdas; Uluçinar, Ufuk

2017-01-01

This study aimed to detect any relationship that may exist between classroom teacher candidates' class participation and their attention levels. The research method was a convergent parallel design, mixing quantitative and qualitative research techniques, and the study group was composed of 21 freshmen studying in the Classroom Teaching Department…

The Views of Class Teachers on Acquisition of Entrepreneurship Ability

ERIC Educational Resources Information Center

Aladag, Soner

2017-01-01

Aim of this study is to determine the views of class teachers on the acquisition of entrepreneurship abilities. With being a qualitative research, adopted approach is phenomenology. Study group was determined by a suitable sampling method. The study group included eight classroom teachers working in primary schools in Aydin. The data of the study…

Patterns of Adolescent Sexual Behavior Predicting Young Adult Sexually Transmitted Infections: A Latent Class Analysis Approach

PubMed Central

Vasilenko, Sara A.; Kugler, Kari C.; Butera, Nicole M.; Lanza, Stephanie T.

2014-01-01

Adolescent sexual behavior is multidimensional, yet most studies of the topic use variable-oriented methods that reduce behaviors to a single dimension. In this study, we used a person-oriented approach to model adolescent sexual behavior comprehensively, using data from the National Longitudinal Study of Adolescent Health. We identified five latent classes of adolescent sexual behavior: Abstinent (39%), Oral Sex (10%), Low-Risk (25%), Multi-Partner Normative (12%), and Multi-Partner Early (13%). Membership in riskier classes of sexual behavior was predicted by substance use and depressive symptoms. Class membership was also associated with young adult STI outcomes although these associations differed by gender. Male adolescents' STI rates increased with membership in classes with more risky behaviors whereas females' rates were consistent among all sexually active classes. These findings demonstrate the advantages of examining adolescent sexuality in a way that emphasizes its complexity. PMID:24449152

Patterns of adolescent sexual behavior predicting young adult sexually transmitted infections: a latent class analysis approach.

PubMed

Vasilenko, Sara A; Kugler, Kari C; Butera, Nicole M; Lanza, Stephanie T

2015-04-01

Adolescent sexual behavior is multidimensional, yet most studies of the topic use variable-oriented methods that reduce behaviors to a single dimension. In this study, we used a person-oriented approach to model adolescent sexual behavior comprehensively, using data from the National Longitudinal Study of Adolescent Health. We identified five latent classes of adolescent sexual behavior: Abstinent (39%), Oral Sex (10%), Low-Risk (25%), Multi-Partner Normative (12%), and Multi-Partner Early (13%). Membership in riskier classes of sexual behavior was predicted by substance use and depressive symptoms. Class membership was also associated with young adult STI outcomes although these associations differed by gender. Male adolescents' STI rates increased with membership in classes with more risky behaviors whereas females' rates were consistent among all sexually active classes. These findings demonstrate the advantages of examining adolescent sexuality in a way that emphasizes its complexity.

Nontargeted quantitation of lipid classes using hydrophilic interaction liquid chromatography-electrospray ionization mass spectrometry with single internal standard and response factor approach.

PubMed

Cífková, Eva; Holčapek, Michal; Lísa, Miroslav; Ovčačíková, Magdaléna; Lyčka, Antonín; Lynen, Frédéric; Sandra, Pat

2012-11-20

The identification and quantitation of a wide range of lipids in complex biological samples is an essential requirement for the lipidomic studies. High-performance liquid chromatography-mass spectrometry (HPLC/MS) has the highest potential to obtain detailed information on the whole lipidome, but the reliable quantitation of multiple lipid classes is still a challenging task. In this work, we describe a new method for the nontargeted quantitation of polar lipid classes separated by hydrophilic interaction liquid chromatography (HILIC) followed by positive-ion electrospray ionization mass spectrometry (ESI-MS) using a single internal lipid standard to which all class specific response factors (RFs) are related to. The developed method enables the nontargeted quantitation of lipid classes and molecules inside these classes in contrast to the conventional targeted quantitation, which is based on predefined selected reaction monitoring (SRM) transitions for selected lipids only. In the nontargeted quantitation method described here, concentrations of lipid classes are obtained by the peak integration in HILIC chromatograms multiplied by their RFs related to the single internal standard (i.e., sphingosyl PE, d17:1/12:0) used as common reference for all polar lipid classes. The accuracy, reproducibility and robustness of the method have been checked by various means: (1) the comparison with conventional lipidomic quantitation using SRM scans on a triple quadrupole (QqQ) mass analyzer, (2) (31)P nuclear magnetic resonance (NMR) quantitation of the total lipid extract, (3) method robustness test using subsequent measurements by three different persons, (4) method transfer to different HPLC/MS systems using different chromatographic conditions, and (5) comparison with previously published results for identical samples, especially human reference plasma from the National Institute of Standards and Technology (NIST human plasma). Results on human plasma, egg yolk and porcine liver extracts are presented and discussed.

Enhancement of Self Efficacy of Vocational School Students in Buffer Solution Topics through Guided Inquiry Learning

NASA Astrophysics Data System (ADS)

M, Ardiany; W, Wahyu; A, Supriatna

2017-09-01

The more students who feel less confident in learning, so doing things that are less responsible, such as brawl, drunkenness and others. So researchers need to do research related to student self efficacy in learning, in order to reduce unwanted things. This study aims to determine the effect of guided inquiry learning on improving self-efficacy of learners in the buffer solution topics. The method used is the mixed method which is the two group pretest postest design. The subjects of the study are 60 students of class XI AK in one of the SMKN in Bandung, consisting of 30 experimental class students and 30 control class students. The instruments used in this study mix method consist of self-efficacy questionnaire of pretest and posttest learners, interview guides, and observation sheet. Data analysis using t test with significant α = 0,05. Based on the result of inquiry of guided inquiry study, there is a significant improvement in self efficacy aspect of students in the topic of buffer solution. Data of pretest and posttest interview, observation, questionnaire showed significant result, that is improvement of experimental class with conventionally guided inquiry learning. The mean of self-efficacy of student learning there is significant difference of experiment class than control class equal to 0,047. There is a significant relationship between guided inquiry learning with self efficacy and guided inquiry learning. Each correlation value is 0.737. The learning process with guided inquiry is fun and challenging so that students can expose their ideas and opinions without being forced. From the results of questionnaires students showed an attitude of interest, sincerity and a good response of learning. While the results of questionnaires teachers showed that guided inquiry learning can make students learn actively, increased self-efficacy.

Exploring Latent Class Based on Growth Rates in Number Sense Ability

ERIC Educational Resources Information Center

Kim, Dongil; Shin, Jaehyun; Lee, Kijyung

2013-01-01

The purpose of this study was to explore latent class based on growth rates in number sense ability by using latent growth class modeling (LGCM). LGCM is one of the noteworthy methods for identifying growth patterns of the progress monitoring within the response to intervention framework in that it enables us to analyze latent sub-groups based not…

Studying Biotechnological Methods Using Animations: The Teacher's Role

NASA Astrophysics Data System (ADS)

Yarden, Hagit; Yarden, Anat

2011-12-01

Animation has great potential for improving the way people learn. A number of studies in different scientific disciplines have shown that instruction involving computer animations can facilitate the understanding of processes at the molecular level. However, using animation alone does not ensure learning. Students sometimes miss essential features when they watch only animations, mainly due to the cognitive load involved. Moreover, students seem to attribute a great deal of authority to the computer and may develop misconceptions by taking animations of abstract concepts too literally. In this study, we attempted to explore teachers' perceptions concerning the use of animations in the classroom while studying biotechnological methods, as well as the teachers' contribution to the enactment of animations in class. Thirty high-school biotechnology teachers participated in a professional development workshop, aimed at investigating how teachers plan for and support learning with animation while studying biotechnological methods in class. From that sample, two teachers agreed to participate in two case studies aimed at characterizing teachers' contribution to the enactment of animations in class while studying biotechnological methods. Our findings reveal marked teacher contribution in the following three aspects: establishing the "hands-on" point of view, helping students deal with the cognitive load that accompanies the use of animation, and implementing constructivist aspects of knowledge construction while studying using animations.

The Effect of the 5E Instructional Model Enriched with Cooperative Learning and Animations on Seventh-Grade Students' Academic Achievement and Scientific Attitudes

ERIC Educational Resources Information Center

Dasdemir, Ikramettin

2016-01-01

The aim of this research is to determine the effect of the different teaching methods, on seventh-grade students' academic achievement and scientific attitudes. The research was carried out using quasi-experimental methods. The research sample consisted of 84 seventh grade students studying in three different classes. One of these classes an…

Applying Blended Learning with Web-Mediated Self-Regulated Learning to Enhance Vocational Students' Computing Skills and Attention to Learn

ERIC Educational Resources Information Center

Shen, Pei-Di; Lee, Tsang-Hsiung; Tsai, Chia-Wen

2011-01-01

Students in the vocational schools in Taiwan largely care little about their grades and do not get involved adequately in their schoolwork. To respond effectively to this challenge of teaching, two cases were studied and compared; one is a class using a traditional method of teaching and the other a class deploying innovative teaching methods of…

Comparison of transect sampling and object-oriented image classification methods of urbanizing catchments

NASA Astrophysics Data System (ADS)

Yang, Y.; Tenenbaum, D. E.

2009-12-01

The process of urbanization has major effects on both human and natural systems. In order to monitor these changes and better understand how urban ecological systems work, urban spatial structure and the variation needs to be first quantified at a fine scale. Because the land-use and land-cover (LULC) in urbanizing areas is highly heterogeneous, the classification of urbanizing environments is the most challenging field in remote sensing. Although a pixel-based method is a common way to do classification, the results are not good enough for many research objectives which require more accurate classification data in fine scales. Transect sampling and object-oriented classification methods are more appropriate for urbanizing areas. Tenenbaum used a transect sampling method using a computer-based facility within a widely available commercial GIS in the Glyndon Catchment and the Upper Baismans Run Catchment, Baltimore, Maryland. It was a two-tiered classification system, including a primary level (which includes 7 classes) and a secondary level (which includes 37 categories). The statistical information of LULC was collected. W. Zhou applied an object-oriented method at the parcel level in Gwynn’s Falls Watershed which includes the two previously mentioned catchments and six classes were extracted. The two urbanizing catchments are located in greater Baltimore, Maryland and drain into Chesapeake Bay. In this research, the two different methods are compared for 6 classes (woody, herbaceous, water, ground, pavement and structure). The comparison method uses the segments in the transect method to extract LULC information from the results of the object-oriented method. Classification results were compared in order to evaluate the difference between the two methods. The overall proportions of LULC classes from the two studies show that there is overestimation of structures in the object-oriented method. For the other five classes, the results from the two methods are similar, except for a difference in the proportions of the woody class. The segment to segment comparison shows that the resolution of the light detection and ranging (LIDAR) data used in the object-oriented method does affect the accuracy of the classification. Shadows of trees and structures are still a big problem in the object-oriented method. For classes that make up a small proportion of the catchments, such as water, neither method was capable of detecting them.

Co-streaming classes: a follow-up study in improving the user experience to better reach users.

PubMed

Hayes, Barrie E; Handler, Lara J; Main, Lindsey R

2011-01-01

Co-streaming classes have enabled library staff to extend open classes to distance education students and other users. Student evaluations showed that the model could be improved. Two areas required attention: audio problems experienced by online participants and staff teaching methods. Staff tested equipment and adjusted software configuration to improve user experience. Staff training increased familiarity with specialized teaching techniques and troubleshooting procedures. Technology testing and staff training were completed, and best practices were developed and applied. Class evaluations indicate improvements in classroom experience. Future plans include expanding co-streaming to more classes and on-going data collection, evaluation, and improvement of classes.

Development and Effectiveness of an Educational Card Game as Supplementary Material in Understanding Selected Topics in Biology

PubMed Central

Gutierrez, Arnel F.

2014-01-01

The complex concepts and vocabulary of biology classes discourage many students. In this study, a pretest–posttest model was used to test the effectiveness of an educational card game in reinforcing biological concepts in comparison with traditional teaching methods. The subjects of this study were two biology classes at Bulacan State University–Sarmiento Campus. Both classes received conventional instruction; however, the experimental group's instruction was supplemented with the card game, while the control group's instruction was reinforced with traditional exercises and assignments. The score increases from pretest to posttest showed that both methods effectively reinforced biological concepts, but a t test showed that the card game is more effective than traditional teaching methods. Additionally, students from the experimental group evaluated the card game using five criteria: goals, design, organization, playability, and usefulness. The students rated the material very satisfactory. PMID:24591506

Development and effectiveness of an educational card game as supplementary material in understanding selected topics in biology.

PubMed

Gutierrez, Arnel F

2014-01-01

The complex concepts and vocabulary of biology classes discourage many students. In this study, a pretest-posttest model was used to test the effectiveness of an educational card game in reinforcing biological concepts in comparison with traditional teaching methods. The subjects of this study were two biology classes at Bulacan State University-Sarmiento Campus. Both classes received conventional instruction; however, the experimental group's instruction was supplemented with the card game, while the control group's instruction was reinforced with traditional exercises and assignments. The score increases from pretest to posttest showed that both methods effectively reinforced biological concepts, but a t test showed that the card game is more effective than traditional teaching methods. Additionally, students from the experimental group evaluated the card game using five criteria: goals, design, organization, playability, and usefulness. The students rated the material very satisfactory.

A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data.

PubMed

Collell, Guillem; Prelec, Drazen; Patil, Kaustubh R

2018-01-31

Class imbalance presents a major hurdle in the application of classification methods. A commonly taken approach is to learn ensembles of classifiers using rebalanced data. Examples include bootstrap averaging (bagging) combined with either undersampling or oversampling of the minority class examples. However, rebalancing methods entail asymmetric changes to the examples of different classes, which in turn can introduce their own biases. Furthermore, these methods often require specifying the performance measure of interest a priori, i.e., before learning. An alternative is to employ the threshold moving technique, which applies a threshold to the continuous output of a model, offering the possibility to adapt to a performance measure a posteriori , i.e., a plug-in method. Surprisingly, little attention has been paid to this combination of a bagging ensemble and threshold-moving. In this paper, we study this combination and demonstrate its competitiveness. Contrary to the other resampling methods, we preserve the natural class distribution of the data resulting in well-calibrated posterior probabilities. Additionally, we extend the proposed method to handle multiclass data. We validated our method on binary and multiclass benchmark data sets by using both, decision trees and neural networks as base classifiers. We perform analyses that provide insights into the proposed method.

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

Mining for class-specific motifs in protein sequence classification

PubMed Central

2013-01-01

Background In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms. PMID:23496846

Heterogeneity in risk of prostate cancer: A Swedish population-based cohort study of competing risks and type 2 diabetes mellitus.

PubMed

Häggström, Christel; Van Hemelrijck, Mieke; Garmo, Hans; Robinson, David; Stattin, Pär; Rowley, Mark; Coolen, Anthony C C; Holmberg, Lars

2018-05-09

Most previous studies of prostate cancer have not taken into account that men in the studied populations are also at risk of competing event, and that these men may have different susceptibility to prostate cancer risk. The aim of this study was to investigate heterogeneity in risk of prostate cancer, using a recently developed latent class regression method for competing risks. We further aimed to elucidate the association between type 2 diabetes mellitus (T2DM) and prostate cancer risk, and to compare the results with conventional methods for survival analysis. We analysed the risk of prostate cancer in 126,482 men from the comparison cohort of the Prostate Cancer Data base Sweden (PCBaSe) 3.0. During a mean follow-up of 6 years 6,036 men were diagnosed with prostate cancer and 22,393 men died. We detected heterogeneity in risk of prostate cancer with two distinct latent classes in the study population. The smaller class included 9% of the study population in which men had a higher risk of prostate cancer and the risk was stronger associated with class membership than any of the covariates included in the study. Moreover, we found no association between T2DM and risk of prostate cancer after removal of the effect of informative censoring due to competing risks. The recently developed latent class for competing risks method could be used to provide new insights in precision medicine with the target to classify individuals regarding different susceptibility to a particular disease, reaction to a risk factor or response to treatment. This article is protected by copyright. All rights reserved. © 2018 UICC.

A COMPUTER DOCKING STUDY OF THE BINDING OF POLYCYCLIC AROMATIC HYDROCARBONS AND THEIR METABOLITES TO THE LIGARD-BINDING DOMAIN OF THE ESTROGEN RECEPTOR

EPA Science Inventory

Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous, anthropogenic chemicals found in the environment. In the present study, computational methods are used to evaluate their potential estrogenicity and the contribution chemicals in this class make to environmental e...

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.

Purely in silico BCS classification: science based quality standards for the world's drugs.

PubMed

Dahan, Arik; Wolk, Omri; Kim, Young Hoon; Ramachandran, Chandrasekharan; Crippen, Gordon M; Takagi, Toshihide; Bermejo, Marival; Amidon, Gordon L

2013-11-04

BCS classification is a vital tool in the development of both generic and innovative drug products. The purpose of this work was to provisionally classify the world's top selling oral drugs according to the BCS, using in silico methods. Three different in silico methods were examined: the well-established group contribution (CLogP) and atom contribution (ALogP) methods, and a new method based solely on the molecular formula and element contribution (KLogP). Metoprolol was used as the benchmark for the low/high permeability class boundary. Solubility was estimated in silico using a thermodynamic equation that relies on the partition coefficient and melting point. The validity of each method was affirmed by comparison to reference data and literature. We then used each method to provisionally classify the orally administered, IR drug products found in the WHO Model list of Essential Medicines, and the top-selling oral drug products in the United States (US), Great Britain (GB), Spain (ES), Israel (IL), Japan (JP), and South Korea (KR). A combined list of 363 drugs was compiled from the various lists, and 257 drugs were classified using the different in silico permeability methods and literature solubility data, as well as BDDCS classification. Lastly, we calculated the solubility values for 185 drugs from the combined set using in silico approach. Permeability classification with the different in silico methods was correct for 69-72.4% of the 29 reference drugs with known human jejunal permeability, and for 84.6-92.9% of the 14 FDA reference drugs in the set. The correlations (r(2)) between experimental log P values of 154 drugs and their CLogP, ALogP and KLogP were 0.97, 0.82 and 0.71, respectively. The different in silico permeability methods produced comparable results: 30-34% of the US, GB, ES and IL top selling drugs were class 1, 27-36.4% were class 2, 22-25.5% were class 3, and 5.46-14% were class 4 drugs, while ∼8% could not be classified. The WHO list included significantly less class 1 and more class 3 drugs in comparison to the countries' lists, probably due to differences in commonly used drugs in developing vs industrial countries. BDDCS classified more drugs as class 1 compared to in silico BCS, likely due to the more lax benchmark for metabolism (70%), in comparison to the strict permeability benchmark (metoprolol). For 185 out of the 363 drugs, in silico solubility values were calculated, and successfully matched the literature solubility data. In conclusion, relatively simple in silico methods can be used to estimate both permeability and solubility. While CLogP produced the best correlation to experimental values, even KLogP, the most simplified in silico method that is based on molecular formula with no knowledge of molecular structure, produced comparable BCS classification to the sophisticated methods. This KLogP, when combined with a mean melting point and estimated dose, can be used to provisionally classify potential drugs from just molecular formula, even before synthesis. 49-59% of the world's top-selling drugs are highly soluble (class 1 and class 3), and are therefore candidates for waivers of in vivo bioequivalence studies. For these drugs, the replacement of expensive human studies with affordable in vitro dissolution tests would ensure their bioequivalence, and encourage the development and availability of generic drug products in both industrial and developing countries.

Comparing the Performance of Improved Classify-Analyze Approaches For Distal Outcomes in Latent Profile Analysis

PubMed Central

Dziak, John J.; Bray, Bethany C.; Zhang, Jieting; Zhang, Minqiang; Lanza, Stephanie T.

2016-01-01

Several approaches are available for estimating the relationship of latent class membership to distal outcomes in latent profile analysis (LPA). A three-step approach is commonly used, but has problems with estimation bias and confidence interval coverage. Proposed improvements include the correction method of Bolck, Croon, and Hagenaars (BCH; 2004), Vermunt’s (2010) maximum likelihood (ML) approach, and the inclusive three-step approach of Bray, Lanza, & Tan (2015). These methods have been studied in the related case of latent class analysis (LCA) with categorical indicators, but not as well studied for LPA with continuous indicators. We investigated the performance of these approaches in LPA with normally distributed indicators, under different conditions of distal outcome distribution, class measurement quality, relative latent class size, and strength of association between latent class and the distal outcome. The modified BCH implemented in Latent GOLD had excellent performance. The maximum likelihood and inclusive approaches were not robust to violations of distributional assumptions. These findings broadly agree with and extend the results presented by Bakk and Vermunt (2016) in the context of LCA with categorical indicators. PMID:28630602

A Framework for Estimating Causal Effects in Latent Class Analysis: Is There a Causal Link Between Early Sex and Subsequent Profiles of Delinquency?

PubMed Central

Lanza, Stephanie T.; Coffman, Donna L.

2013-01-01

Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p=0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p=0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work. PMID:23839479

A framework for estimating causal effects in latent class analysis: is there a causal link between early sex and subsequent profiles of delinquency?

PubMed

Butera, Nicole M; Lanza, Stephanie T; Coffman, Donna L

2014-06-01

Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p = 0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p = 0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work.

The Effects of Incorporating Web-assisted Learning with Team Teaching in Seventh-grade Science Classes

NASA Astrophysics Data System (ADS)

Jang, Syh-Jong

2006-05-01

Due to the implementation of a 9-year integrated curriculum scheme in Taiwan, research on team teaching and web-based technology appears to be urgent. The purpose of this study was incorporated web-assisted learning with team teaching in seventh-grade science classes. The specific research question concerned student performance and attitudes about the teaching method. Two certified science teachers and four classes of the seventh graders participated in this study. It used a mixed methods design, incorporating both quantitative and qualitative techniques. The main data included students’ scores, questionnaires, teachers’ self-reflections, and the researcher’s interviews with teachers. The results showed that the average final examination scores of students experiencing the experimental teaching method were higher than that of those receiving traditional teaching. The two teaching methods showed significant difference in respect of students’ achievement. The research had limitations because of students’ abilities of data collection, computer use, and discussion, but more than one-half of the students preferred the experimental method to traditional teaching. However, team teachers would encounter the problems of technology ability, time constraints, and entrance examination pressure.

Designing Class Methods from Dataflow Diagrams

NASA Astrophysics Data System (ADS)

Shoval, Peretz; Kabeli-Shani, Judith

A method for designing the class methods of an information system is described. The method is part of FOOM - Functional and Object-Oriented Methodology. In the analysis phase of FOOM, two models defining the users' requirements are created: a conceptual data model - an initial class diagram; and a functional model - hierarchical OO-DFDs (object-oriented dataflow diagrams). Based on these models, a well-defined process of methods design is applied. First, the OO-DFDs are converted into transactions, i.e., system processes that supports user task. The components and the process logic of each transaction are described in detail, using pseudocode. Then, each transaction is decomposed, according to well-defined rules, into class methods of various types: basic methods, application-specific methods and main transaction (control) methods. Each method is attached to a proper class; messages between methods express the process logic of each transaction. The methods are defined using pseudocode or message charts.

Students concept understanding of fluid static based on the types of teaching

NASA Astrophysics Data System (ADS)

Rahmawati, I. D.; Suparmi; Sunarno, W.

2018-03-01

This research aims to know the concept understanding of student are taught by guided inquiry based learning and conventional based learning. Subjects in this study are high school students as much as 2 classes and each class consists of 32 students, both classes are homogen. The data was collected by conceptual test in the multiple choice form with the students argumentation of the answer. The data analysis used is qualitative descriptive method. The results of the study showed that the average of class that was using guided inquiry based learning is 78.44 while the class with use conventional based learning is 65.16. Based on these data, the guided inquiry model is an effective learning model used to improve students concept understanding.

Analysis, Occurrence and Toxicity of Haloacetaldehydes in ...

EPA Pesticide Factsheets

Chlorinated and brominated haloacetaldehydes (HALs) are consideredthe 3rd largest class of disinfection by-products (DBPs) by weight. The iodinatedHAL, iodoacetaldehyde, has been recently reported as an emerging DBP infinished drinking waters. Overall, iodinated DBPs, e.g., iodoacetic acids,iodoacetamides, and iodonitriles, are among the most genotoxic of all DBPsidentified. In this context, this chapter reviews the analytical methods available todate to determine HALs in water, and the concentrations at which they are presentin finished drinking waters. Since systematic toxicological effects have been onlyinvestigated for selected chloro- and bromo- HALs, a comparative study of thegenotoxicity and cytotoxicity of this DBP class to mammalian ce11s is alsopresented. This research is part of the Safe and Sustainable Water Research (SSWR) Program, specifically SSWR 2.2.D, which focuses on water contaminants. Haloacetaldehydes are an important class of emerging (non-regulated), disinfection byproducts. Haloacetaldehydes were the third largest disinfection byproduct class by weight in a U.S. Nationwide DBP Occurrence Study. Why was this study done? This study was done because a) improved analytical methods are needed for the haloacetaldehyde disinfection byproducts; b) occurrence data in drinking water are needed; and c) in vitro toxicology data on the class (iodo-, bromo, chloro-) of the haloacetaldehydes are lacking. What is the impact to the scientific field in ge

A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.

PubMed

Chen, Lei; Lu, Jing; Zhang, Ning; Huang, Tao; Cai, Yu-Dong

2014-04-01

In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.

Runtime Support for Type-Safe Dynamic Java Classes

DTIC Science & Technology

2000-01-01

Section 4.3. For each dynamic class C, we create a proxy class, Cproxy, and an implementation class, Cimp . In order to wrap method calls, Cproxy...wrapper method (W) and a reference to the associated method body (M). W explicitly invokes M, which points to the corresponding method body in Cimp ...When C’s implementation Cimp is switched, M is updated to point to the corresponding method object in the new C imp. Cproxy also contains a reference

Pre-Teacher Case Study Analysis of Teaching Life and Earth Science in Multicultural Middle School Classes.

ERIC Educational Resources Information Center

McGinnis, J. Randy

Intending teachers in two science education methods classes (Fall Quarter, n=27; Spring Quarter, n=21) read and discussed a qualitative study describing science teaching and learning in a culturally diverse middle school. The two primary participants in the qualitative study were a white female veteran life science teacher and a white male…

Understanding the Effect of Response Rate and Class Size Interaction on Students Evaluation of Teaching in a Higher Education

ERIC Educational Resources Information Center

Al Kuwaiti, Ahmed; AlQuraan, Mahmoud; Subbarayalu, Arun Vijay

2016-01-01

Objective: This study aims to investigate the interaction between response rate and class size and its effects on students' evaluation of instructors and the courses offered at a higher education Institution in Saudi Arabia. Study Design: A retrospective study design was chosen. Methods: One thousand four hundred and forty four different courses…

A pragmatic comparison of two diabetes education programs in improving type 2 diabetes mellitus outcomes.

PubMed

Dorland, Katherine; Liddy, Clare

2014-03-28

Although it is clear that education programs constitute key elements of improved diabetes management, uncertainty exists regarding the optimal method of delivering that education. In addition to the lack of consensus regarding the most appropriate delivery methods for these programs, there is a paucity of research which evaluates these methods in terms of specific clinical outcomes. This pragmatic study compares the effectiveness of two distinct diabetes education programs in improving clinical outcomes in patients with type 2 diabetes mellitus in a primary care setting. The two diabetes education classes (n = 80 enrolled) retrospectively evaluated were 'the ABC's of Diabetes' (one 2-hour didactic teaching session) and 'Conversation Maps' (3 highly interactive weekly classes, 6 hours in total). Eligible participants (n = 32) had their charts reviewed and outcome measures (i.e., glycosylated hemoglobin levels (HbA1c), low density lipoprotein (LDL), systolic blood pressure (SBP), diastolic blood pressure (DBP), and weight) recorded 1 year prior to and 6 months following the class. Pre- and post-class outcome measures were compared. A trend towards lower HbA1c was observed after completion of both classes, with an average reduction of 0.2%, and 0.6% after 6 months in the 'ABC's of Diabetes' class and 'Conversation Maps' class respectively. A significant decrease in weight was observed 6 months after the 'ABC's of Diabetes' class (p = 0.028), and in LDL after the 'Conversation Maps' class (p = 0.049). Patients with HbA1c ≥ 8% showed a drop of 1.1% in HbA1c 3 months after either class (p = 0.004). No significant difference in outcomes was found between the two diabetes education classes assessed. There was a trend towards improved glycemic control after both classes, and patients with high HbA1c levels demonstrated statistically significant improvements. This indicates that shorter sessions using didactic teaching methods may be equally effective in producing improvements in diabetes self-management as more intensive course formats.

The Effect of Classroom Amplification on the Signal-to-Noise Ratio in Classrooms while Class Is in Session

ERIC Educational Resources Information Center

Larsen, Jeffery B.; Blair, James C.

2008-01-01

Purpose: The purpose of this study was to measure the signal-to-noise ratios in classrooms while class was in session and students were interacting with the teacher and each other. Method: Measurements of noise and reverberation were collected for 5 different classrooms in 3 different schools while class was in session. Activities taking place…

Initial study of Schroedinger eigenmaps for spectral target detection

NASA Astrophysics Data System (ADS)

Dorado-Munoz, Leidy P.; Messinger, David W.

2016-08-01

Spectral target detection refers to the process of searching for a specific material with a known spectrum over a large area containing materials with different spectral signatures. Traditional target detection methods in hyperspectral imagery (HSI) require assuming the data fit some statistical or geometric models and based on the model, to estimate parameters for defining a hypothesis test, where one class (i.e., target class) is chosen over the other classes (i.e., background class). Nonlinear manifold learning methods such as Laplacian eigenmaps (LE) have extensively shown their potential use in HSI processing, specifically in classification or segmentation. Recently, Schroedinger eigenmaps (SE), which is built upon LE, has been introduced as a semisupervised classification method. In SE, the former Laplacian operator is replaced by the Schroedinger operator. The Schroedinger operator includes by definition, a potential term V that steers the transformation in certain directions improving the separability between classes. In this regard, we propose a methodology for target detection that is not based on the traditional schemes and that does not need the estimation of statistical or geometric parameters. This method is based on SE, where the potential term V is taken into consideration to include the prior knowledge about the target class and use it to steer the transformation in directions where the target location in the new space is known and the separability between target and background is augmented. An initial study of how SE can be used in a target detection scheme for HSI is shown here. In-scene pixel and spectral signature detection approaches are presented. The HSI data used comprise various target panels for testing simultaneous detection of multiple objects with different complexities.

Drug-target interaction prediction via class imbalance-aware ensemble learning.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2016-12-22

Multiple computational methods for predicting drug-target interactions have been developed to facilitate the drug discovery process. These methods use available data on known drug-target interactions to train classifiers with the purpose of predicting new undiscovered interactions. However, a key challenge regarding this data that has not yet been addressed by these methods, namely class imbalance, is potentially degrading the prediction performance. Class imbalance can be divided into two sub-problems. Firstly, the number of known interacting drug-target pairs is much smaller than that of non-interacting drug-target pairs. This imbalance ratio between interacting and non-interacting drug-target pairs is referred to as the between-class imbalance. Between-class imbalance degrades prediction performance due to the bias in prediction results towards the majority class (i.e. the non-interacting pairs), leading to more prediction errors in the minority class (i.e. the interacting pairs). Secondly, there are multiple types of drug-target interactions in the data with some types having relatively fewer members (or are less represented) than others. This variation in representation of the different interaction types leads to another kind of imbalance referred to as the within-class imbalance. In within-class imbalance, prediction results are biased towards the better represented interaction types, leading to more prediction errors in the less represented interaction types. We propose an ensemble learning method that incorporates techniques to address the issues of between-class imbalance and within-class imbalance. Experiments show that the proposed method improves results over 4 state-of-the-art methods. In addition, we simulated cases for new drugs and targets to see how our method would perform in predicting their interactions. New drugs and targets are those for which no prior interactions are known. Our method displayed satisfactory prediction performance and was able to predict many of the interactions successfully. Our proposed method has improved the prediction performance over the existing work, thus proving the importance of addressing problems pertaining to class imbalance in the data.

Dealing with contaminated datasets: An approach to classifier training

NASA Astrophysics Data System (ADS)

Homenda, Wladyslaw; Jastrzebska, Agnieszka; Rybnik, Mariusz

2016-06-01

The paper presents a novel approach to classification reinforced with rejection mechanism. The method is based on a two-tier set of classifiers. First layer classifies elements, second layer separates native elements from foreign ones in each distinguished class. The key novelty presented here is rejection mechanism training scheme according to the philosophy "one-against-all-other-classes". Proposed method was tested in an empirical study of handwritten digits recognition.

Do Plants Contain G Protein-Coupled Receptors?1[C][W][OPEN

PubMed Central

Taddese, Bruck; Upton, Graham J.G.; Bailey, Gregory R.; Jordan, Siân R.D.; Abdulla, Nuradin Y.; Reeves, Philip J.; Reynolds, Christopher A.

2014-01-01

Whether G protein-coupled receptors (GPCRs) exist in plants is a fundamental biological question. Interest in deorphanizing new GPCRs arises because of their importance in signaling. Within plants, this is controversial, as genome analysis has identified 56 putative GPCRs, including G protein-coupled receptor1 (GCR1), which is reportedly a remote homolog to class A, B, and E GPCRs. Of these, GCR2 is not a GPCR; more recently, it has been proposed that none are, not even GCR1. We have addressed this disparity between genome analysis and biological evidence through a structural bioinformatics study, involving fold recognition methods, from which only GCR1 emerges as a strong candidate. To further probe GCR1, we have developed a novel helix-alignment method, which has been benchmarked against the class A-class B-class F GPCR alignments. In addition, we have presented a mutually consistent set of alignments of GCR1 homologs to class A, class B, and class F GPCRs and shown that GCR1 is closer to class A and/or class B GPCRs than class A, class B, or class F GPCRs are to each other. To further probe GCR1, we have aligned transmembrane helix 3 of GCR1 to each of the six GPCR classes. Variability comparisons provide additional evidence that GCR1 homologs have the GPCR fold. From the alignments and a GCR1 comparative model, we have identified motifs that are common to GCR1, class A, B, and E GPCRs. We discuss the possibilities that emerge from this controversial evidence that GCR1 has a GPCR fold. PMID:24246381

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.

40 CFR Table E-1 to Subpart E of... - Summary of Test Requirements for Reference and Class I Equivalent Methods for PM2.5 and PM10-2.5

Code of Federal Regulations, 2010 CFR

2010-07-01

... Reference and Class I Equivalent Methods for PM2.5 and PM10-2.5 E Table E-1 to Subpart E of Part 53... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM2.5 or PM10â2.5 Pt. 53...

Putting the person back into psychopathology: an intervention to reduce mental illness stigma in the classroom.

PubMed

Mann, Caroline E; Himelein, Melissa J

2008-07-01

This research aims to compare the effectiveness of two methods of teaching psychopathology in reducing stigma toward mental illness. Based on previous stigma research, a first-person, narrative approach was contrasted with traditional, diagnosis-centered education. STUDY 1 Participants consisted of 53 undergraduates at a small, public university enrolled in two introductory psychology classes. During six hours of class time focused on psychopathology, one class received the experimental pedagogy while the other served as a control, receiving traditional instruction. Stigma was assessed pre- and post-intervention using a social distance scale and vignette design. Statistical analyses compared means and change scores between the two classes. STUDY 1 Students in the experimental classroom showed a significant decrease in stigma following the intervention, whereas those in the control group showed no change. STUDY 2 A follow-up study was conducted to replicate the promising effects demonstrated in Study 1. Two additional classrooms (n = 48) were both exposed to the first-person, narrative pedagogy, and their stigma monitored pre- and post- intervention. STUDY 2 Students reported a significant decrease in stigma following the intervention. Together, these studies suggest that traditional methods of teaching psychopathology do not lessen mental illness stigma, a serious concern that can potentially be reconciled by incorporating more person-centered instructional methods. Results are discussed in terms of their implications for the way psychopathology is taught throughout the mental health field, as well as the practical application of stigma interventions woven into the curriculum.

Inter-class sparsity based discriminative least square regression.

PubMed

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

2018-06-01

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

Classes of Physical Activity and Sedentary Behavior in 5th Grade Children

PubMed Central

Dowda, Marsha; Dishman, Rod K; Pate, Russell R.

2016-01-01

Objectives To identify classes of physical activity (PA) and sedentary behaviors (SB) in 5th grade children, associated factors, and trajectories of change into 7th grade. Methods This study included n=495 children (221 boys, 274 girls) who participated in the Transitions and Activity Changes in Kids (TRACK) Study. PA was assessed objectively and via self-report. Children, parents, and school administrators completed surveys to assess related factors. Latent class analysis, growth modeling, and adjusted multinomial logistic regression procedures were used to classify children based on self-reported PA and SB and examine associated factors. Results Three classes of behavior were identified: Class 1: Low PA/Low SB, Class 2: Moderate PA/High SB, and Class 3: High PA/High SB (boys) or Class 3: High PA (girls). Class 3 children had higher levels of self-efficacy (boys), and enjoyment, parental support, and physical activity equipment at home (girls). Class 2 boys and Class 3 girls did not experience decline in PA (accelerometer) over time. Conclusions Self-efficacy (boys) and home environment (girls) may play a role in shaping patterns of PA in children. Findings may help to inform future interventions to encourage children to meet national PA guidelines. PMID:27103414

Irish set dancing classes for people with Parkinson's disease: The needs of participants and dance teachers.

PubMed

Shanahan, Joanne; Bhriain, Orfhlaith Ní; Morris, Meg E; Volpe, Daniele; Clifford, Amanda M

2016-08-01

As the number of people diagnosed with Parkinson's disease increases, there is a need to develop initiatives that promote health and wellbeing and support self-management. Additionally, as exercise may slow physical decline, there is a need to develop methods that facilitate greater engagement with community-based exercise. The aim of this study is to examine the needs of (1) people with Parkinson's disease and (2) set dancing teachers to enable the development of participant-centred community set dance classes. A mixed methods study design was used. Two consensus group discussions using nominal group technique were held to (1) identify factors pertaining to the needs of people with Parkinson's disease from a set dance class and (2) the educational needs of set dancing teachers to enable them to teach set dancing to people with Parkinson's disease. Group discussions began with silent generation of ideas. A round-robin discussion and grouping of ideas into broader topic areas followed. Finally, participants ranked, by order of priority (1-5), the topic areas developed. Final data analysis involved summation of participants' ranking scores for each topic area. Rich information on the needs of people with Parkinson's disease from a dance class and the educational guidance sought by set dancing teachers was gathered. Topic areas developed include "teaching method" for set dances and "class environment". Accessing community exercise programmes is important for this population. The results of this study will inform the development of an educational resource on Parkinson's disease for set dancing teachers. This resource may facilitate a larger number of teachers to establish sustainable community set dancing classes for people with Parkinson's disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visualizing Communication Structures in Science Classrooms: Tracing Cumulativity in Teacher-Led Whole Class Discussions

ERIC Educational Resources Information Center

Lehesvuori, Sami; Viiri, Jouni; Rasku-Puttonen, Helena; Moate, Josephine; Helaakoski, Jussi

2013-01-01

Teacher-led whole class discussions are essential when it comes to guiding students' construction of knowledge, and recent studies on teaching and learning emphasize the need for more student-centered teaching methods. In previous studies, the extent to which different types of communication take place in the classroom have been extensively…

Using Learners' First Language in EFL Classrooms

ERIC Educational Resources Information Center

Alshehri, Eman

2017-01-01

This study explores the attitudes of EFL teachers towards using learners' first language (L1) in their classes. It also considers the frequency and functions of using L1 in EFL classes. A mixed-methods study using questionnaires and follow-up interviews was conducted to collect data from EFL teachers of the preparatory year at a state university…

The Effects of Web Conferencing on the Community of Inquiry in Online Classes

ERIC Educational Resources Information Center

Stover, Sheri; Miura, Yoko

2015-01-01

This mixed-methods research study compared the level of community of inquiry (CoI) in online graduate classes that use web conferencing (WC) compared to those that do not. This study also investigated students' perceptions of Teaching Presence (TP), Social Presence (SP), and Cognitive Presence (CP). The authors found that students had…

Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K): Third Grade Methodology Report. NCES 2005-018

ERIC Educational Resources Information Center

Tourangeau, Karen; Brick, Mike; Byrne, Lauren; Le, Thanh; Nord, Christine; West, Jerry; Hausken, Elvira Germino

2005-01-01

This methodology report provides technical information about the development, design, and conduct of the third grade data collection of the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K). Detailed information on the development of the instruments, sample design, data collection methods, data preparation and editing,…

Changes in Cranial Base Morphology in Class I and Class II Division 1 Malocclusions

PubMed Central

Agarwal, Anirudh; Pandey, Harsh; Bajaj, Kamal; Pandey, Lavesh

2013-01-01

Introduction: The cranial base plays a key role in craniofacial growth; it helps to integrate spatially and functionally different patterns of growth in various adjoining regions of the skull such as components of the brain, the nasal and oral cavity and the pharynx. The aim of this study was to evaluate the difference in cranial base flexure between skeletal and dental Class I and Class II division 1. Materials & Methods: Lateral cephalometric radiograph, of Class I and Class II with an average growth pattern were analyzed and compared. A total of 103 patients having class I (n=52) and class II (n=51) malocclusion, were taken from Department of Orthodontics, Rajasthan Dental College & Hospital, Jaipur. Cranial base angle (N-S-Ar) and ANB were measured on pre treatment lateral cephalograms. Results: In this study cranial base angle did not show statistically significant difference between the two groups studied. Conclusion: In the assessment of orthodontic problems involving anteroposterior malrelationships of the jaws, the problem is usually the result of size, form and position of the jaw. The present study failed to find any differences in cranial base angle between sagittal malocclusions. How to cite this article: Agarwal A, Pandey H, Bajaj K, Pandey L. Changes in Cranial Base Morphology in Class I and Class II Division 1 Malocclusion. J Int Oral Health 2013; 5(1):39-42. PMID:24155576

The Activity of Class I-IV Alcohol Dehydrogenase Isoenzymes and Aldehyde Dehydrogenase in Bladder Cancer Cells.

PubMed

Orywal, Karolina; Jelski, Wojciech; Werel, Tadeusz; Szmitkowski, Maciej

2018-01-02

The aim of this study was to determine the differences in the activity of Alcohol Dehydrogenase (ADH) isoenzymes and Aldehyde Dehydrogenase (ALDH) in normal and cancerous bladder cells. Class III, IV of ADH and total ADH activity were measured by the photometric method and class I, II ADH and ALDH activity by the fluorometric method. Significantly higher total activity of ADH was found in both, low-grade and high-grade bladder cancer, in comparison to healthy tissues. The increased activity of total ADH in bladder cancer cells may be the cause of metabolic disorders in cancer cells, which may intensify carcinogenesis.

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…

The MOOC-CLIL Project: Using MOOCs to Increase Language, and Social and Online Learning Skills for 5th Grade K-12 Students

ERIC Educational Resources Information Center

de Waard, Inge; Demeulenaere, Kathy

2017-01-01

This study comprises the outcomes and methods of a one year project using Content and Language Integrated Learning (CLIL) and Massive Open Online Courses (MOOCs) embedded in K-12 classes. The Self-Regulated Learning (SRL) of 42 students enrolled in three 5th grade classes were monitored. The students took the MOOCCLIL class for one year…

Spurious Latent Class Problem in the Mixed Rasch Model: A Comparison of Three Maximum Likelihood Estimation Methods under Different Ability Distributions

ERIC Educational Resources Information Center

Sen, Sedat

2018-01-01

Recent research has shown that over-extraction of latent classes can be observed in the Bayesian estimation of the mixed Rasch model when the distribution of ability is non-normal. This study examined the effect of non-normal ability distributions on the number of latent classes in the mixed Rasch model when estimated with maximum likelihood…

Risk-taking behaviors and subgrouping of suicide in Iran: A latent class analysis of national registries data.

PubMed

Hajebi, Ahmad; Abbasi-Ghahramanloo, Abbas; Hashemian, Seyed Sepehr; Khatibi, Seyed Reza; Ghasemzade, Masomeh; Khodadost, Mahmoud

2017-09-01

Suicide is one the most important public health problem which is rapidly growing concerns. The aim of this study was to subgroup suicide using LCA method. This cross-sectional study was conducted in Iran based on 66990 records registered in Ministry of Health in 2014. A case report questionnaire in the form of software was used for case registries. Latent class analysis was used to achieve the research objectives. Four latent classes were identified; (a) Non-lethal attempters without a history of psychiatric disorders, (b) Non-lethal attempters with a history of psychiatric disorders, (c) Lethal attempters without a history of psychiatric disorders, (d) Lethal attempters with a history of psychiatric disorders. The probability of completed/an achieved suicide is high in lethal attempter classes. Being male increases the risk of inclusion in lethal attempters' classes (OR = 4.93). Also, being single (OR = 1.16), having an age lower than 25 years (OR = 1.14) and being a rural citizen (OR = 2.36) associate with lethal attempters classes. The males tend to use more violent methods and have more completed suicide. Majority of the individuals are non-lethal attempters who need to be addressed by implementing preventive interventions and mental support provision. Copyright © 2017. Published by Elsevier B.V.

Lively Discussions vs. Discussions of Substance: Making the Case for Guided Case Study.

ERIC Educational Resources Information Center

Woloshin/Lerman, Phyllis

1996-01-01

Discusses the history and purpose of the case study method used to stimulate in-class discussion. Advocates the use of the guided case study method to ensure that substantive discussions take place and provides nine steps for using the method. Includes a sample case study worksheet. (11 citations) (BCY)

Conveying campus sexual misconduct policy information to college and university students: Results from a 7-campus study.

PubMed

Potter, S J; Edwards, K M; Banyard, V L; Stapleton, J G; Demers, J M; Moynihan, M M

2016-01-01

To examine the efficacy of different methods (ie, in-class policy reading; in-class policy reading and discussion; no reading or discussion) to deliver campus sexual misconduct policy information to students on 7 campuses. A total of 1,195 participants at 7 colleges and universities participated in the study from August to October 2014. Participants were randomly assigned at the class level and completed pretest and posttest surveys assessing knowledge of campus policy and resources and confidence to seek help for sexual assault. Students exposed to a larger dosage of material (in-class policy reading plus discussion) showed greater positive changes in attitudes and knowledge than students who did not receive information or were only read the policy. However, on some indices, students who were only read the policy showed positive outcomes compared with students receiving no intervention. Colleges and universities must use engaging methods to disseminate campus sexual misconduct policies to students.

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.

Practice and effectiveness of web-based problem-based learning approach in a large class-size system: A comparative study.

PubMed

Ding, Yongxia; Zhang, Peili

2018-06-12

Problem-based learning (PBL) is an effective and highly efficient teaching approach that is extensively applied in education systems across a variety of countries. This study aimed to investigate the effectiveness of web-based PBL teaching pedagogies in large classes. The cluster sampling method was used to separate two college-level nursing student classes (graduating class of 2013) into two groups. The experimental group (n = 162) was taught using a web-based PBL teaching approach, while the control group (n = 166) was taught using conventional teaching methods. We subsequently assessed the satisfaction of the experimental group in relation to the web-based PBL teaching mode. This assessment was performed following comparison of teaching activity outcomes pertaining to exams and self-learning capacity between the two groups. When compared with the control group, the examination scores and self-learning capabilities were significantly higher in the experimental group (P < 0.01) compared with the control group. In addition, 92.6% of students in the experimental group expressed satisfaction with the new web-based PBL teaching approach. In a large class-size teaching environment, the web-based PBL teaching approach appears to be more optimal than traditional teaching methods. These results demonstrate the effectiveness of web-based teaching technologies in problem-based learning. Copyright © 2018. Published by Elsevier Ltd.

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.

Agreement between PRE2DUP register data modeling method and comprehensive drug use interview among older persons

PubMed Central

Taipale, Heidi; Tanskanen, Antti; Koponen, Marjaana; Tolppanen, Anna-Maija; Tiihonen, Jari; Hartikainen, Sirpa

2016-01-01

Background PRE2DUP is a modeling method that generates drug use periods (ie, when drug use started and ended) from drug purchases recorded in dispensing-based register data. It is based on the evaluation of personal drug purchasing patterns and considers hospital stays, possible stockpiling of drugs, and package information. Objective The objective of this study was to investigate person-level agreement between self-reported drug use in the interview and drug use modeled from dispensing data with PRE2DUP method for various drug classes used by older persons. Methods Self-reported drug use was assessed from the GeMS Study including a random sample of persons aged ≥75 years from the city of Kuopio, Finland, in 2006. Drug purchases recorded in the Prescription register data of these persons were modeled to determine drug use periods with PRE2DUP modeling method. Agreement between self-reported drug use on the interview date and drug use calculated from register-based data was compared in order to find the frequently used drugs and drug classes, which was evaluated by Cohen’s kappa. Kappa values 0.61–0.80 were considered to represent good and 0.81–1.00 as very good agreement. Results Among 569 participants with mean age of 82 years, the agreement between interview and register data was very good for 75% and very good or good for 93% of the studied drugs or drug classes. Good or very good agreement was observed for drugs that are typically used on regular bases, whereas “as needed” drugs represented poorer results. Conclusion PRE2DUP modeling method validly describes regular drug use among older persons. For most of drug classes investigated, PRE2DUP-modeled register data described drug use as well as interview-based data which are more time-consuming to collect. Further studies should be conducted by comparing it with other methods and in different drug user populations. PMID:27785101

Determination of Pain Phenotypes in Knee Osteoarthritis: A Latent Class Analysis using Data from the Osteoarthritis Initiative Study

PubMed Central

Kittelson, Andrew J.; Stevens-Lapsley, Jennifer E.; Schmiege, Sarah J.

2017-01-01

Objective Knee osteoarthritis (OA) is a broadly applied diagnosis that may encompass multiple subtypes of pain. The purpose of this study was to identify phenotypes of knee OA, using measures from the following pain-related domains: 1) knee OA pathology, 2) psychological distress, and 3) altered pain neurophysiology. Methods Data were selected from a total of 3494 participants at Visit #6 of the Osteoarthritis Initiative (OAI) study. Latent Class Analysis was applied to the following variables: radiographic OA severity, quadriceps strength, Body Mass Index (BMI), Charlson Comorbidity Index (CCI), Center for Epidemiologic Studies Depression subscale (CES-D), Coping Strategies Questionnaire-Catastrophizing subscale (CSQ-Cat), number of bodily pain sites, and knee joint tenderness at 4 sites. Resulting classes were compared on the following demographic and clinical factors: age, sex, pain severity, disability, walking speed, and use of arthritis-related healthcare. Results A four-class model was identified. Class 1 (4% of the study population) had higher CCI scores. Class 2 (24%) had higher knee joint sensitivity. Class 3 (10%) had greater psychological distress. Class 4 (62%) had lesser radiographic OA, little psychological involvement, greater strength, and less pain sensitivity. Additionally, Class 1 was the oldest, on average. Class 4 was the youngest, had the lowest disability, and least pain. Class 3 had the worst disability and most pain. Conclusions Four distinct pain phenotypes of knee OA were identified. Psychological factors, comorbidity status, and joint sensitivity appear to be important in defining phenotypes of knee OA-related pain. PMID:26414884

Common Mental Disorders among Occupational Groups: Contributions of the Latent Class Model

PubMed Central

Martins Carvalho, Fernando; de Araújo, Tânia Maria

2016-01-01

Background. The Self-Reporting Questionnaire (SRQ-20) is widely used for evaluating common mental disorders. However, few studies have evaluated the SRQ-20 measurements performance in occupational groups. This study aimed to describe manifestation patterns of common mental disorders symptoms among workers populations, by using latent class analysis. Methods. Data derived from 9,959 Brazilian workers, obtained from four cross-sectional studies that used similar methodology, among groups of informal workers, teachers, healthcare workers, and urban workers. Common mental disorders were measured by using SRQ-20. Latent class analysis was performed on each database separately. Results. Three classes of symptoms were confirmed in the occupational categories investigated. In all studies, class I met better criteria for suspicion of common mental disorders. Class II discriminated workers with intermediate probability of answers to the items belonging to anxiety, sadness, and energy decrease that configure common mental disorders. Class III was composed of subgroups of workers with low probability to respond positively to questions for screening common mental disorders. Conclusions. Three patterns of symptoms of common mental disorders were identified in the occupational groups investigated, ranging from distinctive features to low probabilities of occurrence. The SRQ-20 measurements showed stability in capturing nonpsychotic symptoms. PMID:27630999

The Effect of Experiences with Animals on the Reading Comprehension Skills of Students in the Seventh Grade

ERIC Educational Resources Information Center

Petersen, Annie

2008-01-01

The Problem: The study examined the difference that animal interactions had on the reading comprehension growth skills of students in the seventh grade. Method: A quasiexperimental study was conducted with two seventh-grade classes at William Howard Taft Middle School. One class received daily 20-minute animal interaction experiences for 5 days.…

Development and Effectiveness of an Educational Card Game as Supplementary Material in Understanding Selected Topics in Biology

ERIC Educational Resources Information Center

Gutierrez, Arnel F.

2014-01-01

The complex concepts and vocabulary of biology classes discourage many students. In this study, a pretest-posttest model was used to test the effectiveness of an educational card game in reinforcing biological concepts in comparison with traditional teaching methods. The subjects of this study were two biology classes at Bulacan State…

Conveying Campus Sexual Misconduct Policy Information to College and University Students: Results from a 7-Campus Study

ERIC Educational Resources Information Center

Potter, S. J.; Edwards, K. M.; Banyard, V. L.; Stapleton, J. G.; Demers, J. M.; Moynihan, M. M.

2016-01-01

Objective: To examine the efficacy of different methods (ie, in-class policy reading; in-class policy reading and discussion; no reading or discussion) to deliver campus sexual misconduct policy information to students on 7 campuses. Participants: A total of 1,195 participants at 7 colleges and universities participated in the study from August to…

A Technology Leader's Role in Initiating a Flipped Classroom in a High School Math Class

ERIC Educational Resources Information Center

Caverly, Gregg

2017-01-01

A mixed methods study was conducted to measure the effectiveness of a flipped classroom in a high school discrete mathematics course. In the flipped classroom, students watched videos of the teacher's lesson for homework while completing problems during class. Two sections of the course were involved in the study, with one group receiving the…

Using Poetry in Social Studies Classes to Teach about Cultural Diversity and Social Justice

ERIC Educational Resources Information Center

McCall, Ava L.

2004-01-01

As a teacher educator committed to raising issues of racial, economic, and gender equality and those related to an appreciation for diversity, the author finds poetry to be a powerful resource in social studies methods classes. When preparing preservice teachers for elementary and middle school levels, she finds that poetry can often capture their…

A Comparative Study of a Kodaly-Based Developmental Music Program and a Traditional Public School Music Program at the Kindergarten Level.

ERIC Educational Resources Information Center

Beatty, Rodger James

A 9-month longitudinal study of two kindergarten classes compared two types of music instruction: a Kodaly-based developmental music program and a traditional public school music program. The class taught through the Kodaly method received instruction that emphasized the development of rhythmic and melodic perception through visual, aural, and…

Effects of a Regular Motor Activity on Somatic and Fitness Variables in Boys Aged 17-18 Years

ERIC Educational Resources Information Center

Piotrowska, Joanna

2011-01-01

Study aim: To assess the somatic and fitness changes in semisedentary boys persuaded to undertake Nordic Walking activities throughout a school year. Material and methods: Two groups of schoolboys aged 17-18 years were studied: regularly attending physical education (PE) classes (Group A; n = 46) and those who avoided PE classes by submitting sick…

A method of assigning socio-economic status classification to British Armed Forces personnel.

PubMed

Yoong, S Y; Miles, D; McKinney, P A; Smith, I J; Spencer, N J

1999-10-01

The objective of this paper was to develop and evaluate a socio-economic status classification method for British Armed Forces personnel. Two study groups comprising of civilian and Armed Forces families were identified from livebirths delivered between 1 January-30 June 1996 within the Northallerton Health district which includes Catterick Garrison and RAF Leeming. The participants were the parents of babies delivered at a District General Hospital, comprising of 436 civilian and 162 Armed Forces families. A new classification method was successfully used to assign Registrar General's social classification to Armed Forces personnel. Comparison of the two study groups showed a significant difference in social class distribution (p = 0.0001). This study has devised a new method for classifying occupations within the Armed Forces to categories of social class thus permitting comparison with Registrar General's classification.

A heuristic method for consumable resource allocation in multi-class dynamic PERT networks

NASA Astrophysics Data System (ADS)

Yaghoubi, Saeed; Noori, Siamak; Mazdeh, Mohammad Mahdavi

2013-06-01

This investigation presents a heuristic method for consumable resource allocation problem in multi-class dynamic Project Evaluation and Review Technique (PERT) networks, where new projects from different classes (types) arrive to system according to independent Poisson processes with different arrival rates. Each activity of any project is operated at a devoted service station located in a node of the network with exponential distribution according to its class. Indeed, each project arrives to the first service station and continues its routing according to precedence network of its class. Such system can be represented as a queuing network, while the discipline of queues is first come, first served. On the basis of presented method, a multi-class system is decomposed into several single-class dynamic PERT networks, whereas each class is considered separately as a minisystem. In modeling of single-class dynamic PERT network, we use Markov process and a multi-objective model investigated by Azaron and Tavakkoli-Moghaddam in 2007. Then, after obtaining the resources allocated to service stations in every minisystem, the final resources allocated to activities are calculated by the proposed method.

Digital modelling of landscape and soil in a mountainous region: A neuro-fuzzy approach

NASA Astrophysics Data System (ADS)

Viloria, Jesús A.; Viloria-Botello, Alvaro; Pineda, María Corina; Valera, Angel

2016-01-01

Research on genetic relationships between soil and landforms has largely improved soil mapping. Recent technological advances have created innovative methods for modelling the spatial soil variation from digital elevation models (DEMs) and remote sensors. This generates new opportunities for the application of geomorphology to soil mapping. This study applied a method based on artificial neural networks and fuzzy clustering to recognize digital classes of land surfaces in a mountainous area in north-central Venezuela. The spatial variation of the fuzzy memberships exposed the areas where each class predominates, while the class centres helped to recognize the topographic attributes and vegetation cover of each class. The obtained classes of terrain revealed the structure of the land surface, which showed regional differences in climate, vegetation, and topography and landscape stability. The land-surface classes were subdivided on the basis of the geological substratum to produce landscape classes that additionally considered the influence of soil parent material. These classes were used as a framework for soil sampling. A redundancy analysis confirmed that changes of landscape classes explained the variation in soil properties (p = 0.01), and a Kruskal-Wallis test showed significant differences (p = 0.01) in clay, hydraulic conductivity, soil organic carbon, base saturation, and exchangeable Ca and Mg between classes. Thus, the produced landscape classes correspond to three-dimensional bodies that differ in soil conditions. Some changes of land-surface classes coincide with abrupt boundaries in the landscape, such as ridges and thalwegs. However, as the model is continuous, it disclosed the remaining variation between those boundaries.

One input-class and two input-class classifications for differentiating olive oil from other edible vegetable oils by use of the normal-phase liquid chromatography fingerprint of the methyl-transesterified fraction.

PubMed

Jiménez-Carvelo, Ana M; Pérez-Castaño, Estefanía; González-Casado, Antonio; Cuadros-Rodríguez, Luis

2017-04-15

A new method for differentiation of olive oil (independently of the quality category) from other vegetable oils (canola, safflower, corn, peanut, seeds, grapeseed, palm, linseed, sesame and soybean) has been developed. The analytical procedure for chromatographic fingerprinting of the methyl-transesterified fraction of each vegetable oil, using normal-phase liquid chromatography, is described and the chemometric strategies applied and discussed. Some chemometric methods, such as k-nearest neighbours (kNN), partial least squared-discriminant analysis (PLS-DA), support vector machine classification analysis (SVM-C), and soft independent modelling of class analogies (SIMCA), were applied to build classification models. Performance of the classification was evaluated and ranked using several classification quality metrics. The discriminant analysis, based on the use of one input-class, (plus a dummy class) was applied for the first time in this study. Copyright © 2016 Elsevier Ltd. All rights reserved.

Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings

PubMed Central

Lin, Tiger W.; Das, Anup; Krishnan, Giri P.; Bazhenov, Maxim; Sejnowski, Terrence J.

2017-01-01

With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005; Pillow et al., 2008), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals. PMID:28777719

Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings.

PubMed

Lin, Tiger W; Das, Anup; Krishnan, Giri P; Bazhenov, Maxim; Sejnowski, Terrence J

2017-10-01

With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008 ), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005 ; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005 ; Pillow et al., 2008 ), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals.

Constructing Social Networks From Secondary Storage With Bulk Analysis Tools

DTIC Science & Technology

2016-06-01

that classic measures of centrality are effective for identifying important nodes and close associates, and that further study of modularity classes...which ground truth was determined by interviews with the owners, and which can be used for future study in this area. Two objectives motivated this thesis...tifying important nodes and close associates, and that further study of modularity classes may be a promising method of partitioning complex components

The Effectiveness of learning materials based on multiple intelligence on the understanding of global warming

NASA Astrophysics Data System (ADS)

Liliawati, W.; Purwanto; Zulfikar, A.; Kamal, R. N.

2018-05-01

This study aims to examine the effectiveness of the use of teaching materials based on multiple intelligences on the understanding of high school students’ material on the theme of global warming. The research method used is static-group pretest-posttest design. Participants of the study were 60 high school students of XI class in one of the high schools in Bandung. Participants were divided into two classes of 30 students each for the experimental class and control class. The experimental class uses compound-based teaching materials while the experimental class does not use a compound intelligence-based teaching material. The instrument used is a test of understanding of the concept of global warming with multiple choices form amounted to 15 questions and 5 essay items. The test is given before and after it is applied to both classes. Data analysis using N-gain and effect size. The results obtained that the N-gain for both classes is in the medium category and the effectiveness of the use of teaching materials based on the results of effect-size test results obtained in the high category.

Sequence-Based Genotyping of Expressed Swine Leukocyte Antigen Class I Alleles by Next-Generation Sequencing Reveal Novel Swine Leukocyte Antigen Class I Haplotypes and Alleles in Belgian, Danish, and Kenyan Fattening Pigs and Göttingen Minipigs.

PubMed

Sørensen, Maria Rathmann; Ilsøe, Mette; Strube, Mikael Lenz; Bishop, Richard; Erbs, Gitte; Hartmann, Sofie Bruun; Jungersen, Gregers

2017-01-01

The need for typing of the swine leukocyte antigen (SLA) is increasing with the expanded use of pigs as models for human diseases and organ-transplantation experiments, their use in infection studies, and for design of veterinary vaccines. Knowledge of SLA sequences is furthermore a prerequisite for the prediction of epitope binding in pigs. The low number of known SLA class I alleles and the limited knowledge of their prevalence in different pig breeds emphasizes the need for efficient SLA typing methods. This study utilizes an SLA class I-typing method based on next-generation sequencing of barcoded PCR amplicons. The amplicons were generated with universal primers and predicted to resolve 68-88% of all known SLA class I alleles dependent on amplicon size. We analyzed the SLA profiles of 72 pigs from four different pig populations; Göttingen minipigs and Belgian, Kenyan, and Danish fattening pigs. We identified 67 alleles, nine previously described haplotypes and 15 novel haplotypes. The highest variation in SLA class I profiles was observed in the Danish pigs and the lowest among the Göttingen minipig population, which also have the highest percentage of homozygote individuals. Highlighting the fact that there are still numerous unknown SLA class I alleles to be discovered, a total of 12 novel SLA class I alleles were identified. Overall, we present new information about known and novel alleles and haplotypes and their prevalence in the tested pig populations.

Analysis and design of continuous class-E power amplifier at sub-nominal condition

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Kai; Zhang, Tianliang

2017-12-01

The continuous class-E power amplifier at sub-nominal condition is proposed in this paper. The class-E power amplifier at continuous mode means it can be high efficient on a series matching networks while at sub-nominal condition means it only requires the zero-voltage-switching condition. Comparing with the classical class-E power amplifier, the proposed design method releases two additional design freedoms, which increase the class-E power amplifier's design flexibility. Also, the proposed continuous class-E power amplifier at sub-nominal condition can perform high efficiency over a broad bandwidth. The performance study of the continuous class-E power amplifier at sub-nominal condition is derived and the design procedure is summarised. The normalised switch voltage and current waveforms are investigated. Furthermore, the influences of different sub-nominal conditions on the power losses of the switch-on resistor and the output power capability are also discussed. A broadband continuous class-E power amplifier based on a Gallium Nitride (GaN) transistor is designed and testified to verify the proposed design methodology. The measurement results show, it can deliver 10-15 W output power with 64-73% power-added efficiency over 1.4-2.8 GHz.

Comparing In-Class and Out-of-Class Computer-Based Tests to Traditional Paper-and-Pencil Tests in Introductory Psychology Courses

ERIC Educational Resources Information Center

Frein, Scott T.

2011-01-01

This article describes three experiments comparing paper-and-pencil tests (PPTs) to computer-based tests (CBTs) in terms of test method preferences and student performance. In Experiment 1, students took tests using three methods: PPT in class, CBT in class, and CBT at the time and place of their choosing. Results indicate that test method did not…

Critical exponents of the 3D antiferromagnetic three-state Potts model using the coherent-anomaly method

NASA Astrophysics Data System (ADS)

Kolesik, Miroslav; Suzuki, Masuo

1995-02-01

The antiferromagnetic three-state Potts model on the simple-cubic lattice is studied using the coherent-anomaly method (CAM). The CAM analysis provides the estimates for the critical exponents which indicate the XY universality class, namely α = -0.011, β = 0.351, γ = 1.309 and δ = 4.73. This observation corroborates the results of the recent Monte Carlo simulations, and disagrees with the proposal of a new universality class.

Classroom Contribution: What Do Students Perceive as Fair Assessment?

ERIC Educational Resources Information Center

Pepper, Molly B.; Pathak, Seemantini

2008-01-01

Assigning a grade to students' class contribution may be 1 of the most controversial and difficult challenges that instructors face. The authors examine the perceived fairness of class contribution grading methods from the perspective of the performance appraisal literature. In 2 scenario studies based on actual grading techniques, the authors…

TV News Analysis Project Motivates Broadcast Class.

ERIC Educational Resources Information Center

Smith, James R.

1980-01-01

Describes the use of content analysis by a journalism class in studying television news. Indicates that the method is flexible, generates familiarity with quantitative approaches to the analysis of broadcast journalism, can result in increased awareness of the complexity of the broadcast news medium, and increases student motivation. (TJ)

SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition

PubMed Central

Melvin, Iain; Ie, Eugene; Kuang, Rui; Weston, Jason; Stafford, William Noble; Leslie, Christina

2007-01-01

Background Predicting a protein's structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing new representations for protein sequences, called string kernels, for use with support vector machine (SVM) classifiers. However, while some of these approaches exhibit state-of-the-art performance at the binary protein classification problem, i.e. discriminating between a particular protein class and all other classes, few of these studies have addressed the real problem of multi-class superfamily or fold recognition. Moreover, there are only limited software tools and systems for SVM-based protein classification available to the bioinformatics community. Results We present a new multi-class SVM-based protein fold and superfamily recognition system and web server called SVM-Fold, which can be found at . Our system uses an efficient implementation of a state-of-the-art string kernel for sequence profiles, called the profile kernel, where the underlying feature representation is a histogram of inexact matching k-mer frequencies. We also employ a novel machine learning approach to solve the difficult multi-class problem of classifying a sequence of amino acids into one of many known protein structural classes. Binary one-vs-the-rest SVM classifiers that are trained to recognize individual structural classes yield prediction scores that are not comparable, so that standard "one-vs-all" classification fails to perform well. Moreover, SVMs for classes at different levels of the protein structural hierarchy may make useful predictions, but one-vs-all does not try to combine these multiple predictions. To deal with these problems, our method learns relative weights between one-vs-the-rest classifiers and encodes information about the protein structural hierarchy for multi-class prediction. In large-scale benchmark results based on the SCOP database, our code weighting approach significantly improves on the standard one-vs-all method for both the superfamily and fold prediction in the remote homology setting and on the fold recognition problem. Moreover, our code weight learning algorithm strongly outperforms nearest-neighbor methods based on PSI-BLAST in terms of prediction accuracy on every structure classification problem we consider. Conclusion By combining state-of-the-art SVM kernel methods with a novel multi-class algorithm, the SVM-Fold system delivers efficient and accurate protein fold and superfamily recognition. PMID:17570145

How Safe and Innovative Are First-in-Class Drugs Approved by Health Canada: A Cohort Study

PubMed Central

2016-01-01

Introduction: First-in-class drugs use a unique mechanism of action. This study assessed the therapeutic innovativeness and safety of these drugs approved by Health Canada from 1997–2012. Methods: A list of new drugs was compiled and a database from the Food and Drug Administration was used to determine first-in-class status. Post-market safety warnings and drugs withdrawn for safety reasons were identified from the MedEffect Canada website. Therapeutic innovation evaluations came from the Patented Medicine Prices Review Board (PMPRB) and Prescrire International. The proportion of first-in-class drugs that were innovative was compared to the proportion of non-first-in-class drugs that were innovative. Kaplan–Meier survival curves assessed safety. Results: In all, 462 drugs were approved by Health Canada during the period under study. Among these, 345 were evaluated by PMPRB and/or Prescrire, and first-in-class data were available for 292. Ninety-eight of the 292 were first-in-class and 16 were innovative compared to 9 of 194 drugs that were not-first-in-class. There was no difference in safety between the two groups. Discussion: Overall, the benefit-to-harm ratio of first-in-class drugs, as measured by post-market safety warnings/withdrawals, is better than those that were not-first-in-class. PMID:28032825

Substance use, mental illness, and familial conflict non-negotiation among HIV-positive African-Americans: latent class regression and a new syndemic framework.

PubMed

Robinson, Allysha C; Knowlton, Amy R; Gielen, Andrea C; Gallo, Joseph J

2016-02-01

We evaluated a synergistic epidemic (syndemic) of substance use, mental illness, and familial conflict non-negotiation among HIV-positive injection drug users (IDU). Baseline BEACON study data was utilized. Latent class analyses identified syndemic classes. These classes were regressed on sex, viral suppression, and acute care non-utilization. Females were hypothesized to have higher syndemic burden, and worse health outcomes than males. Nine percent of participants had high substance use/mental illness prevalence (Class 4); 23 % had moderate levels of all factors (Class 3); 25 % had high mental illness (Class 2); 43 % had moderate substance use/mental illness (Class 1; N = 331). Compared to Classes 1-3, Class 4 was mostly female (p < .05), less likely to achieve viral suppression, and more likely to utilize acute care (p < .05). Interventions should target African-American IDU females to improve their risk of negative medical outcomes. Findings support comprehensive syndemic approaches to HIV interventions, rather than singular treatment methods.

An Analysis of Class II Supplies Requisitions in the Korean Army’s Organizational Supply

DTIC Science & Technology

2009-03-26

five methods for qualitative research : Case study , Ethnography , 45 Phenomenological study , Grounded theory , and...Approaches .. 42 Table 9 Five Qualitative Research Methods ..................................................................... 45 Table 10 Six...Content analysis. Table 9 provides a brief overview of the five methods . Table 9 Five Qualitative

Creative Digital Worksheet Base on Mobile Learning

NASA Astrophysics Data System (ADS)

Wibawa, S. C.; Cholifah, R.; Utami, A. W.; Nurhidayat, A. I.

2018-01-01

The student is required to understand and act in the classroom and it is very important for selecting the media learning to determine the learning outcome. An instructional media is needed to help students achieve the best learning outcome. The objectives of this study are (1) to make Android-based student worksheet, (2) to know the students’ response on Android-based student worksheet in multimedia subject, (3) to determine the student result using Android-based student worksheet. The method used was Research and Development (R&D) using post-test-only in controlled quasi-experimental group design. The subjects of the study were 2 classes, a control class and an experimental class. The results showed (1) Android-based student worksheet was categorized very good as percentage of 85%; (2) the students’ responses was categorized very good as percentage of 86.42%; (3) the experimental class results were better than control class. The average result on cognitive tests on the experimental class was 89.97 and on control class was 78.31; whether the average result on psychomotor test on the experimental class was 89.90 and on the control class was 79.83. In conclusion, student result using Android-based student worksheet was better than those without it.

Enhancement of students’ creative thinking skills on mixture separation topic using project based student worksheet

NASA Astrophysics Data System (ADS)

Nurisalfah, R.; Fadiawati, N.; Jalmo, T.

2018-05-01

The aim of this study is to describe the effectiveness of project based student worksheet in improving students' creative thinking skills. The research method is using quasi experiment with the matching only pre-test post-test control group design. The population in this research is all students of class VII SMP N 2 Belitang Madang Raya with class VII1 as control class and class VII4 as experiment class. The sample of this research is obtaining by purposive sampling technique. The effectiveness of project based student worksheet is based on significant post-test differences between the control class and the experiment class as well as the effect size. The results show that the using of project based student worksheet is effective in improving students' creative thinking skills on mixture separation topic.

Construction and reconstruction concept in mathematics instruction

NASA Astrophysics Data System (ADS)

Mumu, Jeinne; Charitas Indra Prahmana, Rully; Tanujaya, Benidiktus

2017-12-01

The purpose of this paper is to describe two learning activities undertaken by lecturers, so that students can understand a mathematical concept. The mathematical concept studied in this research is the Vector Space in Linear Algebra instruction. Classroom Action Research used as a research method with pre-service mathematics teacher at University of Papua as the research subject. Student participants are divided into two parallel classes, 24 students in regular class, and remedial class consist of 18 students. Both approaches, construct and reconstruction concept, are implemented on both classes. The result shows that concept construction can only be done in regular class while in remedial class, learning with concept construction approach is not able to increase students' understanding on the concept taught. Understanding the concept of a student in a remedial class can only be carried out using the concept reconstruction approach.

Pilates, Mindfulness and Somatic Education.

PubMed

Caldwell, Karen; Adams, Marianne; Quin, Rebecca; Harrison, Mandy; Greeson, Jeffrey

2013-12-01

The Pilates Method is a form of somatic education with the potential to cultivate mindfulness - a mental quality associated with overall well-being. However, controlled studies are needed to determine whether changes in mindfulness are specific to the Pilates Method or also result from other forms of exercise. This quasi-experimental study compared Pilates Method mat classes and recreational exercise classes on measures of mindfulness and well-being at the beginning, middle and end of a 15 week semester. Total mindfulness scores increased overall for the Pilates Method group but not for the exercise control group, and these increases were directly related to end of semester ratings of self-regulatory self-efficacy, perceived stress and mood. Findings suggest that the Pilates Method specifically enhances mindfulness, and these increases are associated with other measures of wellness. The changes in mindfulness identified in this study support the role of the Pilates Method in the mental well-being of its practitioners and its potential to support dancers' overall well-being.

Pilates, Mindfulness and Somatic Education

PubMed Central

Caldwell, Karen; Quin, Rebecca; Harrison, Mandy; Greeson, Jeffrey

2014-01-01

The Pilates Method is a form of somatic education with the potential to cultivate mindfulness – a mental quality associated with overall well-being. However, controlled studies are needed to determine whether changes in mindfulness are specific to the Pilates Method or also result from other forms of exercise. This quasi-experimental study compared Pilates Method mat classes and recreational exercise classes on measures of mindfulness and well-being at the beginning, middle and end of a 15 week semester. Total mindfulness scores increased overall for the Pilates Method group but not for the exercise control group, and these increases were directly related to end of semester ratings of self-regulatory self-efficacy, perceived stress and mood. Findings suggest that the Pilates Method specifically enhances mindfulness, and these increases are associated with other measures of wellness. The changes in mindfulness identified in this study support the role of the Pilates Method in the mental well-being of its practitioners and its potential to support dancers’ overall well-being. PMID:25328542

A Comparison of Different Conceptual Change Pedagogies Employed within the Topic of "Sound Propagation"

ERIC Educational Resources Information Center

Calik, Muammer; Okur, Murat; Taylor, Neil

2011-01-01

The purpose of this study was to compare different conceptual change methods within a topic on "sound propagation". The study was conducted with 80 grade 5 students (aged 11-12 year old) drawn from four cohort classes in an elementary school on the north coast of Black Sea Region in Turkey. While one class was assigned as a control…

The Effects of Project Based Learning on Undergraduate Students' Achievement and Self-Efficacy Beliefs towards Science Teaching

ERIC Educational Resources Information Center

Bilgin, Ibrahim; Karakuyu, Yunus; Ay, Yusuf

2015-01-01

The purpose of this study is to investigate the effects of the Project-Based Learning (PBL) method on undergraduate students' achievement and its association with these students' self-efficacy beliefs about science teaching and pinions about PBL. The sample of the study consisted of two randomly chosen classes from a set of seven classes enrolled…

Globescope: Student Involvement in Culture Trait Studies as Part of the Social Studies Curriculum in Grades 5-12.

ERIC Educational Resources Information Center

Peters, Richard

The program described in this guide provides a method of researching and comparing diverse cultures for middle and high school students. Teams of students investigate cultures from around the world and present findings to the entire class. The team approach enables the class to be exposed to a variety of materials and gives students experience in…

The Effect of Group Work on Misconceptions of 9th Grade Students about Newton's Laws

ERIC Educational Resources Information Center

Ergin, Serap

2016-01-01

In this study, the effect of group work and traditional method on 9th grade students' misconceptions about Newton Laws was investigated. The study was conducted in three classes in an Anatolian Vocational High School in Ankara/Turkey in the second term of the 2014-2015 academic year. Two of these classes were chosen as the experimental group and…

Advantages of continuous genotype values over genotype classes for GWAS in higher polyploids: a comparative study in hexaploid chrysanthemum.

PubMed

Grandke, Fabian; Singh, Priyanka; Heuven, Henri C M; de Haan, Jorn R; Metzler, Dirk

2016-08-24

Association studies are an essential part of modern plant breeding, but are limited for polyploid crops. The increased number of possible genotype classes complicates the differentiation between them. Available methods are limited with respect to the ploidy level or data producing technologies. While genotype classification is an established noise reduction step in diploids, it gains complexity with increasing ploidy levels. Eventually, the errors produced by misclassifications exceed the benefits of genotype classes. Alternatively, continuous genotype values can be used for association analysis in higher polyploids. We associated continuous genotypes to three different traits and compared the results to the output of the genotype caller SuperMASSA. Linear, Bayesian and partial least squares regression were applied, to determine if the use of continuous genotypes is limited to a specific method. A disease, a flowering and a growth trait with h (2) of 0.51, 0.78 and 0.91 were associated with a hexaploid chrysanthemum genotypes. The data set consisted of 55,825 probes and 228 samples. We were able to detect associating probes using continuous genotypes for multiple traits, using different regression methods. The identified probe sets were overlapping, but not identical between the methods. Baysian regression was the most restrictive method, resulting in ten probes for one trait and none for the others. Linear and partial least squares regression led to numerous associating probes. Association based on genotype classes resulted in similar values, but missed several significant probes. A simulation study was used to successfully validate the number of associating markers. Association of various phenotypic traits with continuous genotypes is successful with both uni- and multivariate regression methods. Genotype calling does not improve the association and shows no advantages in this study. Instead, use of continuous genotypes simplifies the analysis, saves computational time and results more potential markers.

Using the gene ontology for microarray data mining: a comparison of methods and application to age effects in human prefrontal cortex.

PubMed

Pavlidis, Paul; Qin, Jie; Arango, Victoria; Mann, John J; Sibille, Etienne

2004-06-01

One of the challenges in the analysis of gene expression data is placing the results in the context of other data available about genes and their relationships to each other. Here, we approach this problem in the study of gene expression changes associated with age in two areas of the human prefrontal cortex, comparing two computational methods. The first method, "overrepresentation analysis" (ORA), is based on statistically evaluating the fraction of genes in a particular gene ontology class found among the set of genes showing age-related changes in expression. The second method, "functional class scoring" (FCS), examines the statistical distribution of individual gene scores among all genes in the gene ontology class and does not involve an initial gene selection step. We find that FCS yields more consistent results than ORA, and the results of ORA depended strongly on the gene selection threshold. Our findings highlight the utility of functional class scoring for the analysis of complex expression data sets and emphasize the advantage of considering all available genomic information rather than sets of genes that pass a predetermined "threshold of significance."

Automatic Vetting for Malice in Android Platforms

DTIC Science & Technology

2016-05-01

be distinguished. For example, both Face- book and Instagram ship a class named Landroid/support/v4/app/Fragment;§ with different method signatures...relationships (e.g., Lcom/ instagram /.../LoadImageTask; is a sub- class of the abstract class Landroid/os/AsyncTask;). Figure 2(c) displays a method graph...7feaf7c75a5305b1083a160f...baa6.dex.dex parent_loader 3 Instagram instagram_classes.dex parent_loader 4 JohnNESLite johnneslite_classes.dex parent_loader (a) Class Loader

Improved Dot Diffusion For Image Halftoning

DTIC Science & Technology

1999-01-01

The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error diffusion method. The method was recently improved...by optimization of the so-called class matrix so that the resulting halftones are comparable to the error diffused halftones . In this paper we will...first review the dot diffusion method. Previously, 82 class matrices were used for dot diffusion method. A problem with this size of class matrix is

Integration of a Community Pharmacy Simulation Program into a Therapeutics Course.

PubMed

Shin, Jaekyu; Tabatabai, Daryush; Boscardin, Christy; Ferrone, Marcus; Brock, Tina

2018-02-01

Objective. To demonstrate the feasibility of integrating the computer simulation, MyDispense, into a therapeutics course and to measure its effects on student perception and learning. Methods. We conducted a prospective study with an experimental phase and an implementation phase. In the first phase, students were randomized to complete a therapeutics case using MyDispense or traditional paper methods in class. In the second phase, all students completed two therapeutic cases using MyDispense in class with the option to complete four additional outside-of-class cases using MyDispense. Students completed pre- and post-tests in class and three surveys. Results. In the experimental phase, mean test scores increased from pre- to post-test for both MyDispense and traditional paper groups, but the difference between the groups was not statistically significant. Students in the traditional paper group reported statistically significant gains in confidence compared to the MyDispense group. In the implementation phase, mean test scores again increased, however, student perception of the use of MyDispense for therapeutics was negative. Completing the optional outside-of-class cases, however, was positively and significantly correlated with the midterm and final examination scores. Conclusion. Implementation of MyDispense in therapeutics may be feasible and has positive effects (eg, correlation with exam scores, capacity for immediate feedback, and potential for effective self-study). With short-term use and in the absence of assessment methods that also require seeking information from patients, students prefer to learn via traditional paper cases.

The efficacy of focus group discussion in teaching ESP speaking skill for prospective vocational school teacher

NASA Astrophysics Data System (ADS)

Nurmasitah, Sita; Faridi, Abdurrachman; Utomo, Aryo Baskoro; Astuti, Pudji

2018-03-01

The aims of the study were to implement the focus group discussion in teaching English for Specific Purposes (ESP) speaking skill for prospective Vocational School teacher and also to find out its effectiveness in improving their English speaking skill in ESP course. Quasi-experimental design was employed in this research. Thirty students of Family Welfare Vocational Education Study Program who were taking ESP course, were divided into two classes; experimental and control class. The research data were collected through interview, observation and the students' speaking assessment. The result showed that the implementation of focus group discussion method in the experimental class effectively increased the students' speaking skill compared to the control class.

Investigation of the relationship between drinking water quality based on content of inorganic components and landform classes using fuzzy AHP (case study: south of Firozabad, west of Fars province, Iran)

NASA Astrophysics Data System (ADS)

Mokarram, Marzieh; Sathyamoorthy, Dinesh

2016-10-01

In this study, the fuzzy analytic hierarchy process (AHP) is used to study the relationship between drinking water quality based on content of inorganic components and landform classes in the south of Firozabad, west of Fars province, Iran. For determination of drinking water quality based on content of inorganic components, parameters of calcium (Ca), chlorine (Cl), magnesium (Mg), thorium (TH), sodium (Na), electrical conductivity (EC), sulfate (SO4), and total dissolved solids (TDS) were used. It was found that 8.29 % of the study area has low water quality; 64.01 %, moderate; 23.33 %, high; and 4.38 %, very high. Areas with suitable drinking water quality based on content of inorganic components are located in parts of the south-eastern and south-western parts of the study area. The relationship between landform class and drinking water quality based on content of inorganic components shows that drinking water quality based on content of inorganic components is high in the stream, valleys, upland drainages, and local ridge classes, and low in the plain small and midslope classes. In fact we can predict water quality using extraction of landform classes from a digital elevation model (DEM) by the Topographic Position Index (TPI) method, so that streams, valleys, upland drainages, and local ridge classes have more water quality than the other classes. In the study we determined that without measurement of water sample characteristics, we can determine water quality by landform classes.

Best practices for learning physiology: combining classroom and online methods.

PubMed

Anderson, Lisa C; Krichbaum, Kathleen E

2017-09-01

Physiology is a requisite course for many professional allied health programs and is a foundational science for learning pathophysiology, health assessment, and pharmacology. Given the demand for online learning in the health sciences, it is important to evaluate the efficacy of online and in-class teaching methods, especially as they are combined to form hybrid courses. The purpose of this study was to compare two hybrid physiology sections in which one section was offered mostly in-class (85% in-class), and the other section was offered mostly online (85% online). The two sections in 2 yr ( year 1 and year 2 ) were compared in terms of knowledge of physiology measured in exam scores and pretest-posttest improvement, and in measures of student satisfaction with teaching. In year 1 , there were some differences on individual exam scores between the two sections, but no significant differences in mean exam scores or in pretest-posttest improvements. However, in terms of student satisfaction, the mostly in-class students in year 1 rated the instructor significantly higher than did the mostly online students. Comparisons between in-class and online students in the year 2 cohort yielded data that showed that mean exam scores were not statistically different, but pre-post changes were significantly greater in the mostly online section; student satisfaction among mostly online students also improved significantly. Education researchers must investigate effective combinations of in-class and online methods for student learning outcomes, while maintaining the flexibility and convenience that online methods provide. Copyright © 2017 the American Physiological Society.

Class attendance, peer similarity, and academic performance in a large field study

PubMed Central

Bjerre-Nielsen, Andreas; Mones, Enys; Lehmann, Sune; Lassen, David Dreyer

2017-01-01

Identifying the factors that determine academic performance is an essential part of educational research. Existing research indicates that class attendance is a useful predictor of subsequent course achievements. The majority of the literature is, however, based on surveys and self-reports, methods which have well-known systematic biases that lead to limitations on conclusions and generalizability as well as being costly to implement. Here we propose a novel method for measuring class attendance that overcomes these limitations by using location and bluetooth data collected from smartphone sensors. Based on measured attendance data of nearly 1,000 undergraduate students, we demonstrate that early and consistent class attendance strongly correlates with academic performance. In addition, our novel dataset allows us to determine that attendance among social peers was substantially correlated (>0.5), suggesting either an important peer effect or homophily with respect to attendance. PMID:29117190

Class attendance, peer similarity, and academic performance in a large field study.

PubMed

Kassarnig, Valentin; Bjerre-Nielsen, Andreas; Mones, Enys; Lehmann, Sune; Lassen, David Dreyer

2017-01-01

Identifying the factors that determine academic performance is an essential part of educational research. Existing research indicates that class attendance is a useful predictor of subsequent course achievements. The majority of the literature is, however, based on surveys and self-reports, methods which have well-known systematic biases that lead to limitations on conclusions and generalizability as well as being costly to implement. Here we propose a novel method for measuring class attendance that overcomes these limitations by using location and bluetooth data collected from smartphone sensors. Based on measured attendance data of nearly 1,000 undergraduate students, we demonstrate that early and consistent class attendance strongly correlates with academic performance. In addition, our novel dataset allows us to determine that attendance among social peers was substantially correlated (>0.5), suggesting either an important peer effect or homophily with respect to attendance.

Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening

PubMed Central

Pan, Rui; Wang, Hansheng; Li, Runze

2016-01-01

This paper is concerned with the problem of feature screening for multi-class linear discriminant analysis under ultrahigh dimensional setting. We allow the number of classes to be relatively large. As a result, the total number of relevant features is larger than usual. This makes the related classification problem much more challenging than the conventional one, where the number of classes is small (very often two). To solve the problem, we propose a novel pairwise sure independence screening method for linear discriminant analysis with an ultrahigh dimensional predictor. The proposed procedure is directly applicable to the situation with many classes. We further prove that the proposed method is screening consistent. Simulation studies are conducted to assess the finite sample performance of the new procedure. We also demonstrate the proposed methodology via an empirical analysis of a real life example on handwritten Chinese character recognition. PMID:28127109

Assessing the development & implementation of a student-centered, "flipped" secondary physics curriculum in which IO-lab digital sensors are issued to students on a 1-to-1 basis

NASA Astrophysics Data System (ADS)

Cunnings, Christopher P.

This teacher-driven, action research dissertation study chronicles the development and implementation of a transformative, two-pronged, student-centered secondary physics education curriculum. From an instructional perspective, the curriculum was situated in the "flipped classroom" teaching approach, which minimizes in-class lecturing and instead predicates classroom learning on collaborative, hands-on, and activity-based lessons. Additionally, all students were issued IO-Lab digital sensors--learning tools developed by professors at the University of Illinois at Urbana-Champaign capable of collecting a vast array of real-time physical data-- on a 1-to-1, 24/7 basis for both in-class and at-home use. In-class, students participated in predominantly activity-based learning, with a sizeable portion of in-class activities incorporating IO-Labs for experimental data collection. Outside of class, students designed real-world research projects using their IO-Labs to study the physics underlying their everyday experiences, and all projects were video recorded, uploaded to YouTube, and then watched in-class to simulate a "mock science conference" in which students provided constructive feedback to each other on their experimental methods and results. The synergistic blending of a) flipped physics instruction, and b) perpetual access to state-of-the-art laboratory equipment, the two prongs forming the basis of this research study, inspired the curriculum title "Flipped IO-Lab," or "F-IO" curriculum. This dissertation study will provide a comprehensive assessment of the benefits and challenges that emerged while designing and implementing the F-IO curriculum from a practitioner's perspective. The assessment of the F-IO curriculum came about through a mixed-methods research methodology during kinematics and dynamics instruction. Specifically, this study includes "Force Concept Inventory" (FCI) pretest/posttest analysis to gauge changes in students' conceptual understanding of physics, as well as "Colorado Learning Attitudes about Science Survey" (CLASS) pre/post data to monitor students' shifts in scientific attitudes throughout the study. The aforementioned pre/post data will be triangulated with field notes and web-based "course opinion survey questions" to provide a comprehensive view of the F-IO curriculum. Significant analysis of the development of the course, as well as the relevant benefits, challenges, and considerations for "flipping" physics instruction, is also contained in this dissertation. The results of the research study include an FCI normalized gain of 0.74 (a "high gain" course), which indicates significant improvement in students' conceptual understanding of Newtonian Mechanics. Additionally, CLASS results indicate significant shifts in student attitudes from generally novice initial scientific perspectives to predominantly expert scientific perspectives by the conclusion of the research study. Of particular interest was students' acknowledgement and appreciation of the real-world implications of what they learned in physics class, as evidenced by CLASS survey data, real-world video challenge projects, and student comments before, during, and after class sessions. However, even despite all of the positive results that emerged throughout the study, a variety of challenges and concerns also materialized with regards to the utilization of F-IO curriculum principles, with the most pronounced being a subset of students whom remained unwilling to embrace web-based and/or flipped instructional teaching methods, preferring instead a more traditional instructional approach. The results and implications of this research study may not only be of interest to physics instructors, but also STEM educators, secondary curriculum designers, digital learning tool designers and researchers, and educational researchers.

Bifurcation to large period oscillations in physical systems controlled by delay

NASA Astrophysics Data System (ADS)

Erneux, Thomas; Walther, Hans-Otto

2005-12-01

An unusual bifurcation to time-periodic oscillations of a class of delay differential equations is investigated. As we approach the bifurcation point, both the amplitude and the frequency of the oscillations go to zero. The class of delay differential equations is a nonlinear extension of a nonevasive control method and is motivated by a recent study of the foreign exchange rate oscillations. By using asymptotic methods, we determine the bifurcation scaling laws for the amplitude and the period of the oscillations.

Three dimensional reliability analyses of currently used methods for assessment of sagittal jaw discrepancy

PubMed Central

Almaqrami, Bushra-Sufyan; Alhammadi, Maged-Sultan

2018-01-01

Background The objective of this study was to analyse three dimensionally the reliability and correlation of angular and linear measurements in assessment of anteroposterior skeletal discrepancy. Material and Methods In this retrospective cross sectional study, a sample of 213 subjects were three-dimensionally analysed from cone-beam computed tomography scans. The sample was divided according to three dimensional measurement of anteroposterior relation (ANB angle) into three groups (skeletal Class I, Class II and Class III). The anterior-posterior cephalometric indicators were measured on volumetric images using Anatomage software (InVivo5.2). These measurements included three angular and seven linear measurements. Cross tabulations were performed to correlate the ANB angle with each method. Intra-class Correlation Coefficient (ICC) test was applied for the difference between the two reliability measurements. P value of < 0.05 was considered significant. Results There was a statistically significant (P<0.05) agreement between all methods used with variability in assessment of different anteroposterior relations. The highest correlation was between ANB and DSOJ (0.913), strong correlation with AB/FH, AB/SN/, MM bisector, AB/PP, Wits appraisal (0.896, 0.890, 0.878, 0.867,and 0.858, respectively), moderate with AD/SN and Beta angle (0.787 and 0.760), and weak correlation with corrected ANB angle (0.550). Conclusions Conjunctive usage of ANB angle with DSOJ, AB/FH, AB/SN/, MM bisector, AB/PP and Wits appraisal in 3D cephalometric analysis provide a more reliable and valid indicator of the skeletal anteroposterior relationship. Clinical relevance: Most of orthodontic literature depends on single method (ANB) with its drawbacks in assessment of skeletal discrepancy which is a cardinal factors for proper treatment planning, this study assessed three dimensionally the degree of correlation between all available methods to make clinical judgement more accurate based on more than one method of assessment. Key words:Anteroposterior relationships, ANB angle, Three-dimension, CBCT. PMID:29750096

Approximation-based common principal component for feature extraction in multi-class brain-computer interfaces.

PubMed

Hoang, Tuan; Tran, Dat; Huang, Xu

2013-01-01

Common Spatial Pattern (CSP) is a state-of-the-art method for feature extraction in Brain-Computer Interface (BCI) systems. However it is designed for 2-class BCI classification problems. Current extensions of this method to multiple classes based on subspace union and covariance matrix similarity do not provide a high performance. This paper presents a new approach to solving multi-class BCI classification problems by forming a subspace resembled from original subspaces and the proposed method for this approach is called Approximation-based Common Principal Component (ACPC). We perform experiments on Dataset 2a used in BCI Competition IV to evaluate the proposed method. This dataset was designed for motor imagery classification with 4 classes. Preliminary experiments show that the proposed ACPC feature extraction method when combining with Support Vector Machines outperforms CSP-based feature extraction methods on the experimental dataset.

Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances.

PubMed

Al-Sahaf, Harith; Zhang, Mengjie; Johnston, Mark

2016-01-01

In the computer vision and pattern recognition fields, image classification represents an important yet difficult task. It is a challenge to build effective computer models to replicate the remarkable ability of the human visual system, which relies on only one or a few instances to learn a completely new class or an object of a class. Recently we proposed two genetic programming (GP) methods, one-shot GP and compound-GP, that aim to evolve a program for the task of binary classification in images. The two methods are designed to use only one or a few instances per class to evolve the model. In this study, we investigate these two methods in terms of performance, robustness, and complexity of the evolved programs. We use ten data sets that vary in difficulty to evaluate these two methods. We also compare them with two other GP and six non-GP methods. The results show that one-shot GP and compound-GP outperform or achieve results comparable to competitor methods. Moreover, the features extracted by these two methods improve the performance of other classifiers with handcrafted features and those extracted by a recently developed GP-based method in most cases.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity: in silico bioinformatic step-by-step guide using quantitative structure-activity relationships.

PubMed

Hattotuwagama, Channa K; Doytchinova, Irini A; Flower, Darren R

2007-01-01

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

40 CFR Figure C-2 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM 2.5 Candidate...

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 6 2014-07-01 2014-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM 2.5 Candidate Equivalent Methods C Figure C-2 to Subpart C of Part... Candidate Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-2 Figure C-2 to Subpart C of Part 53...

40 CFR Figure C-2 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM 2.5 Candidate...

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 6 2013-07-01 2013-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM 2.5 Candidate Equivalent Methods C Figure C-2 to Subpart C of Part... Candidate Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-2 Figure C-2 to Subpart C of Part 53...

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

PubMed

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

2015-09-01

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

Gaming via Computer Simulation Techniques for Junior College Economics Education. Final Report.

ERIC Educational Resources Information Center

Thompson, Fred A.

A study designed to answer the need for more attractive and effective economics education involved the teaching of one junior college economics class by the conventional (lecture) method and an experimental class by computer simulation techniques. Econometric models approximating the "real world" were computer programed to enable the experimental…

Delivery Style Moderates Study Habits in an Online Nutrition Class

ERIC Educational Resources Information Center

Connors, Priscilla

2013-01-01

Objective: To report how the design of an online class affected student ability to stay on task, find critical resources, and communicate with the instructor via e-mail. Methods: Audiorecorded focus group meetings at a United States university featured a structured approach to discussions among undergraduate students enrolled in an Internet…

Class Council between Democracy Learning and Character Education

ERIC Educational Resources Information Center

Budde, Jürgen; Weuster, Nora

2017-01-01

Purpose: Class council has become a popular approach for character education and democracy learning in German schools. However, it is not clear if the expectations are met in social practice. Approach: The data was gained with an ethnographical multiple method approach within three contrasting secondary schools. The study is informed by practice…

Audio and Written Comments in an Online Undergraduate Composition Class: Student and Instructor Approaches and Preferences

ERIC Educational Resources Information Center

Cavanaugh, Andrew; Song, Liyan

2015-01-01

This study investigated students' and instructors' approaches and preferences to audio and written comments in an online undergraduate composition class. A mixed-method design was employed utilizing both a survey instrument and interviews for data collection. Forty-nine students and five instructors participated. Students gave more positive…

Introducing Science Experiments to Rote-Learning Classes in Pakistani Middle Schools

ERIC Educational Resources Information Center

Pell, Anthony William; Iqbal, Hafiz Muhammad; Sohail, Shahida

2010-01-01

A mixed-methods sequential research design has been used to test the effect of introducing teacher science demonstrations to a traditional book-learning sample of 384 Grade 7 boys and girls from five schools in Lahore, Pakistan. In the quasi-experimental quantitative study, the eight classes of comparable ability were designated either…

Physical Activity Levels of Overweight and Nonoverweight High School Students during Physical Education Classes

ERIC Educational Resources Information Center

Hannon, James C.

2008-01-01

Background: This study examined physical activity (PA) levels of overweight and nonoverweight African American and Caucasian students (n = 198) during game play in physical education classes. Methods: Body fat percentages (%BFs) were determined using the skinfold technique and Slaughter et al prediction equations. Girls were classified as…

Using Latent Class Analysis to Model Temperament Types

ERIC Educational Resources Information Center

Loken, Eric

2004-01-01

Mixture models are appropriate for data that arise from a set of qualitatively different subpopulations. In this study, latent class analysis was applied to observational data from a laboratory assessment of infant temperament at four months of age. The EM algorithm was used to fit the models, and the Bayesian method of posterior predictive checks…

A Mixture Rasch Model-Based Computerized Adaptive Test for Latent Class Identification

ERIC Educational Resources Information Center

Jiao, Hong; Macready, George; Liu, Junhui; Cho, Youngmi

2012-01-01

This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback-Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions. When item separation was…

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,…

Informing the Discussion on Evaluator Training: A Look at Evaluators' Course Taking and Professional Practice

ERIC Educational Resources Information Center

Christie, Christina A.; Quiñones, Patricia; Fierro, Leslie

2014-01-01

This classification study examines evaluators' coursework training as a way of understanding evaluation practice. Data regarding courses that span methods and evaluation topics were collected from evaluation practitioners. Using latent class analysis, we establish four distinct classes of evaluator course-taking patterns: quantitative,…

Writing for Physics Mastery.

ERIC Educational Resources Information Center

Weber, Stephen W.

A study examined the effectiveness of incorporating writing as a tool to master the concepts of physics. Subjects were students in the three traditional physics classes and one non-math or conceptual physics class at East High School in Rockford, Illinois. The instructor tried a variety of methods--students wrote criticisms of Carl Sagan videos,…

Latent class analysis of eating and impulsive behavioral symptoms in Taiwanese women with bulimia nervosa.

PubMed

Tseng, Mei-Chih Meg; Hu, Fu-Chang

2012-01-01

The implications of impulsivity in its relationship with binge-eating or purging behaviors remain unclear. This study examined the patterns of eating behaviors and co-morbid impulsive behaviors in individuals with bulimia nervosa n optimally homogeneous classes using latent class analysis (LCA). All participants (n=180) were asked to complete a series of self-reported inventories of impulsive behaviors and other psychological measures. Information regarding the lifetime presence of symptoms of eating disorder was assessed by clinical interviews. LCA was conducted using eating disorder symptoms, impulsive behaviors, and the number of purging methods. Three latent classes of bulimic women were identified. These were women who exhibited relatively higher rates of purging, symptoms of impulsive behavior, and multiple purging methods (17.8%), women who used no more than one purging method with a low occurrence of impulsive behavior (41.7%), and women who showed higher rates of purging behaviors and the use of multiple purging methods with a low rate of impulsive behavior (41.7%). The impulsive sub-group had comparable severity of eating-related measures, frequency of binge-eating, and higher levels of general psychopathology than that of the other two sub-groups. This study provides empirical support for the existence of an impulsive subgroup with distinctive features among a non-Western group of BN patients. This study also suggests that mechanisms other than impulse dysregulation may exist for the development of binge-eating and purging behaviors in bulimia nervosa patients, or the mechanisms contributing to binge-eating and impulsive behaviors may be different. Copyright © 2011 Elsevier Inc. All rights reserved.

The Severe 5%: A Latent Class Analysis of the Externalizing Behavior Spectrum in the United States

PubMed Central

Vaughn, Michael G.; DeLisi, Matt; Gunterbh, Tracy; Fu, Qiang; Beaver, Kevin M.; Perron, Brian E.; Howard, Matthew O.

2012-01-01

Objective Criminological research consistently demonstrates that approximately 5% of study populations are comprised of pathological offenders who account for a preponderance of antisocial behavior and violent crime. Unfortunately, there have been no nationally representative epidemiological studies characterizing the severe 5% group. Materials and Methods Data from the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative sample of 43,093 non-institutionalized U.S. residents aged 18 years and older were analyzed using latent class analysis to assess sociodemographic, psychiatric, and behavioral characteristics. Results Four-classes of respondents were identified vis-à-vis lifetime externalizing behaviors. A normative class (66.1% of respondents) demonstrated little involvement in antisocial conduct. A low substance use/high antisocial behavior class (20.7% of respondents) and high substance use/moderate antisocial behavior (8.0% of respondents) class evinced diverse externalizing and psychiatric symptoms. Finally, a severe class (5.3% of respondents) was characterized by pathological involvement in more varied and intensive forms of antisocial and externalizing behaviors and extensive psychiatric disturbance. Conclusions The current study is the first nationally representative epidemiological study of criminal careers/externalizing behavior spectrum in the United States and validates the existence of the 5% pathological group demonstrated by prior research. PMID:22942480

Profile of Students Uninterested in Practicum Class at Faculty of Engineering Universitas Negeri Surabaya

NASA Astrophysics Data System (ADS)

Munoto; Sondang, Meini; Satriana, FMS

2018-04-01

This study aims to determine the characteristics of students who were uninterested in attending practicum classes. This study applied naturalistic qualitative research methods using participatory observation and interviews. The data validity was ensured by triangulation, detailed description, length of observation time, as well as details and thorough observation. The data were analyzed using domain analysis and followed by conducting taxonomic, component, and thematic analyses. The results of the study indicate that faineant students show a negative behavior while attending laboratory practicums. They have a lack of motivation, effective interaction, and attention. The cognitive abilities vary from low to high. Other causes on how the aspects of the study were low were found as well, therefore improving those aspects allows students to raise their interest in practicum classes. The impact is to create well-skilled vocational teachers in conducting practicum classes in vocational schools and to make graduates better-prepared for the workforce.

Multi-angle backscatter classification and sub-bottom profiling for improved seafloor characterization

NASA Astrophysics Data System (ADS)

Alevizos, Evangelos; Snellen, Mirjam; Simons, Dick; Siemes, Kerstin; Greinert, Jens

2018-06-01

This study applies three classification methods exploiting the angular dependence of acoustic seafloor backscatter along with high resolution sub-bottom profiling for seafloor sediment characterization in the Eckernförde Bay, Baltic Sea Germany. This area is well suited for acoustic backscatter studies due to its shallowness, its smooth bathymetry and the presence of a wide range of sediment types. Backscatter data were acquired using a Seabeam1180 (180 kHz) multibeam echosounder and sub-bottom profiler data were recorded using a SES-2000 parametric sonar transmitting 6 and 12 kHz. The high density of seafloor soundings allowed extracting backscatter layers for five beam angles over a large part of the surveyed area. A Bayesian probability method was employed for sediment classification based on the backscatter variability at a single incidence angle, whereas Maximum Likelihood Classification (MLC) and Principal Components Analysis (PCA) were applied to the multi-angle layers. The Bayesian approach was used for identifying the optimum number of acoustic classes because cluster validation is carried out prior to class assignment and class outputs are ordinal categorical values. The method is based on the principle that backscatter values from a single incidence angle express a normal distribution for a particular sediment type. The resulting Bayesian classes were well correlated to median grain sizes and the percentage of coarse material. The MLC method uses angular response information from five layers of training areas extracted from the Bayesian classification map. The subsequent PCA analysis is based on the transformation of these five layers into two principal components that comprise most of the data variability. These principal components were clustered in five classes after running an external cluster validation test. In general both methods MLC and PCA, separated the various sediment types effectively, showing good agreement (kappa >0.7) with the Bayesian approach which also correlates well with ground truth data (r2 > 0.7). In addition, sub-bottom data were used in conjunction with the Bayesian classification results to characterize acoustic classes with respect to their geological and stratigraphic interpretation. The joined interpretation of seafloor and sub-seafloor data sets proved to be an efficient approach for a better understanding of seafloor backscatter patchiness and to discriminate acoustically similar classes in different geological/bathymetric settings.

Hydrophilic interaction liquid chromatography-mass spectrometry of (lyso)phosphatidic acids, (lyso)phosphatidylserines and other lipid classes.

PubMed

Cífková, Eva; Hájek, Roman; Lísa, Miroslav; HolĿapek, Michal

2016-03-25

The goal of this work is a systematic optimization of hydrophilic interaction liquid chromatography (HILIC) separation of acidic lipid classes (namely phosphatidic acids-PA, lysophosphatidic acids-LPA, phosphatidylserines-PS and lysophosphatidylserines-LPS) and other lipid classes under mass spectrometry (MS) compatible conditions. The main parameters included in this optimization are the type of stationary phases used in HILIC, pH of the mobile phase, the type and concentration of mobile phase additives. Nine HILIC columns with different chemistries (unmodified silica, modified silica using diol, 2-picolylamine, diethylamine and 1-aminoanthracene and hydride silica) are compared with the emphasis on peak shapes of acidic lipid classes. The optimization of pH is correlated with the theoretical calculation of acidobasic equilibria of studied lipid classes. The final method using the hydride column, pH 4 adjusted by formic acid and the gradient of acetonitrile and 40 mmol/L of aqueous ammonium formate provides good peak shapes for all analyzed lipid classes including acidic lipids. This method is applied for the identification of lipids in real samples of porcine brain and kidney extracts. Copyright © 2016 Elsevier B.V. All rights reserved.

Interactive Learning in the Classroom: Is Student Response Method Related to Performance?

ERIC Educational Resources Information Center

Elicker, Joelle D.; McConnell, Nicole L.

2011-01-01

This study examined three methods of responding to in-class multiple-choice concept questions in an Introduction to Psychology course. Specifically, this study compared exam performance and student reactions using three methods of responding to concept questions: (a) a technology-based network system, (b) hand-held flashcards, and (c) hand…

On a class of Newton-like methods for solving nonlinear equations

NASA Astrophysics Data System (ADS)

Argyros, Ioannis K.

2009-06-01

We provide a semilocal convergence analysis for a certain class of Newton-like methods considered also in [I.K. Argyros, A unifying local-semilocal convergence analysis and applications for two-point Newton-like methods in Banach space, J. Math. Anal. Appl. 298 (2004) 374-397; I.K. Argyros, Computational theory of iterative methods, in: C.K. Chui, L. Wuytack (Eds.), Series: Studies in Computational Mathematics, vol. 15, Elsevier Publ. Co, New York, USA, 2007; J.E. Dennis, Toward a unified convergence theory for Newton-like methods, in: L.B. Rall (Ed.), Nonlinear Functional Analysis and Applications, Academic Press, New York, 1971], in order to approximate a locally unique solution of an equation in a Banach space. Using a combination of Lipschitz and center-Lipschitz conditions, instead of only Lipschitz conditions [F.A. Potra, Sharp error bounds for a class of Newton-like methods, Libertas Math. 5 (1985) 71-84], we provide an analysis with the following advantages over the work in [F.A. Potra, Sharp error bounds for a class of Newton-like methods, Libertas Math. 5 (1985) 71-84] which improved the works in [W.E. Bosarge, P.L. Falb, A multipoint method of third order, J. Optimiz. Theory Appl. 4 (1969) 156-166; W.E. Bosarge, P.L. Falb, Infinite dimensional multipoint methods and the solution of two point boundary value problems, Numer. Math. 14 (1970) 264-286; J.E. Dennis, On the Kantorovich hypothesis for Newton's method, SIAM J. Numer. Anal. 6 (3) (1969) 493-507; J.E. Dennis, Toward a unified convergence theory for Newton-like methods, in: L.B. Rall (Ed.), Nonlinear Functional Analysis and Applications, Academic Press, New York, 1971; H.J. Kornstaedt, Ein allgemeiner Konvergenzstaz fü r verschä rfte Newton-Verfahrem, in: ISNM, vol. 28, Birkhaü ser Verlag, Basel and Stuttgart, 1975, pp. 53-69; P. Laasonen, Ein überquadratisch konvergenter iterativer algorithmus, Ann. Acad. Sci. Fenn. Ser I 450 (1969) 1-10; F.A. Potra, On a modified secant method, L'analyse numérique et la theorie de l'approximation 8 (2) (1979) 203-214; F.A. Potra, An application of the induction method of V. Pták to the study of Regula Falsi, Aplikace Matematiky 26 (1981) 111-120; F.A. Potra, On the convergence of a class of Newton-like methods, in: Iterative Solution of Nonlinear Systems of Equations, in: Lecture Notes in Mathematics, vol. 953, Springer-Verlag, New York, 1982; F.A. Potra, V. Pták, Nondiscrete induction and double step secant method, Math. Scand. 46 (1980) 236-250; F.A. Potra, V. Pták, On a class of modified Newton processes, Numer. Funct. Anal. Optim. 2 (1) (1980) 107-120; F.A. Potra, Sharp error bounds for a class of Newton-like methods, Libertas Math. 5 (1985) 71-84; J.W. Schmidt, Untere Fehlerschranken für Regula-Falsi Verfahren, Period. Math. Hungar. 9 (3) (1978) 241-247; J.W. Schmidt, H. Schwetlick, Ableitungsfreie Verfhren mit höherer Konvergenzgeschwindifkeit, Computing 3 (1968) 215-226; J.F. Traub, Iterative Methods for the Solution of Equations, Prentice Hall, Englewood Cliffs, New Jersey, 1964; M.A. Wolfe, Extended iterative methods for the solution of operator equations, Numer. Math. 31 (1978) 153-174]: larger convergence domain and weaker sufficient convergence conditions. Numerical examples further validating the results are also provided.

Statistically Derived Subtypes and Associations with Cerebrospinal Fluid and Genetic Biomarkers in Mild Cognitive Impairment: A Latent Profile Analysis.

PubMed

Eppig, Joel S; Edmonds, Emily C; Campbell, Laura; Sanderson-Cimino, Mark; Delano-Wood, Lisa; Bondi, Mark W

2017-08-01

Research demonstrates heterogeneous neuropsychological profiles among individuals with mild cognitive impairment (MCI). However, few studies have included visuoconstructional ability or used latent mixture modeling to statistically identify MCI subtypes. Therefore, we examined whether unique neuropsychological MCI profiles could be ascertained using latent profile analysis (LPA), and subsequently investigated cerebrospinal fluid (CSF) biomarkers, genotype, and longitudinal clinical outcomes between the empirically derived classes. A total of 806 participants diagnosed by means of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI criteria received a comprehensive neuropsychological battery assessing visuoconstructional ability, language, attention/executive function, and episodic memory. Test scores were adjusted for demographic characteristics using standardized regression coefficients based on "robust" normal control performance (n=260). Calculated Z-scores were subsequently used in the LPA, and CSF-derived biomarkers, genotype, and longitudinal clinical outcome were evaluated between the LPA-derived MCI classes. Statistical fit indices suggested a 3-class model was the optimal LPA solution. The three-class LPA consisted of a mixed impairment MCI class (n=106), an amnestic MCI class (n=455), and an LPA-derived normal class (n=245). Additionally, the amnestic and mixed classes were more likely to be apolipoprotein e4+ and have worse Alzheimer's disease CSF biomarkers than LPA-derived normal subjects. Our study supports significant heterogeneity in MCI neuropsychological profiles using LPA and extends prior work (Edmonds et al., 2015) by demonstrating a lower rate of progression in the approximately one-third of ADNI MCI individuals who may represent "false-positive" diagnoses. Our results underscore the importance of using sensitive, actuarial methods for diagnosing MCI, as current diagnostic methods may be over-inclusive. (JINS, 2017, 23, 564-576).

Incorporating active-learning techniques into the photonics-related teaching in the Erasmus Mundus Master in "Color in Informatics and Media Technology"

NASA Astrophysics Data System (ADS)

Pozo, Antonio M.; Rubiño, Manuel; Hernández-Andrés, Javier; Nieves, Juan L.

2014-07-01

In this work, we present a teaching methodology using active-learning techniques in the course "Devices and Instrumentation" of the Erasmus Mundus Master's Degree in "Color in Informatics and Media Technology" (CIMET). A part of the course "Devices and Instrumentation" of this Master's is dedicated to the study of image sensors and methods to evaluate their image quality. The teaching methodology that we present consists of incorporating practical activities during the traditional lectures. One of the innovative aspects of this teaching methodology is that students apply the concepts and methods studied in class to real devices. For this, students use their own digital cameras, webcams, or cellphone cameras in class. These activities provide students a better understanding of the theoretical subject given in class and encourage the active participation of students.

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI.

PubMed

Mehranian, Abolfazl; Arabi, Hossein; Zaidi, Habib

2016-04-15

In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly challenged by the need of deriving accurate attenuation maps from MR images. A number of strategies have been developed for MRI-guided attenuation correction with different degrees of success. In this work, we compare the quantitative performance of three generic AC methods, including standard 3-class MR segmentation-based, advanced atlas-registration-based and emission-based approaches in the context of brain time-of-flight (TOF) PET/MRI. Fourteen patients referred for diagnostic MRI and (18)F-FDG PET/CT brain scans were included in this comparative study. For each study, PET images were reconstructed using four different attenuation maps derived from CT-based AC (CTAC) serving as reference, standard 3-class MR-segmentation, atlas-registration and emission-based AC methods. To generate 3-class attenuation maps, T1-weighted MRI images were segmented into background air, fat and soft-tissue classes followed by assignment of constant linear attenuation coefficients of 0, 0.0864 and 0.0975 cm(-1) to each class, respectively. A robust atlas-registration based AC method was developed for pseudo-CT generation using local weighted fusion of atlases based on their morphological similarity to target MR images. Our recently proposed MRI-guided maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm was employed to estimate the attenuation map from TOF emission data. The performance of the different AC algorithms in terms of prediction of bones and quantification of PET tracer uptake was objectively evaluated with respect to reference CTAC maps and CTAC-PET images. Qualitative evaluation showed that the MLAA-AC method could sparsely estimate bones and accurately differentiate them from air cavities. It was found that the atlas-AC method can accurately predict bones with variable errors in defining air cavities. Quantitative assessment of bone extraction accuracy based on Dice similarity coefficient (DSC) showed that MLAA-AC and atlas-AC resulted in DSC mean values of 0.79 and 0.92, respectively, in all patients. The MLAA-AC and atlas-AC methods predicted mean linear attenuation coefficients of 0.107 and 0.134 cm(-1), respectively, for the skull compared to reference CTAC mean value of 0.138cm(-1). The evaluation of the relative change in tracer uptake within 32 distinct regions of the brain with respect to CTAC PET images showed that the 3-class MRAC, MLAA-AC and atlas-AC methods resulted in quantification errors of -16.2 ± 3.6%, -13.3 ± 3.3% and 1.0 ± 3.4%, respectively. Linear regression and Bland-Altman concordance plots showed that both 3-class MRAC and MLAA-AC methods result in a significant systematic bias in PET tracer uptake, while the atlas-AC method results in a negligible bias. The standard 3-class MRAC method significantly underestimated cerebral PET tracer uptake. While current state-of-the-art MLAA-AC methods look promising, they were unable to noticeably reduce quantification errors in the context of brain imaging. Conversely, the proposed atlas-AC method provided the most accurate attenuation maps, and thus the lowest quantification bias. Copyright © 2016 Elsevier Inc. All rights reserved.

Teaching Qualitative Research Methods Using "Undercover Boss"

ERIC Educational Resources Information Center

Graham, LaKresha; Schuwerk, Tara J.

2017-01-01

Course(s): Research Methods, Qualitative Research Methods, Organizational Communication, Business Communication. Objectives: After completing this class exercise, students should be able to identify the major components of a qualitative research study, along with the ethical dilemmas that come with doing qualitative research.

Comparison of different methods to quantify fat classes in bakery products.

PubMed

Shin, Jae-Min; Hwang, Young-Ok; Tu, Ock-Ju; Jo, Han-Bin; Kim, Jung-Hun; Chae, Young-Zoo; Rhu, Kyung-Hun; Park, Seung-Kook

2013-01-15

The definition of fat differs in different countries; thus whether fat is listed on food labels depends on the country. Some countries list crude fat content in the 'Fat' section on the food label, whereas other countries list total fat. In this study, three methods were used for determining fat classes and content in bakery products: the Folch method, the automated Soxhlet method, and the AOAC 996.06 method. The results using these methods were compared. Fat (crude) extracted by the Folch and Soxhlet methods was gravimetrically determined and assessed by fat class using capillary gas chromatography (GC). In most samples, fat (total) content determined by the AOAC 996.06 method was lower than the fat (crude) content determined by the Folch or automated Soxhlet methods. Furthermore, monounsaturated fat or saturated fat content determined by the AOAC 996.06 method was lowest. Almost no difference was observed between fat (crude) content determined by the Folch method and that determined by the automated Soxhlet method for nearly all samples. In three samples (wheat biscuits, butter cookies-1, and chocolate chip cookies), monounsaturated fat, saturated fat, and trans fat content obtained by the automated Soxhlet method was higher than that obtained by the Folch method. The polyunsaturated fat content obtained by the automated Soxhlet method was not higher than that obtained by the Folch method in any sample. Copyright © 2012 Elsevier Ltd. All rights reserved.

The effect of peer interactions on Newtonian thinking in secondary physics: What are they saying? How does it help?

NASA Astrophysics Data System (ADS)

Crowe, Jacalyn

Many studies in the field of Physics Education Research (PER) have demonstrated that courses which include a component of interaction among peers achieve significantly higher gains in conceptual understanding. Few of those studies have closely examined the content of those interactions and the role that they play in achieving those gains. This study evaluates the role of peer interaction in children's understanding of Newtonian physics and analyzes the characteristics of peer interaction that are conducive to better learning. The current study took place in a suburban public high school, in a college-preparatory, introductory course in physics. One hundred and seventy eight students were randomly placed in the eight classes participating in the study. Two of the classes were randomly chosen to constitute the treatment group and were taught by the principal investigator. The remaining six classes were taught by five other instructors in the department and served as a control or comparison group. One class session of each instructor was videotaped to assess how class time was typically utilized. In all classes, students used the same textbook, and completed the same problem sets and laboratory investigations. Students in the treatment group participated in peer instruction activities, approximately twice per week, over the course of the semester. Results showed a significant effect of treatment on achievement from pre- to post-test, based on scores on the Force and Motion Conceptual Evaluation (FMCE). Employing peer instruction methods did not require additional instructional time overall. Analysis of classroom videotapes demonstrated that a greater portion of class time is dedicated to active student discussion in classes where peer instruction methods are employed. Conversational data revealed that, in peer discussions, students were routinely involved in conversational mechanisms such as articulating their own thinking, questioning, and explanation. Each of these behaviors is believed to support improved conceptual understanding. Correlating the quantity of total comments and number of substantive comments to achievement on the FMCE post-test produced mixed results, with some significant positive correlations and other positive but non-significant ones. Failure to reach significance for these correlations may have resulted from the small sample size. A focus on changes in students' conceptions about force and motion, as identified by analysis of clusters of FMCE questions, revealed significant differences in changes in those conceptions between the treatment and control groups. Anecdotal evidence from transcripts supports the assertion that, in their conversations, students routinely articulated and discussed their own ideas about these relationships. In conclusion, the study provided evidence that peer instruction methods are an effective and efficient method of supporting improved conceptual understanding for students in a first course in mechanics, but no specific factors present in the discussions could be identified as playing a role for every student. Instead, different aspects of the discussions' format and content may have contributed to the overall achievement of students participating in the discussions.

The Effects of Blog-Mediated Peer Feedback on Learners' Motivation, Collaboration, and Course Satisfaction in a Second Language Writing Course

ERIC Educational Resources Information Center

Zhang, Haisen; Song, Wei; Shen, Suping; Huang, Ronghuai

2014-01-01

This paper reported on a study of using blogs as out-of-class assignments for the development of learners' writing competence. There were 36 students of English majors from an intact second language (L2) writing class participating in this study. A mixed method design was employed to obtain both quantitative and qualitative data. The results…

The impact of rigorous mathematical thinking as learning method toward geometry understanding

NASA Astrophysics Data System (ADS)

Nugraheni, Z.; Budiyono, B.; Slamet, I.

2018-05-01

To reach higher order thinking skill, needed to be mastered the conceptual understanding. RMT is a unique realization of the cognitive conceptual construction approach based on Mediated Learning Experience (MLE) theory by Feurstein and Vygotsky’s sociocultural theory. This was quasi experimental research which was comparing the experimental class that was given Rigorous Mathematical Thinking (RMT) as learning method and control class that was given Direct Learning (DL) as the conventional learning activity. This study examined whether there was different effect of two learning method toward conceptual understanding of Junior High School students. The data was analyzed by using Independent t-test and obtained a significant difference of mean value between experimental and control class on geometry conceptual understanding. Further, by semi-structure interview known that students taught by RMT had deeper conceptual understanding than students who were taught by conventional way. By these result known that Rigorous Mathematical Thinking (RMT) as learning method have positive impact toward Geometry conceptual understanding.

Detailed classification of swimming paths in the Morris Water Maze: multiple strategies within one trial

PubMed Central

Gehring, Tiago V.; Luksys, Gediminas; Sandi, Carmen; Vasilaki, Eleni

2015-01-01

The Morris Water Maze is a widely used task in studies of spatial learning with rodents. Classical performance measures of animals in the Morris Water Maze include the escape latency, and the cumulative distance to the platform. Other methods focus on classifying trajectory patterns to stereotypical classes representing different animal strategies. However, these approaches typically consider trajectories as a whole, and as a consequence they assign one full trajectory to one class, whereas animals often switch between these strategies, and their corresponding classes, within a single trial. To this end, we take a different approach: we look for segments of diverse animal behaviour within one trial and employ a semi-automated classification method for identifying the various strategies exhibited by the animals within a trial. Our method allows us to reveal significant and systematic differences in the exploration strategies of two animal groups (stressed, non-stressed), that would be unobserved by earlier methods. PMID:26423140

40 CFR Figure C-2 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM2.5 Candidate...

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 6 2012-07-01 2012-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM2.5 Candidate Equivalent Methods C Figure C-2 to Subpart C of Part 53... Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-2 Figure C-2 to Subpart C of Part 53—Illustration...

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Code of Federal Regulations, 2013 CFR

2013-07-01

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40 CFR Figure C-3 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM10−2.5 Candidate...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM10â2.5 Candidate Equivalent Methods C Figure C-3 to Subpart C of Part... Candidate Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-3 Figure C-3 to Subpart C of Part 53...

40 CFR Figure C-3 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM10−2.5 Candidate...

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 6 2012-07-01 2012-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM10â2.5 Candidate Equivalent Methods C Figure C-3 to Subpart C of Part... Candidate Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-3 Figure C-3 to Subpart C of Part 53...

40 CFR Figure C-2 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM2.5 Candidate...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM2.5 Candidate Equivalent Methods C Figure C-2 to Subpart C of Part 53... Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-2 Figure C-2 to Subpart C of Part 53—Illustration...

40 CFR Figure C-3 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM 10-2.5 Candidate...

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 6 2014-07-01 2014-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM 10-2.5 Candidate Equivalent Methods C Figure C-3 to Subpart C of... Candidate Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-3 Figure C-3 to Subpart C of Part 53...

40 CFR Figure C-2 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM2.5 Candidate...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM2.5 Candidate Equivalent Methods C Figure C-2 to Subpart C of Part 53... Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-2 Figure C-2 to Subpart C of Part 53—Illustration...

40 CFR Figure C-3 to Subpart C of... - Illustration of the Slope and Intercept Limits for Class II and Class III PM10−2.5 Candidate...

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Illustration of the Slope and Intercept Limits for Class II and Class III PM10â2.5 Candidate Equivalent Methods C Figure C-3 to Subpart C of Part... Candidate Methods and Reference Methods Pt. 53, Subpt. C, Fig. C-3 Figure C-3 to Subpart C of Part 53...

Estimates of Forest Biomass Carbon Storage in Liaoning Province of Northeast China: A Review and Assessment

PubMed Central

Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J.; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

2014-01-01

Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha−1 in 1980 to 31.0 Mg ha−1 in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations. PMID:24586881

Estimates of forest biomass carbon storage inLiaoning Province of Northeast China: a review and assessment.

PubMed

Yu, Dapao; Wang, Xiaoyu; Yin, You; Zhan, Jinyu; Lewis, Bernard J; Tian, Jie; Bao, Ye; Zhou, Wangming; Zhou, Li; Dai, Limin

2014-01-01

Accurate estimates of forest carbon storage and changes in storage capacity are critical for scientific assessment of the effects of forest management on the role of forests as carbon sinks. Up to now, several studies reported forest biomass carbon (FBC) in Liaoning Province based on data from China's Continuous Forest Inventory, however, their accuracy were still not known. This study compared estimates of FBC in Liaoning Province derived from different methods. We found substantial variation in estimates of FBC storage for young and middle-age forests. For provincial forests with high proportions in these age classes, the continuous biomass expansion factor method (CBM) by forest type with age class is more accurate and therefore more appropriate for estimating forest biomass. Based on the above approach designed for this study, forests in Liaoning Province were found to be a carbon sink, with carbon stocks increasing from 63.0 TgC in 1980 to 120.9 TgC in 2010, reflecting an annual increase of 1.9 TgC. The average carbon density of forest biomass in the province has increased from 26.2 Mg ha(-1) in 1980 to 31.0 Mg ha(-1) in 2010. While the largest FBC occurred in middle-age forests, the average carbon density decreased in this age class during these three decades. The increase in forest carbon density resulted primarily from the increased area and carbon storage of mature forests. The relatively long age interval in each age class for slow-growing forest types increased the uncertainty of FBC estimates by CBM-forest type with age class, and further studies should devote more attention to the time span of age classes in establishing biomass expansion factors for use in CBM calculations.

Meta-analysis of teaching methods: a 50k+ student study

NASA Astrophysics Data System (ADS)

Sayre, Eleanor; Archibeque, Benjamin; Gomez, K. Alison; Heckendorf, Tyrel; Madsen, Adrian M.; McKagan, Sarah B.; Schenk, Edward W.; Shepard, Chase; Sorell, Lane; von Korff, Joshua

2015-04-01

The Force Concept Inventory (FCI) and the Force and Motion Conceptual Evaluation (FMCE) are the two most widely-used conceptual tests in introductory mechanics. Because they are so popular, they provide an excellent avenue to compare different teaching methods at different kinds of institutions with varying student populations. We conducted a secondary analysis of all peer-reviewed papers which publish data from US and Canadian colleges and universities. Our data include over fifty thousand students drawn from approximately 100 papers; papers were drawn from Scopus, ERIC, ComPADRE, and journal websites. We augment published data about teaching methods with institutional data such as Carnegie Classification and average SAT scores. We statistically determine the effectiveness of different teaching methods as measured by FCI and FMCE gains and mediated by institutional and course factors. As in the landmark 1998 Hake study, we find that classes using interactive engagement (IE) have significantly larger learning gains than classes using traditional instruction. However, we find a broader distribution of normalized gains occurs in each of traditional and IE classes, and the differences between IE and traditional instruction have changed over time and are more context dependent.

The effects of occupational class transitions on hypertension: racial disparities among working-age men.

PubMed Central

Waitzman, N J; Smith, K R

1994-01-01

OBJECTIVES. This study was undertaken to examine how the interaction between occupational class transitions and race affects the incidence of hypertension. METHODS. A cohort of 1982 men (183 Black), ages 25 to 55, received a baseline medical exam between 1971 and 1975 and a follow-up between 1982 and 1984. Logistic regressions were estimated for hypertension at follow-up controlling for hypertension at baseline, other risk factors associated with blood pressure, and interaction terms identifying specific occupational class transitions among Blacks and Whites. The occupational class matrix was based largely on scores of US Census Bureau occupations from the Dictionary of Occupational Titles. RESULTS. Relative to Whites who remained in professional and technical jobs between baseline and follow-up, Blacks and Whites who remained in lower occupational classes or made specific transitions--notably into the lowest class--had significantly higher incidence rates of hypertension. These differences were greater among Blacks, who are also more concentrated in and less likely to move upward from the lower end of the occupational class matrix. CONCLUSIONS. Widening racial disparities in high blood pressure over the period of study may be partly attributable to characteristics associated with occupational class position and dynamics. PMID:8203691

Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). User's Manual for the ECLS-K:2011 Kindergarten Data File and Electronic Codebook, Public Version. NCES 2015-074

ERIC Educational Resources Information Center

Tourangeau, Karen; Nord, Christine; Lê, Thanh; Sorongon, Alberto G.; Hagedorn, Mary C.; Daly, Peggy; Najarian, Michelle

2015-01-01

This manual provides guidance and documentation for users of the kindergarten (or base year) data of the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11 (ECLS-K:2011). It begins with an overview of the ECLS-K:2011. Subsequent chapters provide details on the study data collection instruments and methods; the direct and indirect…

Swine Leukocyte Antigen Diversity in Canadian Specific Pathogen-Free Yorkshire and Landrace Pigs

PubMed Central

Gao, Caixia; Quan, Jinqiang; Jiang, Xinjie; Li, Changwen; Lu, Xiaoye; Chen, Hongyan

2017-01-01

The highly polymorphic swine major histocompatibility complex (MHC), termed swine leukocyte antigen (SLA), is associated with different levels of immunologic responses to infectious diseases, vaccines, and transplantation. Pig breeds with known SLA haplotypes are important genetic resources for biomedical research. Canadian Yorkshire and Landrace pigs represent the current specific pathogen-free (SPF) breeding stock maintained in the isolation environment at the Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences. In this study, we identified 61 alleles at five polymorphic SLA loci (SLA-1, SLA-2, SLA-3, DRB1, and DQB1) representing 17 class I haplotypes and 11 class II haplotypes using reverse transcription-polymerase chain reaction (RT-PCR) sequence-based typing and PCR-sequence specific primers methods in 367 Canadian SPF Yorkshire and Landrace pigs. The official designation of the alleles has been assigned by the SLA Nomenclature Committee of the International Society for Animal Genetics and released in updated Immuno Polymorphism Database-MHC SLA sequence database [Release 2.0.0.3 (2016-11-03)]. The submissions confirmed some unassigned alleles and standardized nomenclatures of many previously unconfirmed alleles in the GenBank database. Three class I haplotypes, Hp-37.0, 63.0, and 73.0, appeared to be novel and have not previously been reported in other pig populations. One crossover within the class I region and two between class I and class II regions were observed, resulting in three new recombinant haplotypes. The presence of the duplicated SLA-1 locus was confirmed in three class I haplotypes Hp-28.0, Hp-35.0, and Hp-63.0. Furthermore, we also analyzed the functional diversities of 19 identified frequent SLA class I molecules in this study and confirmed the existence of four supertypes using the MHCcluster method. These results will be useful for studying the adaptive immune response and immunological phenotypic differences in pigs, screening potential T-cell epitopes, and further developing the more effective vaccines. PMID:28360911

Dermal and inhalation acute toxic class methods: test procedures and biometric evaluations for the Globally Harmonized Classification System.

PubMed

Holzhütter, H G; Genschow, E; Diener, W; Schlede, E

2003-05-01

The acute toxic class (ATC) methods were developed for determining LD(50)/LC(50) estimates of chemical substances with significantly fewer animals than needed when applying conventional LD(50)/LC(50) tests. The ATC methods are sequential stepwise procedures with fixed starting doses/concentrations and a maximum of six animals used per dose/concentration. The numbers of dead/moribund animals determine whether further testing is necessary or whether the test is terminated. In recent years we have developed classification procedures for the oral, dermal and inhalation routes of administration by using biometric methods. The biometric approach assumes a probit model for the mortality probability of a single animal and assigns the chemical to that toxicity class for which the best concordance is achieved between the statistically expected and the observed numbers of dead/moribund animals at the various steps of the test procedure. In previous publications we have demonstrated the validity of the biometric ATC methods on the basis of data obtained for the oral ATC method in two-animal ring studies with 15 participants from six countries. Although the test procedures and biometric evaluations for the dermal and inhalation ATC methods have already been published, there was a need for an adaptation of the classification schemes to the starting doses/concentrations of the Globally Harmonized Classification System (GHS) recently adopted by the Organization for Economic Co-operation and Development (OECD). Here we present the biometric evaluation of the dermal and inhalation ATC methods for the starting doses/concentrations of the GHS and of some other international classification systems still in use. We have developed new test procedures and decision rules for the dermal and inhalation ATC methods, which require significantly fewer animals to provide predictions of toxicity classes, that are equally good or even better than those achieved by using the conventional LD(50)/LC(50) methods. In order to cope with rather narrow dose/concentration classes of the GHS we have, as in our previous publications, combined the outcome of all results that can be obtained during testing for the allocation to one of the defined toxicity classes of the GHS. Our results strongly recommend the deletion of the dermal LD(50) and the inhalation LC(50) test as regulatory tests and the adoption of the dermal and inhalation ATC methods as internationally accepted alternatives.

Fuzzy support vector machine for microarray imbalanced data classification

NASA Astrophysics Data System (ADS)

Ladayya, Faroh; Purnami, Santi Wulan; Irhamah

2017-11-01

DNA microarrays are data containing gene expression with small sample sizes and high number of features. Furthermore, imbalanced classes is a common problem in microarray data. This occurs when a dataset is dominated by a class which have significantly more instances than the other minority classes. Therefore, it is needed a classification method that solve the problem of high dimensional and imbalanced data. Support Vector Machine (SVM) is one of the classification methods that is capable of handling large or small samples, nonlinear, high dimensional, over learning and local minimum issues. SVM has been widely applied to DNA microarray data classification and it has been shown that SVM provides the best performance among other machine learning methods. However, imbalanced data will be a problem because SVM treats all samples in the same importance thus the results is bias for minority class. To overcome the imbalanced data, Fuzzy SVM (FSVM) is proposed. This method apply a fuzzy membership to each input point and reformulate the SVM such that different input points provide different contributions to the classifier. The minority classes have large fuzzy membership so FSVM can pay more attention to the samples with larger fuzzy membership. Given DNA microarray data is a high dimensional data with a very large number of features, it is necessary to do feature selection first using Fast Correlation based Filter (FCBF). In this study will be analyzed by SVM, FSVM and both methods by applying FCBF and get the classification performance of them. Based on the overall results, FSVM on selected features has the best classification performance compared to SVM.

The Influence of Alternative Pedagogical Methods in Postsecondary Biology Education: How Do Students Experience a Multimedia Case-Study Environment?

ERIC Educational Resources Information Center

Wolter, Bjorn Hugo Karl

2010-01-01

The purpose of this study was to better understand how an online, multimedia case study method influenced students' motivation, performance, and perceptions of science in collegiate level biology classes. It utilized a mix-methods design including data from pre- and post-test, student surveys, and focus group interviews to answer one primary…

Pilot study of a targeted dance class for physical rehabilitation in children with cerebral palsy

PubMed Central

López-Ortiz, Citlali; Egan, Tara; Gaebler-Spira, Deborah J

2016-01-01

Introduction: This pilot study evaluates the effects of a targeted dance class utilizing classical ballet principles for rehabilitation of children with cerebral palsy on balance and upper extremity control. Methods: Twelve children with cerebral palsy (ages 7–15 years) with Gross Motor Function Classification scores II–IV participated in this study and were assigned to either a control group or targeted dance class group. Targeted dance class group participated in 1-h classes three times per week in a 4-week period. The Pediatric Balance Scale and the Quality of Upper Extremity Skills Test were administered before, after, and 1 month after the targeted dance class. Results: Improvements in the Pediatric Balance Scale were present in the targeted dance class group in before versus after and before versus 1 month follow-up comparisons (p-value = 0.0088 and p-value = 0.019, respectively). The Pediatric Balance Scale changes were not significant in the control group. The Quality of Upper Extremity Skills Test did not reach statistical differences in either group. Conclusion: Classical ballet as an art form involves physical training, musical accompaniment, social interactions, and emotional expression that could serve as adjunct to traditional physical therapy. This pilot study demonstrated improvements in balance control. A larger study with a more homogeneous sample is warranted. PMID:27721977

A Holistic Approach to the Social Studies.

ERIC Educational Resources Information Center

Davidson, Bonnie

The document explains the need for holistic social studies teaching methods, proposes a holistic model for use in a fourth grade social studies class, and places the model within the general context of social studies education. A holistic method is defined as a way of teaching which is cognitively and affectively integrated with individual…

Positive Psychology in the Class: The Effectiveness of a Teaching Method Based on Subjective Well-Being and Engagement Increasing Activities

ERIC Educational Resources Information Center

Eryilmaz, Ali

2015-01-01

The aim of the present study is investigate that the effectiveness of a teaching method which is based on subjective well-being increasing activities and engagement increasing activities, has been developed for university students in the present study. The method of the present study is a mixed method. Thus, the most important feature of it has…

Assessing Bilingual Knowledge Organization in Secondary Science Classrooms =

NASA Astrophysics Data System (ADS)

Wu, Jason S.

Improving outcomes for English language learners (ELLs) in secondary science remains an area of high need. The purpose of this study is to investigate bilingual knowledge organization in secondary science classrooms. This study involved thirty-nine bilingual students in three biology classes at a public high school in The Bronx, New York City. Methods included an in-class survey on language use, a science content and English proficiency exam, and bilingual free-recalls. Fourteen students participated in bilingual free-recalls which involved a semi-structured process of oral recall of information learned in science class. Free-recall was conducted in both English and Spanish and analyzed using flow-map methods. Novel methods were developed to quantify and visualize the elaboration and mobilization of ideas shared across languages. It was found that bilingual narratives displayed similar levels of organizational complexity across languages, though English recalls tended to be longer. English proficiency was correlated with narrative complexity in English. There was a high degree of elaboration on concepts shared across languages. Finally, higher Spanish proficiency correlated well with greater overlapping elaboration across languages. These findings are discussed in light of current cognitive theory before presenting the study's limitations and future directions of research.

[Impacts of collaborative teaching method on the teaching achievement of Acupuncture and Moxibustion].

PubMed

Tian, Haomei; Shen, Jing; Shi, Jia; Liu, Mi; Wang, Chao; Liu, Jinzhi; Chen, Chutao

2016-11-12

To explore the impacts of collaborative teaching method on the teaching achievement of Acupuncture and Moxibustion . Six classes in Hunan University of CM of 2012 grade Chinese medicine department were randomized into an observation group and a control group, 3 classes in each one. In the observation group, the collaborative teaching method was adopted, in which, different teaching modes were used according to the characteristics of each chapter and the study initiative of students was predominated. In the control group, the traditional teaching method was used, in which, the class teaching was the primary and the practice was the secondary in the section of techniques of acupuncture and moxibustion. The results of each curriculum and the total results were compared between the two groups during the whole semester. Compared with the control group, in the observation group, the total achievements of curriculum and case analysis combined with the total result of the theory examination were apparently improved (both P <0.01). The collaborative teaching method improves the comprehensive ability of students and provides a new approach to the teaching of Acupuncture and Moxibustion .

Early parenting program as intervention strategy for emotional distress in first-time mothers: a propensity score analysis.

PubMed

Okamoto, Miwako; Ishigami, Hideaki; Tokimoto, Kumiko; Matsuoka, Megumi; Tango, Ryoko

2013-08-01

The purpose of this study is to evaluate the effectiveness of a single session intervention designed to reduce emotional distress in first-time mothers. We held a parenting class for first-time mothers who had given birth at a university hospital in Tokyo, Japan. The program of the class consists of lectures on infant care and group discussion, which is a common form of intervention in Japan. The effectiveness of intervention is assessed according to differences in emotional distress experienced by class participants and nonparticipants, and analyzed by the use of a propensity score method to avoid self-selection bias. In order to be more confident about our results, we employ several variations of this method. Results from statistical analysis show that although the effectiveness of the intervention was limited, it was able to alleviate subjects' loss of self-confidence as mothers. Because this outcome shows a good degree of consistency across methods, it can be considered robust. Moreover, it is roughly consistent with previous studies. Effectiveness can probably be increased by developing a program that improves upon the intervention.

Does self-defense training prevent sexual violence against women?

PubMed

Hollander, Jocelyn A

2014-03-01

Self-defense classes are offered across the nation as a strategy for reducing women's vulnerability to sexual assault. Yet there has been little systematic research assessing the effectiveness of these classes. In this article, I use data from a mixed methods study of a 10-week, university-based, feminist self-defense class to examine the effectiveness of self-defense training over a 1-year follow-up period. My analyses indicate that women who participate in self-defense training are less likely to experience sexual assault and are more confident in their ability to effectively resist assault than similar women who have not taken such a class.

An overview of the kinetic parameters of class B beta-lactamases.

PubMed Central

Felici, A; Amicosante, G; Oratore, A; Strom, R; Ledent, P; Joris, B; Fanuel, L; Frère, J M

1993-01-01

The catalytic properties of three class B beta-lactamases (from Pseudomonas maltophilia, Aeromonas hydrophila and Bacillus cereus) were studied and compared with those of the Bacteroides fragilis enzyme. The A. hydrophila beta-lactamase exhibited a unique specificity profile and could be considered as a rather specific 'carbapenemase'. No relationships were found between sequence similarities and catalytic properties. The problem of the repartition of class B beta-lactamases into sub-classes is discussed. Improved purification methods were devised for the P. maltophilia and A. hydrophila beta-lactamases including, for the latter enzyme, a very efficient affinity chromatography step on a Zn(2+)-chelate column. Images Figure 1 PMID:8471035

[Fast discrimination of edible vegetable oil based on Raman spectroscopy].

PubMed

Zhou, Xiu-Jun; Dai, Lian-Kui; Li, Sheng

2012-07-01

A novel method to fast discriminate edible vegetable oils by Raman spectroscopy is presented. The training set is composed of different edible vegetable oils with known classes. Based on their original Raman spectra, baseline correction and normalization were applied to obtain standard spectra. Two characteristic peaks describing the unsaturated degree of vegetable oil were selected as feature vectors; then the centers of all classes were calculated. For an edible vegetable oil with unknown class, the same pretreatment and feature extraction methods were used. The Euclidian distances between the feature vector of the unknown sample and the center of each class were calculated, and the class of the unknown sample was finally determined by the minimum distance. For 43 edible vegetable oil samples from seven different classes, experimental results show that the clustering effect of each class was more obvious and the class distance was much larger with the new feature extraction method compared with PCA. The above classification model can be applied to discriminate unknown edible vegetable oils rapidly and accurately.

Naming, the formation of stimulus classes, and applied behavior analysis.

PubMed

Stromer, R; Mackay, H A; Remington, B

1996-01-01

The methods used in Sidman's original studies on equivalence classes provide a framework for analyzing functional verbal behavior. Sidman and others have shown how teaching receptive, name-referent matching may produce rudimentary oral reading and word comprehension skills. Eikeseth and Smith (1992) have extended these findings by showing that children with autism may acquire equivalence classes after learning to supply a common oral name to each stimulus in a potential class. A stimulus class analysis suggests ways to examine (a) the problem of programming generalization from teaching situations to other environments, (b) the expansion of the repertoires that occur in those settings, and (c) the use of naming to facilitate these forms of generalization. Such research will help to clarify and extend Horne and Lowe's recent (1996) account of the role of verbal behavior in the formation of stimulus classes.

Influence of Social Class Perceptions on Attributions among Mental Health Practitioners

PubMed Central

Thomposon, Mindi; Diestelmann, Jacob; Cole, Odessa; Keller, Abiola; Minami, Takuya

2018-01-01

Objective A vignette-based study assessed the influence of social class attributions toward a hypothetical client’s difficulty. Method 188 licensed mental health professionals who were recruited through professional listservs completed an online survey after reviewing one of two versions of a vignette describing a hypothetical client that varied based on social class cues. Results As expected, this sample of licensed mental health practitioners detected social class differences based on the descriptors of the hypothetical client across the two vignettes. These perceived social class differences, however, did not impact participants’ attributions toward the client for causing or solving her problems, level of GAF score ascribed to the client, or willingness to work with the client. Conclusions There was no evidence that participants differentially ascribed attributions based on social class. Implications and directions for future research are provided. PMID:24499284

MHC class I loci of the Bar-Headed goose (Anser indicus)

PubMed Central

2010-01-01

MHC class I proteins mediate functions in anti-pathogen defense. MHC diversity has already been investigated by many studies in model avian species, but here we chose the bar-headed goose, a worldwide migrant bird, as a non-model avian species. Sequences from exons encoding the peptide-binding region (PBR) of MHC class I molecules were isolated from liver genomic DNA, to investigate variation in these genes. These are the first MHC class I partial sequences of the bar-headed goose to be reported. A preliminary analysis suggests the presence of at least four MHC class I genes, which share great similarity with those of the goose and duck. A phylogenetic analysis of bar-headed goose, goose and duck MHC class I sequences using the NJ method supports the idea that they all cluster within the anseriforms clade. PMID:21637434

Authentication of bee pollen grains in bright-field microscopy by combining one-class classification techniques and image processing.

PubMed

Chica, Manuel

2012-11-01

A novel method for authenticating pollen grains in bright-field microscopic images is presented in this work. The usage of this new method is clear in many application fields such as bee-keeping sector, where laboratory experts need to identify fraudulent bee pollen samples against local known pollen types. Our system is based on image processing and one-class classification to reject unknown pollen grain objects. The latter classification technique allows us to tackle the major difficulty of the problem, the existence of many possible fraudulent pollen types, and the impossibility of modeling all of them. Different one-class classification paradigms are compared to study the most suitable technique for solving the problem. In addition, feature selection algorithms are applied to reduce the complexity and increase the accuracy of the models. For each local pollen type, a one-class classifier is trained and aggregated into a multiclassifier model. This multiclassification scheme combines the output of all the one-class classifiers in a unique final response. The proposed method is validated by authenticating pollen grains belonging to different Spanish bee pollen types. The overall accuracy of the system on classifying fraudulent microscopic pollen grain objects is 92.3%. The system is able to rapidly reject pollen grains, which belong to nonlocal pollen types, reducing the laboratory work and effort. The number of possible applications of this authentication method in the microscopy research field is unlimited. Copyright © 2012 Wiley Periodicals, Inc.

A systematic review of statistical methods used to test for reliability of medical instruments measuring continuous variables.

PubMed

Zaki, Rafdzah; Bulgiba, Awang; Nordin, Noorhaire; Azina Ismail, Noor

2013-06-01

Reliability measures precision or the extent to which test results can be replicated. This is the first ever systematic review to identify statistical methods used to measure reliability of equipment measuring continuous variables. This studyalso aims to highlight the inappropriate statistical method used in the reliability analysis and its implication in the medical practice. In 2010, five electronic databases were searched between 2007 and 2009 to look for reliability studies. A total of 5,795 titles were initially identified. Only 282 titles were potentially related, and finally 42 fitted the inclusion criteria. The Intra-class Correlation Coefficient (ICC) is the most popular method with 25 (60%) studies having used this method followed by the comparing means (8 or 19%). Out of 25 studies using the ICC, only 7 (28%) reported the confidence intervals and types of ICC used. Most studies (71%) also tested the agreement of instruments. This study finds that the Intra-class Correlation Coefficient is the most popular method used to assess the reliability of medical instruments measuring continuous outcomes. There are also inappropriate applications and interpretations of statistical methods in some studies. It is important for medical researchers to be aware of this issue, and be able to correctly perform analysis in reliability studies.

Bacterial populations within copper mine tailings: long-term effects of amendment with Class A biosolids

USDA-ARS?s Scientific Manuscript database

This study evaluates the effect of surface application of dried Class A biosolids on microbial populations within copper mine tailings. Methods and Results: Mine tailing sites were established at ASARCO Mission Mine close to Sahuarita, Arizona. Site 1 (Dec. 1998) was amended with 248 tons ha-1 of C...

A BETTER INDICATOR STUDY EXAMINES ALTERNATIVE BIOLOGICAL INDICATORS OF DISINFECTION IN LIME-TREATED BIOSOLIDS

EPA Science Inventory

Under the current regulations (CFR 503), Class B biosolids may be land applied with certain site restrictions. One method for achieving Class B status is to raise the pH of the sludge to >12 for a minimum of 2 hours with an alkaline material (normally lime). Alternately, a Clas...

"Fun" Pedagogy Curtails Intellectual Rigor in a U.S. History Class

ERIC Educational Resources Information Center

DiCamillo, Lorrei

2010-01-01

This case study examines a U.S. History class where a veteran teacher uses challenging primary source documents and a debate to encourage his students to think critically about history. The teacher is knowledgeable about the subject matter and articulates a clear purpose for teaching. Surprisingly, the author finds that the teacher's methods,…

A Comparative Study of a Research-Oriented High School Advanced Biology Class and a Conventional Textbook-Centered Class.

ERIC Educational Resources Information Center

Smith, Alva Nelson

Two instructional methods were identified and compared to determine if any significant differences could be noted on three criterion measures. Measurements were conducted in the areas of achievement in biology, science attitudes, and critical thinking ability. Student ability was measured using pre-tests and the Scholastic Aptitude Test. Students…

Prevalence Estimation and Validation of New Instruments in Psychiatric Research: An Application of Latent Class Analysis and Sensitivity Analysis

ERIC Educational Resources Information Center

Pence, Brian Wells; Miller, William C.; Gaynes, Bradley N.

2009-01-01

Prevalence and validation studies rely on imperfect reference standard (RS) diagnostic instruments that can bias prevalence and test characteristic estimates. The authors illustrate 2 methods to account for RS misclassification. Latent class analysis (LCA) combines information from multiple imperfect measures of an unmeasurable latent condition to…

Relationship between Course Length and Graduate Student Outcome Measures

ERIC Educational Resources Information Center

Carman, Carol A.; Bartsch, Robert A.

2017-01-01

One method to increase flexibility in class offerings is through the use of compressed courses, classes that have the same number of contact hours but over a shorter time period (e.g., 8 weeks vs. 15 weeks). Before offering these courses, it is important to determine whether they lead to equivalent or better student outcomes. This study examined…

Bayesian Inference for Growth Mixture Models with Latent Class Dependent Missing Data

ERIC Educational Resources Information Center

Lu, Zhenqiu Laura; Zhang, Zhiyong; Lubke, Gitta

2011-01-01

"Growth mixture models" (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM is first presented in which class…

Health-Related Intensity Profiles of Physical Education Classes at Different Phases of the Teaching/Learning Process

ERIC Educational Resources Information Center

Bronikowski, Michal; Bronikowska, Malgorzata; Kantanista, Adam; Ciekot, Monika; Laudanska-Krzeminska, Ida; Szwed, Szymon

2009-01-01

Study aim: To assess the intensities of three types of physical education (PE) classes corresponding to the phases of the teaching/learning process: Type 1--acquiring and developing skills, Type 2--selecting and applying skills, tactics and compositional principles and Type 3--evaluating and improving performance skills. Material and methods: A…

Mixture Item Response Theory-MIMIC Model: Simultaneous Estimation of Differential Item Functioning for Manifest Groups and Latent Classes

ERIC Educational Resources Information Center

Bilir, Mustafa Kuzey

2009-01-01

This study uses a new psychometric model (mixture item response theory-MIMIC model) that simultaneously estimates differential item functioning (DIF) across manifest groups and latent classes. Current DIF detection methods investigate DIF from only one side, either across manifest groups (e.g., gender, ethnicity, etc.), or across latent classes…

Cultural Differences in Child Rearing: A Comparison of Immigrant Chinese and Caucasian American Mothers.

ERIC Educational Resources Information Center

Kelley, Michelle L.; Tseng, Hui-Mei

1992-01-01

Studies cultural differences in child rearing practices of 38 middle-class Chinese immigrant mothers and 38 middle-class Caucasian-American mothers of 3-8 year olds. Results suggest similarity in child-rearing goals of both groups, although Chinese-American immigrant mothers rely on traditional Chinese methods of socialization to achieve these…

Gender-Specific Instructional Strategies and Student Achievement in 5th Grade Classrooms

ERIC Educational Resources Information Center

Dickey, Millicent Whitener

2014-01-01

There are three purposes of this mixed methods phenomenological case study. First, the researcher attempted to determine if there is evidence that teachers in single-sex classes adjust the delivery of the academic content when compared to coeducational classes. Secondly, while trying to understand the phenomenon of learning in a single-sex…

[Analysis of commercial specifications and grades of wild and cultivated Gentianae Macrophyllae Radix based on multi-indicative constituents].

PubMed

Yang, Yan-Mei; Lin, Li; Lu, You-Yuan; Ma, Xiao-Hui; Jin, Ling; Zhu, Tian-Tian

2016-03-01

The study is aimed to analyze the commercial specifications and grades of wild and cultivated Gentianae Macrophllae Radix based on multi-indicative constituents. The seven kinds of main chemical components containing in Gentianae Macrophyllae Radix were determined by UPLC, and then the quality levels of chemical component of Gentianae Macrophyllae Radix were clustered and classified by modern statistical methods (canonical correspondence analysis, Fisher discriminant analysis and so on). The quality indices were selected and their correlations were analyzed. Lastly, comprehensively quantitative grade division for quality under different commodity-specifications and different grades of same commodity-specifications of wild and planting were divided. The results provide a basis for a reasonable division of specification and grade of the commodity of Gentianae Macrophyllae Radix. The range of quality evaluation of main index components (gentiopicrin, loganin acid and swertiamarin) was proposed, and the Herbal Quality Index (HQI) was introduced. The rank discriminant function was established based on the quality by Fisher discriminant analysis. According to the analysis, the quality of wild and cultivated Luobojiao, one of the commercial specification of Gentianae Macrophyllae Radix was the best, Mahuajiao, the other commercial specification, was average , Xiaoqinjiao was inferior. Among grades, the quality of first-class cultivated Luobojiao was the worst, of second class secondary, and the third class the best; The quality of the first-class of wild Luobojiao was secondary, and the second-class the best; The quality of the second-class of Mahuajiao was secondary, and the first-class was the best; the quality of first-class Xiaoqinjiao was secondary, and the second-class was the better one between the two grades, but not obvious significantly. The method provides a new idea and method for evaluation of comprehensively quantitative on the quality of Gentianae Macrophyllae Radix. Copyright© by the Chinese Pharmaceutical Association.

A classification scheme for turbulent flows based on their joint velocity-intermittency structure

NASA Astrophysics Data System (ADS)

Keylock, C. J.; Nishimura, K.; Peinke, J.

2011-12-01

Kolmogorov's classic theory for turbulence assumed an independence between velocity increments and the value for the velocity itself. However, this assumption is questionable, particularly in complex geophysical flows. Here we propose a framework for studying velocity-intermittency coupling that is similar in essence to the popular quadrant analysis method for studying near-wall flows. However, we study the dominant (longitudinal) velocity component along with a measure of the roughness of the signal, given mathematically by its series of Hölder exponents. Thus, we permit a possible dependence between velocity and intermittency. We compare boundary layer data obtained in a wind tunnel to turbulent jets and wake flows. These flow classes all have distinct velocity-intermittency characteristics, which cause them to be readily distinguished using our technique. Our method is much simpler and quicker to apply than approaches that condition the velocity increment statistics at some scale, r, on the increment statistics at a neighbouring, larger spatial scale, r+Δ, and the velocity itself. Classification of environmental flows is then possible based on their similarities to the idealised flow classes and we demonstrate this using laboratory data for flow in a parallel-channel confluence where the region of flow recirculation in the lee of the step is discriminated as a flow class distinct from boundary layer, jet and wake flows. Hence, using our method, it is possible to assign a flow classification to complex geophysical, turbulent flows depending upon which idealised flow class they most resemble.

Examination of Pre-Service Science Teachers' Activities Using Problem Based Learning Method

ERIC Educational Resources Information Center

Ekici, Didem Inel

2016-01-01

In this study, both the activities prepared by pre-service science teachers regarding the Problem Based Learning method and the pre-service science teachers' views regarding the method were examined before and after applying their activities in a real class environment. 69 pre-service science teachers studying in the 4th grade of the science…

Comparison of Three Tobacco Survey Methods with College Students: A Case Study

ERIC Educational Resources Information Center

James, Delores C. S.; Chen, W. William; Sheu, Jiunn-Jye

2005-01-01

The goals of this case study were to: (1) determine the efficiency and effectiveness of three survey methods--postal mail survey, web-based survey, and random in-class administration survey--in assessing tobacco-related attitudes and behaviors among college students and (2) compare the response rate and procedures of these three methods. There was…

A Comparative Investigation of the Efficiency of Two Classroom Observational Methods.

ERIC Educational Resources Information Center

Kissel, Mary Ann

The problem of this study was to determine whether Method A is a more efficient observational method for obtaining activity type behaviors in an individualized classroom than Method B. Method A requires the observer to record the activities of the entire class at given intervals while Method B requires only the activities of selected individuals…

Making the Undergraduate Classroom into a Policy Think Tank: Reflections from a Field Methods Class

ERIC Educational Resources Information Center

Broughton, Chad

2011-01-01

This article examines the opportunities and limitations presented by organizing an undergraduate field research methods class as a policy think tank working for a government client. Organized as such, the course had both the learning objectives of a traditional undergraduate methods class and the corporate objectives of a policy think tank (i.e.,…

The implementation of integrated science teaching materials based socio-scientific issues to improve students scientific literacy for environmental pollution theme

NASA Astrophysics Data System (ADS)

Yenni, Rita; Hernani, Widodo, Ari

2017-05-01

The study aims to determine the increasing of students' science literacy skills on content aspects and competency of science by using Integrated Science teaching materials based Socio-scientific Issues (SSI) for environmental pollution theme. The method used in the study is quasi-experiment with nonequivalent pretest and posttest control group design. The students of experimental class used teaching materials based SSI, whereas the students of control class were still using the usual textbooks. The result of this study showed a significant difference between the value of N-gain of experimental class and control class, whichalso occurred in every indicator of content aspects and competency of science. This result indicates that using of Integrated Science teaching materials based SSI can improve content aspect and competency of science and can be used as teaching materials alternative in teaching of Integrated Science.

“Chickens Are a Lot Smarter than I Originally Thought”: Changes in Student Attitudes to Chickens Following a Chicken Training Class

PubMed Central

Hazel, Susan J.; O’Dwyer, Lisel; Ryan, Terry

2015-01-01

Simple Summary Our attitudes to animals are linked to our beliefs about their cognitive abilities, such as intelligence and capacity to experience emotional states. In this study, undergraduate students were surveyed on their attitudes to chickens pre- and post- a practical class in which they learnt to clicker train chickens. Students were more likely to agree that chickens are intelligent and easy to teach tricks to, and that chickens feel emotions such as boredom, frustration and happiness, following the practical class. Similar workshops may be an effective method to improve animal training skills, and promote more positive attitudes to specific animal species. Abstract A practical class using clicker training of chickens to apply knowledge of how animals learn and practice skills in animal training was added to an undergraduate course. Since attitudes to animals are related to their perceived intelligence, surveys of student attitudes were completed pre- and post- the practical class, to determine if (1) the practical class changed students’ attitudes to chickens and their ability to experience affective states, and (2) any changes were related to previous contact with chickens, training experience or gender. In the post- versus pre-surveys, students agreed more that chickens are easy to teach tricks to, are intelligent, and have individual personalities and disagreed more that they are difficult to train and are slow learners. Following the class, they were more likely to believe chickens experience boredom, frustration and happiness. Females rated the intelligence and ability to experience affective states in chickens more highly than males, although there were shifts in attitude in both genders. This study demonstrated shifts in attitudes following a practical class teaching clicker training in chickens. Similar practical classes may provide an effective method of teaching animal training skills and promoting more positive attitudes to animals. PMID:26479388

Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.

PubMed

Rakha, E A; Soria, D; Green, A R; Lemetre, C; Powe, D G; Nolan, C C; Garibaldi, J M; Ball, G; Ellis, I O

2014-04-02

Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. In this study, we hypothesised that molecular features of BC are a key driver of tumour behaviour and when coupled with a novel and bespoke application of established clinicopathologic prognostic variables can predict both clinical outcome and relevant therapeutic options more accurately than existing methods. In the current study, a comprehensive panel of biomarkers with relevance to BC was applied to a large and well-characterised series of BC, using immunohistochemistry and different multivariate clustering techniques, to identify the key molecular classes. Subsequently, each class was further stratified using a set of well-defined prognostic clinicopathologic variables. These variables were combined in formulae to prognostically stratify different molecular classes, collectively known as the Nottingham Prognostic Index Plus (NPI+). The NPI+ was then used to predict outcome in the different molecular classes. Seven core molecular classes were identified using a selective panel of 10 biomarkers. Incorporation of clinicopathologic variables in a second-stage analysis resulted in identification of distinct prognostic groups within each molecular class (NPI+). Outcome analysis showed that using the bespoke NPI formulae for each biological BC class provides improved patient outcome stratification superior to the traditional NPI. This study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making.

Confidence intervals for differences between volumes under receiver operating characteristic surfaces (VUS) and generalized Youden indices (GYIs).

PubMed

Yin, Jingjing; Nakas, Christos T; Tian, Lili; Reiser, Benjamin

2018-03-01

This article explores both existing and new methods for the construction of confidence intervals for differences of indices of diagnostic accuracy of competing pairs of biomarkers in three-class classification problems and fills the methodological gaps for both parametric and non-parametric approaches in the receiver operating characteristic surface framework. The most widely used such indices are the volume under the receiver operating characteristic surface and the generalized Youden index. We describe implementation of all methods and offer insight regarding the appropriateness of their use through a large simulation study with different distributional and sample size scenarios. Methods are illustrated using data from the Alzheimer's Disease Neuroimaging Initiative study, where assessment of cognitive function naturally results in a three-class classification setting.

Mathematics Achievement: Traditional Instruction and Technology-Assisted Course Delivery Methods

ERIC Educational Resources Information Center

Vilardi, Robert

2013-01-01

The purpose of this study was to analyze technology-assisted course delivery methods to determine their overall effectiveness as it pertains to mathematics courses. This study analyzed both current and historical data in mathematics classes in the areas of achievement, retention, and grade distribution. The goal of this study was to determine if…

Mathematics Achievement: Traditional Instruction and Technology-Assisted Course Delivery Methods

ERIC Educational Resources Information Center

Vilardi, Robert; Rice, Margaret L.

2014-01-01

The purpose of this study was to analyze technology-assisted course delivery methods to determine their overall effectiveness as it pertains to mathematics courses. This study analyzed both current and historical data in the areas of achievement, retention, and grade distribution for mathematics classes. The study included 14,562 students enrolled…

Crystallographic Study of Itokawa Particle, RA-QD02-0127 by Using Energy-Scanning X-Ray Diffraction Method with Synchrotron Radiation

NASA Astrophysics Data System (ADS)

Hagiya, K.; Ohsumi, K.; Komatsu, M.; Mikouchi, T.; Zolensky, M. E.; Hirata, A.; Yamaguchi, S.; Kurokawa, A.

2016-08-01

Crystallographic study of Itokawa particle, RA-QD02-0127 by using new X-ray diffraction method was performed. The purpose of this study is to understand better the metamorphic and impact shock history of asteroid Itokawa, and other S-class asteroids.

Integrated argument-based inquiry with multiple representation approach to promote scientific argumentation skill

NASA Astrophysics Data System (ADS)

Suminar, Iin; Muslim, Liliawati, Winny

2017-05-01

The purpose of this research was to identify student's written argument embedded in scientific inqury investigation and argumentation skill using integrated argument-based inquiry with multiple representation approach. This research was using quasi experimental method with the nonequivalent pretest-posttest control group design. Sample ot this research was 10th grade students at one of High School in Bandung using two classes, they were 26 students of experiment class and 26 students of control class. Experiment class using integrated argument-based inquiry with multiple representation approach, while control class using argument-based inquiry. This study was using argumentation worksheet and argumentation test. Argumentation worksheet encouraged students to formulate research questions, design experiment, observe experiment and explain the data as evidence, construct claim, warrant, embedded multiple modus representation and reflection. Argumentation testinclude problem which asks students to explain evidence, warrants, and backings support of each claim. The result of this research show experiment class students's argumentation skill performed better than control class students that of experiment class was 0.47 and control class was 0.31. The results of unequal variance t-test for independent means show that students'sargumentationskill of experiment class performed better significantly than students'sargumentationskill of control class.

Recent Advances in Experimental Whole Genome Haplotyping Methods

PubMed Central

Huang, Mengting; Lu, Zuhong

2017-01-01

Haplotype plays a vital role in diverse fields; however, the sequencing technologies cannot resolve haplotype directly. Pioneers demonstrated several approaches to resolve haplotype in the early years, which was extensively reviewed. Since then, numerous methods have been developed recently that have significantly improved phasing performance. Here, we review experimental methods that have emerged mainly over the past five years, and categorize them into five classes according to their maximum scale of contiguity: (i) encapsulation, (ii) 3D structure capture and construction, (iii) compartmentalization, (iv) fluorography, (v) long-read sequencing. Several subsections of certain methods are attached to each class as instances. We also discuss the relative advantages and disadvantages of different classes and make comparisons among representative methods of each class. PMID:28891974

Personality preference distribution of dental students admitted to one dental school using different selection methods.

PubMed

von Bergmann, Hsingchi; Dalrymple, Kirsten R; Shuler, Charles F

2014-04-01

This study sought to determine whether using the Myers-Briggs Type Indicator (MBTI) would detect differences in personality preferences in first-year dental students admitted to the same dental school through different admission methods. First-year dental students admitted in 2000 and 2001 were given the MBTI instrument during orientation prior to the start of classes. In fall 2000, the Class of 2004 had 140 students, with 116 in the traditional track and twenty-four in the parallel problem-based learning (PBL) track. In fall 2001, the Class of 2005 had 144 students, all enrolled in the PBL curriculum. All students admitted to the PBL track had experienced a process that included evaluation of their participation in a small group. Students in the traditional track had individual interviews with faculty members. Both student groups were required to meet the same baseline grade point average and Dental Admission Test standards. In 2000, the PBL students showed personality preferences that were distinctly different from the personality preferences of traditional track students in the categories of Extroversion (89 percent PBL, 44 percent traditional) and Thinking (72 percent PBL, 39 percent traditional). In 2001, the all-PBL class retained the trend towards Extroversion (69 percent). This study suggests that admission method may effectively change the personality preference distribution exhibited by the students who are admitted to dental school.

A study on the impact of prioritising emergency department arrivals on the patient waiting time.

PubMed

Van Bockstal, Ellen; Maenhout, Broos

2018-05-03

In the past decade, the crowding of the emergency department has gained considerable attention of researchers as the number of medical service providers is typically insufficient to fulfil the demand for emergency care. In this paper, we solve the stochastic emergency department workforce planning problem and consider the planning of nurses and physicians simultaneously for a real-life case study in Belgium. We study the patient arrival pattern of the emergency department in depth and consider different patient acuity classes by disaggregating the arrival pattern. We determine the personnel staffing requirements and the design of the shifts based on the patient arrival rates per acuity class such that the resource staffing cost and the weighted patient waiting time are minimised. In order to solve this multi-objective optimisation problem, we construct a Pareto set of optimal solutions via the -constraints method. For a particular staffing composition, the proposed model minimises the patient waiting time subject to upper bounds on the staffing size using the Sample Average Approximation Method. In our computational experiments, we discern the impact of prioritising the emergency department arrivals. Triaging results in lower patient waiting times for higher priority acuity classes and to a higher waiting time for the lowest priority class, which does not require immediate care. Moreover, we perform a sensitivity analysis to verify the impact of the arrival and service pattern characteristics, the prioritisation weights between different acuity classes and the incorporated shift flexibility in the model.

Heavy metals characteristics of settled particles of streets dust from Diwaniyah City- Qadisiyah Governorate - Southern Iraq

NASA Astrophysics Data System (ADS)

Al-Dabbas, Moutaz A.; Mahdi, Khalid H.; Al-Khafaji, Raad; Obayes, Kawthar H.

2018-05-01

Road-side dust samples were collected from selected areas of Diwaniyah city-Qadisiyah Governorate - Southern Iraq. The heavy metals (Fe, Co, Ni, Cu, Zn and Pb) in these streets dust samples were studied and used as indicator for pollution by using three of main indices (I-geo, CF, and PLI). Determination of heavy metal in the roadside dust is with XRD and XRF methods. I-geo for Co, Zn, Pb, and Ni in the studied sites shows relative values of class 1, which indicated the slightly polluted, while I-geo for Fe and Cu shows relative values of class 0, which indicated no pollution. The contamination factor for Co, Zn, Pb, and Ni classified as class 2, which indicate moderately contamination, while the contamination factor for Fe and Cu classified as class 1, which indicate low contamination. PLI values in the all of studied sites classified as class 2 (Deterioration on site quality) indicating local pollution, as well as denote perfection with (class 0) of no pollution. The distribution pattern of metals percentages was affected by gases emitted from transportation vehicles as well as the prevailing wind direction.

Frequency of CPV infection in vaccinated puppies that attended puppy socialization classes.

PubMed

Stepita, Meredith E; Bain, Melissa J; Kass, Philip H

2013-01-01

Socialization is one method of preventing behavior problems in dogs; however, some oppose socialization before 16 wk of age due to the risk of contracting infectious diseases. The objectives of this study were to determine if puppies that attended puppy socialization classes and were vaccinated by a veterinarian at least once were at an increased risk of confirmed canine parvovirus (CPV) infection compared with puppies that did not attend classes and to determine the frequency of suspected CPV infection in puppies vaccinated at least once that attended classes with trainers. Twenty-one clinics in four cities in the United States provided information regarding demographics, vaccination, CPV diagnosis, and class attendance for puppies ≤ 16 wk of age. In addition, 24 trainers in those same cities collected similar information on puppies that attended their classes. In total, 279 puppies attended socialization classes and none were suspected of or diagnosed with CPV infection. Results indicated that vaccinated puppies attending socialization classes were at no greater risk of CPV infection than vaccinated puppies that did not attend those classes.

Pharmacy Students’ Performance and Perceptions in a Flipped Teaching Pilot on Cardiac Arrhythmias

PubMed Central

Ip, Eric J.; Lopes, Ingrid; Rajagopalan, Vanishree

2014-01-01

Objective. To implement the flipped teaching method in a 3-class pilot on cardiac arrhythmias and to assess the impact of the intervention on academic performance and student perceptions. Design. An intervention group of 101 first-year pharmacy students, who took the class with the flipped teaching method, were supplied with prerecorded lectures prior to their 3 classes (1 class in each of the following subjects: basic sciences, pharmacology, and therapeutics) on cardiac arrhythmias. Class time was focused on active-learning and case-based exercises. Students then took a final examination that included questions on cardiac arrhythmias. The examination scores of the intervention group were compared to scores of the Spring 2011 control group of 105 first-year students who took the class with traditional teaching methods. An online survey was conducted to assess student feedback from the intervention group. Assessment. The mean examination scores of the intervention group were significantly higher than the mean examination scores of the control group for the cardiac arrhythmia classes in pharmacology (with 89.6 ± 2.0% vs 56.8 ± 2.2%, respectively) and therapeutics (89.2 ± 1.4% vs 73.7 ± 2.1%, respectively). The survey indicated higher student satisfaction for flipped classes with highly rated learning objectives, recordings, and in-class activities. Conclusion. Use of the flipped teaching method in a 3-class pilot on cardiac arrhythmias improved examination scores for 2 of the 3 classes (pharmacology and therapeutics). Student satisfaction was influenced by the quality of the learning objectives, prerecorded lectures, and inclass active-learning activities. PMID:25657372

Ensemble Clustering Classification compete SVM and One-Class classifiers applied on plant microRNAs Data.

PubMed

Yousef, Malik; Khalifa, Waleed; AbedAllah, Loai

2016-12-22

The performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algorithms. We have demonstrated that the k-nearest neighbor (kNN) classification can be significantly improved by learning a distance metric from labeled examples. The clustering ensemble is used to define the distance between points in respect to how they co-cluster. This distance is then used within the framework of the kNN algorithm to define a classifier named ensemble clustering kNN classifier (EC-kNN). In many instances in our experiments we achieved highest accuracy while SVM failed to perform as well. In this study, we compare the performance of a two-class classifier using EC-kNN with different one-class and two-class classifiers. The comparison was applied to seven different plant microRNA species considering eight feature selection methods. In this study, the averaged results show that ECkNN outperforms all other methods employed here and previously published results for the same data. In conclusion, this study shows that the chosen classifier shows high performance when the distance metric is carefully chosen.

Ensemble Clustering Classification Applied to Competing SVM and One-Class Classifiers Exemplified by Plant MicroRNAs Data.

PubMed

Yousef, Malik; Khalifa, Waleed; AbdAllah, Loai

2016-12-01

The performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algorithms. We have demonstrated that the k-nearest neighbor (kNN) classification can be significantly improved by learning a distance metric from labeled examples. The clustering ensemble is used to define the distance between points in respect to how they co-cluster. This distance is then used within the framework of the kNN algorithm to define a classifier named ensemble clustering kNN classifier (EC-kNN). In many instances in our experiments we achieved highest accuracy while SVM failed to perform as well. In this study, we compare the performance of a two-class classifier using EC-kNN with different one-class and two-class classifiers. The comparison was applied to seven different plant microRNA species considering eight feature selection methods. In this study, the averaged results show that EC-kNN outperforms all other methods employed here and previously published results for the same data. In conclusion, this study shows that the chosen classifier shows high performance when the distance metric is carefully chosen.

Panic disorder and its subtypes: a comprehensive analysis of panic symptom heterogeneity using epidemiological and treatment seeking samples

PubMed Central

Roberson-Nay, R.; Kendler, K. S.

2014-01-01

Background Panic disorder (PD) is a heterogeneous syndrome that can present with a variety of symptom profiles that potentially reflect distinct etiologic pathways. The present study represents the most comprehensive examination of phenotypic variance in PD with and without agoraphobia for the purpose of identifying clinically relevant and etiologically meaningful subtypes. Method Latent class (LC) and factor mixture analysis were used to examine panic symptom data ascertained from three national epidemiologic surveys [Epidemiological Catchment Area (ECA), National Comorbidity Study (NCS), National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), Wave 1], a twin study [Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD)] and a clinical trial (Cross-National Collaborative Panic Study [CNCPS]). Results Factor mixture models (versus LC) generally provided better fit to panic symptom data and suggested two panic classes for the ECA, VATSPSUD and CNCPS, with one class typified by prominent respiratory symptoms. The NCS yielded two classes, but suggested both qualitative and quantitative differences. The more contemporary NESARC sample supported a two and three class model, with the three class model suggesting two variants of respiratory panic. The NESARC’s three class model continued to provide the best fit when the model was restricted to a more severe form of PD/panic disorder with agoraphobia. Conclusions Results from epidemiologic and clinical samples suggest two panic subtypes, with one subtype characterized by a respiratory component and a second class typified by general somatic symptoms. Results are discussed in light of their relevance to the etiopathogenesis of PD. PMID:21557895

Correlation and agreement between eplet mismatches calculated using serological, low-intermediate and high resolution molecular human leukocyte antigen typing methods.

PubMed

Fidler, Samantha; D'Orsogna, Lloyd; Irish, Ashley B; Lewis, Joshua R; Wong, Germaine; Lim, Wai H

2018-03-02

Structural human leukocyte antigen (HLA) matching at the eplet level can be identified by HLAMatchmaker, which requires the entry of four-digit alleles. The aim of this study was to evaluate the agreement between eplet mismatches calculated by serological and two-digit typing methods compared to high-resolution four-digit typing. In a cohort of 264 donor/recipient pairs, the evaluation of measurement error was assessed using intra-class correlation to confirm the absolute agreement between the number of eplet mismatches at class I (HLA-A, -B, C) and II loci (HLA-DQ and -DR) calculated using serological or two-digit molecular typing compared to four-digit molecular typing methods. The proportion of donor/recipient pairs with a difference of >5 eplet mismatches between the HLA typing methods was also determined. Intra-class correlation coefficients between serological and four-digit molecular typing methods were 0.969 (95% confidence intervals [95% CI] 0.960-0.975) and 0.926 (95% CI 0.899-0.944), respectively; and 0.995 (95% CI 0.994-0.996) and 0.993 (95% CI 0.991-0.995), respectively between two-digit and four-digit molecular typing methods. The proportion of donor/recipient pairs with a difference of >5 eplet mismatches at class I and II loci was 4% and 16% for serological versus four-digit molecular typing methods, and 0% and 2% for two-digit versus four-digit molecular typing methods, respectively. In this small predominantly Caucasian population, compared with serology, there is a high level of agreement in the number of eplet mismatches calculated using two-compared to four-digit molecular HLA-typing methods, suggesting that two-digit typing may be sufficient in determining eplet mismatch load in kidney transplantation.

A method for the development of disease-specific reference standards vocabularies from textual biomedical literature resources

PubMed Central

Wang, Liqin; Bray, Bruce E.; Shi, Jianlin; Fiol, Guilherme Del; Haug, Peter J.

2017-01-01

Objective Disease-specific vocabularies are fundamental to many knowledge-based intelligent systems and applications like text annotation, cohort selection, disease diagnostic modeling, and therapy recommendation. Reference standards are critical in the development and validation of automated methods for disease-specific vocabularies. The goal of the present study is to design and test a generalizable method for the development of vocabulary reference standards from expert-curated, disease-specific biomedical literature resources. Methods We formed disease-specific corpora from literature resources like textbooks, evidence-based synthesized online sources, clinical practice guidelines, and journal articles. Medical experts annotated and adjudicated disease-specific terms in four classes (i.e., causes or risk factors, signs or symptoms, diagnostic tests or results, and treatment). Annotations were mapped to UMLS concepts. We assessed source variation, the contribution of each source to build disease-specific vocabularies, the saturation of the vocabularies with respect to the number of used sources, and the generalizability of the method with different diseases. Results The study resulted in 2588 string-unique annotations for heart failure in four classes, and 193 and 425 respectively for pulmonary embolism and rheumatoid arthritis in treatment class. Approximately 80% of the annotations were mapped to UMLS concepts. The agreement among heart failure sources ranged between 0.28 and 0.46. The contribution of these sources to the final vocabulary ranged between 18% and 49%. With the sources explored, the heart failure vocabulary reached near saturation in all four classes with the inclusion of minimal six sources (or between four to seven sources if only counting terms occurred in two or more sources). It took fewer sources to reach near saturation for the other two diseases in terms of the treatment class. Conclusions We developed a method for the development of disease-specific reference vocabularies. Expert-curated biomedical literature resources are substantial for acquiring disease-specific medical knowledge. It is feasible to reach near saturation in a disease-specific vocabulary using a relatively small number of literature sources. PMID:26971304

Evaluation of the Applicability of Different Age Determination Methods for Estimating Age of the Endangered African Wild Dog (Lycaon Pictus).

PubMed

Mbizah, Moreangels M; Steenkamp, Gerhard; Groom, Rosemary J

2016-01-01

African wild dogs (Lycaon pictus) are endangered and their population continues to decline throughout their range. Given their conservation status, more research focused on their population dynamics, population growth and age specific mortality is needed and this requires reliable estimates of age and age of mortality. Various age determination methods from teeth and skull measurements have been applied in numerous studies and it is fundamental to test the validity of these methods and their applicability to different species. In this study we assessed the accuracy of estimating chronological age and age class of African wild dogs, from dental age measured by (i) counting cementum annuli (ii) pulp cavity/tooth width ratio, (iii) tooth wear (measured by tooth crown height) (iv) tooth wear (measured by tooth crown width/crown height ratio) (v) tooth weight and (vi) skull measurements (length, width and height). A sample of 29 African wild dog skulls, from opportunistically located carcasses was analysed. Linear and ordinal regression analysis was done to investigate the performance of each of the six age determination methods in predicting wild dog chronological age and age class. Counting cementum annuli was the most accurate method for estimating chronological age of wild dogs with a 79% predictive capacity, while pulp cavity/tooth width ratio was also a reliable method with a 68% predictive capacity. Counting cementum annuli and pulp cavity/tooth width ratio were again the most accurate methods for separating wild dogs into three age classes (6-24 months; 25-60 months and > 60 months), with a McFadden's Pseudo-R2 of 0.705 and 0.412 respectively. The use of the cementum annuli method is recommended when estimating age of wild dogs since it is the most reliable method. However, its use is limited as it requires tooth extraction and shipping, is time consuming and expensive, and is not applicable to living individuals. Pulp cavity/tooth width ratio is a moderately reliable method for estimating both chronological age and age class. This method gives a balance between accuracy, cost and practicability, therefore it is recommended when precise age estimations are not paramount.

Evaluation of the Applicability of Different Age Determination Methods for Estimating Age of the Endangered African Wild Dog (Lycaon Pictus)

PubMed Central

Steenkamp, Gerhard; Groom, Rosemary J.

2016-01-01

African wild dogs (Lycaon pictus) are endangered and their population continues to decline throughout their range. Given their conservation status, more research focused on their population dynamics, population growth and age specific mortality is needed and this requires reliable estimates of age and age of mortality. Various age determination methods from teeth and skull measurements have been applied in numerous studies and it is fundamental to test the validity of these methods and their applicability to different species. In this study we assessed the accuracy of estimating chronological age and age class of African wild dogs, from dental age measured by (i) counting cementum annuli (ii) pulp cavity/tooth width ratio, (iii) tooth wear (measured by tooth crown height) (iv) tooth wear (measured by tooth crown width/crown height ratio) (v) tooth weight and (vi) skull measurements (length, width and height). A sample of 29 African wild dog skulls, from opportunistically located carcasses was analysed. Linear and ordinal regression analysis was done to investigate the performance of each of the six age determination methods in predicting wild dog chronological age and age class. Counting cementum annuli was the most accurate method for estimating chronological age of wild dogs with a 79% predictive capacity, while pulp cavity/tooth width ratio was also a reliable method with a 68% predictive capacity. Counting cementum annuli and pulp cavity/tooth width ratio were again the most accurate methods for separating wild dogs into three age classes (6–24 months; 25–60 months and > 60 months), with a McFadden’s Pseudo-R2 of 0.705 and 0.412 respectively. The use of the cementum annuli method is recommended when estimating age of wild dogs since it is the most reliable method. However, its use is limited as it requires tooth extraction and shipping, is time consuming and expensive, and is not applicable to living individuals. Pulp cavity/tooth width ratio is a moderately reliable method for estimating both chronological age and age class. This method gives a balance between accuracy, cost and practicability, therefore it is recommended when precise age estimations are not paramount. PMID:27732663

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.

A dictionary learning approach for human sperm heads classification.

PubMed

Shaker, Fariba; Monadjemi, S Amirhassan; Alirezaie, Javad; Naghsh-Nilchi, Ahmad Reza

2017-12-01

To diagnose infertility in men, semen analysis is conducted in which sperm morphology is one of the factors that are evaluated. Since manual assessment of sperm morphology is time-consuming and subjective, automatic classification methods are being developed. Automatic classification of sperm heads is a complicated task due to the intra-class differences and inter-class similarities of class objects. In this research, a Dictionary Learning (DL) technique is utilized to construct a dictionary of sperm head shapes. This dictionary is used to classify the sperm heads into four different classes. Square patches are extracted from the sperm head images. Columnized patches from each class of sperm are used to learn class-specific dictionaries. The patches from a test image are reconstructed using each class-specific dictionary and the overall reconstruction error for each class is used to select the best matching class. Average accuracy, precision, recall, and F-score are used to evaluate the classification method. The method is evaluated using two publicly available datasets of human sperm head shapes. The proposed DL based method achieved an average accuracy of 92.2% on the HuSHeM dataset, and an average recall of 62% on the SCIAN-MorphoSpermGS dataset. The results show a significant improvement compared to a previously published shape-feature-based method. We have achieved high-performance results. In addition, our proposed approach offers a more balanced classifier in which all four classes are recognized with high precision and recall. In this paper, we use a Dictionary Learning approach in classifying human sperm heads. It is shown that the Dictionary Learning method is far more effective in classifying human sperm heads than classifiers using shape-based features. Also, a dataset of human sperm head shapes is introduced to facilitate future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

[Application of single-retainer all-ceramic resin-bonded fixed partial denture in replacing single anterior tooth].

PubMed

Lili, Yang; Debiao, Du; Ruoyu, Ning; Deying, Chen; Junling, Wu

2017-08-01

Objective In this study, we aimed to evaluate the clinical effect of single-retainer all-ceramic resin-bonded fixed partial denture (RBFPD) on the single anterior tooth loss patients. Methods A total of 20 single-retainer all-ceramic RBFPD
were fabricated and evaluated in a two-year follow-up observation. The restorations were examined on the basis of the American Public Health Association (APHA) criteria. Results A total of 20 single-retainer all-ceramic RBFPD achieved class A evaluation after a six-month follow-up observation. One single-retainer all-ceramic RBFPD was classified as class B for secondary caries after a one-year follow-up observation. After a two-year follow-up observation, one single-retainer all-ceramic RBFPD was classified as class B because of secondary caries, and one single-retainer all-ceramic RBFPD was classified as class B because of fracture. Conclusion Single-retainer all-ceramic RBFPD is a promising and optional method in replacing single anterior tooth.

Making friends at antenatal classes: a qualitative exploration of friendship across the transition to motherhood.

PubMed

Nolan, Mary L; Mason, Victoria; Snow, Sarah; Messenger, Wendy; Catling, Jonathon; Upton, Penney

2012-01-01

This study explored how friendships made at antenatal classes preserve new mothers' well-being, postnatally. Eight women from the United Kingdom who had attended antenatal classes in the third trimester were interviewed following the birth of their first baby. Transcripts were analyzed using a constant comparative method. Findings suggest that friendships made at antenatal classes are not only unique but also support women's mental health and enhance self-efficacy because the women give and gain reassurance that their babies are developing normally. Such friendships may reduce demands on overstretched social and health-care services. Childbirth educators, midwives, and nurses can be encouraged to capitalize on the opportunity provided by antenatal classes to facilitate the formation of friendships that can help mothers to find "a new equilibrium."

[Research on the methods for multi-class kernel CSP-based feature extraction].

PubMed

Wang, Jinjia; Zhang, Lingzhi; Hu, Bei

2012-04-01

To relax the presumption of strictly linear patterns in the common spatial patterns (CSP), we studied the kernel CSP (KCSP). A new multi-class KCSP (MKCSP) approach was proposed in this paper, which combines the kernel approach with multi-class CSP technique. In this approach, we used kernel spatial patterns for each class against all others, and extracted signal components specific to one condition from EEG data sets of multiple conditions. Then we performed classification using the Logistic linear classifier. Brain computer interface (BCI) competition III_3a was used in the experiment. Through the experiment, it can be proved that this approach could decompose the raw EEG singles into spatial patterns extracted from multi-class of single trial EEG, and could obtain good classification results.

Growth Mixture Modeling of Academic Achievement in Children of Varying Birth Weight Risk

PubMed Central

Espy, Kimberly Andrews; Fang, Hua; Charak, David; Minich, Nori; Taylor, H. Gerry

2009-01-01

The extremes of birth weight and preterm birth are known to result in a host of adverse outcomes, yet studies to date largely have used cross-sectional designs and variable-centered methods to understand long-term sequelae. Growth mixture modeling (GMM) that utilizes an integrated person- and variable-centered approach was applied to identify latent classes of achievement from a cohort of school-age children born at varying birth weights. GMM analyses revealed two latent achievement classes for calculation, problem-solving, and decoding abilities. The classes differed substantively and persistently in proficiency and in growth trajectories. Birth weight was a robust predictor of class membership for the two mathematics achievement outcomes and a marginal predictor of class membership for decoding. Neither visuospatial-motor skills nor environmental risk at study entry added to class prediction for any of the achievement skills. Among children born preterm, neonatal medical variables predicted class membership uniquely beyond birth weight. More generally, GMM is useful in revealing coherence in the developmental patterns of academic achievement in children of varying weight at birth, and is well suited to investigations of sources of heterogeneity. PMID:19586210

Simple webs of natural environment theme as a result of sharing in science teacher training

NASA Astrophysics Data System (ADS)

Tapilouw, M. C.; Firman, H.; Redjeki, S.; Chandra, D. T.

2018-03-01

Thematic learning is one type of integrated science (Biology, Physics, Chemistry and Earth Science) in Science Education. This study is concerning about simple webs of natural environment theme in science learning, as one of training material in science teacher training program. Making simple web is a goal of first step in teacher training program. Every group explain their web illustration to other group. Twenty Junior High School science teacher above one education foundation participate in science teacher training program. In order to gather simple webs, sharing method was used in this first step of science teacher training. The result of this study is five different simple web of natural environment themes. These webs represent science learning in class VII/Semester I, class VII/Semester II, Class VIII, Class IX/Semester I, Class IX/Semester II based on basic competency in National Curriculum 2013. Each group discussed web of natural environment theme based on their learning experience in real class which basic competency and subject matters are linked with natural environment theme. As a conclusion, simple webs are potential to develop in the next step of science teacher training program and to be implemented in real class.

Keystone Method: A Learning Paradigm in Mathematics

ERIC Educational Resources Information Center

Siadat, M. Vali; Musial, Paul M.; Sagher, Yoram

2008-01-01

This study reports the effects of an integrated instructional program (the Keystone Method) on the students' performance in mathematics and reading, and tracks students' persistence and retention. The subject of the study was a large group of students in remedial mathematics classes at the college, willing to learn but lacking basic educational…

A Comparison of Online and Traditional Instructional Delivery Methods on Learning in College Macroeconomics Courses

ERIC Educational Resources Information Center

Rivas, Rodolfo R.

2009-01-01

This exploratory study centered its investigation in the participants' responses provided in 2 different instructional teaching delivery methods (traditional and online) that utilized active-like teaching learning techniques (case studies, group projects, threaded discussions, class discussions, office hours, lectures, computerized assignments,…

Attribute-Based Methods

Treesearch

Thomas P. Holmes; Wiktor L. Adamowicz

2003-01-01

Stated preference methods of environmental valuation have been used by economists for decades where behavioral data have limitations. The contingent valuation method (Chapter 5) is the oldest stated preference approach, and hundreds of contingent valuation studies have been conducted. More recently, and especially over the last decade, a class of stated preference...

Neighborhood Density and Syntactic Class Effects on Spoken Word Recognition: Specific Language Impairment and Typical Development

ERIC Educational Resources Information Center

Hoover, Jill R.

2018-01-01

Purpose: The purpose of the current study was to determine the effect of neighborhood density and syntactic class on word recognition in children with specific language impairment (SLI) and typical development (TD). Method: Fifteen children with SLI ("M" age = 6;5 [years;months]) and 15 with TD ("M" age = 6;4) completed a…

Learning from the Starry Message: Using Galileo's "Sidereus Nuncius" in Introductory Astronomy Classes

ERIC Educational Resources Information Center

Wiesner, Matthew P.

2015-01-01

Every introductory astronomy class encounters Galileo during the course as the first man to systematically study the sky with a telescope. Every Astronomy 101 student meets Galileo as one of the major catalysts behind the shift from the Ptolemaic to the Copernican system and as one of the great minds behind the scientific method. But most of the…

The Neglected Majority: Mass Communications and the Working Person.

ERIC Educational Resources Information Center

Mendelsohn, Harold

Studies have shown that members of the working class are often overworked, underpaid, overtaxed, and unhappy. They tend to be distrustful of new ideas and methods and to rely on their extended families to meet their needs for human contact. One way in which the working class person may have a chance to widen the character of his interactions with…

Relationship between Bilingual Instruction and Learners' Performance in English as Second Language Context

ERIC Educational Resources Information Center

Khan, Huma Imran

2015-01-01

The prime purpose of this study was to explore a correlation between bilingual instruction in an ESL class and the class performance of the ESL learners at the secondary level. Quantitative research method was used to evaluate the test performance of 60 ESL learners divided into two groups: One was the controlled group (which was given…

Assessment of 6th Grade Elementary School Students, Their Parents' and Branch Teachers' Perspective on Physical Education Classes

ERIC Educational Resources Information Center

Boyraz, Sirin; Ozbar, Nurper; Yetgin, Meral Kucuk; Koksalan, Burke

2015-01-01

A total of 437 volunteers including 54 teachers, 218 6th grade students and 102 parents from Beykoz Elementary Schools participated in this study to understand the perspectives of students, families and teachers on Physical Education classes. The perspectives of students, families and teachers of other branches are identified by survey method.…

Examining the Difference in Student Achievement between Face-to-Face and Online Computer Classes

ERIC Educational Resources Information Center

Hearn, Phillips Turner

2017-01-01

The purpose of this study was to compare the achievement of students taking a computer applications class in one of two instructional methods, traditional face-to-face and online, at a Southeastern community college. The research questions examined more than 3,000 samples from the summer of 2012 through the spring semester of 2016. There were…

A Study of a Multiple Component Feedback Approach to Substantive Revision for Secondary ELL and Multilingual Writers

ERIC Educational Resources Information Center

Early, Jessica Singer; Saidy, Christina

2014-01-01

This mixed method investigation included a quasi-experiment examining if revision instruction enhanced the substantive revising behavior of 15 English language learner (ELL) and multilingual 10th grade students enrolled in an English class for underperforming students in comparison to 14 non-ELL and multilingual students from the same class who…

Social Class Status and Suicide Characteristics: A Survey among Patients Who Attempted Suicide in Isfahan

PubMed Central

Keyvanara, Mahmoud; Mousavi, Seyed Ghafour; Karami, Zahra

2013-01-01

Introduction: Suicide is one of the most prominent problems in health care system in current Iran. It could be impacted by various factors such as social, economic, individual and so on. Researchers show that socio-economic factors and suicide has significantly related. The people in low social class may more engage with social problems than higher social class. They may confront to problems such as crime, violence, unemployment, financial hardship, population density, disorder personality, etc. However, these difficulties could be resulted from relationship of inequality socio-economic and mental or physical health. This research attempted to examine social class status and its relationship with parts of suicide characteristics. Methods: This study applied a descriptive approach. In the cross-sectional research 179 patients who attempted suicide and admitted to the toxicology ward of Nour hospital and to the burning ward of Imam Mousa Kazem hospital, in Isfahan, during a period of 6 months in 2010 were recruited. The randomize sampling for patients admitted to toxicology ward and census for burning ward are applied. Data collected through a questionnaire which Chronbagh coefficient’s alpha was calculated (r= 0/72). Data was analyzed in SPSS software. Findings: The data showed that the majority of patients who attempted suicide were young married women who had diploma and under diploma of level education. They were housewife, engaged in education and unemployment. Finding showed that there are no significant relationships between sex, age, marital status, frequency of attempted suicide and their social class. But there is significant relationship between methods of suicide and social class. Similarly, there are significant relationship between social factors (i.e. family friction, betrothal, unemployment, financial problems and so on) effected on suicide and their social classes. Parts of findings were supported by previous studies. PMID:23687462

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.

Naming, the formation of stimulus classes, and applied behavior analysis.

PubMed Central

Stromer, R; Mackay, H A; Remington, B

1996-01-01

The methods used in Sidman's original studies on equivalence classes provide a framework for analyzing functional verbal behavior. Sidman and others have shown how teaching receptive, name-referent matching may produce rudimentary oral reading and word comprehension skills. Eikeseth and Smith (1992) have extended these findings by showing that children with autism may acquire equivalence classes after learning to supply a common oral name to each stimulus in a potential class. A stimulus class analysis suggests ways to examine (a) the problem of programming generalization from teaching situations to other environments, (b) the expansion of the repertoires that occur in those settings, and (c) the use of naming to facilitate these forms of generalization. Such research will help to clarify and extend Horne and Lowe's recent (1996) account of the role of verbal behavior in the formation of stimulus classes. PMID:8810064

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.

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…

Is Flipping Worth the Fuss: A Mixed Methods Case Study of Screencasting in the Social Studies Classroom Authors

ERIC Educational Resources Information Center

Snyder, Catherine; Besozzi, David; Paska, Lawrence; Oppenlander, Jane

2016-01-01

This action research case study evaluates the effectiveness of using "flipped" instruction in a secondary social studies classroom. The researchers used mixed methods data to determine if flipping the instruction in a social studies class through the use of screencasting increased student learning as measured by pre- and post-unit…

Obsessive–compulsive disorder: subclassification based on co-morbidity

PubMed Central

Nestadt, G.; Di, C. Z.; Riddle, M. A.; Grados, M. A.; Greenberg, B. D.; Fyer, A. J.; McCracken, J. T.; Rauch, S. L.; Murphy, D. L.; Rasmussen, S. A.; Cullen, B.; Pinto, A.; Knowles, J. A.; Piacentini, J.; Pauls, D. L.; Bienvenu, O. J.; Wang, Y.; Liang, K. Y.; Samuels, J. F.; Roche, K. Bandeen

2011-01-01

Background Obsessive–compulsive disorder (OCD) is probably an etiologically heterogeneous condition. Many patients manifest other psychiatric syndromes. This study investigated the relationship between OCD and co-morbid conditions to identify subtypes. Method Seven hundred and six individuals with OCD were assessed in the OCD Collaborative Genetics Study (OCGS). Multi-level latent class analysis was conducted based on the presence of eight co-morbid psychiatric conditions [generalized anxiety disorder (GAD), major depression, panic disorder (PD), separation anxiety disorder (SAD), tics, mania, somatization disorders (Som) and grooming disorders (GrD)]. The relationship of the derived classes to specific clinical characteristics was investigated. Results Two and three classes of OCD syndromes emerge from the analyses. The two-class solution describes lesser and greater co-morbidity classes and the more descriptive three-class solution is characterized by: (1) an OCD simplex class, in which major depressive disorder (MDD) is the most frequent additional disorder; (2) an OCD co-morbid tic-related class, in which tics are prominent and affective syndromes are considerably rarer; and (3) an OCD co-morbid affective-related class in which PD and affective syndromes are highly represented. The OCD co-morbid tic-related class is predominantly male and characterized by high conscientiousness. The OCD co-morbid affective-related class is predominantly female, has a young age at onset, obsessive–compulsive personality disorder (OCPD) features, high scores on the ‘taboo’ factor of OCD symptoms, and low conscientiousness. Conclusions OCD can be classified into three classes based on co-morbidity. Membership within a class is differentially associated with other clinical characteristics. These classes, if replicated, should have important implications for research and clinical endeavors. PMID:19046474

Optimal observables for multiparameter seismic tomography

NASA Astrophysics Data System (ADS)

Bernauer, Moritz; Fichtner, Andreas; Igel, Heiner

2014-08-01

We propose a method for the design of seismic observables with maximum sensitivity to a target model parameter class, and minimum sensitivity to all remaining parameter classes. The resulting optimal observables thereby minimize interparameter trade-offs in multiparameter inverse problems. Our method is based on the linear combination of fundamental observables that can be any scalar measurement extracted from seismic waveforms. Optimal weights of the fundamental observables are determined with an efficient global search algorithm. While most optimal design methods assume variable source and/or receiver positions, our method has the flexibility to operate with a fixed source-receiver geometry, making it particularly attractive in studies where the mobility of sources and receivers is limited. In a series of examples we illustrate the construction of optimal observables, and assess the potentials and limitations of the method. The combination of Rayleigh-wave traveltimes in four frequency bands yields an observable with strongly enhanced sensitivity to 3-D density structure. Simultaneously, sensitivity to S velocity is reduced, and sensitivity to P velocity is eliminated. The original three-parameter problem thereby collapses into a simpler two-parameter problem with one dominant parameter. By defining parameter classes to equal earth model properties within specific regions, our approach mimics the Backus-Gilbert method where data are combined to focus sensitivity in a target region. This concept is illustrated using rotational ground motion measurements as fundamental observables. Forcing dominant sensitivity in the near-receiver region produces an observable that is insensitive to the Earth structure at more than a few wavelengths' distance from the receiver. This observable may be used for local tomography with teleseismic data. While our test examples use a small number of well-understood fundamental observables, few parameter classes and a radially symmetric earth model, the method itself does not impose such restrictions. It can easily be applied to large numbers of fundamental observables and parameters classes, as well as to 3-D heterogeneous earth models.

The effects of forehead and neck position on esthetics of class I, II and III profiles.

PubMed

Salehi, Parisa; Oshagh, Morteza; Aleyasin, Zeinab S; Pakshir, Hamid Reza

2014-01-01

All parts of the face, other than jaw relationships, should be considered in orthodontic treatment planning. The role of forehead and neck in facial esthetics is well known; however, the majority of conventional facial analysis methods have not considered them. Neck and forehead may confer mutual effects on equilibrium and on esthetics of other facial components, and may change the overall convexity/concavity view of the profile. Therefore, the aim of this study was to assess the effect of anteroposterior position of the forehead and neck on the esthetics of skeletal class I, II and III jaw relationships using profile silhouettes. Class II and III jaw relationships were constructed on the silhouette of a class I normal profile by altering the mandibular position. Retruded, normal and protruded positions were also applied for the forehead and neck. Three hundred Iranian laypeople (150 men, 150 women) scored the esthetics of profile silhouettes from 1 to 7. Half of the participants were told to consider the profiles as a man, and the other half were told to consider them as a woman. Data were analyzed using non-parametric methods. Class I jaw relation was found to be the most beautiful profile followed by class II and III respectively. Esthetics of different positions of the neck and forehead were significantly different (P < 0.05). In subjects with a normal neck and forehead position, and those with a retruded neck, the best esthetic relationship was class I, and the worst was class III. For protruded foreheads, the best jaw relationship was class II for females and class I for males, and the worst was class III for both. In a retruded forehead position, the most preferred jaw relationship was class I, and the worst was class II. For profiles with a protruded neck, the best esthetics was found to be in class III jaw relationship, and the worst was in class II. There was a small difference in scoring for male and female profiles (P < 0.05); there were also small differences in scoring trends of men and women (P < 0.05). This study showed that the anteroposterior position of the forehead and neck affects the esthetics of jaw relationships in profile view. In laypeople's opinions, in a normal profile, the overall appearance is more important compared to the independent position of the neck and forehead; however, having jaw abnormalities, the neck plays an important independent role. The preferred jaw relation for profiles with each forehead or neck position was introduced.

The Effect of Inquiry-Based Learning Method on Students' Academic Achievement in Science Course

ERIC Educational Resources Information Center

Abdi, Ali

2014-01-01

The purpose of this study was to investigate the effects of inquiry-based learning method on students' academic achievement in sciences lesson. A total of 40 fifth grade students from two different classes were involved in the study. They were selected through purposive sampling method. The group which was assigned as experimental group was…

Connecting University and Student Teaching Experiences through the Jackdaw Kit Project

ERIC Educational Resources Information Center

Marshall, Jill

2010-01-01

The author shares the challenges faced in her social studies methods class due to the constraints of NCLB. By incorporating the jackdaw kit project within her social studies methods course, her candidates were able to connect what they were talking about in methods and apply it to their students teaching situations where there was little time for…

Similarity-balanced discriminant neighbor embedding and its application to cancer classification based on gene expression data.

PubMed

Zhang, Li; Qian, Liqiang; Ding, Chuntao; Zhou, Weida; Li, Fanzhang

2015-09-01

The family of discriminant neighborhood embedding (DNE) methods is typical graph-based methods for dimension reduction, and has been successfully applied to face recognition. This paper proposes a new variant of DNE, called similarity-balanced discriminant neighborhood embedding (SBDNE) and applies it to cancer classification using gene expression data. By introducing a novel similarity function, SBDNE deals with two data points in the same class and the different classes with different ways. The homogeneous and heterogeneous neighbors are selected according to the new similarity function instead of the Euclidean distance. SBDNE constructs two adjacent graphs, or between-class adjacent graph and within-class adjacent graph, using the new similarity function. According to these two adjacent graphs, we can generate the local between-class scatter and the local within-class scatter, respectively. Thus, SBDNE can maximize the between-class scatter and simultaneously minimize the within-class scatter to find the optimal projection matrix. Experimental results on six microarray datasets show that SBDNE is a promising method for cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of Students' Perceptions Towards An Innovative Teaching-Learning Method During Pharmacology Revision Classes: Autobiography of Drugs.

PubMed

Joshi, Anuradha; Ganjiwale, Jaishree

2015-07-01

Various studies in medical education have shown that active learning strategies should be incorporated into the teaching-learning process to make learning more effective, efficient and meaningful. The aim of this study was to evaluate student's perceptions on an innovative revision method conducted in Pharmacology i.e. in form of Autobiography of Drugs. The main objective of study was to help students revise the core topics in Pharmacology in an interesting way. Questionnaire based survey on a newer method of pharmacology revision in two batches of second year MBBS students of a tertiary care teaching medical college. Various sessions on Autobiography of Drugs were conducted amongst two batches of second year MBBS students, during their Pharmacology revision classes. Student's perceptions were documented with the help of a five point likert scale through a questionnaire regarding quality, content and usefulness of this method. Descriptive analysis. Students of both the batches appreciated the innovative method taken up for revision. The median scores in most of the domains in both batches were four out of five, indicative of good response. Feedback from open-ended questions also revealed that the innovative module on "Autobiography of Drugs" was taken as a positive learning experience by students. Autobiography of drugs has been used to help students recall topics that they have learnt through other teachings methods. Autobiography sessions in Pharmacology during revision slots, can be one of the interesting ways in helping students revise and recall topics which have already been taught in theory classes.

A Revised Class Play Method of Peer Assessment.

ERIC Educational Resources Information Center

Masten, Ann S.; And Others

1985-01-01

Revised Class Play (RCP) was presented as a measure of peer reputation designed to improve the assessment of social competence as well as the psychometric properties of class play method. Administered to third through sixth graders three test dimensions were revealed: sociability-leadership, aggressive-disruptive, and sensitive-isolated. Data…

Expressive writing promotes self-reported physical, social and psychological health among Chinese undergraduates.

PubMed

Yang, Zhihan; Tang, Xiaoqing; Duan, Wenjie; Zhang, Yonghong

2015-03-01

The present study examines the efficacy of expressive writing among Chinese undergraduates. The sample comprised of 74 undergraduates enrolled in a 9-week intervention (35 in experimental class vs. 39 in control class). The writing exercises were well-embedded in an elective course for the two classes. The 46-item simplified Chinese Self-Rated Health Measurement Scale, which assesses psychological, physical and social health, was adopted to measure the outcome of this study. Baseline (second week) and post-test (ninth week) scores were obtained during the classes. After the intervention on the eighth week, the self-reported psychological, social and physical health of the experimental class improved. Psychological health obtained the maximum degree of improvement, followed by social and physical health. Furthermore, female participants gained more psychological improvement than males. These results demonstrated that the expressive writing approach could improve the physical, social and psychological health of Chinese undergraduates, and the method can be applied in university psychological consulting settings in Mainland China. © 2014 International Union of Psychological Science.

A class Hierarchical, object-oriented approach to virtual memory management

NASA Technical Reports Server (NTRS)

Russo, Vincent F.; Campbell, Roy H.; Johnston, Gary M.

1989-01-01

The Choices family of operating systems exploits class hierarchies and object-oriented programming to facilitate the construction of customized operating systems for shared memory and networked multiprocessors. The software is being used in the Tapestry laboratory to study the performance of algorithms, mechanisms, and policies for parallel systems. Described here are the architectural design and class hierarchy of the Choices virtual memory management system. The software and hardware mechanisms and policies of a virtual memory system implement a memory hierarchy that exploits the trade-off between response times and storage capacities. In Choices, the notion of a memory hierarchy is captured by abstract classes. Concrete subclasses of those abstractions implement a virtual address space, segmentation, paging, physical memory management, secondary storage, and remote (that is, networked) storage. Captured in the notion of a memory hierarchy are classes that represent memory objects. These classes provide a storage mechanism that contains encapsulated data and have methods to read or write the memory object. Each of these classes provides specializations to represent the memory hierarchy.

Using case studies to teach an engineering technology technical writing class

NASA Technical Reports Server (NTRS)

Green, M. M.

1981-01-01

The use of the case method in teaching various technical communication skills is described. Features of the method considered include: solving communication problems, identifying an audience, planning written communications, presenting written communications, and using visual aids.

Sample handling for mass spectrometric proteomic investigations of human sera.

PubMed

West-Nielsen, Mikkel; Høgdall, Estrid V; Marchiori, Elena; Høgdall, Claus K; Schou, Christian; Heegaard, Niels H H

2005-08-15

Proteomic investigations of sera are potentially of value for diagnosis, prognosis, choice of therapy, and disease activity assessment by virtue of discovering new biomarkers and biomarker patterns. Much debate focuses on the biological relevance and the need for identification of such biomarkers while less effort has been invested in devising standard procedures for sample preparation and storage in relation to model building based on complex sets of mass spectrometric (MS) data. Thus, development of standardized methods for collection and storage of patient samples together with standards for transportation and handling of samples are needed. This requires knowledge about how sample processing affects MS-based proteome analyses and thereby how nonbiological biased classification errors are avoided. In this study, we characterize the effects of sample handling, including clotting conditions, storage temperature, storage time, and freeze/thaw cycles, on MS-based proteomics of human serum by using principal components analysis, support vector machine learning, and clustering methods based on genetic algorithms as class modeling and prediction methods. Using spiking to artificially create differentiable sample groups, this integrated approach yields data that--even when working with sample groups that differ more than may be expected in biological studies--clearly demonstrate the need for comparable sampling conditions for samples used for modeling and for the samples that are going into the test set group. Also, the study emphasizes the difference between class prediction and class comparison studies as well as the advantages and disadvantages of different modeling methods.

Impact of Maple(TM) on the design, instruction and performance in an undergraduate physics mathematical methods course

NASA Astrophysics Data System (ADS)

Runge, Alan Paul

1997-10-01

A traditional undergraduate physics course on mathematical methods has been redesigned to incorporate the use of Maplesp{sc {TM}}, a computer algebra program, during all aspects of the course. Topics covered were: complex number theory; series approximations; matrix theory; partial differentiation; vector algebra; and vector calculus. Five undergraduate students were enrolled, from sophomore to senior in academic class standing. A qualitative case study methodology was used to describe the changes in the course design resulting from the incorporation of Maplesp{sc {TM}} and their impact on the instruction of the course, and to determine the effects on the students' learning and development of problem solving skills in physics using Maplesp{sc {TM}} as a problem solving tool. The impact of using Maplesp{sc {TM}} on the number and types of interactions is presented. The entire semester long course was included in this study. Each class session is described in detail. Examples of the Maplesp{sc {TM}} materials used are given. The use of the Maplesp{sc {TM}} program was allowed on all homework and exams with each student having their own computer during class. Constraints were made so that the assessment emphasis remained on the mathematics and the conceptual understanding of the problem solving methods. All of the students demonstrated some level of proficiency in using Maplesp{TM} to solve the assigned problems. Strategies for effectively using Maplesp{TM} were presented and were individualized by the students. The students reported positive and negative impacts of using Maplesp{sc {TM}}. All of the students satisfactorily completed the course requirements, receiving final course grades from B to A+. All of them continued to voluntarily use Maplesp{sc {TM}} during the following semester. Instructional methods used included various lecture techniques without Maplesp{sc {TM}} assistance, lectures and demonstrations using only Maplesp{sc {TM}}, and student tasks assigned in class worked with the aid of Maplesp{sc {TM}}. Maplesp{sc {TM}} was used in one of these aspects in all but 3, out of 45, class periods. The use of Maplesp{sc {TM}} constituted about half of the overall class time.

Comparison of four approaches to a rock facies classification problem

USGS Publications Warehouse

Dubois, M.K.; Bohling, Geoffrey C.; Chakrabarti, S.

2007-01-01

In this study, seven classifiers based on four different approaches were tested in a rock facies classification problem: classical parametric methods using Bayes' rule, and non-parametric methods using fuzzy logic, k-nearest neighbor, and feed forward-back propagating artificial neural network. Determining the most effective classifier for geologic facies prediction in wells without cores in the Panoma gas field, in Southwest Kansas, was the objective. Study data include 3600 samples with known rock facies class (from core) with each sample having either four or five measured properties (wire-line log curves), and two derived geologic properties (geologic constraining variables). The sample set was divided into two subsets, one for training and one for testing the ability of the trained classifier to correctly assign classes. Artificial neural networks clearly outperformed all other classifiers and are effective tools for this particular classification problem. Classical parametric models were inadequate due to the nature of the predictor variables (high dimensional and not linearly correlated), and feature space of the classes (overlapping). The other non-parametric methods tested, k-nearest neighbor and fuzzy logic, would need considerable improvement to match the neural network effectiveness, but further work, possibly combining certain aspects of the three non-parametric methods, may be justified. ?? 2006 Elsevier Ltd. All rights reserved.

Phylogenomic Reconstruction of the Oomycete Phylogeny Derived from 37 Genomes

PubMed Central

McCarthy, Charley G. P.

2017-01-01

ABSTRACT The oomycetes are a class of microscopic, filamentous eukaryotes within the Stramenopiles-Alveolata-Rhizaria (SAR) supergroup which includes ecologically significant animal and plant pathogens, most infamously the causative agent of potato blight Phytophthora infestans. Single-gene and concatenated phylogenetic studies both of individual oomycete genera and of members of the larger class have resulted in conflicting conclusions concerning species phylogenies within the oomycetes, particularly for the large Phytophthora genus. Genome-scale phylogenetic studies have successfully resolved many eukaryotic relationships by using supertree methods, which combine large numbers of potentially disparate trees to determine evolutionary relationships that cannot be inferred from individual phylogenies alone. With a sufficient amount of genomic data now available, we have undertaken the first whole-genome phylogenetic analysis of the oomycetes using data from 37 oomycete species and 6 SAR species. In our analysis, we used established supertree methods to generate phylogenies from 8,355 homologous oomycete and SAR gene families and have complemented those analyses with both phylogenomic network and concatenated supermatrix analyses. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and individual clades within the problematic Phytophthora genus. Support for the resolution of the inferred relationships between individual Phytophthora clades varies depending on the methodology used. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes. IMPORTANCE The oomycetes are a class of eukaryotes and include ecologically significant animal and plant pathogens. Single-gene and multigene phylogenetic studies of individual oomycete genera and of members of the larger classes have resulted in conflicting conclusions concerning interspecies relationships among these species, particularly for the Phytophthora genus. The onset of next-generation sequencing techniques now means that a wealth of oomycete genomic data is available. For the first time, we have used genome-scale phylogenetic methods to resolve oomycete phylogenetic relationships. We used supertree methods to generate single-gene and multigene species phylogenies. Overall, our supertree analyses utilized phylogenetic data from 8,355 oomycete gene families. We have also complemented our analyses with superalignment phylogenies derived from 131 single-copy ubiquitous gene families. Our results show that a genome-scale approach to oomycete phylogeny resolves oomycete classes and clades. Our analysis represents an important first step in large-scale phylogenomic analysis of the oomycetes. PMID:28435885

Crying Behavior and the "Nonviolent" Leboyer Method of Delivery.

ERIC Educational Resources Information Center

Hamilton, Joan Safran

This paper reports on a 3-month longitudinal study comparing the crying behavior of a group of babies delivered by the "nonviolent" Leboyer method with a control group delivered by traditional methods. Subjects were 24 white, middle class infants delivered by minimally medicated, multiparous and primiparous mothers. Fourteen newborns…

Infusing Mathematics Content into a Methods Course: Impacting Content Knowledge for Teaching

ERIC Educational Resources Information Center

Burton, Megan; Daane, C. J.; Giesen, Judy

2008-01-01

This study compared content knowledge for teaching mathematics differences between elementary pre-service teachers in a traditional versus an experimental mathematics methods course. The experimental course replaced 20 minutes of traditional methods, each class, with an intervention of elementary mathematics content. The difference between groups…

Designing, Teaching, and Evaluating Two Complementary Mixed Methods Research Courses

ERIC Educational Resources Information Center

Christ, Thomas W.

2009-01-01

Teaching mixed methods research is difficult. This longitudinal explanatory study examined how two classes were designed, taught, and evaluated. Curriculum, Research, and Teaching (EDCS-606) and Mixed Methods Research (EDCS-780) used a research proposal generation process to highlight the importance of the purpose, research question and…

Patterns of Chronic Conditions and Their Associations With Behaviors and Quality of Life, 2010

PubMed Central

Mitchell, Sandra A.; Thompson, William W.; Zack, Matthew M.; Reeve, Bryce B.; Cella, David; Smith, Ashley Wilder

2015-01-01

Introduction Co-occurring chronic health conditions elevate the risk of poor health outcomes such as death and disability, are associated with poor quality of life, and magnify the complexities of self-management, care coordination, and treatment planning. This study assessed patterns of both singular and multiple chronic conditions, behavioral risk factors, and quality of life in a population-based sample. Methods In a national survey, adults (n = 4,184) answered questions about the presence of 27 chronic conditions. We used latent class analysis to identify patterns of chronic conditions and to explore associations of latent class membership with sociodemographic characteristics, behavioral risk factors, and health. Results Latent class analyses indicated 4 morbidity profiles: a healthy class (class 1), a class with predominantly physical health conditions (class 2), a class with predominantly mental health conditions (class 3), and a class with both physical and mental health conditions (class 4). Class 4 respondents reported significantly worse physical health and well-being and more days of activity limitation than those in the other latent classes. Class 4 respondents were also more likely to be obese and sedentary, and those with predominantly mental health conditions were most likely to be current smokers. Conclusions Subgroups with distinct patterns of chronic conditions can provide direction for screening and surveillance, guideline development, and the delivery of complex care services. PMID:26679491

Quadratically Convergent Method for Simultaneously Approaching the Roots of Polynomial Solutions of a Class of Differential Equations

NASA Astrophysics Data System (ADS)

Recchioni, Maria Cristina

2001-12-01

This paper investigates the application of the method introduced by L. Pasquini (1989) for simultaneously approaching the zeros of polynomial solutions to a class of second-order linear homogeneous ordinary differential equations with polynomial coefficients to a particular case in which these polynomial solutions have zeros symmetrically arranged with respect to the origin. The method is based on a family of nonlinear equations which is associated with a given class of differential equations. The roots of the nonlinear equations are related to the roots of the polynomial solutions of differential equations considered. Newton's method is applied to find the roots of these nonlinear equations. In (Pasquini, 1994) the nonsingularity of the roots of these nonlinear equations is studied. In this paper, following the lines in (Pasquini, 1994), the nonsingularity of the roots of these nonlinear equations is studied. More favourable results than the ones in (Pasquini, 1994) are proven in the particular case of polynomial solutions with symmetrical zeros. The method is applied to approximate the roots of Hermite-Sobolev type polynomials and Freud polynomials. A lower bound for the smallest positive root of Hermite-Sobolev type polynomials is given via the nonlinear equation. The quadratic convergence of the method is proven. A comparison with a classical method that uses the Jacobi matrices is carried out. We show that the algorithm derived by the proposed method is sometimes preferable to the classical QR type algorithms for computing the eigenvalues of the Jacobi matrices even if these matrices are real and symmetric.

Students' Responses to Active Instructional Approaches in a Social Studies Methods Course.

ERIC Educational Resources Information Center

Byer, John L.

A study investigated the effects of actively involving students in a social studies methods class on instructor evaluations given by students. Subjects were 30 undergraduates who were all elementary education majors except for one special education major. Subjects (27 female and 3 male) ranged in age from 21 to 53 years old. The experimental…

Modern Methods for Modeling Change in Obesity Research in Nursing.

PubMed

Sereika, Susan M; Zheng, Yaguang; Hu, Lu; Burke, Lora E

2017-08-01

Persons receiving treatment for weight loss often demonstrate heterogeneity in lifestyle behaviors and health outcomes over time. Traditional repeated measures approaches focus on the estimation and testing of an average temporal pattern, ignoring the interindividual variability about the trajectory. An alternate person-centered approach, group-based trajectory modeling, can be used to identify distinct latent classes of individuals following similar trajectories of behavior or outcome change as a function of age or time and can be expanded to include time-invariant and time-dependent covariates and outcomes. Another latent class method, growth mixture modeling, builds on group-based trajectory modeling to investigate heterogeneity within the distinct trajectory classes. In this applied methodologic study, group-based trajectory modeling for analyzing changes in behaviors or outcomes is described and contrasted with growth mixture modeling. An illustration of group-based trajectory modeling is provided using calorie intake data from a single-group, single-center prospective study for weight loss in adults who are either overweight or obese.

State-space reduction and equivalence class sampling for a molecular self-assembly model.

PubMed

Packwood, Daniel M; Han, Patrick; Hitosugi, Taro

2016-07-01

Direct simulation of a model with a large state space will generate enormous volumes of data, much of which is not relevant to the questions under study. In this paper, we consider a molecular self-assembly model as a typical example of a large state-space model, and present a method for selectively retrieving 'target information' from this model. This method partitions the state space into equivalence classes, as identified by an appropriate equivalence relation. The set of equivalence classes H, which serves as a reduced state space, contains none of the superfluous information of the original model. After construction and characterization of a Markov chain with state space H, the target information is efficiently retrieved via Markov chain Monte Carlo sampling. This approach represents a new breed of simulation techniques which are highly optimized for studying molecular self-assembly and, moreover, serves as a valuable guideline for analysis of other large state-space models.

Evaluation of Students’ Perceptions Towards An Innovative Teaching-Learning Method During Pharmacology Revision Classes: Autobiography of Drugs

PubMed Central

Ganjiwale, Jaishree

2015-01-01

Introduction Various studies in medical education have shown that active learning strategies should be incorporated into the teaching–learning process to make learning more effective, efficient and meaningful. Objectives The aim of this study was to evaluate student’s perceptions on an innovative revision method conducted in Pharmacology i.e. in form of Autobiography of Drugs. The main objective of study was to help students revise the core topics in Pharmacology in an interesting way. Settings and Design Questionnaire based survey on a newer method of pharmacology revision in two batches of second year MBBS students of a tertiary care teaching medical college. Materials and Methods Various sessions on Autobiography of Drugs were conducted amongst two batches of second year MBBS students, during their Pharmacology revision classes. Student’s perceptions were documented with the help of a five point likert scale through a questionnaire regarding quality, content and usefulness of this method. Statistical analysis used Descriptive analysis. Results Students of both the batches appreciated the innovative method taken up for revision. The median scores in most of the domains in both batches were four out of five, indicative of good response. Feedback from open-ended questions also revealed that the innovative module on “Autobiography of Drugs” was taken as a positive learning experience by students. Conclusions Autobiography of drugs has been used to help students recall topics that they have learnt through other teachings methods. Autobiography sessions in Pharmacology during revision slots, can be one of the interesting ways in helping students revise and recall topics which have already been taught in theory classes. PMID:26393138

Content-Related Interactions and Methods of Reasoning within Self-Initiated Organic Chemistry Study Groups

ERIC Educational Resources Information Center

Christian, Karen Jeanne

2011-01-01

Students often use study groups to prepare for class or exams; yet to date, we know very little about how these groups actually function. This study looked at the ways in which undergraduate organic chemistry students prepared for exams through self-initiated study groups. We sought to characterize the methods of social regulation, levels of…

Site classification for National Strong Motion Observation Network System (NSMONS) stations in China using an empirical H/V spectral ratio method

NASA Astrophysics Data System (ADS)

Ji, Kun; Ren, Yefei; Wen, Ruizhi

2017-10-01

Reliable site classification of the stations of the China National Strong Motion Observation Network System (NSMONS) has not yet been assigned because of lacking borehole data. This study used an empirical horizontal-to-vertical (H/V) spectral ratio (hereafter, HVSR) site classification method to overcome this problem. First, according to their borehole data, stations selected from KiK-net in Japan were individually assigned a site class (CL-I, CL-II, or CL-III), which is defined in the Chinese seismic code. Then, the mean HVSR curve for each site class was computed using strong motion recordings captured during the period 1996-2012. These curves were compared with those proposed by Zhao et al. (2006a) for four types of site classes (SC-I, SC-II, SC-III, and SC-IV) defined in the Japanese seismic code (JRA, 1980). It was found that an approximate range of the predominant period Tg could be identified by the predominant peak of the HVSR curve for the CL-I and SC-I sites, CL-II and SC-II sites, and CL-III and SC-III + SC-IV sites. Second, an empirical site classification method was proposed based on comprehensive consideration of peak period, amplitude, and shape of the HVSR curve. The selected stations from KiK-net were classified using the proposed method. The results showed that the success rates of the proposed method in identifying CL-I, CL-II, and CL-III sites were 63%, 64%, and 58% respectively. Finally, the HVSRs of 178 NSMONS stations were computed based on recordings from 2007 to 2015 and the sites classified using the proposed method. The mean HVSR curves were re-calculated for three site classes and compared with those from KiK-net data. It was found that both the peak period and the amplitude were similar for the mean HVSR curves derived from NSMONS classification results and KiK-net borehole data, implying the effectiveness of the proposed method in identifying different site classes. The classification results have good agreement with site classes based on borehole data of 81 stations in China, which indicates that our site classification results are acceptable and that the proposed method is practicable.

Correlation of Beta Angle with Antero-Posterior Dysplasia Indicators and FMA: An Institution Based Cephalometric Study

PubMed Central

Singh, Gurinder; Verma, Sanjeev; Singh, Devinder Preet; Yadav, Achla Bharti

2016-01-01

Introduction Beta angle utilizes three skeletal landmarks – point A, point B, and point C (the apparent axis of the condyle). It is formed between A-B line and point A perpendicular to C-B line. Further this angle indicates the severity and the type of skeletal dysplasia in the sagittal dimension and it changes with the growth pattern of the patient. Hence, it is important to study the dependence of beta angle on the growth pattern. Aim The present study was designed to evaluate the correlation of Beta angle with point A–Nasion–point B (ANB) angle, points A and B to palatal plane (App-Bpp), Wit’s appraisal and Maxillary-Mandibular plane angle Bisector (MMB) and Frankfort-Mandibular plane Angle (FMA) in Skeletal Class I, Class II and Class III malocclusion groups. Materials and Methods Pre-treatment lateral head cephalo-grams of 120 subjects in age group of 15-25 years were obtained. Three skeletal Class I, Class II and Class III malocclusion groups (40 each) were assorted on the basis of ANB, MMB, App-Bpp, Wit’s appraisal and FMA. Analysis of variance (ANOVA) and mean differences were calculated to compare the study groups. Bivariate correlations among different parameters of these groups were obtained. Results Normal values of beta angle in skeletal Class I group, skeletal Class II group and skeletal Class III group was 31.33±3.25, 25.28±4.28 and 40.93±4.55 respectively. Overall beta angle showed a strong correlation with all parameters of anterio-posterior dysplasia indicators except FMA. Conclusion Beta angle shows weak correlation with FMA and is not affected by growth pattern/jaw rotation. The normal values are in same range irrespective of the differences in craniofacial morphology. PMID:28050509

Pathognomonic features of Angle's Class II division 2 malocclusion: A comparative cephalometric and arch width study

PubMed Central

Prasad, Singamsetty E.R.V.; Indukuri, Ravikishore Reddy; Singh, Rupesh; Nooney, Anitha; Palagiri, Firoz Babu; Narayana, Veera

2014-01-01

Background: A thorough knowledge of the salient features of malocclusion helps the clinician in arriving at a proper diagnosis and treatment plan, and also to predict the prognosis, prior to the onset of treatment process. Among the four classes of Angle's classification of malocclusion, Class II division 2 occurs with the least frequency. There is still continuing debate in the literature whether the Class II division 2 patients ascribe the pathognomonic skeletal and dental features. Aim of the study: The aim of this study is to describe the unique features of Angle's Class II division 2 malocclusion to differentiate it from Angle's Class II division 1 malocclusion. Materials and Methods: A total of 582 pre-treatment records (study models and cephalograms), with the age of patients ranging from 15 to 22 years, were obtained from the hospital records of Vishnu Dental College, Bhimavaram and Geetam's Dental College, Visakhapatnam. Out of these, 11 pre-treatment records were excluded because of lack of clarity. In the rest of the sample, 283 were Class II division 1 and 288 were Class II division 2. The lateral cephalograms were analyzed by using digiceph and the arch width analysis was done based on the anatomical points described by Staley et al. and Sergl et al. Results: An intergroup evaluation was done by using unpaired Student's “t” test. The skeletal vertical parameters, dental parameters, and the maxillary arch width parameters revealed a statistically significant difference between the two groups of malocclusion. Conclusion: Angle's Class II division 2 malocclusion has a pronounced horizontal growth pattern with decreased lower anterior facial height, retroclined upper anteriors, and significantly increased maxillary arch width parameters. PMID:25558449

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.

Development of "one-pot" method for multi-class compounds in porcine formula feed by multi-function impurity adsorption cleaning followed ultra-performance liquid chromatography-tandem mass spectrometry detection.

PubMed

Wang, Peilong; Wang, Xiao; Zhang, Wei; Su, Xiaoou

2014-02-01

A novel and efficient determination method for multi-class compounds including β-agonists, sedatives, nitro-imidazoles and aflatoxins in porcine formula feed based on a fast "one-pot" extraction/multifunction impurity adsorption (MFIA) clean-up procedure has been developed. 23 target analytes belonging to four different class compounds could be determined simultaneously in a single run. Conditions for "one-pot" extraction were studied in detail. Under the optimized conditions, the multi-class compounds in porcine formula feed samples were extracted and purified with methanol contained ammonia and absorbents by one step. The compounds in extracts were purified by using multi types of absorbent based on MFIA in one pot. The multi-walled carbon nanotubes were employed to improved clean-up efficiency. Shield BEH C18 column was used to separate 23 target analytes, followed by tandem mass spectrometry (MS/MS) detection using an electro-spray ionization source in positive mode. Recovery studies were done at three fortification levels. Overall average recoveries of target compounds in porcine formula feed at each levels were >51.6% based on matrix fortified calibration with coefficients of variation from 2.7% to 13.2% (n=6). The limit of determination (LOD) of these compounds in porcine formula feed sample matrix was <5.0 μg/kg. This method was successfully applied in screening and confirmation of target drugs in >30 porcine formula feed samples. It was demonstrated that the integration of the MFIA protocol with the MS/MS instrument could serve as a valuable strategy for rapid screening and reliable confirmatory analysis of multi-class compounds in real samples. Copyright © 2013 Elsevier B.V. All rights reserved.

Performance recovery of a class of uncertain non-affine systems with unmodelled dynamics: an indirect dynamic inversion method

NASA Astrophysics Data System (ADS)

Yi, Bowen; Lin, Shuyi; Yang, Bo; Zhang, Weidong

2018-02-01

This paper presents an output feedback indirect dynamic inversion (IDI) approach for a class of uncertain nonaffine systems with input unmodelled dynamics. Compared with previous approaches to achieve performance recovery, the proposed method aims at dealing with a broader class of nonaffine-in-control systems with triangular structure. An IDI state feedback law is designed first, in which less knowledge of the model plant is needed compared to earlier approximate dynamic inversion methods, thus yielding more robust performance. After that, an extended high-gain observer is designed to accomplish the task with output feedback. Finally, we prove that the designed IDI controller is equivalent to an adaptive proportional-integral (PI) controller, with respect to both time response equivalence and robustness equivalence. The conclusion implies that for the studied strict-feedback non-affine systems with unmodelled dynamics, there always exits a PI controller to stabilise the systems. The effectiveness and benefits of the designed approach are verified by three examples.

A multiple maximum scatter difference discriminant criterion for facial feature extraction.

PubMed

Song, Fengxi; Zhang, David; Mei, Dayong; Guo, Zhongwei

2007-12-01

Maximum scatter difference (MSD) discriminant criterion was a recently presented binary discriminant criterion for pattern classification that utilizes the generalized scatter difference rather than the generalized Rayleigh quotient as a class separability measure, thereby avoiding the singularity problem when addressing small-sample-size problems. MSD classifiers based on this criterion have been quite effective on face-recognition tasks, but as they are binary classifiers, they are not as efficient on large-scale classification tasks. To address the problem, this paper generalizes the classification-oriented binary criterion to its multiple counterpart--multiple MSD (MMSD) discriminant criterion for facial feature extraction. The MMSD feature-extraction method, which is based on this novel discriminant criterion, is a new subspace-based feature-extraction method. Unlike most other subspace-based feature-extraction methods, the MMSD computes its discriminant vectors from both the range of the between-class scatter matrix and the null space of the within-class scatter matrix. The MMSD is theoretically elegant and easy to calculate. Extensive experimental studies conducted on the benchmark database, FERET, show that the MMSD out-performs state-of-the-art facial feature-extraction methods such as null space method, direct linear discriminant analysis (LDA), eigenface, Fisherface, and complete LDA.

Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings.

PubMed

Mordang, Jan-Jurre; Gubern-Mérida, Albert; Bria, Alessandro; Tortorella, Francesco; den Heeten, Gerard; Karssemeijer, Nico

2017-04-01

Computer-aided detection (CADe) systems for mammography screening still mark many false positives. This can cause radiologists to lose confidence in CADe, especially when many false positives are obviously not suspicious to them. In this study, we focus on obvious false positives generated by microcalcification detection algorithms. We aim at reducing the number of obvious false-positive findings by adding an additional step in the detection method. In this step, a multiclass machine learning method is implemented in which dedicated classifiers learn to recognize the patterns of obvious false-positive subtypes that occur most frequently. The method is compared to a conventional two-class approach, where all false-positive subtypes are grouped together in one class, and to the baseline CADe system without the new false-positive removal step. The methods are evaluated on an independent dataset containing 1,542 screening examinations of which 80 examinations contain malignant microcalcifications. Analysis showed that the multiclass approach yielded a significantly higher sensitivity compared to the other two methods (P < 0.0002). At one obvious false positive per 100 images, the baseline CADe system detected 61% of the malignant examinations, while the systems with the two-class and multiclass false-positive reduction step detected 73% and 83%, respectively. Our study showed that by adding the proposed method to a CADe system, the number of obvious false positives can decrease significantly (P < 0.0002). © 2017 American Association of Physicists in Medicine.

Prevalence of Malocclusion among 6 to 10 Year old Nalgonda School Children

PubMed Central

Reddy, E Rajendra; Manjula, M; Sreelakshmi, N; Rani, S Thabitha; Aduri, Rajesh; Patil, B Dharamraj

2013-01-01

Background: To evaluate the prevalence of malocclusion among 6 to 10 year old children of Nalgonda District. Materials & Methods: A total of 3000 children were examined, out of which 2135 children (1009 boys and 1126 girls) who fulfilled the inclusion criteria were included. The selected sample was examined for Class I, Class II, Class III molar relationship, lower anterior crowding, cross bite (anterior and posterior), open bite, and pseudo class III [edge to edge bite] discrepancies after obtaining the written consent from the concerned school authorities. The collected data was tabulated and statistically analysed using chi-square test. Results: Among the selected sample, 648 (30.35%) children had minor tooth alignment discrepancies. Angle’s Class I molar relation with and without minor discrepancies was observed in 78.6%, Class II in 13.9%, Class III in 7.8% of the subjects surveyed. Lower anterior crowding in 11.8%, anterior cross bite in 4.5%, posterior cross bite in 3.75%, openbite in 3% and Pseudo class III [edge to edge] in 5.97% was noticed among the studied population. There was no statistical significant difference observed gender wise. Conclusion: In the current study, 52% of the studied population had malocclusion with a higher prevalence of Angle’s Class I molar relation with lower anterior crowding. How to cite this article: Reddy ER, Manjula M, Sreelakshmi N, Rani ST, Aduri R, Patil BD. Prevalence of Malocclusion among 6 to 10 Year old Nalgonda School Children. J Int Oral Health 2013; 5(6):49-54 . PMID:24453444

10 CFR 2.305 - Service of documents; methods; proof.

Code of Federal Regulations, 2011 CFR

2011-01-01

... service, or by first-class, express, certified or registered mail. As to each participant that cannot... evidence, may be made by first-class mail in all cases, unless the presiding officer directs otherwise or... by the same or equivalent method, such as by electronic transmission or first-class mail, that they...

A fast learning method for large scale and multi-class samples of SVM

NASA Astrophysics Data System (ADS)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.

The effect on prospective teachers of the learning environment supported by dynamic statistics software

NASA Astrophysics Data System (ADS)

Koparan, Timur

2016-02-01

In this study, the effect on the achievement and attitudes of prospective teachers is examined. With this aim ahead, achievement test, attitude scale for statistics and interviews were used as data collection tools. The achievement test comprises 8 problems based on statistical data, and the attitude scale comprises 13 Likert-type items. The study was carried out in 2014-2015 academic year fall semester at a university in Turkey. The study, which employed the pre-test-post-test control group design of quasi-experimental research method, was carried out on a group of 80 prospective teachers, 40 in the control group and 40 in the experimental group. Both groups had four-hour classes about descriptive statistics. The classes with the control group were carried out through traditional methods while dynamic statistics software was used in the experimental group. Five prospective teachers from the experimental group were interviewed clinically after the application for a deeper examination of their views about application. Qualitative data gained are presented under various themes. At the end of the study, it was found that there is a significant difference in favour of the experimental group in terms of achievement and attitudes, the prospective teachers have affirmative approach to the use of dynamic software and see it as an effective tool to enrich maths classes. In accordance with the findings of the study, it is suggested that dynamic software, which offers unique opportunities, be used in classes by teachers and students.

A Comparison of Computer-Assisted Instruction and the Traditional Method of Teaching Basic Statistics

ERIC Educational Resources Information Center

Ragasa, Carmelita Y.

2008-01-01

The objective of the study is to determine if there is a significant difference in the effects of the treatment and control groups on achievement as well as on attitude as measured by the posttest. A class of 38 sophomore college students in the basic statistics taught with the use of computer-assisted instruction and another class of 15 students…

High School Students' Attitudes and Beliefs on Using the Science Writing Heuristic in an Advanced Placement Chemistry Class

ERIC Educational Resources Information Center

Putti, Alice

2011-01-01

This paper discusses student attitudes and beliefs on using the Science Writing Heuristic (SWH) in an advanced placement (AP) chemistry classroom. During the 2007 school year, the SWH was used in a class of 24 AP chemistry students. Using a Likert-type survey, student attitudes and beliefs on the process were determined. Methods for the study are…

Measurement and Analysis of Student Engagement in University Classes where Varying Levels of PBL Methods of Instruction Are in Use

ERIC Educational Resources Information Center

Ahlfeldt, Stephanie; Mehta, Sudhir; Sellnow, Timothy

2005-01-01

Students participate more in a classroom and also report a better understanding of course concepts when steps are taken to actively engage them. The Student Engagement (SE) Survey was developed and used in this study for measuring student engagement at the class level and consisted of 14 questions adapted from the original National Survey of…

A Sport Education Fitness Season's Impact on Students' Fitness Levels, Knowledge, and In-Class Physical Activity

ERIC Educational Resources Information Center

Ward, Jeffery Kurt; Hastie, Peter A.; Wadsworth, Danielle D.; Foote, Shelby; Brock, Sheri J.; Hollett, Nikki

2017-01-01

Purpose: The purpose of this study was to determine the extent to which a sport education season of fitness could provide students with recommended levels of in-class moderate-to-vigorous physical activity (MVPA) while also increasing students' fitness knowledge and fitness achievement. Method: One hundred and sixty-six 5th-grade students (76…

Figure-ground segmentation based on class-independent shape priors

NASA Astrophysics Data System (ADS)

Li, Yang; Liu, Yang; Liu, Guojun; Guo, Maozu

2018-01-01

We propose a method to generate figure-ground segmentation by incorporating shape priors into the graph-cuts algorithm. Given an image, we first obtain a linear representation of an image and then apply directional chamfer matching to generate class-independent, nonparametric shape priors, which provide shape clues for the graph-cuts algorithm. We then enforce shape priors in a graph-cuts energy function to produce object segmentation. In contrast to previous segmentation methods, the proposed method shares shape knowledge for different semantic classes and does not require class-specific model training. Therefore, the approach obtains high-quality segmentation for objects. We experimentally validate that the proposed method outperforms previous approaches using the challenging PASCAL VOC 2010/2012 and Berkeley (BSD300) segmentation datasets.

Initiating Self-Assessment Strategies in Novice Physiotherapy Students: A Method Case Study

ERIC Educational Resources Information Center

Young, Catherine

2013-01-01

Student self- and peer-assessment strategies ideally are instigated early in programmes for health professionals. This study presents an innovative method of stimulating critical evaluation of clinical skills learned in the practical class setting for first year physiotherapy students. Twice in the semester (beginning and end) students assessed…

NetCTLpan: pan-specific MHC class I pathway epitope predictions

PubMed Central

Larsen, Mette Voldby; Lundegaard, Claus; Nielsen, Morten

2010-01-01

Reliable predictions of immunogenic peptides are essential in rational vaccine design and can minimize the experimental effort needed to identify epitopes. In this work, we describe a pan-specific major histocompatibility complex (MHC) class I epitope predictor, NetCTLpan. The method integrates predictions of proteasomal cleavage, transporter associated with antigen processing (TAP) transport efficiency, and MHC class I binding affinity into a MHC class I pathway likelihood score and is an improved and extended version of NetCTL. The NetCTLpan method performs predictions for all MHC class I molecules with known protein sequence and allows predictions for 8-, 9-, 10-, and 11-mer peptides. In order to meet the need for a low false positive rate, the method is optimized to achieve high specificity. The method was trained and validated on large datasets of experimentally identified MHC class I ligands and cytotoxic T lymphocyte (CTL) epitopes. It has been reported that MHC molecules are differentially dependent on TAP transport and proteasomal cleavage. Here, we did not find any consistent signs of such MHC dependencies, and the NetCTLpan method is implemented with fixed weights for proteasomal cleavage and TAP transport for all MHC molecules. The predictive performance of the NetCTLpan method was shown to outperform other state-of-the-art CTL epitope prediction methods. Our results further confirm the importance of using full-type human leukocyte antigen restriction information when identifying MHC class I epitopes. Using the NetCTLpan method, the experimental effort to identify 90% of new epitopes can be reduced by 15% and 40%, respectively, when compared to the NetMHCpan and NetCTL methods. The method and benchmark datasets are available at http://www.cbs.dtu.dk/services/NetCTLpan/. Electronic supplementary material The online version of this article (doi:10.1007/s00251-010-0441-4) contains supplementary material, which is available to authorized users. PMID:20379710

The group dynamics of women's self-defense training.

PubMed

Brecklin, Leanne R; Middendorf, Rena K

2014-03-01

The current study examines the role of group interaction in a women's self-defense class. Study methods included individual interviews with women who had completed a college-based women-only self-defense course as well as supplemental observation of group behavior during a mock "attack" simulation class. The unique relationship that develops among women's self-defense classmates seems to improve overall learning and performance due to the group collaboration and vicarious experiences. Results demonstrated that women's self-defense courses offer participants a beneficial and supportive group atmosphere.

Molecular characterization of swine leukocyte antigen gene diversity in purebred Pietrain pigs.

PubMed

Essler, Sabine E; Ertl, Werner; Deutsch, Julia; Ruetgen, Barbara C; Groiss, Sandra; Stadler, Maria; Wysoudil, Bhuma; Gerner, Wilhelm; Ho, Chak-Sum; Saalmueller, Armin

2013-04-01

The porcine major histocompatibility complex (MHC) harbors the highly polymorphic swine leukocyte antigen (SLA) class I and II gene clusters encoding glycoproteins that present antigenic peptides to T cells in the adaptive immune response. In Austria, the majority of commercial pigs are F 2 descendants of F 1 Large White/Landrace hybrids paired with Pietrain boars. Therefore, the repertoire of SLA alleles and haplotypes present in Pietrain pigs has an important influence on that of their descendants. In this study, we characterized the SLA class I ( SLA-1 , SLA-2 , SLA-3 ) and class II ( SLA-DRB1 , SLA-DQB1 , SLA-DQA ) genes of 27 purebred Pietrain pigs using a combination of the high-resolution sequence-based typing (SBT) method and a low-resolution (Lr) PCR-based method using allele-group, sequence-specific primers (PCR-SSP). A total of 15 class I and 13 class II haplotypes were identified in the studied cohort. The most common SLA class I haplotype Lr-43.0 ( SLA-1 *11XX- SLA-3 *04XX- SLA-2 *04XX) was identified in 11 animals with a frequency of 20%. For SLA class II, the most prevalent haplotype, Lr-0.14 [ SLA-DRB1 *0901- SLA-DQB1 *0801- SLA-DQA *03XX], was found in 14 animals with a frequency of 26%. Two class II haplotypes, tentatively designated as Lr-Pie-0.1 [ SLA-DRB1 *01XX/be01/ha04- SLA-DQB1 *05XX- SLA - DQA*blank] and Lr-Pie-0.2 [ SLA-DRB1 *06XX- SLA-DQB1 *03XX- SLA-DQA *03XX], appeared to be novel and have never been reported so far in other pig populations. We showed that SLA genotyping using PCR-SSP-based assays represents a rapid and cost-effective way to study SLA diversity in outbred commercial pigs and may facilitate the development of more effective vaccines or identification of disease-resistant pigs in the context of SLA antigens to improve overall swine health. © 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.

Wire connector classification with machine vision and a novel hybrid SVM

NASA Astrophysics Data System (ADS)

Chauhan, Vedang; Joshi, Keyur D.; Surgenor, Brian W.

2018-04-01

A machine vision-based system has been developed and tested that uses a novel hybrid Support Vector Machine (SVM) in a part inspection application with clear plastic wire connectors. The application required the system to differentiate between 4 different known styles of connectors plus one unknown style, for a total of 5 classes. The requirement to handle an unknown class is what necessitated the hybrid approach. The system was trained with the 4 known classes and tested with 5 classes (the 4 known plus the 1 unknown). The hybrid classification approach used two layers of SVMs: one layer was semi-supervised and the other layer was supervised. The semi-supervised SVM was a special case of unsupervised machine learning that classified test images as one of the 4 known classes (to accept) or as the unknown class (to reject). The supervised SVM classified test images as one of the 4 known classes and consequently would give false positives (FPs). Two methods were tested. The difference between the methods was that the order of the layers was switched. The method with the semi-supervised layer first gave an accuracy of 80% with 20% FPs. The method with the supervised layer first gave an accuracy of 98% with 0% FPs. Further work is being conducted to see if the hybrid approach works with other applications that have an unknown class requirement.

Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods.

PubMed

Jiménez-Carvelo, Ana M; González-Casado, Antonio; Pérez-Castaño, Estefanía; Cuadros-Rodríguez, Luis

2017-03-01

A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.

The Story-Presenting Method: a Method for Constructing Multiple Viewpoints to Understand Different Cultures.

PubMed

Watanabe, Tadaharu

2017-09-01

This study will show the results of four dialogical cultural exchange classes, which were held between Japanese and Chinese high school students, and examine the shifts in students' viewpoints and changes in cultural understandings that occurred during those classes. In the first cultural exchange class, students of both countries read a story which described an older student who carelessly wore a T-shirt inside out, and younger students passed by without greeting him. Students of both countries were then asked to write their comments about it. From the second to the fourth class, students discussed the story with each other through exchanging their comments. By presenting another story, which introduced the viewpoint of a third person, and asking them questions that allowed them to reflect on their lives, students also experienced four different viewpoints during these cultural exchange classes. At the beginning of the cultural exchange, students of both countries tended to focus on the similarities in each other's comments, which led to the closing down of the discussion. However, through discussions and experiencing the four different viewpoints, they found there are some essential differences between them around 'ways of greeting' and 'hierarchical relationships between older and younger students', which motivated them to understand their counterparts' culture. Moreover, in the last comments of these cultural exchange classes, it was found that they acquired the viewpoints of cultural others. Given the results of these classes, it is shown that it is effective to present various stories to stimulate cultural understanding.

The Intertextual Method for Art Education Applied in Japanese Paper Theatre--A Study on Discovering Intercultural Differences

ERIC Educational Resources Information Center

Paatela-Nieminen, Martina

2008-01-01

In art education we need methods for studying works of art and visual culture interculturally because there are many multicultural art classes and little consensus as to how to interpret art in different cultures. In this article my central aim was to apply the intertextual method that I developed in my doctoral thesis for Western art education to…

Identification of transitional disks in Chamaeleon with Herschel

NASA Astrophysics Data System (ADS)

Ribas, Á.; Merín, B.; Bouy, H.; Alves de Oliveira, C.; Ardila, D. R.; Puga, E.; Kóspál, Á.; Spezzi, L.; Cox, N. L. J.; Prusti, T.; Pilbratt, G. L.; André, Ph.; Matrà, L.; Vavrek, R.

2013-04-01

Context. Transitional disks are circumstellar disks with inner holes that in some cases are produced by planets and/or substellar companions in these systems. For this reason, these disks are extremely important for the study of planetary system formation. Aims: The Herschel Space Observatory provides an unique opportunity for studying the outer regions of protoplanetary disks. In this work we update previous knowledge on the transitional disks in the Chamaeleon I and II regions with data from the Herschel Gould Belt Survey. Methods: We propose a new method for transitional disk classification based on the WISE 12 μm - PACS 70 μm color, together with inspection of the Herschel images. We applied this method to the population of Class II sources in the Chamaeleon region and studied the spectral energy distributions of the transitional disks in the sample. We also built the median spectral energy distribution of Class II objects in these regions for comparison with transitional disks. Results: The proposed method allows a clear separation of the known transitional disks from the Class II sources. We find six transitional disks, all previously known, and identify five objects previously thought to be transitional as possibly non-transitional. We find higher fluxes at the PACS wavelengths in the sample of transitional disks than those of Class II objects. Conclusions: We show the Herschel 70 μm band to be a robust and efficient tool for transitional disk identification. The sensitivity and spatial resolution of Herschel reveals a significant contamination level among the previously identified transitional disk candidates for the two regions, which calls for a revision of previous samples of transitional disks in other regions. The systematic excess found at the PACS bands could be either a result of the mechanism that produces the transitional phase, or an indication of different evolutionary paths for transitional disks and Class II sources. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.Appendix A is available in electronic form at http://www.aanda.org

Multiple model self-tuning control for a class of nonlinear systems

NASA Astrophysics Data System (ADS)

Huang, Miao; Wang, Xin; Wang, Zhenlei

2015-10-01

This study develops a novel nonlinear multiple model self-tuning control method for a class of nonlinear discrete-time systems. An increment system model and a modified robust adaptive law are proposed to expand the application range, thus eliminating the assumption that either the nonlinear term of the nonlinear system or its differential term is global-bounded. The nonlinear self-tuning control method can address the situation wherein the nonlinear system is not subject to a globally uniformly asymptotically stable zero dynamics by incorporating the pole-placement scheme. A novel, nonlinear control structure based on this scheme is presented to improve control precision. Stability and convergence can be confirmed when the proposed multiple model self-tuning control method is applied. Furthermore, simulation results demonstrate the effectiveness of the proposed method.

Is alternate rapid maxillary expansion and constriction an effective protocol in the treatment of Class III malocclusion? A systematic review

PubMed Central

Pithon, Matheus Melo; Santos, Nathalia de Lima; dos Santos, Camila Rangel Barreto; Baião, Felipe Carvalho Souza; Pinheiro, Murilo Costa Rangel; Matos, Manoel; Souza, Ianderlei Andrade; de Paula, Rafael Pereira

2016-01-01

ABSTRACT Introduction: the treatment of Class III malocclusion in early age is one of the greatest challenges for orthodontists, and the establishment of more effective treatment method is a constant concern for these professionals. Thus, the objective of this systematic review is to verify the effectiveness of the therapy protocol for alternate rapid maxillary expansion and constriction (Alt-RAMEC) in the early treatment of Class III malocclusion. Methods: searches were performed in the following electronic databases: Cochrane Library, Medline (EBSCO and PubMed), SciELO, LILACS and Scopus. The following inclusion criteria were used: in vivo studies conducted with early intervention (patient in craniofacial development phase) with the use of the Alt-RAMEC protocol. Reviews, case reports, editorials, and studies with syndromic patients or under use of systemic drug were excluded. Duplicates were also excluded. The studies were assessed for methodological quality using the Cochrane tool for assessment of risk of bias, and classified as high or low risk of bias. Results: 53 articles were found. Duplicates exclusion was thus performed and 35 articles remained. After inclusion analysis, only 5 matched the criteria. Two articles were classified as low risk of bias and three as high risk of bias. It was observed that the Alt-RAMEC enable protraction in less time and with better results, promoting greater effectiveness in the protraction treatment of Class III malocclusion. Conclusions: Although there is positive evidence of the effectiveness of early treatment with the Alt-RAMEC protocol in patients with Class III malocclusion, further studies are needed to confirm its effectiveness using long-term methodology. PMID:28125138

Development Trajectories and Predictors of the Role Commitment of Nursing Preceptors.

PubMed

Wang, Wei-Fang; Hung, Chich-Hsiu; Li, Chung-Yi

2018-06-01

The commitment of nursing preceptors to their role is an important driving force that supports their clinical teaching and affects teaching quality. Role commitment undergoes dynamic development and thus changes over time. Existing studies have utilized only cross-sectional study designs and have not analyzed the changes in commitment trajectories with related factors. This study aimed to investigate the development trajectories of the commitment of preceptors and to examine the predictors between the trajectories of role commitment among nursing preceptors. A single-group, repeated-measures design was adopted, and 59 participants completed the Commitment to the Preceptor Role Scale and the Preceptor's Perception of Support Scale. The latent class growth analysis method was used to estimate the trajectory class patterns. The Wilcoxon rank-sum test, a nonparametric method, was used to compare the differences in demographic characteristics between the trajectories of commitment among nursing preceptors. Predictors were examined using binary logistic regression analysis. The two-class model was the best-fitting model to describe the trajectories of nursing preceptor commitment. The two classes in this model were "low commitment," which accounted for 90.3% of all the participants, and "high commitment," which accounted for 9.7%. A significant difference was found between the two classes in terms of motivation for being a preceptor (p = .048). Neither demographic characteristics nor organizational support had a predictive effect on the trajectories of commitment development. This study found a low level of role commitment among new preceptors. Moreover, internal motivation was found to be a significant factor affecting the trajectories of this commitment. Therefore, institutions should foster an appropriate environment to enhance the role identity of preceptors as well as cultivate and stimulate their commitment to this role.

Evaluation of Team-Based Learning and Traditional Instruction in Teaching Removable Partial Denture Concepts.

PubMed

Echeto, Luisa F; Sposetti, Venita; Childs, Gail; Aguilar, Maria L; Behar-Horenstein, Linda S; Rueda, Luis; Nimmo, Arthur

2015-09-01

The aim of this study was to evaluate the effectiveness of team-based learning (TBL) methodology on dental students' retention of knowledge regarding removable partial denture (RPD) treatment. The process of learning RPD treatment requires that students first acquire foundational knowledge and then use critical thinking skills to apply that knowledge to a variety of clinical situations. The traditional approach to teaching, characterized by a reliance on lectures, is not the most effective method for learning clinical applications. To address the limitations of that approach, the teaching methodology of the RPD preclinical course at the University of Florida was changed to TBL, which has been shown to motivate student learning and improve clinical performance. A written examination was constructed to compare the impact of TBL with that of traditional teaching regarding students' retention of knowledge and their ability to evaluate, diagnose, and treatment plan a partially edentulous patient with an RPD prosthesis. Students taught using traditional and TBL methods took the same examination. The response rate (those who completed the examination) for the class of 2013 (traditional method) was 94% (79 students of 84); for the class of 2014 (TBL method), it was 95% (78 students of 82). The results showed that students who learned RPD with TBL scored higher on the examination than those who learned RPD with traditional methods. Compared to the students taught with the traditional method, the TBL students' proportion of passing grades was statistically significantly higher (p=0.002), and 23.7% more TBL students passed the examination. The mean score for the TBL class (0.758) compared to the conventional class (0.700) was statistically significant with a large effect size, also demonstrating the practical significance of the findings. The results of the study suggest that TBL methodology is a promising approach to teaching RPD with successful outcomes.

Characterization of swine leukocyte antigen alleles and haplotypes on a novel miniature pig line, Microminipig.

PubMed

Ando, A; Imaeda, N; Ohshima, S; Miyamoto, A; Kaneko, N; Takasu, M; Shiina, T; Kulski, J K; Inoko, H; Kitagawa, H

2014-12-01

Microminipigs are extremely small-sized, novel miniature pigs that were recently developed for medical research. The inbred Microminipigs with defined swine leukocyte antigen (SLA) haplotypes are expected to be useful for allo- and xenotransplantation studies and also for association analyses between SLA haplotypes and immunological traits. To establish SLA-defined Microminipig lines, we characterized the polymorphic SLA alleles for three class I (SLA-1, SLA-2 and SLA-3) and two class II (SLA-DRB1 and SLA-DQB1) genes of 14 parental Microminipigs using a high-resolution nucleotide sequence-based typing method. Eleven class I and II haplotypes, including three recombinant haplotypes, were found in the offspring of the parental Microminipigs. Two class I and class II haplotypes, Hp-31.0 (SLA-1*1502-SLA-3*070102-SLA-2*1601) and Hp-0.37 (SLA-DRB1*0701-SLA-DQB1*0502), are novel and have not so far been reported in other pig breeds. Crossover regions were defined by the analysis of 22 microsatellite markers within the SLA class III region of three recombinant haplotypes. The SLA allele and haplotype information of Microminipigs in this study will be useful to establish SLA homozygous lines including three recombinants for transplantation and immunological studies. © 2014 Stichting International Foundation for Animal Genetics.

Systematic Hybrid Network Scheduling for Multiple Traffic Classes with Host Timing and Phase Constraints

NASA Technical Reports Server (NTRS)

Hall, Brendan (Inventor); Bonk, Ted (Inventor); Varadarajan, Srivatsan (Inventor); Smithgall, William Todd (Inventor); DeLay, Benjamin F. (Inventor)

2017-01-01

Systems and methods for systematic hybrid network scheduling for multiple traffic classes with host timing and phase constraints are provided. In certain embodiments, a method of scheduling communications in a network comprises scheduling transmission of virtual links pertaining to a first traffic class on a global schedule to coordinate transmission of the virtual links pertaining to the first traffic class across all transmitting end stations on the global schedule; and scheduling transmission of each virtual link pertaining to a second traffic class on a local schedule of the respective transmitting end station from which each respective virtual link pertaining to the second traffic class is transmitted such that transmission of each virtual link pertaining to the second traffic class is coordinated only at the respective end station from which each respective virtual link pertaining to the second traffic class is transmitted.

Examining the Latent Class Structure of CO2 Hypersensitivity using Time Course Trajectories of Panic Response Systems

PubMed Central

Roberson-Nay, Roxann; Beadel, Jessica R.; Gorlin, Eugenia I.; Latendresse, Shawn J.; Teachman, Bethany A.

2014-01-01

Background and Objectives Carbon dioxide (CO2) hypersensitivity is hypothesized to be a robust endophenotypic marker of panic spectrum vulnerability. The goal of the current study was to explore the latent class trajectories of three primary response systems theoretically associated with CO2 hypersensitivity: subjective anxiety, panic symptoms, and respiratory rate (fR). Methods Participants (n=376; 56% female) underwent a maintained 7.5% CO2 breathing task that included three phases: baseline, CO2 air breathing, and recovery. Growth mixture modeling was used to compare response classes (1..n) to identify the best-fit model for each marker. Panic correlates also were examined to determine class differences in panic vulnerability. Results For subjective anxiety ratings, a three-class model was selected, with individuals in one class reporting an acute increase in anxiety during 7.5% CO2 breathing and a return to pre-CO2 levels during recovery. A second, smaller latent class was distinguished by elevated anxiety across all three phases. The third class reported low anxiety reported during room air, a mild increase in anxiety during 7.5% CO2 breathing, and a return to baseline during recovery. Latent class trajectories for fR yielded one class whereas panic symptom response yielded two classes. Limitations This study examined CO2 hypersensitivity in one of the largest samples to date, but did not ascertain a general population sample thereby limiting generalizability. Moreover, a true resting baseline measure of fR was not measured. Conclusions Two classes potentially representing different risk pathways were observed. Implications of results will be discussed in the context of panic risk research. PMID:25496936

Evaluation of Different Score Index for Predicting Prognosis in Gamma Knife Radiosurgical Treatment for Brain Metastasis

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

Franzin, Alberto; Snider, Silvia; Picozzi, Piero

2009-07-01

Purpose: To assess the utility of the Radiation Therapy Oncology Group Recursive Partitioning Analysis (RPA) and Score Index for Radiosurgery (SIR) stratification systems in predicting survival in patients with brain metastasis treated with Gamma Knife radiosurgery (GKRS). Methods and Materials: A total of 185 patients were included in the study. Patients were stratified according to RPA and SIR classes. The RPA and SIR classes, age, Karnofsky Performance Status (KPS), and systemic disease were correlated with survival. Results: Five patients were lost to follow-up. Median survival in patients in RPA Class 1 (30 patients) was 17 months; in Class 2 (140more » patients), 10 months; and in Class 3 (10 patients), 3 months. Median survival in patients in SIR Class 1 (30 patients) was 3 months; in Class 2 (135 patients), 8 months; and in Class 3 (15 patients), 20 months. In univariate testing, age younger than 65 years (p = 0.0004), KPS higher than 70 (p = 0.0001), RPA class (p = 0.0078), SIR class (p = 0.0002), and control of the primary tumor (p = 0.02) were significantly associated with improved outcome. In multivariate analysis, KPS (p < 0.0001), SIR class (p = 0.0008), and RPA class (p = 0.03) had statistical value. Conclusions: This study supports the use of GKRS as a single-treatment modality in this selected group of patients. Stratification systems are useful in the estimation of patient eligibility for GKRS. A second-line treatment was necessary in 30% of patients to achieve distal or local brain control. This strategy is useful to control brain metastasis in long-surviving patients.« less

The Method of Immersion the Problem of Comparing Technical Objects in an Expert Shell in the Class of Artificial Intelligence Algorithms

NASA Astrophysics Data System (ADS)

Sergey Vasilievich, Buharin; Aleksandr Vladimirovich, Melnikov; Svetlana Nikolaevna, Chernyaeva; Lyudmila Anatolievna, Korobova

2017-08-01

The method of dip of the underlying computational problem of comparing technical object in an expert shell in the class of data mining methods is examined. An example of using the proposed method is given.

Land use in the Paraiba Valley through remotely sensed data. [Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Lombardo, M. A.; Novo, E. M. L. D.; Niero, M.; Foresti, C.

1980-01-01

A methodology for land use survey was developed and land use modification rates were determined using LANDSAT imagery of the Paraiba Valley (state of Sao Paulo). Both visual and automatic interpretation methods were employed to analyze seven land use classes: urban area, industrial area, bare soil, cultivated area, pastureland, reforestation and natural vegetation. By means of visual interpretation, little spectral differences are observed among those classes. The automatic classification of LANDSAT MSS data using maximum likelihood algorithm shows a 39% average error of omission and a 3.4% error of inclusion for the seven classes. The complexity of land uses in the study area, the large spectral variations of analyzed classes, and the low resolution of LANDSAT data influenced the classification results.

A Comparison of Case Study and Traditional Teaching Methods for Improvement of Oral Communication and Critical-Thinking Skills

ERIC Educational Resources Information Center

Noblitt, Lynnette; Vance, Diane E.; Smith, Michelle L. DePoy

2010-01-01

This study compares a traditional paper presentation approach and a case study method for the development and improvement of oral communication skills and critical-thinking skills in a class of junior forensic science majors. A rubric for rating performance in these skills was designed on the basis of the oral communication competencies developed…

The Impact of Intervention Methods on Emotional Intelligence

ERIC Educational Resources Information Center

Davis, Christopher M.

2013-01-01

This experimental study continued the exploration surrounding emotional intelligence (EI). Emotional intelligence was examined through past and present literature, instrumentation, didactic teaching methods employing EI concepts, and data analysis. The experiment involved participants from two sections of an undergraduate economics class at a…

Barriers and Incentives to Computer Usage in Teaching

DTIC Science & Technology

1988-09-29

classes with one or two computers. Research Methods The two major methods of data-gathering employed in this study were intensive and extensive classroom ... observation and repeated extended interviews with students and teachers. Administrators were also interviewed when appropriate. Classroom observers used

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…

A Method To Ensure Heterogeneous Mixing of Grade 9 Classes.

ERIC Educational Resources Information Center

Brydges, Bruce

This paper presents outcomes of a practicum that was designed to address a need that was created when the Ministry of Education in Ontario, Canada, mandated that all grade 9 classes be "destreamed." A review of educational literature found no methods for ensuring that classes are truly heterogeneously mixed. The practicum was designed to…

Flipping an Agricultural Education Teaching Methods Course

ERIC Educational Resources Information Center

Conner, Nathan W.; Stripling, Christopher T.; Blythe, Jessica M.; Roberts, T. Grady; Stedman, Nicole L. P.

2014-01-01

Flipping or inverting a course is a relatively new approach to structuring a course. Using this method, the lectures traditionally delivered during regularly scheduled class time are converted to a media for delivery online, often in the form of videos. Learners are expected to view the online lectures prior to class. Then in turn, in-class time…

The Mnemonic Keyword Method: Effects on the Vocabulary Acquisition and Retention

ERIC Educational Resources Information Center

Siriganjanavong, Vanlee

2013-01-01

The objectives of the study were to introduce the technique called "Mnemonic Keyword Method" ("MKM") to low proficiency English learners, and to explore the effectiveness of the method in terms of short-term and long-term retention. The sample was purposefully drawn from one intact class consisting of 44 students. They were…

Around the Globe. Teaching English in China.

ERIC Educational Resources Information Center

Allen, James D.; Changshun, Sun

1999-01-01

Describes a method of teaching English-as-a-Second-Language in China started by Han Zhongliang. Han's method is student-centered, with students learning and using English in practical, relevant ways from the beginning of their study. This method breaks away from conventional textbook-centered orientations. Out-of-class games are united with…

Art-Based Learning Strategies in Art Therapy Graduate Education

ERIC Educational Resources Information Center

Deaver, Sarah P.

2012-01-01

This mixed methods research study examined the use of art-based teaching methods in master's level art therapy graduate education in North America. A survey of program directors yielded information regarding in which courses and how frequently art-based methods (individual in-class art making, dyad or group art making, student art projects as…

Finding the Right Mix: Teaching Methods as Predictors for Student Progress on Learning Objectives

ERIC Educational Resources Information Center

Glover, Jacob I.

2012-01-01

This study extends existing student ratings research by exploring how teaching methods, individually and collectively, influence a minimum standard of student achievement on learning objectives and how class size impacts this influence. Twenty teaching methods were used to predict substantial or exceptional progress on each of 12 learning…

Combined LC/MS-platform for analysis of all major stratum corneum lipids, and the profiling of skin substitutes.

PubMed

van Smeden, Jeroen; Boiten, Walter A; Hankemeier, Thomas; Rissmann, Robert; Bouwstra, Joke A; Vreeken, Rob J

2014-01-01

Ceramides (CERs), cholesterol, and free fatty acids (FFAs) are the main lipid classes in human stratum corneum (SC, outermost skin layer), but no studies report on the detailed analysis of these classes in a single platform. The primary aims of this study were to 1) develop an LC/MS method for (semi-)quantitative analysis of all main lipid classes present in human SC; and 2) use this method to study in detail the lipid profiles of human skin substitutes and compare them to human SC lipids. By applying two injections of 10μl, the developed method detects all major SC lipids using RPLC and negative ion mode APCI-MS for detection of FFAs, and NPLC using positive ion mode APCI-MS to analyze CERs and cholesterol. Validation showed this lipid platform to be robust, reproducible, sensitive, and fast. The method was successfully applied on ex vivo human SC, human SC obtained from tape strips and human skin substitutes (porcine SC and human skin equivalents). In conjunction with FFA profiles, clear differences in CER profiles were observed between these different SC sources. Human skin equivalents more closely mimic the lipid composition of human stratum corneum than porcine skin does, although noticeable differences are still present. These differences gave biologically relevant information on some of the enzymes that are probably involved in SC lipid processing. For future research, this provides an excellent method for (semi-)quantitative, 'high-throughput' profiling of SC lipids and can be used to advance the understanding of skin lipids and the biological processes involved. © 2013.

The Effect of Social and Token Economy Reinforcements on Academic Achievement of Students with Intellectual Disabilities

PubMed Central

Ashoori, Mohammad; Sereshki, Narges Adib

2011-01-01

Objective This study investigates the effect of social and token economy reinforcements on academic achievement of 9th grade boy students with intellectual disabilities in an experimental science class in Tehran Province. Method The method used for this study was experimental by pre-test, post- test with a control group. The boy students with intellectual disabilities from three junior high schools participated in this study. The sample consisted of thirty, 9th grade boy students with intellectual disabilities in the selected schools; the schools were chosen by the multi-stage cluster method. To measure the progress of students in the science class, a teacher made test and the Wechsler intelligence test for matching the groups for IQ were used. To ensure validity, the content validity criteria depended tests calculated by the Lashe method and teachers' perspective were used. The reliability coefficient was obtained by the reliability coefficient of related tests; the percent agreement method and the obtained data were analyzed using one-way variance analysis and Shefe prosecution test. Results The results showed that there was a significant increase in academic achievement of students with intellectual disabilities when using token economy than using social reinforcements compared with the control group. Also, when using social reinforcements, the academic achievement of students was more than the control group. Conclusion Token economy and social reinforcements increased the academic achievement of students with intellectual disabilities in the science class; and also the effect of token economy reinforcements was more than social reinforcements on the subjects. PMID:22952517

Time evolution of a Gaussian class of quasi-distribution functions under quadratic Hamiltonian.

PubMed

Ginzburg, D; Mann, A

2014-03-10

A Lie algebraic method for propagation of the Wigner quasi-distribution function (QDF) under quadratic Hamiltonian was presented by Zoubi and Ben-Aryeh. We show that the same method can be used in order to propagate a rather general class of QDFs, which we call the "Gaussian class." This class contains as special cases the well-known Wigner, Husimi, Glauber, and Kirkwood-Rihaczek QDFs. We present some examples of the calculation of the time evolution of those functions.

Body build classes as a method for systematization of age-related anthropometric changes in girls aged 7-8 and 17-18 years.

PubMed

Kasmel, Jaan; Kaarma, Helje; Koskel, Säde; Tiit, Ene-Margit

2004-03-01

A total of 462 schoolgirls aged 7-8 and 17-18 years were examined anthropometrically (45 body measurements and 10 skinfolds) in a cross-sectional study. The data were processed in two age groups: 7-8-year-olds (n = 205) and 17-18-year-olds (n = 257). Relying on average height and weight in the groups, both groups were divided into five body build classes: small, medium, large, pyknomorphous and leptomorphous. In these classes, the differences in all other body measurements were compared, and in both age groups, analogous systematic differences were found in length, width and depth measurements and circumferences. This enabled us to compare proportional changes in body measurements during ten years, using for this ratios of averages of basic measurements and measurement groups in the same body build classes. Statistical analysis by the sign test revealed statistically significant differences between various body build classes in the growth of averages. Girls belonging to the small class differed from the girls of the large class by an essentially greater increase in their measurements. Our results suggest that the growth rate of body measurements of girls with different body build can be studied by the help of body build classification.

Static analysis of class invariants in Java programs

NASA Astrophysics Data System (ADS)

Bonilla-Quintero, Lidia Dionisia

2011-12-01

This paper presents a technique for the automatic inference of class invariants from Java bytecode. Class invariants are very important for both compiler optimization and as an aid to programmers in their efforts to reduce the number of software defects. We present the original DC-invariant analysis from Adam Webber, talk about its shortcomings and suggest several different ways to improve it. To apply the DC-invariant analysis to identify DC-invariant assertions, all that one needs is a monotonic method analysis function and a suitable assertion domain. The DC-invariant algorithm is very general; however, the method analysis can be highly tuned to the problem in hand. For example, one could choose shape analysis as the method analysis function and use the DC-invariant analysis to simply extend it to an analysis that would yield class-wide invariants describing the shapes of linked data structures. We have a prototype implementation: a system we refer to as "the analyzer" that infers DC-invariant unary and binary relations and provides them to the user in a human readable format. The analyzer uses those relations to identify unnecessary array bounds checks in Java programs and perform null-reference analysis. It uses Adam Webber's relational constraint technique for the class-invariant binary relations. Early results with the analyzer were very imprecise in the presence of "dirty-called" methods. A dirty-called method is one that is called, either directly or transitively, from any constructor of the class, or from any method of the class at a point at which a disciplined field has been altered. This result was unexpected and forced an extensive search for improved techniques. An important contribution of this paper is the suggestion of several ways to improve the results by changing the way dirty-called methods are handled. The new techniques expand the set of class invariants that can be inferred over Webber's original results. The technique that produces better results uses in-line analysis. Final results are promising: we can infer sound class invariants for full-scale, not just toy applications.

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences.

PubMed

Mizianty, Marcin J; Kurgan, Lukasz

2009-12-13

Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences. The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes. The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at http://biomine.ece.ualberta.ca/MODAS/.

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences

PubMed Central

2009-01-01

Background Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences. Results The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes. Conclusions The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at http://biomine.ece.ualberta.ca/MODAS/. PMID:20003388

A method for measuring different classes of human immunoglobulins specific for the penicilloyl group

PubMed Central

Wheeler, A. W.

1971-01-01

A method is described for the detection of human immunoglobulins of the four main classes specific for the penicilloyl group. The technique is an adaptation of the red cell linked antigen antiglobulin reaction based on the finding that benzyl penicilloylated rabbit γ-globulin, specific for human erythrocytes, reacted specifically with erythrocytes but did not agglutinate them. In turn this complex reacted specifically with human penicilloyl antibody and it was then possible to titrate each immunoglobulin class by the addition of anti-immunoglobulin sera. The method described here was used to compare titres of penicilloyl specific immunoglobulins of the same class between different sera. The test was found to be less sensitive than the hapten modified bacteriophage reduction test but had the advantage that individual immunoglobulin classes could be compared. In the absence of a reliable method for the diagnosis of pencillin allergy, it is hoped that the technique described will be a useful addition to existing in vivo and in vitro methods of determining the antibody response of the patient to the penicilloyl group. PMID:4105475

Fourier Transform Infrared Spectroscopic Studies Of Wheat In The Mid Infrared

NASA Astrophysics Data System (ADS)

Olinger, Jill M.; Griffiths, Peter R.

1989-12-01

Official grain standards of the United States state that wheat may be divided into seven classes which are: Durum, Red Durum, Hard Red Spring, Hard Red Winter, Soft Red Winter, White, and Mixed.1 Most end uses of wheat involve converting the grain into flour through one of a variety of grinding methods. The quality of wheat-based products is often very dependent upon the type or class of wheat which was used to make the flour. Pasta products, for example, are made almost exclusively from the flour of durum wheats, which are the hardest of the wheats listed above. The highest quality breads are produced using flour from wheats classed as hard, whereas cakes, cookies and pastries are considered best when flour from wheats classed as soft are used. It is obvious then that the capability of determining the class of a particular wheat, especially with respect to hardness, is of economic importance to growers, processors, and merchants of wheat and wheat products. Hardness has been measured in many different ways 2-5 but, as of yet, no one method has become the method of choice. This paper reports on the use of principal components analysis (PCA) of mid infrared diffuse reflectance (DR) spectra of diluted ground wheats to aid in the classification of those wheats with respect to their hardness. The theory and mathematics involved in a principal component analysis have been described elsewhere.9

Inquiring into Three Approaches to Hands-On Learning in Elementary and Secondary Science Methods Courses.

ERIC Educational Resources Information Center

Barnes, Marianne B.; Foley, Kathleen R.

1999-01-01

Investigates three approaches to hands-on science learning in two contexts, an elementary science methods class and a secondary science methods class. Focused on an activity on foam. Concludes that when developing models for teaching science methods courses, methods instructors need to share power with prospective teachers. (Author/MM)

Digitized Speech Characteristics in Patients with Maxillectomy Defects.

PubMed

Elbashti, Mahmoud E; Sumita, Yuka I; Hattori, Mariko; Aswehlee, Amel M; Taniguchi, Hisashi

2017-12-06

Accurate evaluation of speech characteristics through formant frequency measurement is important for proper speech rehabilitation in patients after maxillectomy. This study aimed to evaluate the utility of digital acoustic analysis and vowel pentagon space for the prediction of speech ability after maxillectomy, by comparing the acoustic characteristics of vowel articulation in three classes of maxillectomy defects. Aramany's classifications I, II, and IV were used to group 27 male patients after maxillectomy. Digital acoustic analysis of five Japanese vowels-/a/, /e/, /i/, /o/, and /u/-was performed using a speech analysis system. First formant (F1) and second formant (F2) frequencies were calculated using an autocorrelation method. Data were plotted on an F1-F2 plane for each patient, and the F1 and F2 ranges were calculated. The vowel pentagon spaces were also determined. One-way ANOVA was applied to compare all results between the three groups. Class II maxillectomy patients had a significantly higher F2 range than did Class I and Class IV patients (p = 0.002). In contrast, there was no significant difference in the F1 range between the three classes. The vowel pentagon spaces were significantly larger in class II maxillectomy patients than in Class I and Class IV patients (p = 0.014). The results of this study indicate that the acoustic characteristics of maxillectomy patients are affected by the defect area. This finding may provide information for obturator design based on vowel articulation and defect class. © 2017 by the American College of Prosthodontists.

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

The effect of social and token economy reinforcements on academic achievement of students with intellectual disabilities.

PubMed

Mirzamani, S Mahmood; Ashoori, Mohammad; Sereshki, Narges Adib

2011-01-01

This study investigates the effect of social and token economy reinforcements on academic achievement of 9th grade boy students with intellectual disabilities in an experimental science class in Tehran Province. The method used for this study was experimental by pre-test, post- test with a control group. The boy students with intellectual disabilities from three junior high schools participated in this study. The sample consisted of thirty, 9th grade boy students with intellectual disabilities in the selected schools; the schools were chosen by the multi-stage cluster method. To measure the progress of students in the science class, a teacher made test and the Wechsler intelligence test for matching the groups for IQ were used. To ensure validity, the content validity criteria depended tests calculated by the Lashe method and teachers' perspective were used. The reliability coefficient was obtained by the reliability coefficient of related tests; the percent agreement method and the obtained data were analyzed using one-way variance analysis and Shefe prosecution test. The results showed that there was a significant increase in academic achievement of students with intellectual disabilities when using token economy than using social reinforcements compared with the control group. Also, when using social reinforcements, the academic achievement of students was more than the control group. Token economy and social reinforcements increased the academic achievement of students with intellectual disabilities in the science class; and also the effect of token economy reinforcements was more than social reinforcements on the subjects.

Accessing and constructing driving data to develop fuel consumption forecast model

NASA Astrophysics Data System (ADS)

Yamashita, Rei-Jo; Yao, Hsiu-Hsen; Hung, Shih-Wei; Hackman, Acquah

2018-02-01

In this study, we develop a forecasting models, to estimate fuel consumption based on the driving behavior, in which vehicles and routes are known. First, the driving data are collected via telematics and OBDII. Then, the driving fuel consumption formula is used to calculate the estimate fuel consumption, and driving behavior indicators are generated for analysis. Based on statistical analysis method, the driving fuel consumption forecasting model is constructed. Some field experiment results were done in this study to generate hundreds of driving behavior indicators. Based on data mining approach, the Pearson coefficient correlation analysis is used to filter highly fuel consumption related DBIs. Only highly correlated DBI will be used in the model. These DBIs are divided into four classes: speed class, acceleration class, Left/Right/U-turn class and the other category. We then use K-means cluster analysis to group to the driver class and the route class. Finally, more than 12 aggregate models are generated by those highly correlated DBIs, using the neural network model and regression analysis. Based on Mean Absolute Percentage Error (MAPE) to evaluate from the developed AMs. The best MAPE values among these AM is below 5%.

A new iterative triclass thresholding technique in image segmentation.

PubMed

Cai, Hongmin; Yang, Zhong; Cao, Xinhua; Xia, Weiming; Xu, Xiaoyin

2014-03-01

We present a new method in image segmentation that is based on Otsu's method but iteratively searches for subregions of the image for segmentation, instead of treating the full image as a whole region for processing. The iterative method starts with Otsu's threshold and computes the mean values of the two classes as separated by the threshold. Based on the Otsu's threshold and the two mean values, the method separates the image into three classes instead of two as the standard Otsu's method does. The first two classes are determined as the foreground and background and they will not be processed further. The third class is denoted as a to-be-determined (TBD) region that is processed at next iteration. At the succeeding iteration, Otsu's method is applied on the TBD region to calculate a new threshold and two class means and the TBD region is again separated into three classes, namely, foreground, background, and a new TBD region, which by definition is smaller than the previous TBD regions. Then, the new TBD region is processed in the similar manner. The process stops when the Otsu's thresholds calculated between two iterations is less than a preset threshold. Then, all the intermediate foreground and background regions are, respectively, combined to create the final segmentation result. Tests on synthetic and real images showed that the new iterative method can achieve better performance than the standard Otsu's method in many challenging cases, such as identifying weak objects and revealing fine structures of complex objects while the added computational cost is minimal.

Evaluation of an urban traffic Noise-Exposed population based on points of interest and noise maps: The case of Guangzhou.

PubMed

Wang, Haibo; Chen, Hanjie; Cai, Ming

2018-08-01

The primary objective of this study was to develop an evaluation method for assessing an urban traffic noise-exposed population and apply it in the main urban area of Guangzhou. The method based on points of interest (POIs) and noise map is realized in several steps. First, after regionalizing based on road networks and executing a cluster analysis for regions according to the properties of POIs, the environmental noise functional regions (NFRs) of the urban area are presented. Then, surrounding POIs are used to infer the type of buildings, and according to the attraction of different building types and the whole population of the region, the population distribution at the building level is calculated. Finally, with the help of a noise map, an evaluation method for assessing an urban traffic noise-exposed population is proposed. The method is applied in the main urban area of Guangzhou, and the results reveal the followings. 1) At daytime and nighttime, 23.63% and 30.53% of the population, respectively, experience noise levels that exceed the noise standards. The per capita noise exposure value at daytime and nighttime is 0.9 dB and 2.0 dB, respectively. 2) The percentages of the exposed population of Yuexiu District were 28.89% at daytime and 35.65% at nighttime, which are the largest, followed by the exposed population percentages of Liwan, Haizhu, and Tianhe Districts. 3) From the view of different classes of NFRs, the percentages of the exposed population of Class 1 and Class 4 are larger than the percentages of the exposed population from the other classes, especially at nighttime (48.24% of Class 1 and 40.79% of Class 4). 4) Although there are masses of people affected by traffic noise, a large percentage of them (85%) experience not more than 5 dB of traffic noise superscale. Copyright © 2018 Elsevier Ltd. All rights reserved.

Semicompeting risks in aging research: methods, issues and needs

PubMed Central

Varadhan, Ravi; Xue, Qian-Li; Bandeen-Roche, Karen

2015-01-01

A semicompeting risks problem involves two-types of events: a nonterminal and a terminal event (death). Typically, the nonterminal event is the focus of the study, but the terminal event can preclude the occurrence of the nonterminal event. Semicompeting risks are ubiquitous in studies of aging. Examples of semicompeting risk dyads include: dementia and death, frailty syndrome and death, disability and death, and nursing home placement and death. Semicompeting risk models can be divided into two broad classes: models based only on observables quantities (class O) and those based on potential (latent) failure times (class L). The classical illness-death model belongs to class O. This model is a special case of the multistate models, which has been an active area of methodology development. During the past decade and a half, there has also been a flurry of methodological activity on semicompeting risks based on latent failure times (L models). These advances notwithstanding, the semi-competing risks methodology has not penetrated biomedical research, in general, and gerontological research, in particular. Some possible reasons for this lack of uptake are: the methods are relatively new and sophisticated, conceptual problems associated with potential failure time models are difficult to overcome, paucity of expository articles aimed at educating practitioners, and non-availability of readily usable software. The main goals of this review article are: (i) to describe the major types of semicompeting risks problems arising in aging research, (ii) to provide a brief survey of the semicompeting risks methods, (iii) to suggest appropriate methods for addressing the problems in aging research, (iv) to highlight areas where more work is needed, and (v) to suggest ways to facilitate the uptake of the semicompeting risks methodology by the broader biomedical research community. PMID:24729136

Application of Wavelet Transform for PDZ Domain Classification

PubMed Central

Daqrouq, Khaled; Alhmouz, Rami; Balamesh, Ahmed; Memic, Adnan

2015-01-01

PDZ domains have been identified as part of an array of signaling proteins that are often unrelated, except for the well-conserved structural PDZ domain they contain. These domains have been linked to many disease processes including common Avian influenza, as well as very rare conditions such as Fraser and Usher syndromes. Historically, based on the interactions and the nature of bonds they form, PDZ domains have most often been classified into one of three classes (class I, class II and others - class III), that is directly dependent on their binding partner. In this study, we report on three unique feature extraction approaches based on the bigram and trigram occurrence and existence rearrangements within the domain's primary amino acid sequences in assisting PDZ domain classification. Wavelet packet transform (WPT) and Shannon entropy denoted by wavelet entropy (WE) feature extraction methods were proposed. Using 115 unique human and mouse PDZ domains, the existence rearrangement approach yielded a high recognition rate (78.34%), which outperformed our occurrence rearrangements based method. The recognition rate was (81.41%) with validation technique. The method reported for PDZ domain classification from primary sequences proved to be an encouraging approach for obtaining consistent classification results. We anticipate that by increasing the database size, we can further improve feature extraction and correct classification. PMID:25860375

Impact of the 3-D model strategy on science learning of the solar system

NASA Astrophysics Data System (ADS)

Alharbi, Mohammed

The purpose of this mixed method study, quantitative and descriptive, was to determine whether the first-middle grade (seventh grade) students at Saudi schools are able to learn and use the Autodesk Maya software to interact and create their own 3-D models and animations and whether their use of the software influences their study habits and their understanding of the school subject matter. The study revealed that there is value to the science students regarding the use of 3-D software to create 3-D models to complete science assignments. Also, this study aimed to address the middle-school students' ability to learn 3-D software in art class, and then ultimately use it in their science class. The success of this study may open the way to consider the impact of 3-D modeling on other school subjects, such as mathematics, art, and geography. When the students start using graphic design, including 3-D software, at a young age, they tend to develop personal creativity and skills. The success of this study, if applied in schools, will provide the community with skillful young designers and increase awareness of graphic design and the new 3-D technology. Experimental method was used to answer the quantitative research question, are there significant differences applying the learning method using 3-D models (no 3-D, premade 3-D, and create 3-D) in a science class being taught about the solar system and its impact on the students' science achievement scores? Descriptive method was used to answer the qualitative research questions that are about the difficulty of learning and using Autodesk Maya software, time that students take to use the basic levels of Polygon and Animation parts of the Autodesk Maya software, and level of students' work quality.

Influence of pharyngeal airway respiration pressure on Class II mandibular retrusion in children: A computational fluid dynamics study of inspiration and expiration.

PubMed

Iwasaki, T; Sato, H; Suga, H; Takemoto, Y; Inada, E; Saitoh, I; Kakuno, K; Kanomi, R; Yamasaki, Y

2017-05-01

To examine the influence of negative pressure of the pharyngeal airway on mandibular retraction during inspiration in children with nasal obstruction using the computational fluid dynamics (CFD) method. Sixty-two children were divided into Classes I, II (mandibular retrusion) and III (mandibular protrusion) malocclusion groups. Cone-beam computed tomography data were used to reconstruct three-dimensional shapes of the nasal and pharyngeal airways. Airflow pressure was simulated using CFD to calculate nasal resistance and pharyngeal airway pressure during inspiration and expiration. Nasal resistance of the Class II group was significantly higher than that of the other two groups, and oropharyngeal airway inspiration pressure in the Class II (-247.64 Pa) group was larger than that in the Class I (-43.51 Pa) and Class III (-31.81 Pa) groups (P<.001). The oropharyngeal airway inspiration-expiration pressure difference in the Class II (-27.38 Pa) group was larger than that in the Class I (-5.17 Pa) and Class III (0.68 Pa) groups (P=.006). Large negative inspiratory pharyngeal airway pressure due to nasal obstruction in children with Class II malocclusion may be related to their retrognathia. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Tapping into Graduate Students' Collaborative Technology Experience in a Research Methods Class: Insights on Teaching Research Methods in a Malaysian and American Setting

ERIC Educational Resources Information Center

Vasquez-Colina, Maria D.; Maslin-Ostrowski, Pat; Baba, Suria

2017-01-01

This case study used qualitative and quantitative methods to investigate challenges of learning and teaching research methods by examining graduate students' use of collaborative technology (i.e., digital tools that enable collaboration and information seeking such as software and social media) and students' computer self-efficacy. We conducted…

Examining Preservice Teacher Belief Changes in the Context of Coordinated Mathematics Methods Coursework and Classroom Experiences

ERIC Educational Resources Information Center

Bahr, Damon; Monroe, Eula E.; Shaha, Steven H.

2013-01-01

The purpose of this study was to compare changes in beliefs of two groups of preservice teachers involved in two types of opportunities to immediately apply methods for teaching accompanying an elementary mathematics methods course. Students in one group applied the methods learned in class through weekly 30-minute peer-teaching sessions, while…

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

PubMed Central

Arshad, Sannia; Rho, Seungmin

2014-01-01

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

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

PubMed

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

2014-01-01

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

Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds.

PubMed

Cannon, Edward O; Amini, Ata; Bender, Andreas; Sternberg, Michael J E; Muggleton, Stephen H; Glen, Robert C; Mitchell, John B O

2007-05-01

We investigate the classification performance of circular fingerprints in combination with the Naive Bayes Classifier (MP2D), Inductive Logic Programming (ILP) and Support Vector Inductive Logic Programming (SVILP) on a standard molecular benchmark dataset comprising 11 activity classes and about 102,000 structures. The Naive Bayes Classifier treats features independently while ILP combines structural fragments, and then creates new features with higher predictive power. SVILP is a very recently presented method which adds a support vector machine after common ILP procedures. The performance of the methods is evaluated via a number of statistical measures, namely recall, specificity, precision, F-measure, Matthews Correlation Coefficient, area under the Receiver Operating Characteristic (ROC) curve and enrichment factor (EF). According to the F-measure, which takes both recall and precision into account, SVILP is for seven out of the 11 classes the superior method. The results show that the Bayes Classifier gives the best recall performance for eight of the 11 targets, but has a much lower precision, specificity and F-measure. The SVILP model on the other hand has the highest recall for only three of the 11 classes, but generally far superior specificity and precision. To evaluate the statistical significance of the SVILP superiority, we employ McNemar's test which shows that SVILP performs significantly (p < 5%) better than both other methods for six out of 11 activity classes, while being superior with less significance for three of the remaining classes. While previously the Bayes Classifier was shown to perform very well in molecular classification studies, these results suggest that SVILP is able to extract additional knowledge from the data, thus improving classification results further.

Analysis of Classes of Singular Steady State Reaction Diffusion Equations

NASA Astrophysics Data System (ADS)

Son, Byungjae

We study positive radial solutions to classes of steady state reaction diffusion problems on the exterior of a ball with both Dirichlet and nonlinear boundary conditions. We study both Laplacian as well as p-Laplacian problems with reaction terms that are p-sublinear at infinity. We consider both positone and semipositone reaction terms and establish existence, multiplicity and uniqueness results. Our existence and multiplicity results are achieved by a method of sub-supersolutions and uniqueness results via a combination of maximum principles, comparison principles, energy arguments and a-priori estimates. Our results significantly enhance the literature on p-sublinear positone and semipositone problems. Finally, we provide exact bifurcation curves for several one-dimensional problems. In the autonomous case, we extend and analyze a quadrature method, and in the nonautonomous case, we employ shooting methods. We use numerical solvers in Mathematica to generate the bifurcation curves.

Disability pension by occupational class - the impact of work-related factors: The Hordaland Health Study Cohort

PubMed Central

2011-01-01

Background The social gradient in disability pension is well recognized, however mechanisms accounting for the gradient are largely unknown. The aim of this study was to examine the association between occupational class and subsequent disability pension among middle-aged men and women, and to what extent work-related factors accounted for the association. Methods A subsample (N = 7031) of the population-based Hordaland Health Study (HUSK) conducted in 1997-99, provided self-reported information on health and work-related factors, and were grouped in four strata by Erikson, Goldthorpe and Portocareros occupational class scheme. The authors obtained follow-up data on disability pension by linking the health survey to national registries of benefit (FD-trygd). They employed Cox regression analysis and adjusted for gender, health (medical conditions, mental health, self-perceived health, somatic symptoms) and work-related factors (working hours, years in current occupation, physical demands, job demands, job control). Results A strong gradient in disability pension by occupational class was found. In the fully adjusted model the risk (hazard ratio) ranged from 1.41 (95% CI 0.84 to 2.33) in the routine non-manual class, 1.87 (95% CI 1.07 to 3.27) in the skilled manual class and 2.12 (95% CI 1.14 to 3.95) in the unskilled manual class, employing the administrator and professional class as reference. In the gender and health-adjusted model work-related factors mediated the impact of occupational class on subsequent disability pension with 5% in the routine non-manual class, 26% in the skilled manual class and 24% in the unskilled manual class. The impact of job control and physical demands was modest, and mainly seen among skilled and unskilled manual workers. Conclusions Workers in the skilled and unskilled manual classes had a substantial unexplained risk of disability pension. Work-related factors only had a moderate impact on the disability risk. Literature indicates an accumulation of hazards in the manual classes. This should be taken into account when interpreting the gradient in disability pension. PMID:21619716

Estudio comparativo de los metodos analitico-sintetico y global en el aprendizaje de la lectura (Comparative Study of the Analytical-Synthetical (Phonics) and Global (Sight) Reading Methods).

ERIC Educational Resources Information Center

Carbonell de Grompone, Maria A.; And Others

An investigation into the phonics and sight methods of reading instruction being taught in Uruguay schools seeks valid predictions in support of each approach. The study, written in Spanish, examines the progressive reading habits and abilities of 12 first-grade classes. Teachers assigned to teach each method uniformly had equivalent training and…

The Effect of a Modified Moore Method on Attitudes and Beliefs in Precalculus

ERIC Educational Resources Information Center

Bailey, Brad; Cooper, Thomas E.; Briggs, Karen S.

2012-01-01

As part of a study on the effects of teaching with a Modified Moore Method (MMM), a survey containing 20 items from Schoenfeld's (1989) investigation of attitudes and beliefs about mathematics was administered to students in undergraduate precalculus classes. The study included one section of precalculus taught with an MMM, a student-centered and…

Learning Financial Accounting in a Tertiary Institution of a Developing Country. An Investigation into Instructional Methods

ERIC Educational Resources Information Center

Abeysekera, Indra

2011-01-01

This study examines three instructional methods (traditional, interactive, and group case-based study), and student opinions on their preference for learning financial accounting in large classes at a metropolitan university in Sri Lanka. It analyses the results of a survey questionnaire of students, using quantitative techniques to determine the…

Establishing the Reliability and Validity of the ASSIST Questionnaire: A South African Sample Perspective

ERIC Educational Resources Information Center

Simelane-Mnisi, Sibongile; Mji, Andile

2017-01-01

Introduction: The Approaches and Study Skills Inventory for Students (ASSIST Short Version) was used to better understand the students' approaches to learning in a mathematics classes. Method: Quantitave method was used in this study. Participants were 345 first and second year mathematics students from a university in the Gauteng province of…

Developing Argumentation Ability as a Way to Promote Technological Literacy

ERIC Educational Resources Information Center

Choresh, Cilla; Mevarech, Zemira R.; Frank, Moti

2009-01-01

The main purpose of this study is to investigate the effects of three instructional methods on students' technological literacy (TL) and argumentation ability. Participants were 285 seventh grade Israeli boys and girls (12-13-year-old) who studied in 18 technology classes in four junior high schools. The three teaching methods were: (a) teaching…

Discriminative components of data.

PubMed

Peltonen, Jaakko; Kaski, Samuel

2005-01-01

A simple probabilistic model is introduced to generalize classical linear discriminant analysis (LDA) in finding components that are informative of or relevant for data classes. The components maximize the predictability of the class distribution which is asymptotically equivalent to 1) maximizing mutual information with the classes, and 2) finding principal components in the so-called learning or Fisher metrics. The Fisher metric measures only distances that are relevant to the classes, that is, distances that cause changes in the class distribution. The components have applications in data exploration, visualization, and dimensionality reduction. In empirical experiments, the method outperformed, in addition to more classical methods, a Renyi entropy-based alternative while having essentially equivalent computational cost.

The Influence of Circadian Type, Time of Day and Class Difficulty on Students' Grades

ERIC Educational Resources Information Center

McElroy, Todd; Mosteller, Lynn

2006-01-01

Introduction: In this paper we investigate how students' class grades are affected by individual differences in circadian rhythm, class time-of-day and class difficulty. Method: Using a sample of university students, we assessed morningness and eveningness personality type, and then obtained students recalled classes as well as their…

Getting Students to Read before Class: Innovation in a University in Chile

ERIC Educational Resources Information Center

McGinn, Noel F.; Schiefelbein, Ernesto

2015-01-01

Reading before class has been demonstrated to improve student learning. This article describes the installation and effectiveness of a strategy to encourage student class preparation. The strategy, called the Class-to-Class Method, has been implemented in a large private university in Chile. The university hopes that this innovation will reduce…

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

A cross-sectional survey to assess the effect of socioeconomic status on the oral hygiene habits

PubMed Central

Oberoi, Sukhvinder Singh; Sharma, Gaurav; Oberoi, Avneet

2016-01-01

Background: It is widely accepted that there are socioeconomic inequalities in oral health. A socioeconomic gradient is found in a range of clinical and self-reported oral health outcomes. Aim: The present study was conducted to assess the differences in oral hygiene practices among patients from different socioeconomic status (SES) visiting the Outpatient Department of the Sudha Rustagi College of Dental Sciences. Materials and Methods: A cross-sectional survey was conducted from June to October 2014 to assess the effect of SES on the oral hygiene habits. The questionnaire included the questions related to the demographic profile and assessment of the oral hygiene habits of the study population. Results: Toothbrush and toothpaste were being used significantly (P < 0.05) more by lower middle class (84.4%) and upper middle class (100.0%). A significantly higher frequency of cleaning teeth (twice a day) was reported among the lower middle class (17.2%) and upper middle class (21.5%). The majority (34.3%) of the study population changed their toothbrush once in 3 months. The cleaning of tongue was reported by patients belonging to the upper middle (62.0%), lower middle (52.1%), and upper lower class (30.0%). The use of tongue cleaner was reported to be significantly (P < 0.05) more among upper middle (10.1%) class patients. A significantly higher number of patients from the lower class (81.3%) never visited a dentist. Conclusion: The oral hygiene practices of the patients from upper and lower middle class was found to be satisfactory whereas it was poor among patients belonging to lower and upper lower class. PMID:29242690

Enhancing students' science literacy using solar cell learning multimedia containing science and nano technology

NASA Astrophysics Data System (ADS)

Eliyawati, Sunarya, Yayan; Mudzakir, Ahmad

2017-05-01

This research attempts to enhance students' science literacy in the aspects of students' science content, application context, process, and students' attitude using solar cell learning multimedia containing science and nano technology. The quasi-experimental method with pre-post test design was used to achieve these objectives. Seventy-two students of class XII at a high school were employed as research's subject. Thirty-six students were in control class and another thirty-six were in experiment class. Variance test (t-test) was performed on the average level of 95% to identify the differences of students' science literacy in both classes. As the result, there were significant different of learning outcomes between experiment class and control class. Almost half of students (41.67%) in experiment class are categorized as high. Therefore, the learning using solar cell learning multimedia can improve students' science literacy, especially in the students' science content, application context, and process aspects with n-gain(%) 59.19 (medium), 63.04 (medium), and 52.98 (medium). This study can be used to develop learning multimedia in other science context.

Pole-Like Street Furniture Decompostion in Mobile Laser Scanning Data

NASA Astrophysics Data System (ADS)

Li, F.; Oude Elberink, S.; Vosselman, G.

2016-06-01

Automatic semantic interpretation of street furniture has become a popular topic in recent years. Current studies detect street furniture as connected components of points above the street level. Street furniture classification based on properties of such components suffers from large intra class variability of shapes and cannot deal with mixed classes like traffic signs attached to light poles. In this paper, we focus on the decomposition of point clouds of pole-like street furniture. A novel street furniture decomposition method is proposed, which consists of three steps: (i) acquirement of prior-knowledge, (ii) pole extraction, (iii) components separation. For the pole extraction, a novel global pole extraction approach is proposed to handle 3 different cases of street furniture. In the evaluation of results, which involves the decomposition of 27 different instances of street furniture, we demonstrate that our method decomposes mixed classes street furniture into poles and different components with respect to different functionalities.

Novel trace chemical detection algorithms: a comparative study

NASA Astrophysics Data System (ADS)

Raz, Gil; Murphy, Cara; Georgan, Chelsea; Greenwood, Ross; Prasanth, R. K.; Myers, Travis; Goyal, Anish; Kelley, David; Wood, Derek; Kotidis, Petros

2017-05-01

Algorithms for standoff detection and estimation of trace chemicals in hyperspectral images in the IR band are a key component for a variety of applications relevant to law-enforcement and the intelligence communities. Performance of these methods is impacted by the spectral signature variability due to presence of contaminants, surface roughness, nonlinear dependence on abundances as well as operational limitations on the compute platforms. In this work we provide a comparative performance and complexity analysis of several classes of algorithms as a function of noise levels, error distribution, scene complexity, and spatial degrees of freedom. The algorithm classes we analyze and test include adaptive cosine estimator (ACE and modifications to it), compressive/sparse methods, Bayesian estimation, and machine learning. We explicitly call out the conditions under which each algorithm class is optimal or near optimal as well as their built-in limitations and failure modes.

The job content questionnaire in various occupational contexts: applying a latent class model.

PubMed

Santos, Kionna Oliveira Bernardes; Araújo, Tânia Maria de; Carvalho, Fernando Martins; Karasek, Robert

2017-05-17

To evaluate Job Content Questionnaire(JCQ) performance using the latent class model. We analysed cross-sectional studies conducted in Brazil and examined three occupational categories: petroleum industry workers (n=489), teachers (n=4392) and primary healthcare workers (3078)and 1552 urban workers from a representative sample of the city of Feira de Santana in Bahia, Brazil. An appropriate number of latent classes was extracted and described each occupational category using latent class analysis, a multivariate method that evaluates constructs and takes into accountthe latent characteristics underlying the structure of measurement scales. The conditional probabilities of workers belonging to each class were then analysed graphically. Initially, the latent class analysis extracted four classes corresponding to the four job types (active, passive, low strain and high strain) proposed by the Job-Strain model (JSM) and operationalised by the JCQ. However, after taking into consideration the adequacy criteria to evaluate the number of extracted classes, three classes (active, low strain and high strain) were extracted from the studies of urban workers and teachers and four classes (active, passive, low strain and high strain) from the study of primary healthcare and petroleum industry workers. The four job types proposed by the JSM were identified among primary healthcare and petroleum industry workers-groups with relatively high levels of skill discretion and decision authority. Three job types were identified for teachers and urban workers; however, passive job situations were not found within these groups. The latent class analysis enabled us to describe the conditional standard responses of the job types proposed by the model, particularly in relation to active jobs and high and low strain situations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A novel class sensitive hashing technique for large-scale content-based remote sensing image retrieval

NASA Astrophysics Data System (ADS)

Reato, Thomas; Demir, Begüm; Bruzzone, Lorenzo

2017-10-01

This paper presents a novel class sensitive hashing technique in the framework of large-scale content-based remote sensing (RS) image retrieval. The proposed technique aims at representing each image with multi-hash codes, each of which corresponds to a primitive (i.e., land cover class) present in the image. To this end, the proposed method consists of a three-steps algorithm. The first step is devoted to characterize each image by primitive class descriptors. These descriptors are obtained through a supervised approach, which initially extracts the image regions and their descriptors that are then associated with primitives present in the images. This step requires a set of annotated training regions to define primitive classes. A correspondence between the regions of an image and the primitive classes is built based on the probability of each primitive class to be present at each region. All the regions belonging to the specific primitive class with a probability higher than a given threshold are highly representative of that class. Thus, the average value of the descriptors of these regions is used to characterize that primitive. In the second step, the descriptors of primitive classes are transformed into multi-hash codes to represent each image. This is achieved by adapting the kernel-based supervised locality sensitive hashing method to multi-code hashing problems. The first two steps of the proposed technique, unlike the standard hashing methods, allow one to represent each image by a set of primitive class sensitive descriptors and their hash codes. Then, in the last step, the images in the archive that are very similar to a query image are retrieved based on a multi-hash-code-matching scheme. Experimental results obtained on an archive of aerial images confirm the effectiveness of the proposed technique in terms of retrieval accuracy when compared to the standard hashing methods.

Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach.

PubMed

Nielsen, Morten; Lundegaard, Claus; Worning, Peder; Hvid, Christina Sylvester; Lamberth, Kasper; Buus, Søren; Brunak, Søren; Lund, Ole

2004-06-12

Prediction of which peptides will bind a specific major histocompatibility complex (MHC) constitutes an important step in identifying potential T-cell epitopes suitable as vaccine candidates. MHC class II binding peptides have a broad length distribution complicating such predictions. Thus, identifying the correct alignment is a crucial part of identifying the core of an MHC class II binding motif. In this context, we wish to describe a novel Gibbs motif sampler method ideally suited for recognizing such weak sequence motifs. The method is based on the Gibbs sampling method, and it incorporates novel features optimized for the task of recognizing the binding motif of MHC classes I and II. The method locates the binding motif in a set of sequences and characterizes the motif in terms of a weight-matrix. Subsequently, the weight-matrix can be applied to identifying effectively potential MHC binding peptides and to guiding the process of rational vaccine design. We apply the motif sampler method to the complex problem of MHC class II binding. The input to the method is amino acid peptide sequences extracted from the public databases of SYFPEITHI and MHCPEP and known to bind to the MHC class II complex HLA-DR4(B1*0401). Prior identification of information-rich (anchor) positions in the binding motif is shown to improve the predictive performance of the Gibbs sampler. Similarly, a consensus solution obtained from an ensemble average over suboptimal solutions is shown to outperform the use of a single optimal solution. In a large-scale benchmark calculation, the performance is quantified using relative operating characteristics curve (ROC) plots and we make a detailed comparison of the performance with that of both the TEPITOPE method and a weight-matrix derived using the conventional alignment algorithm of ClustalW. The calculation demonstrates that the predictive performance of the Gibbs sampler is higher than that of ClustalW and in most cases also higher than that of the TEPITOPE method.

Evaluation of POE and instructor-led problem-solving approaches integrated into force and motion lecture classes using a model analysis technique

NASA Astrophysics Data System (ADS)

Rakkapao, S.; Pengpan, T.; Srikeaw, S.; Prasitpong, S.

2014-01-01

This study aims to investigate the use of the predict-observe-explain (POE) approach integrated into large lecture classes on forces and motion. It is compared to the instructor-led problem-solving method using model analysis. The samples are science (SC, N = 420) and engineering (EN, N = 434) freshmen, from Prince of Songkla University, Thailand. Research findings from the force and motion conceptual evaluation indicate that the multimedia-supported POE method promotes students’ learning better than the problem-solving method, in particular for the velocity and acceleration concepts. There is a small shift of the students’ model states after the problem-solving instruction. Moreover, by using model analysis instructors are able to investigate students’ misconceptions and evaluate teaching methods. It benefits instructors in organizing subsequent instructional materials.

Improved pan-specific MHC class I peptide-binding predictions using a novel representation of the MHC-binding cleft environment.

PubMed

Carrasco Pro, S; Zimic, M; Nielsen, M

2014-02-01

Major histocompatibility complex (MHC) molecules play a key role in cell-mediated immune responses presenting bounded peptides for recognition by the immune system cells. Several in silico methods have been developed to predict the binding affinity of a given peptide to a specific MHC molecule. One of the current state-of-the-art methods for MHC class I is NetMHCpan, which has a core ingredient for the representation of the MHC class I molecule using a pseudo-sequence representation of the binding cleft amino acid environment. New and large MHC-peptide-binding data sets are constantly being made available, and also new structures of MHC class I molecules with a bound peptide have been published. In order to test if the NetMHCpan method can be improved by integrating this novel information, we created new pseudo-sequence definitions for the MHC-binding cleft environment from sequence and structural analyses of different MHC data sets including human leukocyte antigen (HLA), non-human primates (chimpanzee, macaque and gorilla) and other animal alleles (cattle, mouse and swine). From these constructs, we showed that by focusing on MHC sequence positions found to be polymorphic across the MHC molecules used to train the method, the NetMHCpan method achieved a significant increase in the predictive performance, in particular, of non-human MHCs. This study hence showed that an improved performance of MHC-binding methods can be achieved not only by the accumulation of more MHC-peptide-binding data but also by a refined definition of the MHC-binding environment including information from non-human species. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Correlation and agreement between eplet mismatches calculated using serological, low-intermediate and high resolution molecular human leukocyte antigen typing methods

PubMed Central

Fidler, Samantha; D’Orsogna, Lloyd; Irish, Ashley B.; Lewis, Joshua R.; Wong, Germaine; Lim, Wai H.

2018-01-01

Structural human leukocyte antigen (HLA) matching at the eplet level can be identified by HLAMatchmaker, which requires the entry of four-digit alleles. The aim of this study was to evaluate the agreement between eplet mismatches calculated by serological and two-digit typing methods compared to high-resolution four-digit typing. In a cohort of 264 donor/recipient pairs, the evaluation of measurement error was assessed using intra-class correlation to confirm the absolute agreement between the number of eplet mismatches at class I (HLA-A, -B, C) and II loci (HLA-DQ and -DR) calculated using serological or two-digit molecular typing compared to four-digit molecular typing methods. The proportion of donor/recipient pairs with a difference of >5 eplet mismatches between the HLA typing methods was also determined. Intra-class correlation coefficients between serological and four-digit molecular typing methods were 0.969 (95% confidence intervals [95% CI] 0.960–0.975) and 0.926 (95% CI 0.899–0.944), respectively; and 0.995 (95% CI 0.994–0.996) and 0.993 (95% CI 0.991–0.995), respectively between two-digit and four-digit molecular typing methods. The proportion of donor/recipient pairs with a difference of >5 eplet mismatches at class I and II loci was 4% and 16% for serological versus four-digit molecular typing methods, and 0% and 2% for two-digit versus four-digit molecular typing methods, respectively. In this small predominantly Caucasian population, compared with serology, there is a high level of agreement in the number of eplet mismatches calculated using two-compared to four-digit molecular HLA-typing methods, suggesting that two-digit typing may be sufficient in determining eplet mismatch load in kidney transplantation. PMID:29568344

Improved Airport Noise Modeling for High Altitudes and Flexible Flight Operations

NASA Technical Reports Server (NTRS)

Forsyth, David W.; Follet, Jesse I.

2006-01-01

The FAA's Integrated Noise Model (INM) is widely used to estimate noise in the vicinity of airports. This study supports the development of standards by which the fleet data in the INM can be updated. A comparison of weather corrections to noise data using INM Spectral Classes is made with the Boeing integrated method. The INM spectral class method is shown to work well, capturing noise level differences due to weather especially at long distances. Two studies conducted at the Denver International Airport are included in the appendices. The two studies adopted different approaches to modeling flight operations at the airport. When compared to the original, year 2000, results, it is apparent that changes made to the INM in terms of modeling processes and databases have resulted in improved agreement between predicted and measured noise levels.

How Effective Is the Jigsaw Method when Used to Introduce New Science Curricula in Middle School Science?

ERIC Educational Resources Information Center

Dollard, Mark W.; Mahoney, Kate

2010-01-01

The purpose of this study was to determine the effects of the Jigsaw method, a cooperative learning tool, on content knowledge and attitude toward learning science. A group of 64 students in an 8th grade physical science class located in rural western New York participated in this study. As an intervention for this action research study, science…

Classification of independent components of EEG into multiple artifact classes.

PubMed

Frølich, Laura; Andersen, Tobias S; Mørup, Morten

2015-01-01

In this study, we aim to automatically identify multiple artifact types in EEG. We used multinomial regression to classify independent components of EEG data, selecting from 65 spatial, spectral, and temporal features of independent components using forward selection. The classifier identified neural and five nonneural types of components. Between subjects within studies, high classification performances were obtained. Between studies, however, classification was more difficult. For neural versus nonneural classifications, performance was on par with previous results obtained by others. We found that automatic separation of multiple artifact classes is possible with a small feature set. Our method can reduce manual workload and allow for the selective removal of artifact classes. Identifying artifacts during EEG recording may be used to instruct subjects to refrain from activity causing them. Copyright © 2014 Society for Psychophysiological Research.

Joint Geophysical Inversion With Multi-Objective Global Optimization Methods

NASA Astrophysics Data System (ADS)

Lelievre, P. G.; Bijani, R.; Farquharson, C. G.

2015-12-01

Pareto multi-objective global optimization (PMOGO) methods generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. Providing a suite of models, as opposed to a single model that minimizes a weighted sum of objectives, allows a more complete assessment of the possibilities and avoids the often difficult choice of how to weight each objective. We are applying PMOGO methods to three classes of inverse problems. The first class are standard mesh-based problems where the physical property values in each cell are treated as continuous variables. The second class of problems are also mesh-based but cells can only take discrete physical property values corresponding to known or assumed rock units. In the third class we consider a fundamentally different type of inversion in which a model comprises wireframe surfaces representing contacts between rock units; the physical properties of each rock unit remain fixed while the inversion controls the position of the contact surfaces via control nodes. This third class of problem is essentially a geometry inversion, which can be used to recover the unknown geometry of a target body or to investigate the viability of a proposed Earth model. Joint inversion is greatly simplified for the latter two problem classes because no additional mathematical coupling measure is required in the objective function. PMOGO methods can solve numerically complicated problems that could not be solved with standard descent-based local minimization methods. This includes the latter two classes of problems mentioned above. There are significant increases in the computational requirements when PMOGO methods are used but these can be ameliorated using parallelization and problem dimension reduction strategies.

The Scientific Method and Scientific Inquiry: Tensions in Teaching and Learning

ERIC Educational Resources Information Center

Tang, Xiaowei; Coffey, Janet E.; Elby, Andy; Levin, Daniel M.

2010-01-01

Typically, the scientific method in science classrooms takes the form of discrete, ordered steps meant to guide students' inquiry. In this paper, we examine how focusing on the scientific method as discrete steps affects students' inquiry and teachers' perceptions thereof. To do so, we study a ninth-grade environmental science class in which…

A Comparison of Competency-Based Instruction with Conventional Instruction in the Home Economics Classroom.

ERIC Educational Resources Information Center

Preston, Janet E.; Kunz, Margie H.

This study compared student learning in secondary consumer and homemaking foods classes using three different methods of teacher preparation. In Method 1, teachers were provided with lists of competencies and workshop training for using the competencies. In Method 2, teachers were provided with lists of competencies and no workshop training; and…

The Effectiveness of Programed Instruction Versus the Lecture-Discussion Method of Teaching Basic Metallurgical Concepts.

ERIC Educational Resources Information Center

Bockman, David Carl

The purpose of this study was to compare the conventional lecture-discussion method and an illustrated programed textbook method when teaching a unit of instruction on the basic concepts of metallurgy. The control group used a portion of a conventional textbook accompanied by lecture, chalkboard illustration, and class discussion. The experimental…

Exploring Students' Articulation of Value in a Social Research Methods Class: Towards a Phenomenography of Value Making

ERIC Educational Resources Information Center

Guglietti, Maria

2015-01-01

This study describes journalism students' value making of social research methods, such as sampling, data gathering strategies and quantitative and qualitative data analysis, by using a mixed-­method approach to analyze 260 written reflection assignments. In their reflections, 26 student participants assessed the value of their new knowledge of…

40 CFR 53.52 - Leak check test.

Code of Federal Regulations, 2014 CFR

2014-07-01

... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM 2.5 or PM 10-2.5 § 53.52... to include the facility, including components, instruments, operator controls, a written procedure...

Multi-class SVM model for fMRI-based classification and grading of liver fibrosis

NASA Astrophysics Data System (ADS)

Freiman, M.; Sela, Y.; Edrei, Y.; Pappo, O.; Joskowicz, L.; Abramovitch, R.

2010-03-01

We present a novel non-invasive automatic method for the classification and grading of liver fibrosis from fMRI maps based on hepatic hemodynamic changes. This method automatically creates a model for liver fibrosis grading based on training datasets. Our supervised learning method evaluates hepatic hemodynamics from an anatomical MRI image and three T2*-W fMRI signal intensity time-course scans acquired during the breathing of air, air-carbon dioxide, and carbogen. It constructs a statistical model of liver fibrosis from these fMRI scans using a binary-based one-against-all multi class Support Vector Machine (SVM) classifier. We evaluated the resulting classification model with the leave-one out technique and compared it to both full multi-class SVM and K-Nearest Neighbor (KNN) classifications. Our experimental study analyzed 57 slice sets from 13 mice, and yielded a 98.2% separation accuracy between healthy and low grade fibrotic subjects, and an overall accuracy of 84.2% for fibrosis grading. These results are better than the existing image-based methods which can only discriminate between healthy and high grade fibrosis subjects. With appropriate extensions, our method may be used for non-invasive classification and progression monitoring of liver fibrosis in human patients instead of more invasive approaches, such as biopsy or contrast-enhanced imaging.

Improvement of training set structure in fusion data cleaning using Time-Domain Global Similarity method

NASA Astrophysics Data System (ADS)

Liu, J.; Lan, T.; Qin, H.

2017-10-01

Traditional data cleaning identifies dirty data by classifying original data sequences, which is a class-imbalanced problem since the proportion of incorrect data is much less than the proportion of correct ones for most diagnostic systems in Magnetic Confinement Fusion (MCF) devices. When using machine learning algorithms to classify diagnostic data based on class-imbalanced training set, most classifiers are biased towards the major class and show very poor classification rates on the minor class. By transforming the direct classification problem about original data sequences into a classification problem about the physical similarity between data sequences, the class-balanced effect of Time-Domain Global Similarity (TDGS) method on training set structure is investigated in this paper. Meanwhile, the impact of improved training set structure on data cleaning performance of TDGS method is demonstrated with an application example in EAST POlarimetry-INTerferometry (POINT) system.

Study of Fuel Economy and Emission Reduction Methods for Marine and Locomotive Diesel Engines

DOT National Transportation Integrated Search

1975-09-01

This interim report presents the results of the first phase of a two-part program to investigate methods of improving fuel consumption and reducing exhaust emissions for in-service diesel engines used as prime movers in locomotives and several classe...

Project-Based Learning in Programmable Logic Controller

NASA Astrophysics Data System (ADS)

Seke, F. R.; Sumilat, J. M.; Kembuan, D. R. E.; Kewas, J. C.; Muchtar, H.; Ibrahim, N.

2018-02-01

Project-based learning is a learning method that uses project activities as the core of learning and requires student creativity in completing the project. The aims of this study is to investigate the influence of project-based learning methods on students with a high level of creativity in learning the Programmable Logic Controller (PLC). This study used experimental methods with experimental class and control class consisting of 24 students, with 12 students of high creativity and 12 students of low creativity. The application of project-based learning methods into the PLC courses combined with the level of student creativity enables the students to be directly involved in the work of the PLC project which gives them experience in utilizing PLCs for the benefit of the industry. Therefore, it’s concluded that project-based learning method is one of the superior learning methods to apply on highly creative students to PLC courses. This method can be used as an effort to improve student learning outcomes and student creativity as well as to educate prospective teachers to become reliable educators in theory and practice which will be tasked to create qualified human resources candidates in order to meet future industry needs.

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.

An analysis of the impact of three high school schedules on student achievement in advanced placement biology classes

NASA Astrophysics Data System (ADS)

Arons-Polan, Bonnie

This study examined the effect of three schedule types on student achievement in Advanced Placement Biology classes. AP Biology test scores from students on three types of full-year schedules were analyzed to assess the impact schedule type had on student achievement. The three schedules included the block and traditional schedules, and the rotating/hybrid, a blend of the former two schedules. The results indicated the variable most closely associated with success on the AP Biology exam was the length of experience the teachers had teaching the course, regardless of schedule type. Although significant differences were seen in mean AP Biology test scores among the three schedule types, this could be explained by the relationship between instructors' experience and schedule type. Regression analysis determined the two strongest predictors of successful performance on the AP Biology exam were instructors' experience and perceived teaching style, regardless of schedule type. It appears that the economically developed suburbs, had teachers with the largest amount of experience teaching AP Biology, and these teachers reported using a direct approach to teaching, using lecture greater than 50% of the time. The results of this study also suggest when restructuring to improve student achievement, educators should examine other variables in addition to the high school schedule. Restructuring the day to allow for longer classes must be accompanied by professional staff development to allow teachers to develop new teaching methods. Most of the teachers in the survey reported using lecture a great deal of the time, regardless of schedule type. Comments from the teachers from the various schedules revealed that the ability to add student centered, inquiry based activities and labs were dependent on adequate class time. No information on whether or not the teachers were given professional development to expand their repertoire of teaching methods when the school adopted a block or rotating hybrid schedule was obtained. Limitations to this study include the fact that there was no independent verification of teaching style as reported by the teachers in this study. This study involved only Advanced Placement Biology classes, so no generalizations can be made to other science classes.

Spatio-temporal evolutions of non-orthogonal equatorial wave modes derived from observations

NASA Astrophysics Data System (ADS)

Barton, Cory

Equatorial waves have been studied extensively due to their importance to the tropical climate and weather systems. Historically, their activity is diagnosed mainly in the wavenumber-frequency domain. Recently, many studies have projected observational data onto parabolic cylinder functions (PCFs), which represent the meridional structure of individual wave modes, to attain time-dependent spatial wave structures. The non-orthogonality of wave modes has yet posed a problem when attempting to separate data into wave fields where the waves project onto the same structure functions. We propose the development and application of a new methodology for equatorial wave expansion of instantaneous flows using the full equatorial wave spectrum. By creating a mapping from the meridional structure function amplitudes to the equatorial wave class amplitudes, we are able to diagnose instantaneous wave fields and determine their evolution. Because all meridional modes are shared by some subset of the wave classes, we require constraints on the wave class amplitudes to yield a closed system with a unique solution for all waves' spatial structures, including IG waves. A synthetic field is analyzed using this method to determine its accuracy for data of a single vertical mode. The wave class spectra diagnosed using this method successfully match the correct dispersion curves even if the incorrect depth is chosen for the spatial decomposition. In the case of more than one depth scale, waves with varying equivalent depth may be similarly identified using the dispersion curves. The primary vertical mode is the 200 m equivalent depth mode, which is that of the peak projection response. A distinct spectral power peak along the Kelvin wave dispersion curve for this value validates our choice of equivalent depth, although the possibility of depth varying with time and height is explored. The wave class spectra diagnosed assuming this depth scale mostly match their expected dispersion curves, showing that this method successfully partitions the wave spectra by calculating wave amplitudes in physical space. This is particularly striking because the time evolution, and therefore the frequency characteristics, is determined simply by a timeseries of independently-diagnosed instantaneous horizontal fields. We use the wave fields diagnosed by this method to study wave evolution in the context of the stratospheric QBO of zonal wind, confirming the continuous evolution of the selection mechanism for equatorial waves in the middle atmosphere. The amplitude cycle synchronized with the background zonal wind as predicted by QBO theory is present in the wave class fields even though the dynamics are not forced by the method itself. We have additionally identified a time-evolution of the zonal wavenumber spectrum responsible for the amplitude variability in physical space. Similar to the temporal characteristics, the vertical structures are also the result of a simple height cross-section through multiple independently-diagnosed levels.

Do Convolutional Neural Networks Learn Class Hierarchy?

PubMed

Bilal, Alsallakh; Jourabloo, Amin; Ye, Mao; Liu, Xiaoming; Ren, Liu

2018-01-01

Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.

Classes in Themselves and for Themselves: The Practice of Monitorial Education for Different Social Classes in Sweden, 1820-1843

ERIC Educational Resources Information Center

Larsson, Esbjörn

2016-01-01

This article investigates the monitorial system of education in Sweden between 1820 and 1843. In contrast to previous research, which has emphasised monitorial education as a method for disciplining poor children, this article compares the use of the method in schools for the working classes and in academic schools. Using concepts such as…

Keeping Goliath on His Toes: A Case-Discussion Method for Increasing Engagement and Individual Accountability in Large Classes

ERIC Educational Resources Information Center

Harding, Lora Mitchell

2018-01-01

Application-based assignments are often forgone in large marketing classes because of the daunting implementation and assessment challenges they present. One solution is to divide large classes into groups, but groups present their own challenges--of note, the potential for students to free-ride on the efforts of others. The 4Ps method of case…

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

Field study learning model to introduce environmental health problems to medical students at the faculty of medicine, University of Brawijaya, Malang, Indonesia

NASA Astrophysics Data System (ADS)

Zuhriyah, Lilik; Setijowati, Nanik; Andarini, Sri

2017-11-01

Some diseases in the community have a relationship with the environment. Therefore, medical students need to be exposed early to environmental problems in the community. The aim of this paper is to explain the role of field studies for medical students in introducing environmental health problems at an early stage. Field studies were applied by the Department of Public Health in 2005-2006 and 164 students from Semester II, which come from two classes, were required to join it. The portion score of the field study was 10%. Each class consisted of ten groups. Each group consisted of approximately eight students. Each group took different topics/targets of observation. These included ecological farming, household waste management, communal waste management, family medicine plants, food home industry, food street vendors, slaughterhouses, traditional markets, management of communal waste water, and recycling home industry. Each group observed in a community and interviewed related informants. Students were required to make a report and present it in their class. At the end of the exam, students were required to assess the benefit of this activity using a range of 1 (minimal) to 5 (maximal). The students considered the benefits of the field study method, giving an average score of 3.9 and 3.95 for presentation and discussion in class. Some students proposed to maintain field studies and discussion, and to conduct this method every semester with more time. Other students suggested that a lecturer accompany them in the field. Several students regretted unpunctual discussion time that reduced lecture time. The learning model of field study increased the students' interest in the subject of public health.

Existence, regularity, and concentration phenomenon of nontrivial solitary waves for a class of generalized variable coefficient Kadomtsev-Petviashvili equation

NASA Astrophysics Data System (ADS)

Alves, Claudianor O.; Miyagaki, Olímpio H.

2017-08-01

In this paper, we establish some results concerning the existence, regularity, and concentration phenomenon of nontrivial solitary waves for a class of generalized variable coefficient Kadomtsev-Petviashvili equation. Variational methods are used to get an existence result, as well as, to study the concentration phenomenon, while the regularity is more delicate because we are leading with functions in an anisotropic Sobolev space.

Contemporary clinical trials in ventricular tachycardia and fibrillation: implications of ESVEM, CASCADE, and CASH for clinical management.

PubMed

Anderson, J L

1995-10-01

Recent clinical trials in patients with ventricular tachycardia (VT) or fibrillation (VF) have occurred in the setting of the disappointing results of postinfarction secondary prevention studies using Class I antiarrhythmics (e.g., CAST). ESVEM addressed in a randomized trial whether electrophysiologic study (EPS) or Holter monitoring (HM) is a more accurate predictor of long-term antiarrhythmic drug efficacy in VT/VF patients (N=486) and what the relative efficacy of various antiarrhythmic agents is for VT/VF. Surprisingly, arrhythmia recurrence rates were not significantly different by the method of determining an efficacy prediction. However, arrhythmia recurrence and mortality were lower (by about 50% at 1 year) in patients treated with sotalol (a mixed Class II/III agent) than with other drugs (Class I). CASCADE evaluated empiric amiodarone versus guided (EPS or HM) standard (Class I) therapy in survivors of out-of-hospital cardiac arrest due to VF. The primary endpoint of cardiac death, resuscitated VF, or syncopal shock (in ICD patients) was reduced by amiodarone compared with conventional therapy (9% vs 23% at 1 year). An interim report of the ongoing CASH study suggested in 230 survivors of cardiac arrest that propafenone (Class IC) provided less effective prophylaxis (approximately 20% 1-year mortality) compared with randomly assigned therapies with amiodarone, metoprolol, or an ICD (approximately 14% mortality rates) and was excluded from further study. These studies have led to a paradigm shift in the approach to antiarrhythmic therapy of VT/VF: drugs with antisympathetic plus Class III (refractoriness prolonging) action (i.e., sotalol, amiodarone) are superior to traditional drugs with Class I( conduction slowing) effects, even when guided by EPS or HM.

OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets.

PubMed

García-Pedrajas, Nicolás; Perez-Rodríguez, Javier; de Haro-García, Aida

2013-02-01

In current research, an enormous amount of information is constantly being produced, which poses a challenge for data mining algorithms. Many of the problems in extremely active research areas, such as bioinformatics, security and intrusion detection, or text mining, share the following two features: large data sets and class-imbalanced distribution of samples. Although many methods have been proposed for dealing with class-imbalanced data sets, most of these methods are not scalable to the very large data sets common to those research fields. In this paper, we propose a new approach to dealing with the class-imbalance problem that is scalable to data sets with many millions of instances and hundreds of features. This proposal is based on the divide-and-conquer principle combined with application of the selection process to balanced subsets of the whole data set. This divide-and-conquer principle allows the execution of the algorithm in linear time. Furthermore, the proposed method is easy to implement using a parallel environment and can work without loading the whole data set into memory. Using 40 class-imbalanced medium-sized data sets, we will demonstrate our method's ability to improve the results of state-of-the-art instance selection methods for class-imbalanced data sets. Using three very large data sets, we will show the scalability of our proposal to millions of instances and hundreds of features.

The effectiveness of module based on guided inquiry method to improve students’ logical thinking ability

NASA Astrophysics Data System (ADS)

Ash-Shiddieqy, M. H.; Suparmi, A.; Sunarno, W.

2018-04-01

The purpose of this research is to understand the effectiveness of module based on guided inquiry method to improve students’ logical thinking ability. This research only evaluate the students’ logical ability after follows the learning activities that used developed physics module based on guided inquiry method. After the learning activities, students This research method uses a test instrument that adapts TOLT instrument. There are samples of 68 students of grade XI taken from SMA Negeri 4 Surakarta.Based on the results of the research can be seen that in the experimental class and control class, the posttest value aspect of probabilistic reasoning has the highest value than other aspects, whereas the posttest value of the proportional reasoning aspect has the lowest value. The average value of N-gain in the experimental class is 0.39, while in the control class is 0.30. Nevertheless, the N-gain values obtained in the experimental class are larger than the control class, so the guided inquiry-based module is considered more effective for improving students’ logical thinking. Based on the data obtained from the research shows the modules available to help teachers and students in learning activities. The developed Physics module is integrated with every syntax present in guided inquiry method, so it can be used to improve students’ logical thinking ability.

Post-boosting of classification boundary for imbalanced data using geometric mean.

PubMed

Du, Jie; Vong, Chi-Man; Pun, Chi-Man; Wong, Pak-Kin; Ip, Weng-Fai

2017-12-01

In this paper, a novel imbalance learning method for binary classes is proposed, named as Post-Boosting of classification boundary for Imbalanced data (PBI), which can significantly improve the performance of any trained neural networks (NN) classification boundary. The procedure of PBI simply consists of two steps: an (imbalanced) NN learning method is first applied to produce a classification boundary, which is then adjusted by PBI under the geometric mean (G-mean). For data imbalance, the geometric mean of the accuracies of both minority and majority classes is considered, that is statistically more suitable than the common metric accuracy. PBI also has the following advantages over traditional imbalance methods: (i) PBI can significantly improve the classification accuracy on minority class while improving or keeping that on majority class as well; (ii) PBI is suitable for large data even with high imbalance ratio (up to 0.001). For evaluation of (i), a new metric called Majority loss/Minority advance ratio (MMR) is proposed that evaluates the loss ratio of majority class to minority class. Experiments have been conducted for PBI and several imbalance learning methods over benchmark datasets of different sizes, different imbalance ratios, and different dimensionalities. By analyzing the experimental results, PBI is shown to outperform other imbalance learning methods on almost all datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of Effectiveness of Collaborative Learning Methods and Traditional Methods in Physics Classes at Northern Maine Technical College.

ERIC Educational Resources Information Center

Overlock, Terrence H., Sr.

To determine the effect of collaborative learning methods on the success rate of physics students at Northern Maine Technical College (NMTC), a study was undertaken to compare the mean final exam scores of a students in a physics course taught by traditional lecture/lab methods to those in a group taught by collaborative techniques. The…

The analytical transfer matrix method for PT-symmetric complex potential

NASA Astrophysics Data System (ADS)

Naceri, Leila; Hammou, Amine B.

2017-07-01

We have extended the analytical transfer matrix (ATM) method to solve quantum mechanical bound state problems with complex PT-symmetric potentials. Our work focuses on a class of models studied by Bender and Jones, we calculate the energy eigenvalues, discuss the critical values of g and compare the results with those obtained from other methods such as exact numerical computation and WKB approximation method.

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

PubMed

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

2013-01-01

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

Joint Feature Selection and Classification for Multilabel Learning.

PubMed

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

2018-03-01

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

Instructor and peer bullying in college students: Distinct typologies based on Latent Class Analysis.

PubMed

Marraccini, Marisa E; Brick, Leslie Ann D; Weyandt, Lisa L

2018-03-22

Although bullying is traditionally considered within the context of primary and secondary school, recent evidence suggests that bullying continues into college and workplace settings. Participants/Method: Latent class analysis (LCA) was employed to classify college bullying involvement typologies among 325 college students attending a northeastern university. Four classes concerning bullying involvement were revealed: Non-involved (36%); Instructor victim (30%); Peer bully-victim (22%); and Peer bully-victim/ Instructor victim (12%). Findings from this study, which classified college bullying experiences by incorporating both peer and instructor (teacher and professor) bullying, add substantially to the literature by providing insight into patterns of relatively unexplored bullying behaviors.

A COMPARISON OF TEACHING METHODS BUILDING CULTURAL COMPETENCY INFORMED BY CONTACT THEORY.

PubMed

Stough-Hunter, Anjel; Guinan, Jill; Hart, Julie P

2016-01-01

This study examines students' levels of cultural competency before and after taking three different semester-long courses dealing with diversity and cultural competence with each course representing a different teaching methodology. A new 20-item survey, designed for students across disciplines, was used to measure cultural competency among 226 students from the fall of2012 to the spring of2 015. Differences were examined between scores before and after taking each class, as well as differences between classes. There were significant improvements in all three groups, and a significant difference between two of the three classes in the improvement of scores.

Bamboo Classification Using WorldView-2 Imagery of Giant Panda Habitat in a Large Shaded Area in Wolong, Sichuan Province, China.

PubMed

Tang, Yunwei; Jing, Linhai; Li, Hui; Liu, Qingjie; Yan, Qi; Li, Xiuxia

2016-11-22

This study explores the ability of WorldView-2 (WV-2) imagery for bamboo mapping in a mountainous region in Sichuan Province, China. A large area of this place is covered by shadows in the image, and only a few sampled points derived were useful. In order to identify bamboos based on sparse training data, the sample size was expanded according to the reflectance of multispectral bands selected using the principal component analysis (PCA). Then, class separability based on the training data was calculated using a feature space optimization method to select the features for classification. Four regular object-based classification methods were applied based on both sets of training data. The results show that the k -nearest neighbor ( k -NN) method produced the greatest accuracy. A geostatistically-weighted k -NN classifier, accounting for the spatial correlation between classes, was then applied to further increase the accuracy. It achieved 82.65% and 93.10% of the producer's and user's accuracies respectively for the bamboo class. The canopy densities were estimated to explain the result. This study demonstrates that the WV-2 image can be used to identify small patches of understory bamboos given limited known samples, and the resulting bamboo distribution facilitates the assessments of the habitats of giant pandas.

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

Dynamic Restarting Schemes for Eigenvalue Problems

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

Wu, Kesheng; Simon, Horst D.

1999-03-10

In studies of restarted Davidson method, a dynamic thick-restart scheme was found to be excellent in improving the overall effectiveness of the eigen value method. This paper extends the study of the dynamic thick-restart scheme to the Lanczos method for symmetric eigen value problems and systematically explore a range of heuristics and strategies. We conduct a series of numerical tests to determine their relative strength and weakness on a class of electronic structure calculation problems.

Productive whole-class discussions: A qualitative analysis of peer leader behaviors in general chemistry

NASA Astrophysics Data System (ADS)

Eckart, Teresa Mcclain

The intention of this research was to describe behaviors and characteristics of General Chemistry I peer leaders using a pedagogical reform method referred to as Peer-led Guided Inquiry (PLGI), and to discuss the ways in which these peer leaders created productive whole-class discussions. This reform technique engaged students to work on guided inquiry activities while working cooperatively in small groups, led by undergraduate peer leaders. These sessions were video recorded and transcribed. The data was evaluated using grounded theory methods of analysis. This study examined the dialog between students and peer leaders, paying specific attention to question types and observed patterns of interactions. The research took shape by examining the kinds of questions asked by peer leaders and the purposes these questions served. In addition to looking at questions, different kinds of behaviors displayed by peer leaders during their small group sessions were also observed. A close examination of peer leader questions and behaviors aided in developing an answer to the overall research question regarding what factors are associated with productive whole-class discussions. Five major categories of peer leader behaviors evolved from the data and provided a means to compare and contrast productive whole-class discussions. While no category single-handedly determined if a discussion was good or bad, there was a tendency for peer leaders who exhibited positive traits in at least three of the following categories to have consistently better whole-class discussions: Procedural Practices, Supervisory Qualities, Questioning Techniques, Feedback/Responses, and Interpersonal Skills. Furthermore, each of the major categories is tied directly to Interpersonal, Communication, and Leadership skills and their interactions with each other. This study also addressed applications that each of these categories has on instructional practices and their need in peer leader training. In addition, a scale was developed for rating the relative effectiveness of whole-class discussions in terms of student participation. This study provides a tool for measuring productive whole-class discussions, as well as practical applications for peer leader (or teacher) training.

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

40 CFR 53.52 - Leak check test.

Code of Federal Regulations, 2011 CFR

2011-07-01

... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM2.5 or PM10â2.5 § 53.52... to include the facility, including components, instruments, operator controls, a written procedure...

40 CFR 53.52 - Leak check test.

Code of Federal Regulations, 2012 CFR

2012-07-01

... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM2.5 or PM10â2.5 § 53.52... to include the facility, including components, instruments, operator controls, a written procedure...

40 CFR 53.52 - Leak check test.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MONITORING REFERENCE AND EQUIVALENT METHODS Procedures for Testing Physical (Design) and Performance Characteristics of Reference Methods and Class I and Class II Equivalent Methods for PM2.5 or PM10â2.5 § 53.52... to include the facility, including components, instruments, operator controls, a written procedure...

Classification and global distribution of ocean precipitation types based on satellite passive microwave signatures

NASA Astrophysics Data System (ADS)

Gautam, Nitin

The main objectives of this thesis are to develop a robust statistical method for the classification of ocean precipitation based on physical properties to which the SSM/I is sensitive and to examine how these properties vary globally and seasonally. A two step approach is adopted for the classification of oceanic precipitation classes from multispectral SSM/I data: (1)we subjectively define precipitation classes using a priori information about the precipitating system and its possible distinct signature on SSM/I data such as scattering by ice particles aloft in the precipitating cloud, emission by liquid rain water below freezing level, the difference of polarization at 19 GHz-an indirect measure of optical depth, etc.; (2)we then develop an objective classification scheme which is found to reproduce the subjective classification with high accuracy. This hybrid strategy allows us to use the characteristics of the data to define and encode classes and helps retain the physical interpretation of classes. The classification methods based on k-nearest neighbor and neural network are developed to objectively classify six precipitation classes. It is found that the classification method based neural network yields high accuracy for all precipitation classes. An inversion method based on minimum variance approach was used to retrieve gross microphysical properties of these precipitation classes such as column integrated liquid water path, column integrated ice water path, and column integrated min water path. This classification method is then applied to 2 years (1991-92) of SSM/I data to examine and document the seasonal and global distribution of precipitation frequency corresponding to each of these objectively defined six classes. The characteristics of the distribution are found to be consistent with assumptions used in defining these six precipitation classes and also with well known climatological patterns of precipitation regions. The seasonal and global distribution of these six classes is also compared with the earlier results obtained from Comprehensive Ocean Atmosphere Data Sets (COADS). It is found that the gross pattern of the distributions obtained from SSM/I and COADS data match remarkably well with each other.

Relative Effects of Programmed Instruction and Demonstration Methods on Students' Academic Performance in Science

ERIC Educational Resources Information Center

Uhumuavbi, P. O.; Mamudu, J. A.

2009-01-01

This study compared the effects of Programmed Instruction and Demonstration methods on students academic performance in science in Esan West Local Government Area of Edo State. A sampling technique (balloting) was used in selecting two schools in Esan West local government area for the study. Two intact classes of fifty (50) students each from the…

Paul Revere Rides through High School Government Class: Teacher Research and the Power of Discussion to Motivate Thinking

ERIC Educational Resources Information Center

Newstreet, Carmen

2008-01-01

Teachers in the secondary social studies classroom do not regularly take the time to practice structured reflection on their teaching methods. In our current standards-driven environment, social studies classrooms are often not seen as places of higher learning. To combat these stereotypes, the author presents a method for accomplishing reflection…

An Introduction to the Work (and Play) of Writing Studies Research Methods through Micro Study

ERIC Educational Resources Information Center

Aiken, Suzan; Beard, Emily J.; McClure, David R. E.; Nickoson, Lee

2013-01-01

This article addresses the benefits and challenges involved with assigning small-scale research projects in one research methods class as means of introducing new(er) researchers to the work and rewards of empirical writing research. The following discussion does not claim to offer examples of cutting-edge methodological work. That is not our goal…

Studying the Effectiveness of Physical Education in the Secondary School (by the Example of Kazakhstan)

ERIC Educational Resources Information Center

Botagariyev, ?ulegen A.; Kubiyeva, Svetlana S.; Baizakova, Venera E.; Mambetov, Nurolla; Tulegenov, Yerkin K.; Aralbayev, Alpysbay S.; Kairgozhin, Dulat U.

2016-01-01

The purpose of this study was to determine the effectiveness of the existing model of teaching physical training in secondary schools and the analysis of a game like method introduced to improve physical fitness of students. The authors substantiated the use of a game like method during physical training classes, which implementation should create…

A Modified Content Analysis of Selected Secondary Reading Methods Textbooks: 1970-2008

ERIC Educational Resources Information Center

Hunt, Teresita Michele

2009-01-01

The purpose of this study was to examine how secondary teachers have been taught to teach reading-to-learn over the last four decades, and to teach the struggling and reluctant readers in their classes. In this study, twelve secondary reading methods textbooks were analyzed. The textbooks were chosen based on four criteria: (a) availability, (b)…

Career Barriers Perceived by Hard-of-Hearing Adolescents: Implications for Practice From a Mixed-Methods Study

ERIC Educational Resources Information Center

Punch, Renee; Creed, Peter A.; Hyde, Merv B.

2006-01-01

This study incorporated both quantitative and qualitative methods to examine the perception of career barriers by hard-of-hearing high school students being educated in regular classes with itinerant teacher support. Sixty-five students in Years 10, 11, and 12 completed a questionnaire about potential general and hearing-related barriers, and 12…

A Mixed Methods Analysis of the Effects of an Integrative Geobiological Study of Petrified Wood in Introductory College Geology Classrooms

ERIC Educational Resources Information Center

Clary, Renee M.; Wandersee, James H.

2007-01-01

Mixed methods research conducted across three semesters in introductory college geology classes (n=187, 190, 138) attempted to ascertain whether integrated study of petrified wood could serve as a portal to improved student geobiological understanding of fossilization, geologic time, and evolution. The Petrified Wood Survey[TM] was administered as…

A Study to Determine the Effectiveness of Letter Evaluation as a Learning Device in Business Correspondence Courses.

ERIC Educational Resources Information Center

Baker, William Henry

The purpose of this study was to determine whether a letter-evaluation method would be as effective as the traditional letter-writing method when applied in a college level business correspondence class. One hundred twenty-nine Brigham Young University students were divided into two experimental and two control groups, and categorized according to…

Can We Control Cheating in the Classroom?

ERIC Educational Resources Information Center

Kerkvliet, Joe; Sigmund, Charles L.

1999-01-01

Examines the determinants of class-specific academic cheating on examinations, class-to-class differences in the severity of the cheating problem across 12 principles of economics classes, whether control measures are effective, and the relative effectiveness of deterrent measures. Considers methods for gathering data on cheating. (CMK)

Hybrid teaching method for undergraduate student in Marine Geology class in Indonesia

NASA Astrophysics Data System (ADS)

Yusuf Awaluddin, M.; Yuliadi, Lintang

2016-04-01

Bridging Geosciences to the future generations in interesting and interactive ways are challenging for lecturers and teachers. In the past, one-way 'classic' face-to-face teaching method has been used as the only alternative for undergraduate's Marine Geology class in Padjadjaran University, Indonesia. Currently, internet users in Indonesia have been increased significantly, among of them are young generations and students. The advantage of the internet as a teaching method in Geosciences topic in Indonesia is still limited. Here we have combined between the classic and the online method for undergraduate teaching. The case study was in Marine Geology class, Padjadjaran University, with 70 students as participants and 2 instructors. We used Edmodo platform as a primary tool in our teaching and Dropbox as cloud storage. All online teaching activities such as assignment, quiz, discussion and examination were done in concert with the classic one with proportion 60% and 40% respectively. We found that the students had the different experience in this hybrid teaching method as shown in their feedback through this platform. This hybrid method offers interactive ways not only between the lecturers and the students but also among students. Classroom meeting is still needed to expose their work and for general discussion.Nevertheless, the only problem was the lack of internet access in the campus when all our students accessing the platform at the same time.

Using latent class analysis to model prescription medications in the measurement of falling among a community elderly population

PubMed Central

2013-01-01

Background Falls among the elderly are a major public health concern. Therefore, the possibility of a modeling technique which could better estimate fall probability is both timely and needed. Using biomedical, pharmacological and demographic variables as predictors, latent class analysis (LCA) is demonstrated as a tool for the prediction of falls among community dwelling elderly. Methods Using a retrospective data-set a two-step LCA modeling approach was employed. First, we looked for the optimal number of latent classes for the seven medical indicators, along with the patients’ prescription medication and three covariates (age, gender, and number of medications). Second, the appropriate latent class structure, with the covariates, were modeled on the distal outcome (fall/no fall). The default estimator was maximum likelihood with robust standard errors. The Pearson chi-square, likelihood ratio chi-square, BIC, Lo-Mendell-Rubin Adjusted Likelihood Ratio test and the bootstrap likelihood ratio test were used for model comparisons. Results A review of the model fit indices with covariates shows that a six-class solution was preferred. The predictive probability for latent classes ranged from 84% to 97%. Entropy, a measure of classification accuracy, was good at 90%. Specific prescription medications were found to strongly influence group membership. Conclusions In conclusion the LCA method was effective at finding relevant subgroups within a heterogenous at-risk population for falling. This study demonstrated that LCA offers researchers a valuable tool to model medical data. PMID:23705639

Usability of Computerized Lung Auscultation-Sound Software (CLASS) for learning pulmonary auscultation.

PubMed

Machado, Ana; Oliveira, Ana; Jácome, Cristina; Pereira, Marco; Moreira, José; Rodrigues, João; Aparício, José; Jesus, Luis M T; Marques, Alda

2018-04-01

The mastering of pulmonary auscultation requires complex acoustic skills. Computer-assisted learning tools (CALTs) have potential to enhance the learning of these skills; however, few have been developed for this purpose and do not integrate all the required features. Thus, this study aimed to assess the usability of a new CALT for learning pulmonary auscultation. Computerized Lung Auscultation-Sound Software (CLASS) usability was assessed by eight physiotherapy students using computer screen recordings, think-aloud reports, and facial expressions. Time spent in each task, frequency of messages and facial expressions, number of clicks and problems reported were counted. The timelines of the three methods used were matched/synchronized and analyzed. The tasks exercises and annotation of respiratory sounds were the ones requiring more clicks (median 132, interquartile range [23-157]; 93 [53-155]; 91 [65-104], respectively) and where most errors (19; 37; 15%, respectively) and problems (n = 7; 6; 3, respectively) were reported. Each participant reported a median of 6 problems, with a total of 14 different problems found, mainly related with CLASS functionalities (50%). Smile was the only facial expression presented in all tasks (n = 54). CLASS is the only CALT available that meets all the required features for learning pulmonary auscultation. The combination of the three usability methods identified advantages/disadvantages of CLASS and offered guidance for future developments, namely in annotations and exercises. This will allow the improvement of CLASS and enhance students' activities for learning pulmonary auscultation skills.

The Effect of STEM Learning through the Project of Designing Boat Model toward Student STEM Literacy

NASA Astrophysics Data System (ADS)

Tati, T.; Firman, H.; Riandi, R.

2017-09-01

STEM Learning focusses on development of STEM-literate society, the research about implementation of STEM learning to develope students’ STEM literacy is still limited. This study is aimed to examine the effect of implementation STEM learning through the project of designing boat model on students STEM literacy in energy topic. The method of this study was a quasi-experiment with non-randomized pretest-posttest control group design. There were two classes involved, the experiment class used Project Based Learning with STEM approach and control class used Project-Based Learning without STEM approach. A STEM Literacy test instrument was developed to measure students STEM literacy which consists of science literacy, mathematics literacy, and technology-engineering literacy. The analysis showed that there were significant differences on improvement science literacy, mathematics technology-engineering between experiment class and control class with effect size more than 0.8 (large effect). The difference of improvement of STEM literacy between experiment class and control class is caused by the existence of design engineering activity which required students to apply the knowledge from every field of STEM. The challenge that was faced in STEM learning through design engineering activity was how to give the students practice to integrate STEM field in solving the problems. In additional, most of the students gave positive response toward implementation of STEM learning through design boat model project.

Professionality, Preservice Teachers, and Twitter

ERIC Educational Resources Information Center

Gomez, Miguel; Journell, Wayne

2017-01-01

In this study, we explore how preservice teachers utilized Twitter during one middle grades social studies methods course. Specifically, we analyzed how various Twitter assignments--following specific accounts, weekly communication with class members, and participation in #sschats--contributed to either "restricted" or…

Cheetah paradigm revisited: MHC diversity in the world's largest free-ranging population.

PubMed

Castro-Prieto, Aines; Wachter, Bettina; Sommer, Simone

2011-04-01

For more than two decades, the cheetah (Acinonyx jubatus) has been considered a paradigm of disease vulnerability associated with low genetic diversity, particularly at the immune genes of the major histocompatibility complex (MHC). Cheetahs have been used as a classic example in numerous conservation genetics textbooks as well as in many related scientific publications. However, earlier studies used methods with low resolution to quantify MHC diversity and/or small sample sizes. Furthermore, high disease susceptibility was reported only for captive cheetahs, whereas free-ranging cheetahs show no signs of infectious diseases and a good general health status. We examined whether the diversity at MHC class I and class II-DRB loci in 149 Namibian cheetahs was higher than previously reported using single-strand conformation polymorphism analysis, cloning, and sequencing. MHC genes were examined at the genomic and transcriptomic levels. We detected ten MHC class I and four class II-DRB alleles, of which nine MHC class I and all class II-DRB alleles were expressed. Phylogenetic analyses and individual genotypes suggested that the alleles belong to four MHC class I and three class II-DRB putative loci. Evidence of positive selection was detected in both MHC loci. Our study indicated that the low number of MHC class I alleles previously observed in cheetahs was due to a smaller sample size examined. On the other hand, the low number of MHC class II-DRB alleles previously observed in cheetahs was further confirmed. Compared with other mammalian species including felids, cheetahs showed low levels of MHC diversity, but this does not seem to influence the immunocompetence of free-ranging cheetahs in Namibia and contradicts the previous conclusion that the cheetah is a paradigm species of disease vulnerability.

Argumentation in Science Class: Its Planning, Practice, and Effect on Student Motivation

NASA Astrophysics Data System (ADS)

Taneja, Anju

Studies have shown an association between argumentative discourse in science class, better understanding of science concepts, and improved academic performance. However, there is lack of research on how argumentation can increase student motivation. This mixed methods concurrent nested study uses Bandura's construct of motivation and concepts of argumentation and formative feedback to understand how teachers orchestrate argumentation in science class and how it affects motivation. Qualitative data was collected through interviews of 4 grade-9 science teachers and through observing teacher-directed classroom discourse. Classroom observations allowed the researcher to record the rhythm of discourse by characterizing teacher and student speech as teacher presentation (TP), teacher guided authoritative discussion (AD), teacher guided dialogic discussion (DD), and student initiation (SI). The Student Motivation Towards Science Learning survey was administered to 67 students before and after a class in which argumentation was used. Analysis of interviews showed teachers collaborated to plan argumentation. Analysis of discourse identified the characteristics of argumentation and provided evidence of students' engagement in argumentation in a range of contexts. Student motivation scores were tested using Wilcoxon signed rank tests and Mann-Whitney U-tests, which showed no significant change. However, one construct of motivation---active learning strategy---significantly increased. Quantitative findings also indicate that teachers' use of multiple methods in teaching science can affect various constructs of students' motivation. This study promotes social change by providing teachers with insight about how to engage all students in argumentation.

Virtual classroom helps medical education for both Chinese and foreign students.

PubMed

Shi, C; Wang, L; Li, X; Chai, S; Niu, W; Kong, Y; Zhou, W; Yin, W

2015-11-01

The rapid development of computer and internet technology has a strong influence over one's quality of education within different fields of study. To determine the potential benefits of introducing internet into medical school classes, a pilot study was conducted in three different Chinese medical schools. Seven hundred and eight medical school undergraduates, 385 dental school students and 366 foreign students were randomly recruited to complete a self-administered questionnaire. The contents included personal information, current usage of computer and internet, and attitudes towards the computerised teaching methods. Two forum groups were created using instant message software and were randomly assigned to two classes, allowing students to freely ask or discuss questions with the help of their teachers in these two virtual classrooms. All 1539 questionnaires were accepted and analysed. Although there were some differences between Chinese and foreign undergraduates, both group of students were highly proficient in internet usage and navigation. Overwhelmingly, 88.37% of the students owned a computer and frequently logged onto the internet. Most of them believed that the internet is a helpful adjunct to their studies and held positive attitudes towards computerised teaching. Compared to the classes that were not assigned internet forums, the two experimental classes performed significantly better on the examination. Our results suggest that computerised teaching methods have significant potential to assist in learning for both Chinese and foreign medical undergraduates. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.