Functional Analysis and Treatment of Aggression Maintained by Preferred Conversational Topics

ERIC Educational Resources Information Center

Roscoe, Eileen M.; Kindle, Arianne E.; Pence, Sacha T.

2010-01-01

After an initial functional analysis of a participant's aggression showed unclear outcomes, we conducted preference and reinforcer assessments to identify preferred forms of attention that may maintain problem behavior. Next, we conducted an extended functional analysis that included a modified attention condition. Results showed that the…

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

RELATIVE CONTRIBUTIONS OF THREE DESCRIPTIVE METHODS: IMPLICATIONS FOR BEHAVIORAL ASSESSMENT

PubMed Central

Pence, Sacha T; Roscoe, Eileen M; Bourret, Jason C; Ahearn, William H

2009-01-01

This study compared the outcomes of three descriptive analysis methods—the ABC method, the conditional probability method, and the conditional and background probability method—to each other and to the results obtained from functional analyses. Six individuals who had been diagnosed with developmental delays and exhibited problem behavior participated. Functional analyses indicated that participants' problem behavior was maintained by social positive reinforcement (n  =  2), social negative reinforcement (n  =  2), or automatic reinforcement (n  =  2). Results showed that for all but 1 participant, descriptive analysis outcomes were similar across methods. In addition, for all but 1 participant, the descriptive analysis outcome differed substantially from the functional analysis outcome. This supports the general finding that descriptive analysis is a poor means of determining functional relations. PMID:19949536

[The structural functional analysis of functioning of day-hospitals of the Russian Federation].

PubMed

2012-01-01

The article deals with the results of structural functional analysis of functioning of day-hospitals in the Russian Federation. The dynamic analysis is presented concerning day-hospitals' network, capacity; financial support, beds stock structure, treated patients structure, volumes of diagnostic tests and curative procedures. The need in developing of population medical care in conditions of day-hospitals is demonstrated.

Psychometric Properties on Lecturers' Beliefs on Teaching Function: Rasch Model Analysis

ERIC Educational Resources Information Center

Mofreh, Samah Ali Mohsen; Ghafar, Mohammed Najib Abdul; Omar, Abdul Hafiz Hj; Mosaku, Monsurat; Ma'ruf, Amar

2014-01-01

This paper focuses on the psychometric analysis of lecturers' beliefs on teaching function (LBTF) survey using Rasch Model analysis. The sample comprised 34 Community Colleges' lecturers. The Rasch Model is applied to produce specific measurements on the lecturers' beliefs on teaching function in order to generalize results and inferential…

Functional Analysis and Reduction of Inappropriate Spitting

ERIC Educational Resources Information Center

Carter, Stacy L.; Wheeler, John J.

2007-01-01

Functional analysis was used to determine the possible function of inappropriate spitting behavior of an adult woman who had been diagnosed with profound mental retardation. Results of an initial descriptive assessment indicated a possible attention function and led to an attention-based intervention, which was deemed ineffective at reducing the…

ACCEPTANCE OF FUNCTIONAL FOOD AMONG CHILEAN CONSUMERS: APPLE LEATHER.

PubMed

van Vliet, Maya; Adasme-Berrios, Cristian; Schnettler, Berta

2015-10-01

the aim of this study is to measure acceptance of a specific functional food: apple (fruit) leather, based on organoleptic characteristics and to identify consumer types and preferences for natural additives which increase the product's functionality and meet current nutritional needs. a sample of 800 consumers provided an evaluation of apple leather in terms of acceptance (liking). A sensorial panel was carried out using a 9-point hedonic scale. Cluster analysis was used to identify different acceptance-based consumer types. In addition, a conjoint analysis was carried out to determine preference for different additives. the cluster analysis resulted in four groups with significant differences in the average likings obtained from the sensory panel. Results indicate that the sweetness of the tested apple leather was evaluated best among all groups and, on average, color was rated as the worst attribute. However, overall likings differ significantly between groups. Results from the conjoint analysis indicate that, in general, consumers prefer natural additives included in the product which enhance functionality. although there is a "global acceptance" of the product, there are significant differences between groups. The results of the conjoint analysis indicate that, in general, consumers prefer the aggregation of natural additives which increase the product's functionality. Apple leather with natural additives, such as anticariogenics and antioxidants, can be considered a functional substitute of unhealthy snacks and/or sweets. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Use of Analog Functional Analysis in Assessing the Function of Mealtime Behavior Problems.

ERIC Educational Resources Information Center

Girolami, Peter A.; Scotti, Joseph R.

2001-01-01

This study applied the methodology of an analog experimental (functional) analysis of behavior to the specific interaction between parents and three children with mental retardation exhibiting food refusal and related mealtime problems. Analog results were highly consistent with other forms of functional assessment data, including interviews,…

Grey Matter Alterations Co-Localize with Functional Abnormalities in Developmental Dyslexia: An ALE Meta-Analysis

PubMed Central

Linkersdörfer, Janosch; Lonnemann, Jan; Lindberg, Sven; Hasselhorn, Marcus; Fiebach, Christian J.

2012-01-01

The neural correlates of developmental dyslexia have been investigated intensively over the last two decades and reliable evidence for a dysfunction of left-hemispheric reading systems in dyslexic readers has been found in functional neuroimaging studies. In addition, structural imaging studies using voxel-based morphometry (VBM) demonstrated grey matter reductions in dyslexics in several brain regions. To objectively assess the consistency of these findings, we performed activation likelihood estimation (ALE) meta-analysis on nine published VBM studies reporting 62 foci of grey matter reduction in dyslexic readers. We found six significant clusters of convergence in bilateral temporo-parietal and left occipito-temporal cortical regions and in the cerebellum bilaterally. To identify possible overlaps between structural and functional deviations in dyslexic readers, we conducted additional ALE meta-analyses of imaging studies reporting functional underactivations (125 foci from 24 studies) or overactivations (95 foci from 11 studies ) in dyslexics. Subsequent conjunction analyses revealed overlaps between the results of the VBM meta-analysis and the meta-analysis of functional underactivations in the fusiform and supramarginal gyri of the left hemisphere. An overlap between VBM results and the meta-analysis of functional overactivations was found in the left cerebellum. The results of our study provide evidence for consistent grey matter variations bilaterally in the dyslexic brain and substantial overlap of these structural variations with functional abnormalities in left hemispheric regions. PMID:22916214

A time-frequency analysis method to obtain stable estimates of magnetotelluric response function based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Cai, Jianhua

2017-05-01

The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.

Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

PubMed

Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

2012-06-08

Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

Functional Analyses and Treatment of Precursor Behavior

PubMed Central

Najdowski, Adel C; Wallace, Michele D; Ellsworth, Carrie L; MacAleese, Alicia N; Cleveland, Jackie M

2008-01-01

Functional analysis has been demonstrated to be an effective method to identify environmental variables that maintain problem behavior. However, there are cases when conducting functional analyses of severe problem behavior may be contraindicated. The current study applied functional analysis procedures to a class of behavior that preceded severe problem behavior (precursor behavior) and evaluated treatments based on the outcomes of the functional analyses of precursor behavior. Responding for all participants was differentiated during the functional analyses, and individualized treatments eliminated precursor behavior. These results suggest that functional analysis of precursor behavior may offer an alternative, indirect method to assess the operant function of severe problem behavior. PMID:18468282

Function Invariant and Parameter Scale-Free Transformation Methods

ERIC Educational Resources Information Center

Bentler, P. M.; Wingard, Joseph A.

1977-01-01

A scale-invariant simple structure function of previously studied function components for principal component analysis and factor analysis is defined. First and second partial derivatives are obtained, and Newton-Raphson iterations are utilized. The resulting solutions are locally optimal and subjectively pleasing. (Author/JKS)

Effects of computer-based training on procedural modifications to standard functional analyses.

PubMed

Schnell, Lauren K; Sidener, Tina M; DeBar, Ruth M; Vladescu, Jason C; Kahng, SungWoo

2018-01-01

Few studies have evaluated methods for training decision-making when functional analysis data are undifferentiated. The current study evaluated computer-based training to teach 20 graduate students to arrange functional analysis conditions, analyze functional analysis data, and implement procedural modifications. Participants were exposed to training materials using interactive software during a 1-day session. Following the training, mean scores on the posttest, novel cases probe, and maintenance probe increased for all participants. These results replicate previous findings during a 1-day session and include a measure of participant acceptability of the training. Recommendations for future research on computer-based training and functional analysis are discussed. © 2017 Society for the Experimental Analysis of Behavior.

Objective function analysis for electric soundings (VES), transient electromagnetic soundings (TEM) and joint inversion VES/TEM

NASA Astrophysics Data System (ADS)

Bortolozo, Cassiano Antonio; Bokhonok, Oleg; Porsani, Jorge Luís; Monteiro dos Santos, Fernando Acácio; Diogo, Liliana Alcazar; Slob, Evert

2017-11-01

Ambiguities in geophysical inversion results are always present. How these ambiguities appear in most cases open to interpretation. It is interesting to investigate ambiguities with regard to the parameters of the models under study. Residual Function Dispersion Map (RFDM) can be used to differentiate between global ambiguities and local minima in the objective function. We apply RFDM to Vertical Electrical Sounding (VES) and TEM Sounding inversion results. Through topographic analysis of the objective function we evaluate the advantages and limitations of electrical sounding data compared with TEM sounding data, and the benefits of joint inversion in comparison with the individual methods. The RFDM analysis proved to be a very interesting tool for understanding the joint inversion method of VES/TEM. Also the advantage of the applicability of the RFDM analyses in real data is explored in this paper to demonstrate not only how the objective function of real data behaves but the applicability of the RFDM approach in real cases. With the analysis of the results, it is possible to understand how the joint inversion can reduce the ambiguity of the methods.

Combining Multiobjective Optimization and Cluster Analysis to Study Vocal Fold Functional Morphology

PubMed Central

Palaparthi, Anil; Riede, Tobias

2017-01-01

Morphological design and the relationship between form and function have great influence on the functionality of a biological organ. However, the simultaneous investigation of morphological diversity and function is difficult in complex natural systems. We have developed a multiobjective optimization (MOO) approach in association with cluster analysis to study the form-function relation in vocal folds. An evolutionary algorithm (NSGA-II) was used to integrate MOO with an existing finite element model of the laryngeal sound source. Vocal fold morphology parameters served as decision variables and acoustic requirements (fundamental frequency, sound pressure level) as objective functions. A two-layer and a three-layer vocal fold configuration were explored to produce the targeted acoustic requirements. The mutation and crossover parameters of the NSGA-II algorithm were chosen to maximize a hypervolume indicator. The results were expressed using cluster analysis and were validated against a brute force method. Results from the MOO and the brute force approaches were comparable. The MOO approach demonstrated greater resolution in the exploration of the morphological space. In association with cluster analysis, MOO can efficiently explore vocal fold functional morphology. PMID:24771563

A Top Level Analysis of Training Management Functions.

ERIC Educational Resources Information Center

Ackerson, Jack

1995-01-01

Discusses how to conduct a top-level analysis of training management functions to identify problems within a training system resulting from rapid growth, the acquisition of new departments, or mergers. The data gathering process and analyses are explained, training management functions and activities are described, and root causes and solutions…

Classroom-Based Strategies to Incorporate Hypothesis Testing in Functional Behavior Assessments

ERIC Educational Resources Information Center

Lloyd, Blair P.; Weaver, Emily S.; Staubitz, Johanna L.

2017-01-01

When results of descriptive functional behavior assessments are unclear, hypothesis testing can help school teams understand how the classroom environment affects a student's challenging behavior. This article describes two hypothesis testing strategies that can be used in classroom settings: structural analysis and functional analysis. For each…

Functional analysis and treatment of problem behavior in early education classrooms.

PubMed

Greer, Brian D; Neidert, Pamela L; Dozier, Claudia L; Payne, Steven W; Zonneveld, Kimberley L M; Harper, Amy M

2013-01-01

We conducted functional analyses (FA) with 4 typically developing preschool children during ongoing classroom activities and evaluated treatments that were based on FA results. Results of each child's FA suggested social-positive reinforcement functions, and differential reinforcement of alternative behavior plus time-out was effective in decreasing problem behavior and increasing appropriate behavior. We discuss the utility of classroom-based FAs and potential compromises to experimental control. © Society for the Experimental Analysis of Behavior.

A statewide survey assessing practitioners' use and perceived utility of functional assessment.

PubMed

Roscoe, Eileen M; Phillips, Katurri M; Kelly, Maureen A; Farber, Rachel; Dube, William V

2015-12-01

The field of applied behavior analysis emphasizes the importance of conducting functional assessment before treatment development for problem behavior. There is, however, little information regarding the extent to which practitioners are using functional assessment in applied settings for individuals with developmental disabilities (DD). The purpose of the current study was to conduct a survey to assess the degree to which various types of functional assessment are implemented in agencies that serve individuals with DD in Massachusetts. Practitioners were asked to indicate their perception about and use of the various categories of functional assessment (e.g., indirect assessment, descriptive assessment, and functional analysis). From the 205 respondents who completed the survey, the most frequently used functional assessment was descriptive assessment. Results indicated that although the majority (67.8%) of practitioners believe functional analysis to be the most informative assessment tool for selecting behavioral treatment, only 34.6% of respondents indicated that they typically use functional analysis to inform the development of a behavior plan. © Society for the Experimental Analysis of Behavior.

Identification of BRCA1 missense substitutions that confer partial functional activity: potential moderate risk variants?

PubMed

Lovelock, Paul K; Spurdle, Amanda B; Mok, Myth T S; Farrugia, Daniel J; Lakhani, Sunil R; Healey, Sue; Arnold, Stephen; Buchanan, Daniel; Couch, Fergus J; Henderson, Beric R; Goldgar, David E; Tavtigian, Sean V; Chenevix-Trench, Georgia; Brown, Melissa A

2007-01-01

Many of the DNA sequence variants identified in the breast cancer susceptibility gene BRCA1 remain unclassified in terms of their potential pathogenicity. Both multifactorial likelihood analysis and functional approaches have been proposed as a means to elucidate likely clinical significance of such variants, but analysis of the comparative value of these methods for classifying all sequence variants has been limited. We have compared the results from multifactorial likelihood analysis with those from several functional analyses for the four BRCA1 sequence variants A1708E, G1738R, R1699Q, and A1708V. Our results show that multifactorial likelihood analysis, which incorporates sequence conservation, co-inheritance, segregation, and tumour immunohistochemical analysis, may improve classification of variants. For A1708E, previously shown to be functionally compromised, analysis of oestrogen receptor, cytokeratin 5/6, and cytokeratin 14 tumour expression data significantly strengthened the prediction of pathogenicity, giving a posterior probability of pathogenicity of 99%. For G1738R, shown to be functionally defective in this study, immunohistochemistry analysis confirmed previous findings of inconsistent 'BRCA1-like' phenotypes for the two tumours studied, and the posterior probability for this variant was 96%. The posterior probabilities of R1699Q and A1708V were 54% and 69%, respectively, only moderately suggestive of increased risk. Interestingly, results from functional analyses suggest that both of these variants have only partial functional activity. R1699Q was defective in foci formation in response to DNA damage and displayed intermediate transcriptional transactivation activity but showed no evidence for centrosome amplification. In contrast, A1708V displayed an intermediate transcriptional transactivation activity and a normal foci formation response in response to DNA damage but induced centrosome amplification. These data highlight the need for a range of functional studies to be performed in order to identify variants with partially compromised function. The results also raise the possibility that A1708V and R1699Q may be associated with a low or moderate risk of cancer. While data pooling strategies may provide more information for multifactorial analysis to improve the interpretation of the clinical significance of these variants, it is likely that the development of current multifactorial likelihood approaches and the consideration of alternative statistical approaches will be needed to determine whether these individually rare variants do confer a low or moderate risk of breast cancer.

A density difference based analysis of orbital-dependent exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Grabowski, Ireneusz; Teale, Andrew M.; Fabiano, Eduardo; Śmiga, Szymon; Buksztel, Adam; Della Sala, Fabio

2014-03-01

We present a density difference based analysis for a range of orbital-dependent Kohn-Sham functionals. Results for atoms, some members of the neon isoelectronic series and small molecules are reported and compared with ab initio wave function calculations. Particular attention is paid to the quality of approximations to the exchange-only optimised effective potential (OEP) approach: we consider both the localised Hartree-Fock as well as the Krieger-Li-Iafrate methods. Analysis of density differences at the exchange-only level reveals the impact of the approximations on the resulting electronic densities. These differences are further quantified in terms of the ground state energies, frontier orbital energy differences and highest occupied orbital energies obtained. At the correlated level, an OEP approach based on a perturbative second-order correlation energy expression is shown to deliver results comparable with those from traditional wave function approaches, making it suitable for use as a benchmark against which to compare standard density functional approximations.

Identification of BRCA1 missense substitutions that confer partial functional activity: potential moderate risk variants?

PubMed Central

Lovelock, Paul K; Spurdle, Amanda B; Mok, Myth TS; Farrugia, Daniel J; Lakhani, Sunil R; Healey, Sue; Arnold, Stephen; Buchanan, Daniel; Investigators, kConFab; Couch, Fergus J; Henderson, Beric R; Goldgar, David E; Tavtigian, Sean V; Chenevix-Trench, Georgia; Brown, Melissa A

2007-01-01

Introduction Many of the DNA sequence variants identified in the breast cancer susceptibility gene BRCA1 remain unclassified in terms of their potential pathogenicity. Both multifactorial likelihood analysis and functional approaches have been proposed as a means to elucidate likely clinical significance of such variants, but analysis of the comparative value of these methods for classifying all sequence variants has been limited. Methods We have compared the results from multifactorial likelihood analysis with those from several functional analyses for the four BRCA1 sequence variants A1708E, G1738R, R1699Q, and A1708V. Results Our results show that multifactorial likelihood analysis, which incorporates sequence conservation, co-inheritance, segregation, and tumour immunohistochemical analysis, may improve classification of variants. For A1708E, previously shown to be functionally compromised, analysis of oestrogen receptor, cytokeratin 5/6, and cytokeratin 14 tumour expression data significantly strengthened the prediction of pathogenicity, giving a posterior probability of pathogenicity of 99%. For G1738R, shown to be functionally defective in this study, immunohistochemistry analysis confirmed previous findings of inconsistent 'BRCA1-like' phenotypes for the two tumours studied, and the posterior probability for this variant was 96%. The posterior probabilities of R1699Q and A1708V were 54% and 69%, respectively, only moderately suggestive of increased risk. Interestingly, results from functional analyses suggest that both of these variants have only partial functional activity. R1699Q was defective in foci formation in response to DNA damage and displayed intermediate transcriptional transactivation activity but showed no evidence for centrosome amplification. In contrast, A1708V displayed an intermediate transcriptional transactivation activity and a normal foci formation response in response to DNA damage but induced centrosome amplification. Conclusion These data highlight the need for a range of functional studies to be performed in order to identify variants with partially compromised function. The results also raise the possibility that A1708V and R1699Q may be associated with a low or moderate risk of cancer. While data pooling strategies may provide more information for multifactorial analysis to improve the interpretation of the clinical significance of these variants, it is likely that the development of current multifactorial likelihood approaches and the consideration of alternative statistical approaches will be needed to determine whether these individually rare variants do confer a low or moderate risk of breast cancer. PMID:18036263

Crustal Structure Beneath Taiwan Using Frequency-band Inversion of Receiver Function Waveforms

NASA Astrophysics Data System (ADS)

Tomfohrde, D. A.; Nowack, R. L.

Receiver function analysis is used to determine local crustal structure beneath Taiwan. We have performed preliminary data processing and polarization analysis for the selection of stations and events and to increase overall data quality. Receiver function analysis is then applied to data from the Taiwan Seismic Network to obtain radial and transverse receiver functions. Due to the limited azimuthal coverage, only the radial receiver functions are analyzed in terms of horizontally layered crustal structure for each station. In order to improve convergence of the receiver function inversion, frequency-band inversion (FBI) is implemented, in which an iterative inversion procedure with sequentially higher low-pass corner frequencies is used to stabilize the waveform inversion. Frequency-band inversion is applied to receiver functions at six stations of the Taiwan Seismic Network. Initial 20-layer crustal models are inverted for using prior tomographic results for the initial models. The resulting 20-1ayer models are then simplified to 4 to 5 layer models and input into an alternating depth and velocity frequency-band inversion. For the six stations investigated, the resulting simplified models provide an average estimate of 38 km for the Moho thickness surrounding the Central Range of Taiwan. Also, the individual station estimates compare well with the recent tomographic model of and the refraction results of Rau and Wu (1995) and the refraction results of Ma and Song (1997).

A Comparative Study of Definitions on Limit and Continuity of Functions

ERIC Educational Resources Information Center

Shipman, Barbara A.

2012-01-01

Differences in definitions of limit and continuity of functions as treated in courses on calculus and in rigorous undergraduate analysis yield contradictory outcomes and unexpected language. There are results about limits in calculus that are false by the definitions of analysis, functions not continuous by one definition and continuous by…

Functional Analysis of Episodic Self-Injury Correlated with Recurrent Otitis Media.

ERIC Educational Resources Information Center

O'Reilly, Mark F.

1997-01-01

A functional analysis examined the consequences that maintained episodic self-injury and the relationship between those consequences and otitis media for a 26-month-old child with developmental disabilities. Results indicated that self-injury occurred only during periods of otitis media and may have served as a sensory escape function. (Author/CR)

Impact of ontology evolution on functional analyses.

PubMed

Groß, Anika; Hartung, Michael; Prüfer, Kay; Kelso, Janet; Rahm, Erhard

2012-10-15

Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes. Our results show that past changes in the GO are non-uniformly distributed over different branches of the ontology. Considering the semantic relatedness of significant categories in analysis results allows a more realistic stability assessment for functional enrichment studies. We observe that the results of term-enrichment analyses tend to be surprisingly stable despite changes in ontology and annotation.

FUNCTIONAL ANALYSIS AND TREATMENT OF COPROPHAGIA

PubMed Central

Ing, Anna D; Roane, Henry S; Veenstra, Rebecca A

2011-01-01

In the current investigation, functional analysis results suggested that coprophagia, the ingestion of fecal matter, was maintained by automatic reinforcement. Providing noncontingent access to alternative stimuli decreased coprophagia, and the intervention was generalized to two settings. PMID:21541128

Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

NASA Astrophysics Data System (ADS)

Curceac, S.; Ternynck, C.; Ouarda, T.

2015-12-01

Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation, volume 2, part 1. Appendix A: Software documentation

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Fermelia, A. J.; Haley, D. C.; Gremban, K. D.; Vanbaalen, J.; Walsh, R. W.

1982-01-01

Documentation of the preliminary software developed as a framework for a generalized integrated robotic system simulation is presented. The program structure is composed of three major functions controlled by a program executive. The three major functions are: system definition, analysis tools, and post processing. The system definition function handles user input of system parameters and definition of the manipulator configuration. The analysis tools function handles the computational requirements of the program. The post processing function allows for more detailed study of the results of analysis tool function executions. Also documented is the manipulator joint model software to be used as the basis of the manipulator simulation which will be part of the analysis tools capability.

Use of a latency-based demand assessment to identify potential demands for functional analyses.

PubMed

Call, Nathan A; Miller, Sarah J; Mintz, Joslyn Cynkus; Mevers, Joanna Lomas; Scheithauer, Mindy C; Eshelman, Julie E; Beavers, Gracie A

2016-12-01

Unlike potential tangible positive reinforcers, which are typically identified for inclusion in functional analyses empirically using preference assessments, demands are most often selected arbitrarily or based on caregiver report. The present study evaluated the use of a demand assessment with 12 participants who exhibited escape-maintained problem behavior. Participants were exposed to 10 demands, with aversiveness measured by average latency to the first instance of problem behavior. In subsequent functional analyses, results of a demand condition that included the demand with the shortest latency to problem behavior resulted in identification of an escape function for 11 of the participants. In contrast, a demand condition that included the demand with the longest latency resulted in identification of an escape function for only 5 participants. The implication of these findings is that for the remaining 7 participants, selection of the demand for the functional analysis without using the results of the demand assessment could have produced a false-negative finding. © 2016 Society for the Experimental Analysis of Behavior.

Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

PubMed Central

Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

2014-01-01

The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

On spectral techniques in analysis of Boolean networks

NASA Astrophysics Data System (ADS)

Kesseli, Juha; Rämö, Pauli; Yli-Harja, Olli

2005-06-01

In this work we present results that can be used for analysis of Boolean networks. The results utilize Fourier spectra of the functions in the network. An accurate formula is given for Derrida plots of networks of finite size N based on a result on Boolean functions presented in another context. Derrida plots are widely used to examine the stability issues of Boolean networks. For the limit N→∞, we give a computationally simple form that can be used as a good approximation for rather small networks as well. A formula for Derrida plots of random Boolean networks (RBNs) presented earlier in the literature is given an alternative derivation. It is shown that the information contained in the Derrida plot is equal to the average Fourier spectrum of the functions in the network. In the case of random networks the mean Derrida plot can be obtained from the mean spectrum of the functions. The method is applied to real data by using the Boolean functions found in genetic regulatory networks of eukaryotic cells in an earlier study. Conventionally, Derrida plots and stability analysis have been computed with statistical sampling resulting in poorer accuracy.

INFANT SIGN TRAINING AND FUNCTIONAL ANALYSIS

PubMed Central

Normand, Matthew P; Machado, Mychal A; Hustyi, Kristin M; Morley, Allison J

2011-01-01

We taught manual signs to typically developing infants using a reversal design and caregiver-nominated stimuli. We delivered the stimuli on a time-based schedule during baseline. During the intervention, we used progressive prompting and reinforcement, described by Thompson et al. (2004, 2007), to establish mands. Following sign training, we conducted functional analyses and verified that the signs functioned as mands. These results provide preliminary validation for the verbal behavior functional analysis methodology and further evidence of the functional independence of verbal operants. PMID:21709786

Neurophysiological analysis of echolocation in bats

NASA Technical Reports Server (NTRS)

Suga, N.

1972-01-01

An analysis of echolocation and signal processing in brown bats is presented. Data cover echo detection, echo ranging, echolocalization, and echo analysis. Efforts were also made to identify the part of the brain that carries out the most essential processing function for echolocation. Results indicate the inferior colliculus and the auditory nuclei function together to process this information.

Functional Analysis and Treatment of Problem Behavior in Early Education Classrooms

ERIC Educational Resources Information Center

Greer, Brian D.; Neidert, Pamela L.; Dozier, Claudia L.; Payne, Steven W.; Zonneveld, Kimberley L. M.; Harper, Amy M.

2013-01-01

We conducted functional analyses (FA) with 4 typically developing preschool children during ongoing classroom activities and evaluated treatments that were based on FA results. Results of each child's FA suggested social-positive reinforcement functions, and differential reinforcement of alternative behavior plus time-out was effective in…

Long-Term Exposure to Primary Traffic Pollutants and Lung Function in Children: Cross-Sectional Study and Meta-Analysis.

PubMed

Barone-Adesi, Francesco; Dent, Jennifer E; Dajnak, David; Beevers, Sean; Anderson, H Ross; Kelly, Frank J; Cook, Derek G; Whincup, Peter H

2015-01-01

There is widespread concern about the possible health effects of traffic-related air pollution. Nitrogen dioxide (NO2) is a convenient marker of primary pollution. We investigated the associations between lung function and current residential exposure to a range of air pollutants (particularly NO2, NO, NOx and particulate matter) in London children. Moreover, we placed the results for NO2 in context with a meta-analysis of published estimates of the association. Associations between primary traffic pollutants and lung function were investigated in 4884 children aged 9-10 years who participated in the Child Heart and Health Study in England (CHASE). A systematic literature search identified 13 studies eligible for inclusion in a meta-analysis. We combined results from the meta-analysis with the distribution of the values of FEV1 in CHASE to estimate the prevalence of children with abnormal lung function (FEV1<80% of predicted value) expected under different scenarios of NO2 exposure. In CHASE, there were non-significant inverse associations between all pollutants except ozone and both FEV1 and FVC. In the meta-analysis, a 10 μg/m3 increase in NO2 was associated with an 8 ml lower FEV1 (95% CI: -14 to -1 ml; p: 0.016). The observed effect was not modified by a reported asthma diagnosis. On the basis of these results, a 10 μg/m3 increase in NO2 level would translate into a 7% (95% CI: 4% to 12%) increase of the prevalence of children with abnormal lung function. Exposure to traffic pollution may cause a small overall reduction in lung function and increase the prevalence of children with clinically relevant declines in lung function.

OBSERVER RATING VERSUS THREE-DIMENSIONAL MOTION ANALYSIS OF LOWER EXTREMITY KINEMATICS DURING FUNCTIONAL SCREENING TESTS: A SYSTEMATIC REVIEW.

PubMed

Maclachlan, Liam; White, Steven G; Reid, Duncan

2015-08-01

Functional assessments are conducted in both clinical and athletic settings in an attempt to identify those individuals who exhibit movement patterns that may increase their risk of non-contact injury. In place of highly sophisticated three-dimensional motion analysis, functional testing can be completed through observation. To evaluate the validity of movement observation assessments by summarizing the results of articles comparing human observation in real-time or video play-back and three-dimensional motion analysis of lower extremity kinematics during functional screening tests. Systematic review. A computerized systematic search was conducted through Medline, SPORTSdiscus, Scopus, Cinhal, and Cochrane health databases between February and April of 2014. Validity studies comparing human observation (real-time or video play-back) to three-dimensional motion analysis of functional tasks were selected. Only studies comprising uninjured, healthy subjects conducting lower extremity functional assessments were appropriate for review. Eligible observers were certified health practitioners or qualified members of sports and athletic training teams that conduct athlete screening. The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to appraise the literature. Results are presented in terms of functional tasks. Six studies met the inclusion criteria. Across these studies, two-legged squats, single-leg squats, drop-jumps, and running and cutting manoeuvres were the functional tasks analysed. When compared to three-dimensional motion analysis, observer ratings of lower extremity kinematics, such as knee position in relation to the foot, demonstrated mixed results. Single-leg squats achieved target sensitivity values (≥ 80%) but not specificity values (≥ 50%>%). Drop-jump task agreement ranged from poor (< 50%) to excellent (> 80%). Two-legged squats achieved 88% sensitivity and 85% specificity. Mean underestimations as large as 198 (peak knee flexion) were found in the results of those assessing running and side-step cutting manoeuvres. Variables such as the speed of movement, the methods of rating, the profiles of participants and the experience levels of observers may have influenced the outcomes of functional testing. The small number of studies used limits generalizability. Furthermore, this review used two dimensional video-playback for the majority of observations. If the movements had been rated in real-time three dimensional video, the results may have been different. Slower, speed controlled movements using dichotomous ratings reach target sensitivity and demonstrate higher overall levels of agreement. As a result, their utilization in functional screening is advocated. 1A.

Trade-Off Analysis between Concerns Based on Aspect-Oriented Requirements Engineering

NASA Astrophysics Data System (ADS)

Laurito, Abelyn Methanie R.; Takada, Shingo

The identification of functional and non-functional concerns is an important activity during requirements analysis. However, there may be conflicts between the identified concerns, and they must be discovered and resolved through trade-off analysis. Aspect-Oriented Requirements Engineering (AORE) has trade-off analysis as one of its goals, but most AORE approaches do not actually offer support for trade-off analysis; they focus on describing concerns and generating their composition. This paper proposes an approach for trade-off analysis based on AORE using use cases and the Requirements Conflict Matrix (RCM) to represent compositions. RCM shows the positive or negative effect of non-functional concerns over use cases and other non-functional concerns. Our approach is implemented within a tool called E-UCEd (Extended Use Case Editor). We also show the results of evaluating our tool.

Analysis of Online Composite Mirror Descent Algorithm.

PubMed

Lei, Yunwen; Zhou, Ding-Xuan

2017-03-01

We study the convergence of the online composite mirror descent algorithm, which involves a mirror map to reflect the geometry of the data and a convex objective function consisting of a loss and a regularizer possibly inducing sparsity. Our error analysis provides convergence rates in terms of properties of the strongly convex differentiable mirror map and the objective function. For a class of objective functions with Hölder continuous gradients, the convergence rates of the excess (regularized) risk under polynomially decaying step sizes have the order [Formula: see text] after [Formula: see text] iterates. Our results improve the existing error analysis for the online composite mirror descent algorithm by avoiding averaging and removing boundedness assumptions, and they sharpen the existing convergence rates of the last iterate for online gradient descent without any boundedness assumptions. Our methodology mainly depends on a novel error decomposition in terms of an excess Bregman distance, refined analysis of self-bounding properties of the objective function, and the resulting one-step progress bounds.

Improving information retrieval in functional analysis.

PubMed

Rodriguez, Juan C; González, Germán A; Fresno, Cristóbal; Llera, Andrea S; Fernández, Elmer A

2016-12-01

Transcriptome analysis is essential to understand the mechanisms regulating key biological processes and functions. The first step usually consists of identifying candidate genes; to find out which pathways are affected by those genes, however, functional analysis (FA) is mandatory. The most frequently used strategies for this purpose are Gene Set and Singular Enrichment Analysis (GSEA and SEA) over Gene Ontology. Several statistical methods have been developed and compared in terms of computational efficiency and/or statistical appropriateness. However, whether their results are similar or complementary, the sensitivity to parameter settings, or possible bias in the analyzed terms has not been addressed so far. Here, two GSEA and four SEA methods and their parameter combinations were evaluated in six datasets by comparing two breast cancer subtypes with well-known differences in genetic background and patient outcomes. We show that GSEA and SEA lead to different results depending on the chosen statistic, model and/or parameters. Both approaches provide complementary results from a biological perspective. Hence, an Integrative Functional Analysis (IFA) tool is proposed to improve information retrieval in FA. It provides a common gene expression analytic framework that grants a comprehensive and coherent analysis. Only a minimal user parameter setting is required, since the best SEA/GSEA alternatives are integrated. IFA utility was demonstrated by evaluating four prostate cancer and the TCGA breast cancer microarray datasets, which showed its biological generalization capabilities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Generalization of the subsonic kernel function in the s-plane, with applications to flutter analysis

NASA Technical Reports Server (NTRS)

Cunningham, H. J.; Desmarais, R. N.

1984-01-01

A generalized subsonic unsteady aerodynamic kernel function, valid for both growing and decaying oscillatory motions, is developed and applied in a modified flutter analysis computer program to solve the boundaries of constant damping ratio as well as the flutter boundary. Rates of change of damping ratios with respect to dynamic pressure near flutter are substantially lower from the generalized-kernel-function calculations than from the conventional velocity-damping (V-g) calculation. A rational function approximation for aerodynamic forces used in control theory for s-plane analysis gave rather good agreement with kernel-function results, except for strongly damped motion at combinations of high (subsonic) Mach number and reduced frequency.

Conservation analysis and decomposition of residue correlation networks in the phospholipase A2 superfamily (PLA2s): Insights into the structure-function relationships of snake venom toxins.

PubMed

Oliveira, Alberto; Bleicher, Lucas; Schrago, Carlos G; Silva Junior, Floriano Paes

2018-05-01

Phospholipases A2 (PLA 2 s) comprise a superfamily of glycerophospholipids hydrolyzing enzymes present in many organisms in nature, whose catalytic activity was majorly unveiled by analysis of snake venoms. The latter have pharmaceutical and biotechnological interests and can be divided into different functional sub-classes. Our goal was to identify important residues and their relation to the functional and class-specific characteristics in the PLA 2 s family with special emphasis on snake venom PLA 2 s (svPLA 2 s). We identified such residues by conservation analysis and decomposition of residue coevolution networks (DRCN), annotated the results based on the available literature on PLA 2 s, structural analysis and molecular dynamics simulations, and related the results to the phylogenetic distribution of these proteins. A filtered alignment of PLA 2 s revealed 14 highly conserved positions and 3 sets of coevolved residues, which were annotated according to their structural or functional role. These residues are mostly involved in ligand binding and catalysis, calcium-binding, the formation of disulfide bridges and a hydrophobic cluster close to the binding site. An independent validation of the inference of structure-function relationships from our co-evolution analysis on the svPLA2s family was obtained by the analysis of the pattern of selection acting on the Viperidae and Elapidae lineages. Additionally, a molecular dynamics simulation on the Lys49 PLA 2 from Agkistrodon contortrix laticinctus was carried out to further investigate the correlation of the Lys49-Glu69 pair. Our results suggest this configuration can result in a novel conformation where the binding cavity collapses due to the approximation of two loops caused by a strong salt bridge between Glu69 and Arg34. Finally, phylogenetic analysis indicated a correlation between the presence of residues in the coevolved sets found in this analysis and the clade localization. The results provide a guide for important positions in the family of PLA 2 s, and potential new objects of investigation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative analysis of taxonomic, functional, and metabolic patterns of microbiomes from 14 full-scale biogas reactors by metagenomic sequencing and radioisotopic analysis.

PubMed

Luo, Gang; Fotidis, Ioannis A; Angelidaki, Irini

2016-01-01

Biogas production is a very complex process due to the high complexity in diversity and interactions of the microorganisms mediating it, and only limited and diffuse knowledge exists about the variation of taxonomic and functional patterns of microbiomes across different biogas reactors, and their relationships with the metabolic patterns. The present study used metagenomic sequencing and radioisotopic analysis to assess the taxonomic, functional, and metabolic patterns of microbiomes from 14 full-scale biogas reactors operated under various conditions treating either sludge or manure. The results from metagenomic analysis showed that the dominant methanogenic pathway revealed by radioisotopic analysis was not always correlated with the taxonomic and functional compositions. It was found by radioisotopic experiments that the aceticlastic methanogenic pathway was dominant, while metagenomics analysis showed higher relative abundance of hydrogenotrophic methanogens. Principal coordinates analysis showed the sludge-based samples were clearly distinct from the manure-based samples for both taxonomic and functional patterns, and canonical correspondence analysis showed that the both temperature and free ammonia were crucial environmental variables shaping the taxonomic and functional patterns. The study further the overall patterns of functional genes were strongly correlated with overall patterns of taxonomic composition across different biogas reactors. The discrepancy between the metabolic patterns determined by metagenomic analysis and metabolic pathways determined by radioisotopic analysis was found. Besides, a clear correlation between taxonomic and functional patterns was demonstrated for biogas reactors, and also the environmental factors that shaping both taxonomic and functional genes patterns were identified.

Stylistic Patterns in Language Teaching Research Articles: A Multidimensional Analysis

ERIC Educational Resources Information Center

Kitjaroenpaiboon, Woravit; Getkham, Kanyarat

2016-01-01

This paper presents the results of a multidimensional analysis to investigate stylistic patterns and their communicative functions in language teaching research articles. The findings were that language teaching research articles contained six stylistic patterns and communicative functions. Pattern I consisted of seven salient positive features…

Functional Analysis and Treatment of Noncompliance by Preschool Children

ERIC Educational Resources Information Center

Wilder, David A.; Harris, Carelle; Reagan, Renee; Rasey, Amy

2007-01-01

A functional analysis showed that noncompliance occurred most often for 2 preschoolers when it resulted in termination of a preferred activity, suggesting that noncompliance was maintained by positive reinforcement. A differential reinforcement procedure, which involved contingent access to coupons that could be exchanged for uninterrupted access…

[Design and implementation of online statistical analysis function in information system of air pollution and health impact monitoring].

PubMed

Lü, Yiran; Hao, Shuxin; Zhang, Guoqing; Liu, Jie; Liu, Yue; Xu, Dongqun

2018-01-01

To implement the online statistical analysis function in information system of air pollution and health impact monitoring, and obtain the data analysis information real-time. Using the descriptive statistical method as well as time-series analysis and multivariate regression analysis, SQL language and visual tools to implement online statistical analysis based on database software. Generate basic statistical tables and summary tables of air pollution exposure and health impact data online; Generate tendency charts of each data part online and proceed interaction connecting to database; Generate butting sheets which can lead to R, SAS and SPSS directly online. The information system air pollution and health impact monitoring implements the statistical analysis function online, which can provide real-time analysis result to its users.

The Effect of Group Therapy With Transactional Analysis Approach on Emotional Intelligence, Executive Functions and Drug Dependency.

PubMed

Forghani, Masoomeh; Ghanbari Hashem Abadi, Bahram Ali

2016-06-01

The aim of the present study was to evaluate the effect of group psychotherapy with transactional analysis (TA) approach on emotional intelligence (EI), executive functions and substance dependency among drug-addicts at rehabilitation centers in Mashhad city, Iran, in 2013. In this quasi-experimental study with pretest, posttest, case- control stages, 30 patients were selected from a rehabilitation center and randomly divided into two groups. The case group received 12 sessions of group psychotherapy with transactional analysis approach. Then the effects of independent variable (group psychotherapy with TA approach) on EI, executive function and drug dependency were assessed. The Bar-on test was used for EI, Stroop test for measuring executive function and morphine test, meth-amphetamines and B2 test for evaluating drug dependency. Data were analyzed using multifactorial covariance analysis, Levenes' analysis, MANCOVA, t-student and Pearson correlation coefficient tests t with SPSS software. Our results showed that group psychotherapy with the TA approach was effective in improving EI, executive functions and decreasing drug dependency (P < 0.05). The result of this study showed that group psychotherapy with TA approach has significant effects on addicts and prevents addiction recurrence by improving the coping capabilities and some mental functions of the subjects. However, there are some limitations regarding this study including follow-up duration and sample size.

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Rasch analysis of the Italian Lower Extremity Functional Scale: insights on dimensionality and suggestions for an improved 15-item version.

PubMed

Bravini, Elisabetta; Giordano, Andrea; Sartorio, Francesco; Ferriero, Giorgio; Vercelli, Stefano

2017-04-01

To investigate dimensionality and the measurement properties of the Italian Lower Extremity Functional Scale using both classical test theory and Rasch analysis methods, and to provide insights for an improved version of the questionnaire. Rasch analysis of individual patient data. Rehabilitation centre. A total of 135 patients with musculoskeletal diseases of the lower limb. Patients were assessed with the Lower Extremity Functional Scale before and after the rehabilitation. Rasch analysis showed some problems related to rating scale category functioning, items fit, and items redundancy. After an iterative process, which resulted in the reduction of rating scale categories from 5 to 4, and in the deletion of 5 items, the psychometric properties of the Italian Lower Extremity Functional Scale improved. The retained 15 items with a 4-level response format fitted the Rasch model (internal construct validity), and demonstrated unidimensionality and good reliability indices (person-separation reliability 0.92; Cronbach's alpha 0.94). Then, the analysis showed differential item functioning for six of the retained items. The sensitivity to change of the Italian 15-item Lower Extremity Functional Scale was nearly equal to the one of the original version (effect size: 0.93 and 0.98; standardized response mean: 1.20 and 1.28, respectively for the 15-item and 20-item versions). The Italian Lower Extremity Functional Scale had unsatisfactory measurement properties. However, removing five items and simplifying the scoring from 5 to 4 levels resulted in a more valid measure with good reliability and sensitivity to change.

Efficient reliability analysis of structures with the rotational quasi-symmetric point- and the maximum entropy methods

NASA Astrophysics Data System (ADS)

Xu, Jun; Dang, Chao; Kong, Fan

2017-10-01

This paper presents a new method for efficient structural reliability analysis. In this method, a rotational quasi-symmetric point method (RQ-SPM) is proposed for evaluating the fractional moments of the performance function. Then, the derivation of the performance function's probability density function (PDF) is carried out based on the maximum entropy method in which constraints are specified in terms of fractional moments. In this regard, the probability of failure can be obtained by a simple integral over the performance function's PDF. Six examples, including a finite element-based reliability analysis and a dynamic system with strong nonlinearity, are used to illustrate the efficacy of the proposed method. All the computed results are compared with those by Monte Carlo simulation (MCS). It is found that the proposed method can provide very accurate results with low computational effort.

Development of Activity-based Cost Functions for Cellulase, Invertase, and Other Enzymes

NASA Astrophysics Data System (ADS)

Stowers, Chris C.; Ferguson, Elizabeth M.; Tanner, Robert D.

As enzyme chemistry plays an increasingly important role in the chemical industry, cost analysis of these enzymes becomes a necessity. In this paper, we examine the aspects that affect the cost of enzymes based upon enzyme activity. The basis for this study stems from a previously developed objective function that quantifies the tradeoffs in enzyme purification via the foam fractionation process (Cherry et al., Braz J Chem Eng 17:233-238, 2000). A generalized cost function is developed from our results that could be used to aid in both industrial and lab scale chemical processing. The generalized cost function shows several nonobvious results that could lead to significant savings. Additionally, the parameters involved in the operation and scaling up of enzyme processing could be optimized to minimize costs. We show that there are typically three regimes in the enzyme cost analysis function: the low activity prelinear region, the moderate activity linear region, and high activity power-law region. The overall form of the cost analysis function appears to robustly fit the power law form.

Progressing from initially ambiguous functional analyses: three case examples.

PubMed

Tiger, Jeffrey H; Fisher, Wayne W; Toussaint, Karen A; Kodak, Tiffany

2009-01-01

Most often functional analyses are initiated using a standard set of test conditions, similar to those described by Iwata, Dorsey, Slifer, Bauman, and Richman [Iwata, B. A., Dorsey, M. F., Slifer, K. J., Bauman, K. E., & Richman, G. S. (1994). Toward a functional analysis of self-injury. Journal of Applied Behavior Analysis, 27, 197-209 (Reprinted from Analysis and Intervention in Developmental Disabilities, 2, 3-20, 1982)]. These test conditions involve the careful manipulation of motivating operations, discriminative stimuli, and reinforcement contingencies to determine the events related to the occurrence and maintenance of problem behavior. Some individuals display problem behavior that is occasioned and reinforced by idiosyncratic or otherwise unique combinations of environmental antecedents and consequences of behavior, which are unlikely to be detected using these standard assessment conditions. For these individuals, modifications to the standard test conditions or the inclusion of novel test conditions may result in clearer assessment outcomes. The current study provides three case examples of individuals whose functional analyses were initially undifferentiated; however, modifications to the standard conditions resulted in the identification of behavioral functions and the implementation of effective function-based treatments.

Stochastic resonance energy harvesting for a rotating shaft subject to random and periodic vibrations: influence of potential function asymmetry and frequency sweep

NASA Astrophysics Data System (ADS)

Kim, Hongjip; Che Tai, Wei; Zhou, Shengxi; Zuo, Lei

2017-11-01

Stochastic resonance is referred to as a physical phenomenon that is manifest in nonlinear systems whereby a weak periodic signal can be significantly amplified with the aid of inherent noise or vice versa. In this paper, stochastic resonance is considered to harvest energy from two typical vibrations in rotating shafts: random whirl vibration and periodic stick-slip vibration. Stick-slip vibrations impose a constant offset in centrifugal force and distort the potential function of the harvester, leading to potential function asymmetry. A numerical analysis based on a finite element method was conducted to investigate stochastic resonance with potential function asymmetry. Simulation results revealed that a harvester with symmetric potential function generates seven times higher power than that with asymmetric potential function. Furthermore, a frequency-sweep analysis also showed that stochastic resonance has hysteretic behavior, resulting in frequency difference between up-sweep and down-sweep excitations. An electromagnetic energy harvesting system was constructed to experimentally verify the numerical analysis. In contrast to traditional stochastic resonance harvesters, the proposed harvester uses magnetic force to compensate the offset in the centrifugal force. System identification was performed to obtain the parameters needed in the numerical analysis. With the identified parameters, the numerical simulations showed good agreement with the experiment results with around 10% error, which verified the effect of potential function asymmetry and frequency sweep excitation condition on stochastic resonance. Finally, attributed to compensating the centrifugal force offset, the proposed harvester generated nearly three times more open-circuit output voltage than its traditional counterpart.

Classifying Different Emotional States by Means of EEG-Based Functional Connectivity Patterns

PubMed Central

Lee, You-Yun; Hsieh, Shulan

2014-01-01

This study aimed to classify different emotional states by means of EEG-based functional connectivity patterns. Forty young participants viewed film clips that evoked the following emotional states: neutral, positive, or negative. Three connectivity indices, including correlation, coherence, and phase synchronization, were used to estimate brain functional connectivity in EEG signals. Following each film clip, participants were asked to report on their subjective affect. The results indicated that the EEG-based functional connectivity change was significantly different among emotional states. Furthermore, the connectivity pattern was detected by pattern classification analysis using Quadratic Discriminant Analysis. The results indicated that the classification rate was better than chance. We conclude that estimating EEG-based functional connectivity provides a useful tool for studying the relationship between brain activity and emotional states. PMID:24743695

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Free vibrations and buckling analysis of laminated plates by oscillatory radial basis functions

NASA Astrophysics Data System (ADS)

Neves, A. M. A.; Ferreira, A. J. M.

2015-12-01

In this paper the free vibrations and buckling analysis of laminated plates is performed using a global meshless method. A refined version of Kant's theorie which accounts for transverse normal stress and through-the-thickness deformation is used. The innovation is the use of oscillatory radial basis functions. Numerical examples are performed and results are presented and compared to available references. Such functions proved to be an alternative to the tradicional nonoscillatory radial basis functions.

First passage time: Connecting random walks to functional responses in heterogeneous environments (Invited)

NASA Astrophysics Data System (ADS)

Lewis, M. A.; McKenzie, H.; Merrill, E.

2010-12-01

In this talk I will outline first passage time analysis for animals undertaking complex movement patterns, and will demonstrate how first passage time can be used to derive functional responses in predator prey systems. The result is a new approach to understanding type III functional responses based on a random walk model. I will extend the analysis to heterogeneous environments to assess the effects of linear features on functional responses in wolves and elk using GPS tracking data.

Distinct Neural-Functional Effects of Treatments With Selective Serotonin Reuptake Inhibitors, Electroconvulsive Therapy, and Transcranial Magnetic Stimulation and Their Relations to Regional Brain Function in Major Depression: A Meta-analysis.

PubMed

Chau, David T; Fogelman, Phoebe; Nordanskog, Pia; Drevets, Wayne C; Hamilton, J Paul

2017-05-01

Functional neuroimaging studies have examined the neural substrates of treatments for major depressive disorder (MDD). Low sample size and methodological heterogeneity, however, undermine the generalizability of findings from individual studies. We conducted a meta-analysis to identify reliable neural changes resulting from different modes of treatment for MDD and compared them with each other and with reliable neural functional abnormalities observed in depressed versus control samples. We conducted a meta-analysis of studies reporting changes in brain activity (e.g., as indexed by positron emission tomography) following treatments with selective serotonin reuptake inhibitors (SSRIs), electroconvulsive therapy (ECT), or transcranial magnetic stimulation. Additionally, we examined the statistical reliability of overlap among thresholded meta-analytic SSRI, ECT, and transcranial magnetic stimulation maps as well as a map of abnormal neural function in MDD. Our meta-analysis revealed that 1) SSRIs decrease activity in the anterior insula, 2) ECT decreases activity in central nodes of the default mode network, 3) transcranial magnetic stimulation does not result in reliable neural changes, and 4) regional effects of these modes of treatment do not significantly overlap with each other or with regions showing reliable functional abnormality in MDD. SSRIs and ECT produce neurally distinct effects relative to each other and to the functional abnormalities implicated in depression. These treatments therefore may exert antidepressant effects by diminishing neural functions not implicated in depression but that nonetheless impact mood. We discuss how the distinct neural changes resulting from SSRIs and ECT can account for both treatment effects and side effects from these therapies as well as how to individualize these treatments. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Effectiveness of Functional Electrical Stimulation in Improving Clinical Outcomes in the Upper Arm following Stroke: A Systematic Review and Meta-Analysis

PubMed Central

Vafadar, Amir K.; Côté, Julie N.; Archambault, Philippe S.

2015-01-01

Background. Different therapeutic methods are being used to prevent or decrease long-term impairments of the upper arm in stroke patients. Functional electrical stimulation (FES) is one of these methods, which aims to stimulate the nerves of the weakened muscles so that the resulting muscle contractions resemble those of a functional task. Objectives. The objective of this study was to review the evidence for the effect of FES on (1) shoulder subluxation, (2) pain, and (3) upper arm motor function in stroke patients, when added to conventional therapy. Methods. From the 727 retrieved articles, 10 (9 RCTs, 1 quasi-RCT) were selected for final analysis and were rated based on the PEDro (Physiotherapy Evidence Database) scores and the Sackett's levels of evidence. A meta-analysis was performed for all three considered outcomes. Results. The results of the meta-analyses showed a significant difference in shoulder subluxation in experimental groups compared to control groups, only if FES was applied early after stroke. No effects were found on pain or motor function outcomes. Conclusion. FES can be used to prevent or reduce shoulder subluxation early after stroke. However, it should not be used to reduce pain or improve upper arm motor function after stroke. PMID:25685805

On the Utility of Content Analysis in Author Attribution: "The Federalist."

ERIC Educational Resources Information Center

Martindale, Colin; McKenzie, Dean

1995-01-01

Compares the success of lexical statistics, content analysis, and function words in determining the true author of "The Federalist." The function word approach proved most successful in attributing the papers to James Madison. Lexical statistics contributed nothing, while content analytic measures resulted in some success. (MJP)

Integrative analysis of environmental sequences using MEGAN4.

PubMed

Huson, Daniel H; Mitra, Suparna; Ruscheweyh, Hans-Joachim; Weber, Nico; Schuster, Stephan C

2011-09-01

A major challenge in the analysis of environmental sequences is data integration. The question is how to analyze different types of data in a unified approach, addressing both the taxonomic and functional aspects. To facilitate such analyses, we have substantially extended MEGAN, a widely used taxonomic analysis program. The new program, MEGAN4, provides an integrated approach to the taxonomic and functional analysis of metagenomic, metatranscriptomic, metaproteomic, and rRNA data. While taxonomic analysis is performed based on the NCBI taxonomy, functional analysis is performed using the SEED classification of subsystems and functional roles or the KEGG classification of pathways and enzymes. A number of examples illustrate how such analyses can be performed, and show that one can also import and compare classification results obtained using others' tools. MEGAN4 is freely available for academic purposes, and installers for all three major operating systems can be downloaded from www-ab.informatik.uni-tuebingen.de/software/megan.

EXPLORING FUNCTIONAL CONNECTIVITY IN FMRI VIA CLUSTERING.

PubMed

Venkataraman, Archana; Van Dijk, Koene R A; Buckner, Randy L; Golland, Polina

2009-04-01

In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering algorithms as alternatives to the commonly used Seed-Based Analysis. To enable clustering of the entire brain volume, we use the Nyström Method to approximate the necessary spectral decompositions. We apply K-Means, Spectral Clustering and Seed-Based Analysis to resting-state fMRI data collected from 45 healthy young adults. Without placing any a priori constraints, both clustering methods yield partitions that are associated with brain systems previously identified via Seed-Based Analysis. Our empirical results suggest that clustering provides a valuable tool for functional connectivity analysis.

Evaluation of functional outcome of the floating knee injury using multivariate analysis.

PubMed

Yokoyama, Kazuhiko; Tsukamoto, Tatsuro; Aoki, Shinichi; Wakita, Ryuji; Uchino, Masataka; Noumi, Takashi; Fukushima, Nobuaki; Itoman, Moritoshi

2002-11-01

The objective of this study is to evaluate significant contributing factors affecting the functional prognosis of floating knee injuries using multivariate analysis. A total of 68 floating knee injuries (67 patients) were treated at Kitasato University Hospital from 1986 to 1999. Both the femoral fractures and the tibial fractures were managed surgically by various methods. The functional results of these injuries were evaluated using the grading system of Karlström and Olerud. Follow-up periods ranged from 2 to 19 years (mean 50.2 months) after the original injury. We defined satisfactory (S) outcomes as those cases with excellent or good results and unsatisfactory (US) outcomes as those cases with acceptable or poor results. Logistic regression analysis was used as a multivariate analysis, and the dependent variables were defined as a satisfactory outcome or as an unsatisfactory outcome. The explanatory variables were predicting factors influencing the functional outcome such as age at trauma, gender, severity of soft-tissue injury in the femur and the tibia, AO fracture grade in the femur and the tibia, Fraser type (type I or type II), Injury Severity Score (ISS), and fixation time after injury (less than 1 week or more than 1 week) in the femur and the tibia. The final functional results were as follows: 25 cases had excellent results, 15 cases good results, 16 cases acceptable results, and 12 cases poor results. The predictive logistic regression equation was as follows: Log 1-p/p = 3.12-1.52 x Fraser type - 1.65 x severity of soft-tissue injury in the tibia - 1.31 x fixation time after injury in the tibia - 0.821 x AO fracture grade in the tibia + 1.025 x fixation time after injury in the femur - 0.687 x AO fracture grade in the femur ( p=0.01). Among the variables, Fraser type and the severity of soft-tissue injury in the tibia were significantly related to the final result. The multivariate analysis showed that both the involvement of the knee joint and the severity grade of soft-tissue injury in the tibia represented significant risk factors of poor outcome in floating knee injuries in this study.

Average symbol error rate for M-ary quadrature amplitude modulation in generalized atmospheric turbulence and misalignment errors

NASA Astrophysics Data System (ADS)

Sharma, Prabhat Kumar

2016-11-01

A framework is presented for the analysis of average symbol error rate (SER) for M-ary quadrature amplitude modulation in a free-space optical communication system. The standard probability density function (PDF)-based approach is extended to evaluate the average SER by representing the Q-function through its Meijer's G-function equivalent. Specifically, a converging power series expression for the average SER is derived considering the zero-boresight misalignment errors in the receiver side. The analysis presented here assumes a unified expression for the PDF of channel coefficient which incorporates the M-distributed atmospheric turbulence and Rayleigh-distributed radial displacement for the misalignment errors. The analytical results are compared with the results obtained using Q-function approximation. Further, the presented results are supported by the Monte Carlo simulations.

Analyzing coastal environments by means of functional data analysis

NASA Astrophysics Data System (ADS)

Sierra, Carlos; Flor-Blanco, Germán; Ordoñez, Celestino; Flor, Germán; Gallego, José R.

2017-07-01

Here we used Functional Data Analysis (FDA) to examine particle-size distributions (PSDs) in a beach/shallow marine sedimentary environment in Gijón Bay (NW Spain). The work involved both Functional Principal Components Analysis (FPCA) and Functional Cluster Analysis (FCA). The grainsize of the sand samples was characterized by means of laser dispersion spectroscopy. Within this framework, FPCA was used as a dimension reduction technique to explore and uncover patterns in grain-size frequency curves. This procedure proved useful to describe variability in the structure of the data set. Moreover, an alternative approach, FCA, was applied to identify clusters and to interpret their spatial distribution. Results obtained with this latter technique were compared with those obtained by means of two vector approaches that combine PCA with CA (Cluster Analysis). The first method, the point density function (PDF), was employed after adapting a log-normal distribution to each PSD and resuming each of the density functions by its mean, sorting, skewness and kurtosis. The second applied a centered-log-ratio (clr) to the original data. PCA was then applied to the transformed data, and finally CA to the retained principal component scores. The study revealed functional data analysis, specifically FPCA and FCA, as a suitable alternative with considerable advantages over traditional vector analysis techniques in sedimentary geology studies.

Evaluation of Road Performance Based on International Roughness Index and Falling Weight Deflectometer

NASA Astrophysics Data System (ADS)

Hasanuddin; Setyawan, A.; Yulianto, B.

2018-03-01

Assessment to the performance of road pavement is deemed necessary to improve the management quality of road maintenance and rehabilitation. This research to evaluate the road base on functional and structural and recommendations handling done. Assessing the pavement performance is conducted with functional and structural evaluation. Functional evaluation of pavement is based on the value of IRI (International Roughness Index) which among others is derived from reading NAASRA for analysis and recommended road handling. Meanwhile, structural evaluation of pavement is done by analyzing deflection value based on FWD (Falling Weight Deflectometer) data resulting in SN (Structural Number) value. The analysis will result in SN eff (Structural Number Effective) and SN f (Structural Number Future) value obtained from comparing SN eff to SN f value that leads to SCI (Structural Condition Index) value. SCI value implies the possible recommendation for handling pavement. The study done to Simpang Tuan-Batas Kota Jambi road segment was based on functional analysis. The study indicated that the road segment split into 12 segments in which segment 1, 3, 5, 7, 9, and 11 were of regular maintenance, segment 2, 4, 8, 10, 12 belonged to periodic maintenance, and segment 6 was of rehabilitation. The structural analysis resulted in 8 segments consisting of segment 1 and 2 recommended for regular maintenance, segment 3, 4, 5, and 7 for functional overlay, and 6 and 8 were of structural overlay.

Growth Type and Functional Trajectories: An Empirical Study of Urban Expansion in Nanjing, China

PubMed Central

Yuan, Feng

2016-01-01

Drawing upon the Landsat satellite images of Nanjing from 1985, 1995, 2001, 2007, and 2013, this paper integrates the convex hull analysis and common edge analysis at double scales, and develops a comprehensive matrix analysis to distinguish the different types of urban land expansion. The results show that Nanjing experienced rapid urban expansion, dominated by a mix of residential and manufacturing land from 1985 to 2013, which in turn has promoted Nanjing’s shift from a compact mononuclear city to a polycentric one. Spatial patterns of three specific types of growth, namely infilling, extension, and enclave were quite different in four consecutive periods. These patterns result primarily from the existing topographic constraints, as well as government-oriented urban planning and policies. By intersecting the function maps, we also reveal the functional evolution of newly-developed urban land. Moreover, both self-enhancing and mutual promotion of the newly developed functions are surveyed over the last decade. Our study confirms that the integration of a multi-scale method and multi-perspective analysis, such as the spatiotemporal patterns and functional evolution, helps us to better understand the rapid urban growth in China. PMID:26845155

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

Comparisons of synthesized and individual reinforcement contingencies during functional analysis.

PubMed

Fisher, Wayne W; Greer, Brian D; Romani, Patrick W; Zangrillo, Amanda N; Owen, Todd M

2016-09-01

Researchers typically modify individual functional analysis (FA) conditions after results are inconclusive (Hanley, Iwata, & McCord, 2003). Hanley, Jin, Vanselow, and Hanratty (2014) introduced a marked departure from this practice, using an interview-informed synthesized contingency analysis (IISCA). In the test condition, they delivered multiple contingencies simultaneously (e.g., attention and escape) after each occurrence of problem behavior; in the control condition, they delivered those same reinforcers noncontingently and continuously. In the current investigation, we compared the results of the IISCA with a more traditional FA in which we evaluated each putative reinforcer individually. Four of 5 participants displayed destructive behavior that was sensitive to the individual contingencies evaluated in the traditional FA. By contrast, none of the participants showed a response pattern consistent with the assumption of the IISCA. We discuss the implications of these findings on the development of accurate and efficient functional analyses. © 2016 Society for the Experimental Analysis of Behavior.

Spatial Assessment of Forest Ecosystem Functions and Services using Human Relating Factors for SDG

NASA Astrophysics Data System (ADS)

Song, C.; Lee, W. K.; Jeon, S. W.; Kim, T.; Lim, C. H.

2015-12-01

Application of ecosystem service concept in environmental related decision making could be numerical and objective standard for policy maker between preserving and developing perspective of environment. However, pursuing maximum benefit from natural capital through ecosystem services caused failure by losing ecosystem functions through its trade-offs. Therefore, difference between ecosystem functions and services were demonstrated and would apply human relating perspectives. Assessment results of ecosystem functions and services can be divided 3 parts. Tree growth per year set as the ecosystem function factor and indicated through so called pure function map. After that, relating functions can be driven such as water conservation, air pollutant purification, climate change regulation, and timber production. Overall process and amount are numerically quantified. These functional results can be transferred to ecosystem services by multiplying economic unit value, so function reflecting service maps can be generated. On the other hand, above services, to implement more reliable human demand, human reflecting service maps are also be developed. As the validation, quantified ecosystem functions are compared with former results through pixel based analysis. Three maps are compared, and through comparing difference between ecosystem function and services and inversed trends in function based and human based service are analysed. In this study, we could find differences in PF, FRS, and HRS in relation to based ecosystem conditions. This study suggests that the differences in PF, FRS, and HRS should be understood in the decision making process for sustainable management of ecosystem services. Although the analysis is based on in sort existing process separation, it is important to consider the possibility of different usage of ecosystem function assessment results and ecosystem service assessment results in SDG policy making. Furthermore, process based functional approach can suggest environmental information which is reflected the other kinds of perspective.

The bioimpedance analysis of a parenchyma of a liver in the conditions of its extensive resection in experiment

NASA Astrophysics Data System (ADS)

Agibalov, D. Y.; Panchenkov, D. N.; Chertyuk, V. B.; Leonov, S. D.; Astakhov, D. A.

2017-01-01

The liver failure which is result of disharmony of functionality of a liver to requirements of an organism is the main reason for unsatisfactory results of an extensive resection of a liver. However, uniform effective criterion of definition of degree of a liver failure it isn’t developed now. One of data acquisition methods about a morfo-functional condition of internals is the bioimpedance analysis (BIA) based on impedance assessment (full electric resistance) of a biological tissue. Measurements of an impedance are used in medicine and biology for the characteristic of physical properties of living tissue, studying of the changes bound to a functional state and its structural features. In experimental conditions we carried out an extensive resection of a liver on 27 white laboratory rats of the Vistar line. The comparative characteristic of data of a bioimpedansometriya in intraoperative and after the operational period with the main existing methods of assessment of a functional condition of a liver was carried out. By results of the work performed by us it is possible to claim that the bioimpedance analysis of a liver on the basis of an invasive bioimpedansometriya allows to estimate morphological features and functional activity of a liver before performance of an extensive resection of a liver. The data obtained during scientific work are experimental justification for use of an impedansometriya during complex assessment of functional reserves of a liver. Preliminary data of clinical approbation at a stage of introduction of a technique speak about rather high informational content of a bioimpedansometriya. The subsequent analysis of efficiency of the invasive bioimpedance analysis of a liver requires further accumulation of clinical data. However even at this stage the method showed the prospect for further use in clinical surgical hepathology.

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

Keefer, Donald A.; Shaffer, Eric G.; Storsved, Brynne

A free software application, RVA, has been developed as a plugin to the US DOE-funded ParaView visualization package, to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed as an open-source plugin to the 64 bit Windows version of ParaView 3.14. RVA was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing jointmore » visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.« less

RVA: A Plugin for ParaView 3.14

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

2015-09-04

RVA is a plugin developed for the 64-bit Windows version of the ParaView 3.14 visualization package. RVA is designed to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed onmore » enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.« less

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function

PubMed Central

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D.

2009-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings. PMID:19834575

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function.

PubMed

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D

2008-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings.

Energy Response Function of CALET Gamma Ray Burst Monitor

NASA Astrophysics Data System (ADS)

Yamada, Y.; Sakamoto, T.; Yoshida, A.; Calet Collaboration

2016-10-01

We will explain the development of the CGBM energy response function. We will also show the spectral analysis results of CGBM using our developed energy response function for simultaneously detected bright GRBs by other GRB detectors.

A Rasch-Validated Version of the Upper Extremity Functional Index for Interval-Level Measurement of Upper Extremity Function

PubMed Central

Chesworth, Bert M.

2013-01-01

Background The original 20-item Upper Extremity Functional Index (UEFI) has not undergone Rasch validation. Objective The purpose of this study was to determine whether Rasch analysis supports the UEFI as a measure of a single construct (ie, upper extremity function) and whether a Rasch-validated UEFI has adequate reproducibility for individual-level patient evaluation. Design This was a secondary analysis of data from a repeated-measures study designed to evaluate the measurement properties of the UEFI over a 3-week period. Methods Patients (n=239) with musculoskeletal upper extremity disorders were recruited from 17 physical therapy clinics across 4 Canadian provinces. Rasch analysis of the UEFI measurement properties was performed. If the UEFI did not fit the Rasch model, misfitting patients were deleted, items with poor response structure were corrected, and misfitting items and redundant items were deleted. The impact of differential item functioning on the ability estimate of patients was investigated. Results A 15-item modified UEFI was derived to achieve fit to the Rasch model where the total score was supported as a measure of upper extremity function only. The resultant UEFI-15 interval-level scale (0–100, worst to best state) demonstrated excellent internal consistency (person separation index=0.94) and test-retest reliability (intraclass correlation coefficient [2,1]=.95). The minimal detectable change at the 90% confidence interval was 8.1. Limitations Patients who were ambidextrous or bilaterally affected were excluded to allow for the analysis of differential item functioning due to limb involvement and arm dominance. Conclusion Rasch analysis did not support the validity of the 20-item UEFI. However, the UEFI-15 was a valid and reliable interval-level measure of a single dimension: upper extremity function. Rasch analysis supports using the UEFI-15 in physical therapist practice to quantify upper extremity function in patients with musculoskeletal disorders of the upper extremity. PMID:23813086

Quantum computation and analysis of Wigner and Husimi functions: toward a quantum image treatment.

PubMed

Terraneo, M; Georgeot, B; Shepelyansky, D L

2005-06-01

We study the efficiency of quantum algorithms which aim at obtaining phase-space distribution functions of quantum systems. Wigner and Husimi functions are considered. Different quantum algorithms are envisioned to build these functions, and compared with the classical computation. Different procedures to extract more efficiently information from the final wave function of these algorithms are studied, including coarse-grained measurements, amplitude amplification, and measure of wavelet-transformed wave function. The algorithms are analyzed and numerically tested on a complex quantum system showing different behavior depending on parameters: namely, the kicked rotator. The results for the Wigner function show in particular that the use of the quantum wavelet transform gives a polynomial gain over classical computation. For the Husimi distribution, the gain is much larger than for the Wigner function and is larger with the help of amplitude amplification and wavelet transforms. We discuss the generalization of these results to the simulation of other quantum systems. We also apply the same set of techniques to the analysis of real images. The results show that the use of the quantum wavelet transform allows one to lower dramatically the number of measurements needed, but at the cost of a large loss of information.

Further studies on stability analysis of nonlinear Roesser-type two-dimensional systems

NASA Astrophysics Data System (ADS)

Dai, Xiao-Lin

2014-04-01

This paper is concerned with further relaxations of the stability analysis of nonlinear Roesser-type two-dimensional (2D) systems in the Takagi-Sugeno fuzzy form. To achieve the goal, a novel slack matrix variable technique, which is homogenous polynomially parameter-dependent on the normalized fuzzy weighting functions with arbitrary degree, is developed and the algebraic properties of the normalized fuzzy weighting functions are collected into a set of augmented matrices. Consequently, more information about the normalized fuzzy weighting functions is involved and the relaxation quality of the stability analysis is significantly improved. Moreover, the obtained result is formulated in the form of linear matrix inequalities, which can be easily solved via standard numerical software. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed result.

Longitudinal assessment of stereotypic, proto-injurious, and self-injurious behavior exhibited by young children with developmental delays.

PubMed

Richman, David M; Lindauer, Steven E

2005-11-01

Twelve children (CA, 12 to 32 months) with developmental delay were observed in their homes during monthly analogue functional analysis probes to document patterns of emerging self-injurious behavior. Two patterns of emerging self-injury were observed for 5 participants: (a) The topography and functional analysis pattern remained the same, but the behavior eventually caused tissue damage; or (b) a new topography emerged that was similar to an established stereotypic motor behavior. Functional analysis results were inconclusive for the majority of target behaviors across participants due to undifferentiated responding across conditions. One participant exhibited two topographies that appeared to become sensitive to positive reinforcement over time. Results are discussed in terms of implications for future research on early intervention and prevention of self-injury.

Dynamic gene expression analysis in a H1N1 influenza virus mouse pneumonia model.

PubMed

Bao, Yanyan; Gao, Yingjie; Shi, Yujing; Cui, Xiaolan

2017-06-01

H1N1, a major pathogenic subtype of influenza A virus, causes a respiratory infection in humans and livestock that can range from a mild infection to more severe pneumonia associated with acute respiratory distress syndrome. Understanding the dynamic changes in the genome and the related functional changes induced by H1N1 influenza virus infection is essential to elucidating the pathogenesis of this virus and thereby determining strategies to prevent future outbreaks. In this study, we filtered the significantly expressed genes in mouse pneumonia using mRNA microarray analysis. Using STC analysis, seven significant gene clusters were revealed, and using STC-GO analysis, we explored the significant functions of these seven gene clusters. The results revealed GOs related to H1N1 virus-induced inflammatory and immune functions, including innate immune response, inflammatory response, specific immune response, and cellular response to interferon-beta. Furthermore, the dynamic regulation relationships of the key genes in mouse pneumonia were revealed by dynamic gene network analysis, and the most important genes were filtered, including Dhx58, Cxcl10, Cxcl11, Zbp1, Ifit1, Ifih1, Trim25, Mx2, Oas2, Cd274, Irgm1, and Irf7. These results suggested that during mouse pneumonia, changes in the expression of gene clusters and the complex interactions among genes lead to significant changes in function. Dynamic gene expression analysis revealed key genes that performed important functions. These results are a prelude to advancements in mouse H1N1 influenza virus infection biology, as well as the use of mice as a model organism for human H1N1 influenza virus infection studies.

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Anderson, M. R.; Schmidt, D. K.

1986-01-01

In the case of approach and landing, it is universally accepted that the pilot uses more than one vehicle response, or output, to close his control loops. Therefore, to model this task, a multi-loop analysis technique is required. The analysis problem has been in obtaining reasonable analytic estimates of the describing functions representing the pilot's loop compensation. Once these pilot describing functions are obtained, appropriate performance and workload metrics must then be developed for the landing task. The optimal control approach provides a powerful technique for obtaining the necessary describing functions, once the appropriate task objective is defined in terms of a quadratic objective function. An approach is presented through the use of a simple, reasonable objective function and model-based metrics to evaluate loop performance and pilot workload. The results of an analysis of the LAHOS (Landing and Approach of Higher Order Systems) study performed by R.E. Smith is also presented.

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

Jason L. Wright

Finding and identifying Cryptography is a growing concern in the malware analysis community. In this paper, a heuristic method for determining the likelihood that a given function contains a cryptographic algorithm is discussed and the results of applying this method in various environments is shown. The algorithm is based on frequency analysis of opcodes that make up each function within a binary.

Self-Injurious Behavior and Functional Analysis: Where Are the Descriptions of Participant Protections?

ERIC Educational Resources Information Center

Weeden, Marc; Mahoney, Amanda; Poling, Alan

2010-01-01

This study examined the reporting of participant protections in studies involving functional analysis and self-injurious behavior and published from 1994 through 2008. Results indicated that session termination criteria were rarely reported and other specific participant safeguards were seldom described. The absence of such information in no way…

Functional analysis of the zebrafish ortholog of HMGCS1 reveals independent functions for cholesterol and isoprenoids in craniofacial development

PubMed Central

Hernandez, Jose A.; Gonzalez, Cesar G.

2017-01-01

There are 8 different human syndromes caused by mutations in the cholesterol synthesis pathway. A subset of these disorders such as Smith-Lemli-Opitz disorder, are associated with facial dysmorphia. However, the molecular and cellular mechanisms underlying such facial deficits are not fully understood, primarily because of the diverse functions associated with the cholesterol synthesis pathway. Recent evidence has demonstrated that mutation of the zebrafish ortholog of HMGCR results in orofacial clefts. Here we sought to expand upon these data, by deciphering the cholesterol dependent functions of the cholesterol synthesis pathway from the cholesterol independent functions. Moreover, we utilized loss of function analysis and pharmacological inhibition to determine the extent of sonic hedgehog (Shh) signaling in animals with aberrant cholesterol and/or isoprenoid synthesis. Our analysis confirmed that mutation of hmgcs1, which encodes the first enzyme in the cholesterol synthesis pathway, results in craniofacial abnormalities via defects in cranial neural crest cell differentiation. Furthermore targeted pharmacological inhibition of the cholesterol synthesis pathway revealed a novel function for isoprenoid synthesis during vertebrate craniofacial development. Mutation of hmgcs1 had no effect on Shh signaling at 2 and 3 days post fertilization (dpf), but did result in a decrease in the expression of gli1, a known Shh target gene, at 4 dpf, after morphological deficits in craniofacial development and chondrocyte differentiation were observed in hmgcs1 mutants. These data raise the possibility that deficiencies in cholesterol modulate chondrocyte differentiation by a combination of Shh independent and Shh dependent mechanisms. Moreover, our results describe a novel function for isoprenoids in facial development and collectively suggest that cholesterol regulates craniofacial development through versatile mechanisms. PMID:28686747

Interconnection of Key Microbial Functional Genes for Enhanced Benzo[a]pyrene Biodegradation in Sediments by Microbial Electrochemistry.

PubMed

Yan, Zaisheng; He, Yuhong; Cai, Haiyuan; Van Nostrand, Joy D; He, Zhili; Zhou, Jizhong; Krumholz, Lee R; Jiang, He-Long

2017-08-01

Sediment microbial fuel cells (SMFCs) can stimulate the degradation of polycyclic aromatic hydrocarbons in sediments, but the mechanism of this process is poorly understood at the microbial functional gene level. Here, the use of SMFC resulted in 92% benzo[a]pyrene (BaP) removal over 970 days relative to 54% in the controls. Sediment functions, microbial community structure, and network interactions were dramatically altered by the SMFC employment. Functional gene analysis showed that c-type cytochrome genes for electron transfer, aromatic degradation genes, and extracellular ligninolytic enzymes involved in lignin degradation were significantly enriched in bulk sediments during SMFC operation. Correspondingly, chemical analysis of the system showed that these genetic changes resulted in increases in the levels of easily oxidizable organic carbon and humic acids which may have resulted in increased BaP bioavailability and increased degradation rates. Tracking microbial functional genes and corresponding organic matter responses should aid mechanistic understanding of BaP enhanced biodegradation by microbial electrochemistry and development of sustainable bioremediation strategies.

Two novel mutations in the POU1F1 gene generate null alleles through different mechanisms leading to combined pituitary hormone deficiency.

PubMed

Turton, J P; Strom, M; Langham, S; Dattani, M T; Le Tissier, P

2012-03-01

  Mutations in the POU1F1 gene severely affect the development and function of the anterior pituitary gland and lead to combined pituitary hormone deficiency (CPHD).   The clinical and genetic analysis of a patient presenting with CPHD and functional characterization of identified mutations.   We describe a male patient with extreme short stature, learning difficulties, anterior pituitary hypoplasia, secondary hypothyroidism and undetectable prolactin, growth hormone (GH) and insulin-like growth factor 1 (IGF1), with normal random cortisol.   The POU1F1 coding region was amplified by PCR and sequenced; the functional consequence of the mutations was analysed by cell transfection and in vitro assays.   Genetic analysis revealed compound heterozygosity for two novel putative loss of function mutations in POU1F1: a transition at position +3 of intron 1 [IVS1+3nt(A>G)] and a point mutation in exon 6 resulting in a substitution of arginine by tryptophan (R265W). Functional analysis revealed that IVS1+3nt(A>G) results in a reduction in the correctly spliced POU1F1 mRNA, which could be corrected by mutations of the +4, +5 and +6 nucleotides. Analysis of POU1F1(R265W) revealed complete loss of function resulting from severely reduced protein stability.   Combined pituitary hormone deficiency in this patient is caused by loss of POU1F1 function by two novel mechanisms, namely aberrant splicing (IVS1+3nt (A>G) and protein instability (R265W). Identification of the genetic basis of CPHD enabled the cessation of hydrocortisone therapy without the need for further assessment for evolving endocrinopathy. © 2012 Blackwell Publishing Ltd.

Using the Oxford Foot Model to determine the association between objective measures of foot function and results of the AOFAS Ankle-Hindfoot Scale and the Foot Function Index: a prospective gait analysis study in Germany

PubMed Central

Kostuj, Tanja; Stief, Felix; Hartmann, Kirsten Anna; Schaper, Katharina; Arabmotlagh, Mohammad; Baums, Mike H; Meurer, Andrea; Krummenauer, Frank; Lieske, Sebastian

2018-01-01

Objective After cross-cultural adaption for the German translation of the Ankle-Hindfoot Scale of the American Orthopaedic Foot and Ankle Society (AOFAS-AHS) and agreement analysis with the Foot Function Index (FFI-D), the following gait analysis study using the Oxford Foot Model (OFM) was carried out to show which of the two scores better correlates with objective gait dysfunction. Design and participants Results of the AOFAS-AHS and FFI-D, as well as data from three-dimensional gait analysis were collected from 20 patients with mild to severe ankle and hindfoot pathologies. Kinematic and kinetic gait data were correlated with the results of the total AOFAS scale and FFI-D as well as the results of those items representing hindfoot function in the AOFAS-AHS assessment. With respect to the foot disorders in our patients (osteoarthritis and prearthritic conditions), we correlated the total range of motion (ROM) in the ankle and subtalar joints as identified by the OFM with values identified during clinical examination ‘translated’ into score values. Furthermore, reduced walking speed, reduced step length and reduced maximum ankle power generation during push-off were taken into account and correlated to gait abnormalities described in the scores. An analysis of correlations with CIs between the FFI-D and the AOFAS-AHS items and the gait parameters was performed by means of the Jonckheere-Terpstra test; furthermore, exploratory factor analysis was applied to identify common information structures and thereby redundancy in the FFI-D and the AOFAS-AHS items. Results Objective findings for hindfoot disorders, namely a reduced ROM, in the ankle and subtalar joints, respectively, as well as reduced ankle power generation during push-off, showed a better correlation with the AOFAS-AHS total score—as well as AOFAS-AHS items representing ROM in the ankle, subtalar joints and gait function—compared with the FFI-D score. Factor analysis, however, could not identify FFI-D items consistently related to these three indicator parameters (pain, disability and function) found in the AOFAS-AHS. Furthermore, factor analysis did not support stratification of the FFI-D into two subscales. Conclusions The AOFAS-AHS showed a good agreement with objective gait parameters and is therefore better suited to evaluate disability and functional limitations of patients suffering from foot and ankle pathologies compared with the FFI-D. PMID:29626046

Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

2016-03-29

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

[Results from the German shoulder- and elbow arthroplasty register (SEPR) : Anatomic or reverse shoulder arthroplasty in B2-glenoids?

PubMed

Magosch, P; Habermeyer, P; Lichtenberg, S; Tauber, M; Gohlke, F; Mauch, F; Boehm, D; Loew, M; Zeifang, F; Pötzl, W

2017-12-01

Anatomic shoulder arthroplasty in osteoarthritis with biconcave glenoid wear results in decreased functional results and a higher rate of early glenoid loosening. The aim of the data analysis of the German shoulder arthroplasty register was to clarify whether reverse shoulder arthroplasty can provide better functional results and a lower complication rate than anatomic arthroplasty in osteoarthritis with biconcave glenoid wear. The analysis included 1052 completely documented primary implanted arthroplasties with a minimum follow-up of 2 years. In 119 cases, a B2-type glenoid was present. Out of these cases, 86 were treated with an anatomic shoulder arthroplasty, and in 33 cases a reverse shoulder arthroplasty was implanted. The mean follow-up was 47.6 months. The Constant score with its subcategories, as well as the active range of movement improved significantly after anatomic and after reverse shoulder arthroplasty. We observed no difference in functional results between both types of arthroplasty; however, reverse arthroplasty showed a significant higher revision rate (21.2%) (3% glenoid loosening, 6% prosthetic instability) than anatomic shoulder arthroplasty (12.8%) (11.6% glenoid loosening, 1.2% prosthetic instability), whereas anatomic shoulder arthroplasty showed a higher rate of glenoid loosening. Functional and radiographic results of both types of arthroplasty are comparable with the results reported in the literature, although our analysis represents results from an implant registry (data pertaining to medical care quality).

A Reverse-Genetics Mutational Analysis of the Barley HvDWARF Gene Results in Identification of a Series of Alleles and Mutants with Short Stature of Various Degree and Disturbance in BR Biosynthesis Allowing a New Insight into the Process.

PubMed

Gruszka, Damian; Gorniak, Malgorzata; Glodowska, Ewelina; Wierus, Ewa; Oklestkova, Jana; Janeczko, Anna; Maluszynski, Miroslaw; Szarejko, Iwona

2016-04-22

Brassinosteroids (BRs) are plant steroid hormones, regulating a broad range of physiological processes. The largest amount of data related with BR biosynthesis has been gathered in Arabidopsis thaliana, however understanding of this process is far less elucidated in monocot crops. Up to now, only four barley genes implicated in BR biosynthesis have been identified. Two of them, HvDWARF and HvBRD, encode BR-6-oxidases catalyzing biosynthesis of castasterone, but their relation is not yet understood. In the present study, the identification of the HvDWARF genomic sequence, its mutational and functional analysis and characterization of new mutants are reported. Various types of mutations located in different positions within functional domains were identified and characterized. Analysis of their impact on phenotype of the mutants was performed. The identified homozygous mutants show reduced height of various degree and disrupted skotomorphogenesis. Mutational analysis of the HvDWARF gene with the "reverse genetics" approach allowed for its detailed functional analysis at the level of protein functional domains. The HvDWARF gene function and mutants' phenotypes were also validated by measurement of endogenous BR concentration. These results allowed a new insight into the BR biosynthesis in barley.

Dynamics Analysis of Anti-predator Model on Intermediate Predator With Ratio Dependent Functional Responses

NASA Astrophysics Data System (ADS)

Savitri, D.

2018-01-01

This articel discusses a predator prey model with anti-predator on intermediate predator using ratio dependent functional responses. Dynamical analysis performed on the model includes determination of equilibrium point, stability and simulation. Three kinds of equilibrium points have been discussed, namely the extinction of prey point, the extinction of intermediate predator point and the extinction of predator point are exists under certain conditions. It can be shown that the result of numerical simulations are in accordance with analitical results

Can Automated Facial Expression Analysis Show Differences Between Autism and Typical Functioning?

PubMed

Borsos, Zsófia; Gyori, Miklos

2017-01-01

Exploratory analyses of emotional expressions using a commercially available facial expression recognition software are reported, from the context of a serious game for screening purposes. Our results are based on a comparative analysis of two matched groups of kindergarten-age children (high-functioning children with autism spectrum condition: n=13; typically developing children: n=13). Results indicate that this technology has the potential to identify autism-specific emotion expression features, and may play a role in affective diagnostic and assistive technologies.

Structural and magnetic properties of turmeric functionalized CoFe2O4 nanocomposite powder

NASA Astrophysics Data System (ADS)

Mehran, E.; Farjami Shayesteh, S.; Sheykhan, M.

2016-10-01

The structural and magnetic properties of the synthesized pure and functionalized CoFe2O4 magnetic nanoparticles (NPs) are studied by analyzing the results from the x-ray diffraction (XRD), transmission electron microscopy (TEM), FT-IR spectroscopy, thermogravimetry (TG), and vibrating sample magnetometer (VSM). To extract the structure and lattice parameters from the XRD analysis results, we first apply the pseudo-Voigt model function to the experimental data obtained from XRD analysis and then the Rietveld algorithm is used in order to optimize the model function to estimate the true intensity values. Our simulated intensities are in good agreement with the experimental peaks, therefore, all structural parameters such as crystallite size and lattice constant are achieved through this simulation. Magnetic analysis reveals that the synthesized functionalized NPs have a saturation magnetization almost equal to that of pure nanoparticles (PNPs). It is also found that the presence of the turmeric causes a small reduction in coercivity of the functionalized NPs in comparison with PNP. Our TGA and FTIR results show that the turmeric is bonded very well to the surface of the NPs. So it can be inferred that a nancomposite (NC) powder of turmeric and nanoparticles is produced. As an application, the anti-arsenic characteristic of turmeric makes the synthesized functionalized NPs or NC powder a good candidate for arsenic removal from polluted industrial waste water. Project supported by the University of Guilan and the Iran Nanotechnology Initiative Council.

Comparison of analysis and flight test data for a drone aircraft with active flutter suppression

NASA Technical Reports Server (NTRS)

Newsom, J. R.; Pototzky, A. S.

1981-01-01

This paper presents a comparison of analysis and flight test data for a drone aircraft equipped with an active flutter suppression system. Emphasis is placed on the comparison of modal dampings and frequencies as a function of Mach number. Results are presented for both symmetric and antisymmetric motion with flutter suppression off. Only symmetric results are presented for flutter suppression on. Frequency response functions of the vehicle are presented from both flight test data and analysis. The analysis correlation is improved by using an empirical aerodynamic correction factor which is proportional to the ratio of experimental to analytical steady-state lift curve slope. In addition to presenting the mathematical models and a brief description of existing analytical techniques, an alternative analytical technique for obtaining closed-loop results is presented.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Comparison of analysis and flight test data for a drone aircraft with active flutter suppression

NASA Technical Reports Server (NTRS)

Newsom, J. R.; Pototzky, A. S.

1981-01-01

A drone aircraft equipped with an active flutter suppression system is considered with emphasis on the comparison of modal dampings and frequencies as a function of Mach number. Results are presented for both symmetric and antisymmetric motion with flutter suppression off. Only symmetric results are given for flutter suppression on. Frequency response functions of the vehicle are presented from both flight test data and analysis. The analysis correlation is improved by using an empirical aerodynamic correction factor which is proportional to the ratio of experimental to analytical steady-state lift curve slope. The mathematical models are included and existing analytical techniques are described as well as an alternative analytical technique for obtaining closed-loop results.

On algorithmic optimization of histogramming functions for GEM systems

NASA Astrophysics Data System (ADS)

Krawczyk, Rafał D.; Czarski, Tomasz; Kolasinski, Piotr; Poźniak, Krzysztof T.; Linczuk, Maciej; Byszuk, Adrian; Chernyshova, Maryna; Juszczyk, Bartlomiej; Kasprowicz, Grzegorz; Wojenski, Andrzej; Zabolotny, Wojciech

2015-09-01

This article concerns optimization methods for data analysis for the X-ray GEM detector system. The offline analysis of collected samples was optimized for MATLAB computations. Compiled functions in C language were used with MEX library. Significant speedup was received for both ordering-preprocessing and for histogramming of samples. Utilized techniques with obtained results are presented.

The Effects of a School-Based Functional Analysis on Subsequent Classroom Behavior

ERIC Educational Resources Information Center

Davis, Tonya N.; Durand, Shannon; Fuentes, Lisa; Dacus, Sharon; Blenden, Kara

2014-01-01

In this study we analyzed the effects of conducting a school-based functional analysis on subsequent classroom behavior. Each participant was observed in the classroom during activities that were reported by teachers to result in high levels of challenging behavior. Participants were observed during (a) baseline, prior to the administration of a…

Implications of Motivating Operations for the Functional Analysis of Consumer Choice

ERIC Educational Resources Information Center

Fagerstrom, Asle; Foxall, Gordon R.; Arntzen, Erik

2010-01-01

The present article introduces the concept of Motivating Operation (MO) to the context of consumer choice and discusses the function of the concept of MO in the context of the Behavioral Perspective Model (BPM). Including MO as part of the consumer behavior setting leads to a more comprehensive analysis and, as a result, improves our understanding…

Using Videoconferencing to Conduct Functional Analysis of Challenging Behavior and Develop Classroom Behavioral Support Plans for Students with Autism

ERIC Educational Resources Information Center

Machalicek, Wendy; O'Reilly, Mark; Chan, Jeffrey M.; Lang, Russell; Rispoli, Mandy; Davis, Tonya; Shogren, Karrie; Sigafoos, Jeff; Lancioni, Giulio; Antonucci, Massimo; Langthorne, Paul; Andrews, Alonzo; Didden, Robert

2009-01-01

We conducted a functional analysis of challenging behavior for two students with autism using widely available videoconferencing equipment (laptop computers equipped with web cameras). Observers used the videoconferencing facilities to collect data on challenging behavior and to instruct the therapist conducting the assessment. Results of the…

Principal Components Analysis on the spectral Bidirectional Reflectance Distribution Function of ceramic colour standards.

PubMed

Ferrero, A; Campos, J; Rabal, A M; Pons, A; Hernanz, M L; Corróns, A

2011-09-26

The Bidirectional Reflectance Distribution Function (BRDF) is essential to characterize an object's reflectance properties. This function depends both on the various illumination-observation geometries as well as on the wavelength. As a result, the comprehensive interpretation of the data becomes rather complex. In this work we assess the use of the multivariable analysis technique of Principal Components Analysis (PCA) applied to the experimental BRDF data of a ceramic colour standard. It will be shown that the result may be linked to the various reflection processes occurring on the surface, assuming that the incoming spectral distribution is affected by each one of these processes in a specific manner. Moreover, this procedure facilitates the task of interpolating a series of BRDF measurements obtained for a particular sample. © 2011 Optical Society of America

Fracture mechanics analysis of cracked structures using weight function and neural network method

NASA Astrophysics Data System (ADS)

Chen, J. G.; Zang, F. G.; Yang, Y.; Shi, K. K.; Fu, X. L.

2018-06-01

Stress intensity factors(SIFs) due to thermal-mechanical load has been established by using weight function method. Two reference stress states sere used to determine the coefficients in the weight function. Results were evaluated by using data from literature and show a good agreement between them. So, the SIFs can be determined quickly using the weight function obtained when cracks subjected to arbitrary loads, and presented method can be used for probabilistic fracture mechanics analysis. A probabilistic methodology considering Monte-Carlo with neural network (MCNN) has been developed. The results indicate that an accurate probabilistic characteristic of the KI can be obtained by using the developed method. The probability of failure increases with the increasing of loads, and the relationship between is nonlinear.

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

Characterizing Bonding Patterns in Diradicals and Triradicals by Density-Based Wave Function Analysis: A Uniform Approach.

PubMed

Orms, Natalie; Rehn, Dirk R; Dreuw, Andreas; Krylov, Anna I

2018-02-13

Density-based wave function analysis enables unambiguous comparisons of the electronic structure computed by different methods and removes ambiguity of orbital choices. We use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high- and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such as polyradicals. We show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of the bonding pattern.

Image-derived input function with factor analysis and a-priori information.

PubMed

Simončič, Urban; Zanotti-Fregonara, Paolo

2015-02-01

Quantitative PET studies often require the cumbersome and invasive procedure of arterial cannulation to measure the input function. This study sought to minimize the number of necessary blood samples by developing a factor-analysis-based image-derived input function (IDIF) methodology for dynamic PET brain studies. IDIF estimation was performed as follows: (a) carotid and background regions were segmented manually on an early PET time frame; (b) blood-weighted and tissue-weighted time-activity curves (TACs) were extracted with factor analysis; (c) factor analysis results were denoised and scaled using the voxels with the highest blood signal; (d) using population data and one blood sample at 40 min, whole-blood TAC was estimated from postprocessed factor analysis results; and (e) the parent concentration was finally estimated by correcting the whole-blood curve with measured radiometabolite concentrations. The methodology was tested using data from 10 healthy individuals imaged with [(11)C](R)-rolipram. The accuracy of IDIFs was assessed against full arterial sampling by comparing the area under the curve of the input functions and by calculating the total distribution volume (VT). The shape of the image-derived whole-blood TAC matched the reference arterial curves well, and the whole-blood area under the curves were accurately estimated (mean error 1.0±4.3%). The relative Logan-V(T) error was -4.1±6.4%. Compartmental modeling and spectral analysis gave less accurate V(T) results compared with Logan. A factor-analysis-based IDIF for [(11)C](R)-rolipram brain PET studies that relies on a single blood sample and population data can be used for accurate quantification of Logan-V(T) values.

A Comparison of Descriptive and Functional Analyses of Inappropriate Mealtime Behavior.

PubMed

Borrero, Carrie S W; England, Jennie D; Sarcia, Ben; Woods, Julia N

2016-12-01

In recent years, rather than being used to assess the potential function of a response, descriptive assessment methods have been applied to evaluate potential consequences or contingencies for problem behavior (Borrero, Woods, Borrero, Masler, & Lesser in Journal of Applied Behavior Analysis, 43 , 71-88. doi: 10.1901/jaba.2010.43-71, 2010) or to assist with designing baseline conditions to approximate caregiver behavior (Casey et al. in Behavior Modification, 33 , 537-558. doi: 10.1177/0145445509341457, 2009). It has been shown that descriptive assessments of some forms of problem behavior (e.g., self-injury, aggression) are not good indicators of behavioral function and should not be used exclusively when conducting functional behavior assessments (Thompson & Iwata in Journal of Applied Behavior Analysis, 40 , 333-338. doi: 10.1901/jaba.2007.56.06/epdf, 2007). However, the extent to which descriptive assessments of inappropriate mealtime behavior can predict behavioral function is not yet clear. We conducted descriptive assessments of inappropriate mealtime behavior and compared the results to functional analyses for ten children with severe food refusal. Results showed that, for 71 % of participants, the descriptive and functional analyses matched. These results suggest that the correspondence between descriptive and functional analyses, at least for inappropriate mealtime behavior, may be higher than that for other forms of problem behavior.

How Root Cause Analysis Can Improve the Value Methodology

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

Wixson, James Robert

2002-05-01

Root cause analysis (RCA) is an important methodology that can be integrated with the VE Job Plan to generate superior results from the VE Methodology. The point at which RCA is most appropriate is after the function analysis and FAST Model have been built and functions for improvement have been chosen. These functions are then subjected to a simple, but, rigorous RCA to get to the root cause of their deficiencies, whether it is high cost/poor value, poor quality, or poor reliability. Once the most probable causes for these problems have been arrived at, better solutions for improvement can bemore » developed in the creativity phase because the team better understands the problems associated with these functions.« less

snpGeneSets: An R Package for Genome-Wide Study Annotation

PubMed Central

Mei, Hao; Li, Lianna; Jiang, Fan; Simino, Jeannette; Griswold, Michael; Mosley, Thomas; Liu, Shijian

2016-01-01

Genome-wide studies (GWS) of SNP associations and differential gene expressions have generated abundant results; next-generation sequencing technology has further boosted the number of variants and genes identified. Effective interpretation requires massive annotation and downstream analysis of these genome-wide results, a computationally challenging task. We developed the snpGeneSets package to simplify annotation and analysis of GWS results. Our package integrates local copies of knowledge bases for SNPs, genes, and gene sets, and implements wrapper functions in the R language to enable transparent access to low-level databases for efficient annotation of large genomic data. The package contains functions that execute three types of annotations: (1) genomic mapping annotation for SNPs and genes and functional annotation for gene sets; (2) bidirectional mapping between SNPs and genes, and genes and gene sets; and (3) calculation of gene effect measures from SNP associations and performance of gene set enrichment analyses to identify functional pathways. We applied snpGeneSets to type 2 diabetes (T2D) results from the NHGRI genome-wide association study (GWAS) catalog, a Finnish GWAS, and a genome-wide expression study (GWES). These studies demonstrate the usefulness of snpGeneSets for annotating and performing enrichment analysis of GWS results. The package is open-source, free, and can be downloaded at: https://www.umc.edu/biostats_software/. PMID:27807048

Study on Online Analysis of Transfer Function of Variable-Speed Rolling Mill Motor with Shaft Torsional Vibration Systems

NASA Astrophysics Data System (ADS)

Tamaoki, Toshifumi; Takanezawa, Makoto; Kimoto, Masanori; Morita, Noboru; Hoshino, Takeo; Hashizume, Kenji

The torsional vibration between metal rolling rolls and a rolling mill motor, may occur in recent days, as a result of higher speed response adjustment for variable speed rolling mill motor drive system. Issues in this paper are focused on excess acceleration value, in tangential direction of the mill motor rotor, which is caused by the motor shaft torsional resonance at the white noise signal superposition to the speed reference signal of the motor drive system for the online transfer function analysis. As a result of the acceleration analysis, the acceleration values in “G” (Relative acceleration value on the basis of Gravity) can be plotted on “Bode-Diagram”, which is namely frequency response for the speed signal amplitude transmission ratio. In addition, relation between the white noise amplitude reduction and the transfer function analysis accuracy deterioration is also examined, in this paper. As the amplitude of the white noise decreases, the analysis error increases because of the reduction in the resolution when the amplitude of the white noise signal is small.

A "Healthy-Contingencies" Behavioral Intervention

ERIC Educational Resources Information Center

St. Peter, Claire C.; Marsteller, Tonya M.

2017-01-01

Interventions based on functional analyses may result in better treatment outcomes than those using arbitrary reinforcers. However, functional analyses may be impractical in some situations, or an immediate intervention may be necessary while a functional analysis is being conducted. In these situations, delivering the social reinforcers most…

The neuronal correlates of intranasal trigeminal function – An ALE meta-analysis of human functional brain imaging data

PubMed Central

Albrecht, Jessica; Kopietz, Rainer; Frasnelli, Johannes; Wiesmann, Martin; Hummel, Thomas; Lundström, Johan N.

2009-01-01

Almost every odor we encounter in daily life has the capacity to produce a trigeminal sensation. Surprisingly, few functional imaging studies exploring human neuronal correlates of intranasal trigeminal function exist, and results are to some degree inconsistent. We utilized activation likelihood estimation (ALE), a quantitative voxel-based meta-analysis tool, to analyze functional imaging data (fMRI/PET) following intranasal trigeminal stimulation with carbon dioxide (CO2), a stimulus known to exclusively activate the trigeminal system. Meta-analysis tools are able to identify activations common across studies, thereby enabling activation mapping with higher certainty. Activation foci of nine studies utilizing trigeminal stimulation were included in the meta-analysis. We found significant ALE scores, thus indicating consistent activation across studies, in the brainstem, ventrolateral posterior thalamic nucleus, anterior cingulate cortex, insula, precentral gyrus, as well as in primary and secondary somatosensory cortices – a network known for the processing of intranasal nociceptive stimuli. Significant ALE values were also observed in the piriform cortex, insula, and the orbitofrontal cortex, areas known to process chemosensory stimuli, and in association cortices. Additionally, the trigeminal ALE statistics were directly compared with ALE statistics originating from olfactory stimulation, demonstrating considerable overlap in activation. In conclusion, the results of this meta-analysis map the human neuronal correlates of intranasal trigeminal stimulation with high statistical certainty and demonstrate that the cortical areas recruited during the processing of intranasal CO2 stimuli include those outside traditional trigeminal areas. Moreover, through illustrations of the considerable overlap between brain areas that process trigeminal and olfactory information; these results demonstrate the interconnectivity of flavor processing. PMID:19913573

Between Domain Cognitive Dispersion and Functional Abilities in Older Adults

PubMed Central

Fellows, Robert P.; Schmitter-Edgecombe, Maureen

2016-01-01

Objective Within-person variability in cognitive performance is related to neurological integrity, but the association with functional abilities is less clear. The primary aim of this study was to examine the association between cognitive dispersion, or within-person variability, and everyday multitasking and the way in which these variables may influence performance on a naturalistic assessment of functional abilities. Method Participants were 156 community-dwelling adults, age 50 or older. Cognitive dispersion was calculated by measuring within-person variability in cognitive domains, established through principal components analysis. Path analysis was used to determine the independent contribution of cognitive dispersion to functional ability, mediated by multitasking. Results Results of the path analysis revealed that the number of subtasks interweaved (i.e., multitasked) mediated the association between cognitive dispersion and task sequencing and accuracy. Although increased multitasking was associated with worse task performance in the path model, secondary analyses revealed that for individuals with low cognitive dispersion, increased multitasking was associated with better task performance, whereas for those with higher levels of dispersion multitasking was negatively correlated with task performance. Conclusion These results suggest that cognitive dispersion between domains may be a useful indicator of multitasking and daily living skills among older adults. PMID:26300441

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

PubMed

Sun, Duanchen; Liu, Yinliang; Zhang, Xiang-Sun; Wu, Ling-Yun

2017-09-21

High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets derived from microarray or RNA-seq experiments, is still a challenging task. Gene Ontology (GO) is commonly used in the functional enrichment studies. The GO terms identified via current functional enrichment analysis tools often contain direct parent or descendant terms in the GO hierarchical structure. Highly redundant terms make users difficult to analyze the underlying biological processes. In this paper, a novel network-based probabilistic generative model, NetGen, was proposed to perform the functional enrichment analysis. An additional protein-protein interaction (PPI) network was explicitly used to assist the identification of significantly enriched GO terms. NetGen achieved a superior performance than the existing methods in the simulation studies. The effectiveness of NetGen was explored further on four real datasets. Notably, several GO terms which were not directly linked with the active gene list for each disease were identified. These terms were closely related to the corresponding diseases when accessed to the curated literatures. NetGen has been implemented in the R package CopTea publicly available at GitHub ( http://github.com/wulingyun/CopTea/ ). Our procedure leads to a more reasonable and interpretable result of the functional enrichment analysis. As a novel term combination-based functional enrichment analysis method, NetGen is complementary to current individual term-based methods, and can help to explore the underlying pathogenesis of complex diseases.

Functional complexity and ecosystem stability: an experimental approach

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

Van Voris, P.; O'Neill, R.V.; Shugart, H.H.

1978-01-01

The complexity-stability hypothesis was experimentally tested using intact terrestrial microcosms. Functional complexity was defined as the number and significance of component interactions (i.e., population interactions, physical-chemical reactions, biological turnover rates) influenced by nonlinearities, feedbacks, and time delays. It was postulated that functional complexity could be nondestructively measured through analysis of a signal generated from the system. Power spectral analysis of hourly CO/sub 2/ efflux, from eleven old-field microcosms, was analyzed for the number of low frequency peaks and used to rank the functional complexity of each system. Ranking of ecosystem stability was based on the capacity of the system tomore » retain essential nutrients and was measured by net loss of Ca after the system was stressed. Rank correlation supported the hypothesis that increasing ecosystem functional complexity leads to increasing ecosystem stability. The results indicated that complex functional dynamics can serve to stabilize the system. The results also demonstrated that microcosms are useful tools for system-level investigations.« less

Structural and Functional Analysis of HIV-1 Coreceptors: Roles of Charged Residues and Posttranslational Modifications on Coreceptor Activity

DTIC Science & Technology

2000-01-01

to sites of inflammation. They may have additional functions. For example analysis of CXCR4 knockout mice show that CXCR4, which is chemotactic for... mice had similar phenotypes (195). Homozygous knockout of CXCR4 or SDF-1 results in embyonic lethality. Though CCR5 appears to be dispensable, other...chemokine receptors have vital functions. CXCR5 knockout mice have B-cell homing defects (118), and CXCR2 knockout mice overproduce B-cells and

Structural and Functional Analysis of HIV-1 Coreceptors: Roles of Charged Residues and Posttranslational Modifications on Coreceptor Activity

DTIC Science & Technology

2000-01-01

various organs and to sites of inflammation. They may have additional functions. For example analysis of CXCR4 knockout mice show that CXCR4, which...SDF-1 knockout mice had similar phenotypes (195). Homozygous knockout of CXCR4 or SDF-1 results in embyonic lethality. Though CCR5 appears to be...dispensable, other chemokine receptors have vital functions. CXCR5 knockout mice have B-cell homing defects (118), and CXCR2 knockout mice

Using normalization 3D model for automatic clinical brain quantative analysis and evaluation

NASA Astrophysics Data System (ADS)

Lin, Hong-Dun; Yao, Wei-Jen; Hwang, Wen-Ju; Chung, Being-Tau; Lin, Kang-Ping

2003-05-01

Functional medical imaging, such as PET or SPECT, is capable of revealing physiological functions of the brain, and has been broadly used in diagnosing brain disorders by clinically quantitative analysis for many years. In routine procedures, physicians manually select desired ROIs from structural MR images and then obtain physiological information from correspondent functional PET or SPECT images. The accuracy of quantitative analysis thus relies on that of the subjectively selected ROIs. Therefore, standardizing the analysis procedure is fundamental and important in improving the analysis outcome. In this paper, we propose and evaluate a normalization procedure with a standard 3D-brain model to achieve precise quantitative analysis. In the normalization process, the mutual information registration technique was applied for realigning functional medical images to standard structural medical images. Then, the standard 3D-brain model that shows well-defined brain regions was used, replacing the manual ROIs in the objective clinical analysis. To validate the performance, twenty cases of I-123 IBZM SPECT images were used in practical clinical evaluation. The results show that the quantitative analysis outcomes obtained from this automated method are in agreement with the clinical diagnosis evaluation score with less than 3% error in average. To sum up, the method takes advantage of obtaining precise VOIs, information automatically by well-defined standard 3-D brain model, sparing manually drawn ROIs slice by slice from structural medical images in traditional procedure. That is, the method not only can provide precise analysis results, but also improve the process rate for mass medical images in clinical.

Spherical Harmonic Analysis of Particle Velocity Distribution Function: Comparison of Moments and Anisotropies using Cluster Data

NASA Technical Reports Server (NTRS)

Gurgiolo, Chris; Vinas, Adolfo F.

2009-01-01

This paper presents a spherical harmonic analysis of the plasma velocity distribution function using high-angular, energy, and time resolution Cluster data obtained from the PEACE spectrometer instrument to demonstrate how this analysis models the particle distribution function and its moments and anisotropies. The results show that spherical harmonic analysis produced a robust physical representation model of the velocity distribution function, resolving the main features of the measured distributions. From the spherical harmonic analysis, a minimum set of nine spectral coefficients was obtained from which the moment (up to the heat flux), anisotropy, and asymmetry calculations of the velocity distribution function were obtained. The spherical harmonic method provides a potentially effective "compression" technique that can be easily carried out onboard a spacecraft to determine the moments and anisotropies of the particle velocity distribution function for any species. These calculations were implemented using three different approaches, namely, the standard traditional integration, the spherical harmonic (SPH) spectral coefficients integration, and the singular value decomposition (SVD) on the spherical harmonic methods. A comparison among the various methods shows that both SPH and SVD approaches provide remarkable agreement with the standard moment integration method.

Does the use of orthoses improve self-reported pain and function measures in patients with plantar fasciitis? A meta-analysis.

PubMed

Lee, Sae Yong; McKeon, Patrick; Hertel, Jay

2009-02-01

To perform a meta-analysis examining the effects of foot orthoses on self-reported pain and function in patients with plantar fasciitis. MEDLINE, SPORTDiscus, and CINAHL were searched from their inception until December 2007 using the terms "foot", "plantar fascia", "arch", "orthotic", "orthoses" and "plantar fasciitis". Original research studies which met these criteria were included: (1) randomised controlled trials or prospective cohort designs, (2) the patients had to be suffering from plantar fasciitis at the time of recruitment, (3) evaluated the efficacy of foot orthoses with self-reported pain and/or function, (4) means, standard deviations, and sample size of each group had to be reported. We utilised the Roos, Engstrom, and Soderberg (Roos, E., Engstrom, M., & Soderberg, B. (2006). Foot orthoses for the treatment of plantar fasciitis. Foot and Ankle International, 8, 606-611) night splint condition to compare our pooled orthoses results. The meta-analysis results showed significant reductions in pain after orthotic intervention. The Roos et al.' (Roos, E., Engstrom, M., & Soderberg, B. (2006). Foot orthoses for the treatment of plantar fasciitis. Foot and Ankle International, 8, 606-611) study also showed significant reduction in pain after night splint treatment. The meta-analysis results also showed significant increases in function after orthotic use. In contrast, the Roos et al.' (Roos, E., Engstrom, M., & Soderberg, B. (2006). Foot orthoses for the treatment of plantar fasciitis. Foot and Ankle International, 8, 606-611) study did not show a significant increase in function after night splinting for 12 weeks. The use of foot orthoses in patients with plantar fasciitis appears to be associated with reduced pain and increased function.

NovelFam3000 – Uncharacterized human protein domains conserved across model organisms

PubMed Central

Kemmer, Danielle; Podowski, Raf M; Arenillas, David; Lim, Jonathan; Hodges, Emily; Roth, Peggy; Sonnhammer, Erik LL; Höög, Christer; Wasserman, Wyeth W

2006-01-01

Background Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins. Description From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system. Conclusion Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families. PMID:16533400

Further studies of crania from ancient northern Africa: an analysis of crania from first dynasty Egyptian tombs, using discriminant functions.

PubMed

Keita, S O

1992-03-01

An analysis of First Dynasty crania from Abydos was undertaken using multiple discriminant functions. The results demonstrate greater affinity with Upper Nile Valley patterns, but also suggest change from earlier craniometric trends. Gene flow and movement of northern officials to the important southern city may explain the findings.

Finite element analysis of functionally graded bone plate at femur bone fracture site

NASA Astrophysics Data System (ADS)

Satapathy, Pravat Kumar; Sahoo, Bamadev; Panda, L. N.; Das, S.

2018-03-01

This paper focuses on the analysis of fractured Femur bone with functionally graded bone plate. The Femur bone is modeled by using the data from the CT (Computerized Tomography) scan and the material properties are assigned using Mimics software. The fracture fixation plate used here is composed of Functionally Graded Material (FGM). The functionally graded bone plate is considered to be composed of different layers of homogeneous materials. Finite element method approach is adopted for analysis. The volume fraction of the material is calculated by considering its variation along the thickness direction (z) according to a power law and the effective properties of the homogeneous layers are estimated. The model developed is validated by comparing numerical results available in the literature. Static analysis has been performed for the bone plate system by considering both axial compressive load and torsional load. The investigation shows that by introducing FG bone plate instead of titanium, the stress at the fracture site increases by 63 percentage and the deformation decreases by 15 percentage, especially when torsional load is taken into consideration. The present model yields better results in comparison with the commercially available bone plates.

Bragg-cell receiver study

NASA Technical Reports Server (NTRS)

Wilson, Lonnie A.

1987-01-01

Bragg-cell receivers are employed in specialized Electronic Warfare (EW) applications for the measurement of frequency. Bragg-cell receiver characteristics are fully characterized for simple RF emitter signals. This receiver is early in its development cycle when compared to the IFM receiver. Functional mathematical models are derived and presented in this report for the Bragg-cell receiver. Theoretical analysis is presented and digital computer signal processing results are presented for the Bragg-cell receiver. Probability density function analysis are performed for output frequency. Probability density function distributions are observed to depart from assumed distributions for wideband and complex RF signals. This analysis is significant for high resolution and fine grain EW Bragg-cell receiver systems.

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

NASA Technical Reports Server (NTRS)

Carter, M. C.; Madison, M. W.

1973-01-01

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

An advanced probabilistic structural analysis method for implicit performance functions

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

On-Line GIS Analysis and Image Processing for Geoportal Kielce/poland Development

NASA Astrophysics Data System (ADS)

Hejmanowska, B.; Głowienka, E.; Florek-Paszkowski, R.

2016-06-01

GIS databases are widely available on the Internet, but mainly for visualization with limited functionality; very simple queries are possible i.e. attribute query, coordinate readout, line and area measurements or pathfinder. A little more complex analysis (i.e. buffering or intersection) are rare offered. Paper aims at the concept of Geoportal functionality development in the field of GIS analysis. Multi-Criteria Evaluation (MCE) is planned to be implemented in web application. OGC Service is used for data acquisition from the server and results visualization. Advanced GIS analysis is planned in PostGIS and Python programming. In the paper an example of MCE analysis basing on Geoportal Kielce is presented. Other field where Geoportal can be developed is implementation of processing new available satellite images free of charge (Sentinel-2, Landsat 8, ASTER, WV-2). Now we are witnessing a revolution in access to the satellite imagery without charge. This should result in an increase of interest in the use of these data in various fields by a larger number of users, not necessarily specialists in remote sensing. Therefore, it seems reasonable to expand the functionality of Internet's tools for data processing by non-specialists, by automating data collection and prepared predefined analysis.

Using the Oxford Foot Model to determine the association between objective measures of foot function and results of the AOFAS Ankle-Hindfoot Scale and the Foot Function Index: a prospective gait analysis study in Germany.

PubMed

Kostuj, Tanja; Stief, Felix; Hartmann, Kirsten Anna; Schaper, Katharina; Arabmotlagh, Mohammad; Baums, Mike H; Meurer, Andrea; Krummenauer, Frank; Lieske, Sebastian

2018-04-05

After cross-cultural adaption for the German translation of the Ankle-Hindfoot Scale of the American Orthopaedic Foot and Ankle Society (AOFAS-AHS) and agreement analysis with the Foot Function Index (FFI-D), the following gait analysis study using the Oxford Foot Model (OFM) was carried out to show which of the two scores better correlates with objective gait dysfunction. Results of the AOFAS-AHS and FFI-D, as well as data from three-dimensional gait analysis were collected from 20 patients with mild to severe ankle and hindfoot pathologies.Kinematic and kinetic gait data were correlated with the results of the total AOFAS scale and FFI-D as well as the results of those items representing hindfoot function in the AOFAS-AHS assessment. With respect to the foot disorders in our patients (osteoarthritis and prearthritic conditions), we correlated the total range of motion (ROM) in the ankle and subtalar joints as identified by the OFM with values identified during clinical examination 'translated' into score values. Furthermore, reduced walking speed, reduced step length and reduced maximum ankle power generation during push-off were taken into account and correlated to gait abnormalities described in the scores. An analysis of correlations with CIs between the FFI-D and the AOFAS-AHS items and the gait parameters was performed by means of the Jonckheere-Terpstra test; furthermore, exploratory factor analysis was applied to identify common information structures and thereby redundancy in the FFI-D and the AOFAS-AHS items. Objective findings for hindfoot disorders, namely a reduced ROM, in the ankle and subtalar joints, respectively, as well as reduced ankle power generation during push-off, showed a better correlation with the AOFAS-AHS total score-as well as AOFAS-AHS items representing ROM in the ankle, subtalar joints and gait function-compared with the FFI-D score.Factor analysis, however, could not identify FFI-D items consistently related to these three indicator parameters (pain, disability and function) found in the AOFAS-AHS. Furthermore, factor analysis did not support stratification of the FFI-D into two subscales. The AOFAS-AHS showed a good agreement with objective gait parameters and is therefore better suited to evaluate disability and functional limitations of patients suffering from foot and ankle pathologies compared with the FFI-D. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Traumatic brain injury impairs small-world topology

PubMed Central

Pandit, Anand S.; Expert, Paul; Lambiotte, Renaud; Bonnelle, Valerie; Leech, Robert; Turkheimer, Federico E.

2013-01-01

Objective: We test the hypothesis that brain networks associated with cognitive function shift away from a “small-world” organization following traumatic brain injury (TBI). Methods: We investigated 20 TBI patients and 21 age-matched controls. Resting-state functional MRI was used to study functional connectivity. Graph theoretical analysis was then applied to partial correlation matrices derived from these data. The presence of white matter damage was quantified using diffusion tensor imaging. Results: Patients showed characteristic cognitive impairments as well as evidence of damage to white matter tracts. Compared to controls, the graph analysis showed reduced overall connectivity, longer average path lengths, and reduced network efficiency. A particular impact of TBI is seen on a major network hub, the posterior cingulate cortex. Taken together, these results confirm that a network critical to cognitive function shows a shift away from small-world characteristics. Conclusions: We provide evidence that key brain networks involved in supporting cognitive function become less small-world in their organization after TBI. This is likely to be the result of diffuse white matter damage, and may be an important factor in producing cognitive impairment after TBI. PMID:23596068

Comparison of Traditional and Trial-Based Methodologies for Conducting Functional Analyses

ERIC Educational Resources Information Center

LaRue, Robert H.; Lenard, Karen; Weiss, Mary Jane; Bamond, Meredith; Palmieri, Mark; Kelley, Michael E.

2010-01-01

Functional analysis represents a sophisticated and empirically supported functional assessment procedure. While these procedures have garnered considerable empirical support, they are often underused in clinical practice. Safety risks resulting from the evocation of maladaptive behavior and the length of time required to conduct functional…

Tract-based Spatial Statistics and fMRI Analysis in Patients with Small Cell Lung Cancer before Prophylactic Cranial Irradiation

NASA Astrophysics Data System (ADS)

Benezi, S.; Bromis, K.; Karavasilis, E.; Karanasiou, I. S.; Koutsoupidou, M.; Matsopoulos, G.; Ventouras, E.; Uzunoglu, N.; Kouloulias, V.; Papathanasiou, M.; Foteineas, A.; Efstathopoulos, E.; Kelekis, N.; Kelekis, D.

2015-09-01

Prophylactic cranial irradiation (PCI) is known to increase life expectancy to a significant degree in Small Cell Lung Cancer (SCLC) patients. The overall scope of this research is to investigate changes in structural and functional connectivity between SCLC patients and controls before and after PCI treatment. In the current study specifically we use diffusion tensor imaging (DTI) and functional Magnetic Resonance (fMRI) to identify potential alterations in white matter structure and brain function respectively, in SCLC patients before PCI compared to healthy participants. The results in DTI analysis have showed lower fractional anisotropy (FA) and higher eigenvalues in white matter regions in the patient group. Similarly, in fMRI analysis a lower level of activation in the primary somatosensory cortex was reported. The results presented herein are subject to further investigation with larger patient and control groups.

The Questions about Behavioral Function (QABF): Current Status as a Method of Functional Assessment

ERIC Educational Resources Information Center

Matson, Johnny L.; Tureck, Kimberly; Rieske, Robert

2012-01-01

Functional assessment has now entered the mainstream for evaluation and to aid in the treatment of challenging behaviors, while experimental functional analysis was at the forefront of this movement, this particular methodology has proven to be impractical, and thus has limited utility in real world settings. As a result of these factors…

Rehabilitation in neuro-oncology: a meta-analysis of published data and a mono-institutional experience.

PubMed

Formica, Vincenzo; Del Monte, Girolamo; Giacchetti, Ilaria; Grenga, Italia; Giaquinto, Salvatore; Fini, Massimo; Roselli, Mario

2011-06-01

Rehabilitation for cancer patients with central nervous system (CNS) involvement is rarely considered and data on its use are limited. The purpose of the present study is to collect all available published data on neuro-oncology rehabilitation and perform a meta-analysis where results were presented in a comparable manner. Moreover, the authors report results on cancer patients with neurological disabilities undergoing rehabilitation at their unit. A PubMed search was performed to identify studies regarding cancer patients with CNS involvement undergoing inpatient physical rehabilitation. Studies with a complete functional evaluation at admission and discharge were selected. As the most common evaluation scales were Functional Independence Measure (FIM) and Barthel Index (BI), only articles with complete FIM and/or BI data were selected for the meta-analysis. Moreover, 23 cancer patients suffering from diverse neurological disabilities underwent standard rehabilitation program between April 2005 and December 2007 at the San Raffaele Pisana Rehabilitation Center. Patient demographics and relevant clinical data were collected. Motricity Index, Trunk Control Test score, and BI were monitored during rehabilitation to assess patient progresses. BI results of patients in this study were included in the meta-analysis. The meta-analysis included results of a total of 994 patients. A statistically significant (P < .05) improvement of both BI and FIM scores was demonstrated after rehabilitation (standardized mean difference = 0.60 and 0.75, respectively). Functional status determined by either FIM or BI improved on average by 36%. Published data demonstrate that patients with brain tumors undergoing inpatient rehabilitation appear to make functional gains in line with those seen in similar patients with nonneoplastic conditions.

Maximization of Learning Speed in the Motor Cortex Due to Neuronal Redundancy

PubMed Central

Takiyama, Ken; Okada, Masato

2012-01-01

Many redundancies play functional roles in motor control and motor learning. For example, kinematic and muscle redundancies contribute to stabilizing posture and impedance control, respectively. Another redundancy is the number of neurons themselves; there are overwhelmingly more neurons than muscles, and many combinations of neural activation can generate identical muscle activity. The functional roles of this neuronal redundancy remains unknown. Analysis of a redundant neural network model makes it possible to investigate these functional roles while varying the number of model neurons and holding constant the number of output units. Our analysis reveals that learning speed reaches its maximum value if and only if the model includes sufficient neuronal redundancy. This analytical result does not depend on whether the distribution of the preferred direction is uniform or a skewed bimodal, both of which have been reported in neurophysiological studies. Neuronal redundancy maximizes learning speed, even if the neural network model includes recurrent connections, a nonlinear activation function, or nonlinear muscle units. Furthermore, our results do not rely on the shape of the generalization function. The results of this study suggest that one of the functional roles of neuronal redundancy is to maximize learning speed. PMID:22253586

The effects of videotape modeling on staff acquisition of functional analysis methodology.

PubMed

Moore, James W; Fisher, Wayne W

2007-01-01

Lectures and two types of video modeling were compared to determine their relative effectiveness in training 3 staff members to conduct functional analysis sessions. Video modeling that contained a larger number of therapist exemplars resulted in mastery-level performance eight of the nine times it was introduced, whereas neither lectures nor partial video modeling produced significant improvements in performance. Results demonstrated that video modeling provided an effective training strategy but only when a wide range of exemplars of potential therapist behaviors were depicted in the videotape.

The Effects of Videotape Modeling on Staff Acquisition of Functional Analysis Methodology

PubMed Central

Moore, James W; Fisher, Wayne W

2007-01-01

Lectures and two types of video modeling were compared to determine their relative effectiveness in training 3 staff members to conduct functional analysis sessions. Video modeling that contained a larger number of therapist exemplars resulted in mastery-level performance eight of the nine times it was introduced, whereas neither lectures nor partial video modeling produced significant improvements in performance. Results demonstrated that video modeling provided an effective training strategy but only when a wide range of exemplars of potential therapist behaviors were depicted in the videotape. PMID:17471805

New method to incorporate Type B uncertainty into least-squares procedures in radionuclide metrology.

PubMed

Han, Jubong; Lee, K B; Lee, Jong-Man; Park, Tae Soon; Oh, J S; Oh, Pil-Jei

2016-03-01

We discuss a new method to incorporate Type B uncertainty into least-squares procedures. The new method is based on an extension of the likelihood function from which a conventional least-squares function is derived. The extended likelihood function is the product of the original likelihood function with additional PDFs (Probability Density Functions) that characterize the Type B uncertainties. The PDFs are considered to describe one's incomplete knowledge on correction factors being called nuisance parameters. We use the extended likelihood function to make point and interval estimations of parameters in the basically same way as the least-squares function used in the conventional least-squares method is derived. Since the nuisance parameters are not of interest and should be prevented from appearing in the final result, we eliminate such nuisance parameters by using the profile likelihood. As an example, we present a case study for a linear regression analysis with a common component of Type B uncertainty. In this example we compare the analysis results obtained from using our procedure with those from conventional methods. Copyright © 2015. Published by Elsevier Ltd.

A Quality Function Deployment Framework for the Service Quality of Health Information Websites

PubMed Central

Kim, Dohoon

2010-01-01

Objectives This research was conducted to identify both the users' service requirements on health information websites (HIWs) and the key functional elements for running HIWs. With the quality function deployment framework, the derived service attributes (SAs) are mapped into the suppliers' functional characteristics (FCs) to derive the most critical FCs for the users' satisfaction. Methods Using the survey data from 228 respondents, the SAs, FCs and their relationships were analyzed using various multivariate statistical methods such as principal component factor analysis, discriminant analysis, correlation analysis, etc. Simple and compound FC priorities were derived by matrix calculation. Results Nine factors of SAs and five key features of FCs were identified, and these served as the basis for the house of quality model. Based on the compound FC priorities, the functional elements pertaining to security and privacy, and usage support should receive top priority in the course of enhancing HIWs. Conclusions The quality function deployment framework can improve the FCs of the HIWs in an effective, structured manner, and it can also be utilized for critical success factors together with their strategic implications for enhancing the service quality of HIWs. Therefore, website managers could efficiently improve website operations by considering this study's results. PMID:21818418

Limits of clinical tests to screen autonomic function in diabetes type 1.

PubMed

Ducher, M; Bertram, D; Sagnol, I; Cerutti, C; Thivolet, C; Fauvel, J P

2001-11-01

A precocious detection of cardiac autonomic dysfunction is of major clinical interest that could lead to a more intensive supervision of diabetic patients. However, classical clinical exploration of cardiac autonomic function is not easy to undertake in a reproducible way. Thus, respective interests of autonomic nervous parameters provided by both clinical tests and computerized analysis of resting blood pressure were checked in type 1 diabetic patients without orthostatic hypotension and microalbuminuria. Thirteen diabetic subjects matched for age and gender to thirteen healthy subjects volunteered to participate to the study. From clinical tests (standing up, deep breathing, Valsalva maneuver, handgrip test), autonomic function was scored according to Ewing's methodology. Analysis of resting beat to beat blood pressure provided autonomic indices of the cardiac function (spectral analysis or Z analysis). 5 of the 13 diabetic patients exhibited a pathological score (more than one pathological response) suggesting the presence of cardiovascular autonomic dysfunction. The most discriminative test was the deep breathing test. However, spectral indices of BP recordings and baro-reflex sensitivity (BRS) of these 5 subjects were similar to those of healthy subjects and of remaining diabetic subjects. Alteration in Ewing's score given by clinical tests may not reflect an alteration of cardiac autonomic function in asymptomatic type 1 diabetic patients, because spectral indices of sympathetic and parasympathetic (including BRS) function were within normal range. Our results strongly suggest to confront results provided by both methodologies before concluding to an autonomic cardiac impairment in asymptomatic diabetic patients.

Incorporating Functional Imaging Information into rpFNA Analysis for Breast Cancer Detection in High Risk Women

DTIC Science & Technology

2010-03-01

TITLE: INCORPORATING FUNCTIONAL IMAGING INFORMATION TO rpFNA ANALYSIS FOR BREAST CANCER DETECTION IN HIGH-RISK WOMEN PRINCIPAL INVESTIGATOR...Imaging Information into rpFNA 5a. CONTRACT NUMBER Analysis for Breast Cancer Detection in High Risk Women 5b. GRANT NUMBER W81XWH-08-1-0192 5c...results of random periareolar fine needle aspiration (rpFNA) in women at high risk for breast cancer. In this second year of work, efforts have been

Setting Standards for Medically-Based Running Analysis

PubMed Central

Vincent, Heather K.; Herman, Daniel C.; Lear-Barnes, Leslie; Barnes, Robert; Chen, Cong; Greenberg, Scott; Vincent, Kevin R.

2015-01-01

Setting standards for medically based running analyses is necessary to ensure that runners receive a high-quality service from practitioners. Medical and training history, physical and functional tests, and motion analysis of running at self-selected and faster speeds are key features of a comprehensive analysis. Self-reported history and movement symmetry are critical factors that require follow-up therapy or long-term management. Pain or injury is typically the result of a functional deficit above or below the site along the kinematic chain. PMID:25014394

Construction and Analysis of Functional Networks in the Gut Microbiome of Type 2 Diabetes Patients.

PubMed

Li, Lianshuo; Wang, Zicheng; He, Peng; Ma, Shining; Du, Jie; Jiang, Rui

2016-10-01

Although networks of microbial species have been widely used in the analysis of 16S rRNA sequencing data of a microbiome, the construction and analysis of a complete microbial gene network are in general problematic because of the large number of microbial genes in metagenomics studies. To overcome this limitation, we propose to map microbial genes to functional units, including KEGG orthologous groups and the evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG) orthologous groups, to enable the construction and analysis of a microbial functional network. We devised two statistical methods to infer pairwise relationships between microbial functional units based on a deep sequencing dataset of gut microbiome from type 2 diabetes (T2D) patients as well as healthy controls. Networks containing such functional units and their significant interactions were constructed subsequently. We conducted a variety of analyses of global properties, local properties, and functional modules in the resulting functional networks. Our data indicate that besides the observations consistent with the current knowledge, this study provides novel biological insights into the gut microbiome associated with T2D. Copyright © 2016. Production and hosting by Elsevier Ltd.

Motor function and incident dementia: a systematic review and meta-analysis.

PubMed

Kueper, Jacqueline Kathleen; Speechley, Mark; Lingum, Navena Rebecca; Montero-Odasso, Manuel

2017-09-01

cognitive and mobility decline are interrelated processes, whereby mobility decline coincides or precedes the onset of cognitive decline. to assess whether there is an association between performance on motor function tests and incident dementia. electronic database, grey literature and hand searching identified studies testing for associations between baseline motor function and incident dementia in older adults. of 2,540 potentially relevant documents, 37 met the final inclusion criteria and were reviewed qualitatively. Three meta-analyses were conducted using data from 10 studies. Three main motor domains-upper limb motor function, parkinsonism and lower limb motor function-emerged as associated with increased risk of incident dementia. Studies including older adults without neurological overt disease found a higher risk of incident dementia associated with poorer performance on composite motor function scores, balance and gait velocity (meta-analysis pooled HR = 1.94, 95% CI: 1.41, 2.65). Mixed results were found across different study samples for upper limb motor function, overall parkinsonism (meta-analysis pooled OR = 3.05, 95% CI: 1.31, 7.08), bradykinesia and rigidity. Studies restricted to older adults with Parkinson's Disease found weak or no association with incident dementia even for motor domains highly associated in less restrictive samples. Tremor was not associated with an increased risk of dementia in any population (meta-analysis pooled HR = 0.80, 95% CI 0.31, 2.03). lower limb motor function was associated with increased risk of developing dementia, while tremor and hand grip strength were not. Our results support future research investigating the inclusion of quantitative motor assessment, specifically gait velocity tests, for clinical dementia risk evaluation. © The Author 2017. Published by Oxford University Press on behalf of the British Geriatrics Society.All rights reserved. For permissions, please email: journals.permissions@oup.com

Accuracy of Presurgical Functional MR Imaging for Language Mapping of Brain Tumors: A Systematic Review and Meta-Analysis.

PubMed

Weng, Hsu-Huei; Noll, Kyle R; Johnson, Jason M; Prabhu, Sujit S; Tsai, Yuan-Hsiung; Chang, Sheng-Wei; Huang, Yen-Chu; Lee, Jiann-Der; Yang, Jen-Tsung; Yang, Cheng-Ta; Tsai, Ying-Huang; Yang, Chun-Yuh; Hazle, John D; Schomer, Donald F; Liu, Ho-Ling

2018-02-01

Purpose To compare functional magnetic resonance (MR) imaging for language mapping (hereafter, language functional MR imaging) with direct cortical stimulation (DCS) in patients with brain tumors and to assess factors associated with its accuracy. Materials and Methods PubMed/MEDLINE and related databases were searched for research articles published between January 2000 and September 2016. Findings were pooled by using bivariate random-effects and hierarchic summary receiver operating characteristic curve models. Meta-regression and subgroup analyses were performed to evaluate whether publication year, functional MR imaging paradigm, magnetic field strength, statistical threshold, and analysis software affected classification accuracy. Results Ten articles with a total of 214 patients were included in the analysis. On a per-patient basis, the pooled sensitivity and specificity of functional MR imaging was 44% (95% confidence interval [CI]: 14%, 78%) and 80% (95% CI: 54%, 93%), respectively. On a per-tag basis (ie, each DCS stimulation site or "tag" was considered a separate data point across all patients), the pooled sensitivity and specificity were 67% (95% CI: 51%, 80%) and 55% (95% CI: 25%, 82%), respectively. The per-tag analysis showed significantly higher sensitivity for studies with shorter functional MR imaging session times (P = .03) and relaxed statistical threshold (P = .05). Significantly higher specificity was found when expressive language task (P = .02), longer functional MR imaging session times (P < .01), visual presentation of stimuli (P = .04), and stringent statistical threshold (P = .01) were used. Conclusion Results of this study showed moderate accuracy of language functional MR imaging when compared with intraoperative DCS, and the included studies displayed significant methodologic heterogeneity. © RSNA, 2017 Online supplemental material is available for this article.

Hand function evaluation: a factor analysis study.

PubMed

Jarus, T; Poremba, R

1993-05-01

The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

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

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

Analysis of the functional gene structure and metabolic potential of microbial community in high arsenic groundwater.

PubMed

Li, Ping; Jiang, Zhou; Wang, Yanhong; Deng, Ye; Van Nostrand, Joy D; Yuan, Tong; Liu, Han; Wei, Dazhun; Zhou, Jizhong

2017-10-15

Microbial functional potential in high arsenic (As) groundwater ecosystems remains largely unknown. In this study, the microbial community functional composition of nineteen groundwater samples was investigated using a functional gene array (GeoChip 5.0). Samples were divided into low and high As groups based on the clustering analysis of geochemical parameters and microbial functional structures. The results showed that As related genes (arsC, arrA), sulfate related genes (dsrA and dsrB), nitrogen cycling related genes (ureC, amoA, and hzo) and methanogen genes (mcrA, hdrB) in groundwater samples were correlated with As, SO 4 2- , NH 4 + or CH 4 concentrations, respectively. Canonical correspondence analysis (CCA) results indicated that some geochemical parameters including As, total organic content, SO 4 2- , NH 4 + , oxidation-reduction potential (ORP) and pH were important factors shaping the functional microbial community structures. Alkaline and reducing conditions with relatively low SO 4 2- , ORP, and high NH 4 + , as well as SO 4 2- and Fe reduction and ammonification involved in microbially-mediated geochemical processes could be associated with As enrichment in groundwater. This study provides an overall picture of functional microbial communities in high As groundwater aquifers, and also provides insights into the critical role of microorganisms in As biogeochemical cycling. Copyright © 2017 Elsevier Ltd. All rights reserved.

Study of space shuttle orbiter system management computer function. Volume 1: Analysis, baseline design

NASA Technical Reports Server (NTRS)

1975-01-01

A system analysis of the shuttle orbiter baseline system management (SM) computer function is performed. This analysis results in an alternative SM design which is also described. The alternative design exhibits several improvements over the baseline, some of which are increased crew usability, improved flexibility, and improved growth potential. The analysis consists of two parts: an application assessment and an implementation assessment. The former is concerned with the SM user needs and design functional aspects. The latter is concerned with design flexibility, reliability, growth potential, and technical risk. The system analysis is supported by several topical investigations. These include: treatment of false alarms, treatment of off-line items, significant interface parameters, and a design evaluation checklist. An in-depth formulation of techniques, concepts, and guidelines for design of automated performance verification is discussed.

Functional Analysis and Treatment of Multiply Controlled Inappropriate Mealtime Behavior

ERIC Educational Resources Information Center

Bachmeyer, Melanie H.; Piazza, Cathleen C.; Fredrick, Laura D.; Reed, Gregory K.; Rivas, Kristi D.; Kadey, Heather J.

2009-01-01

Functional analyses identified children whose inappropriate mealtime behavior was maintained by escape and adult attention. Function-based extinction procedures were tested individually and in combination. Attention extinction alone did not result in decreases in inappropriate mealtime behavior or a significant increase in acceptance. By contrast,…

A Demonstration of Individual Preference for Novel Mands during Functional Communication Training

ERIC Educational Resources Information Center

Winborn-Kemmerer, Lisa; Ringdahl, Joel E.; Wacker, David P.; Kitsukawa, Kana

2009-01-01

Preference for mand topography was evaluated for 2 individuals with developmental disabilities who exhibited problem behavior. The results of a functional analysis showed that each participant's problem behavior was maintained by social reinforcement. Participants were taught two novel mand topographies for the same functional reinforcer, and each…

Classroom Application of a Trial-Based Functional Analysis

ERIC Educational Resources Information Center

Bloom, Sarah E.; Iwata, Brian A.; Fritz, Jennifer N.; Roscoe, Eileen M.; Carreau, Abbey B.

2011-01-01

We evaluated a trial-based approach to conducting functional analyses in classroom settings. Ten students referred for problem behavior were exposed to a series of assessment trials, which were interspersed among classroom activities throughout the day. Results of these trial-based functional analyses were compared to those of more traditional…

Statistical Time Series Models of Pilot Control with Applications to Instrument Discrimination

NASA Technical Reports Server (NTRS)

Altschul, R. E.; Nagel, P. M.; Oliver, F.

1984-01-01

A general description of the methodology used in obtaining the transfer function models and verification of model fidelity, frequency domain plots of the modeled transfer functions, numerical results obtained from an analysis of poles and zeroes obtained from z plane to s-plane conversions of the transfer functions, and the results of a study on the sequential introduction of other variables, both exogenous and endogenous into the loop are contained.

CXTFIT/Excel A modular adaptable code for parameter estimation, sensitivity analysis and uncertainty analysis for laboratory or field tracer experiments

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

Tang, Guoping; Mayes, Melanie; Parker, Jack C

2010-01-01

We implemented the widely used CXTFIT code in Excel to provide flexibility and added sensitivity and uncertainty analysis functions to improve transport parameter estimation and to facilitate model discrimination for multi-tracer experiments on structured soils. Analytical solutions for one-dimensional equilibrium and nonequilibrium convection dispersion equations were coded as VBA functions so that they could be used as ordinary math functions in Excel for forward predictions. Macros with user-friendly interfaces were developed for optimization, sensitivity analysis, uncertainty analysis, error propagation, response surface calculation, and Monte Carlo analysis. As a result, any parameter with transformations (e.g., dimensionless, log-transformed, species-dependent reactions, etc.) couldmore » be estimated with uncertainty and sensitivity quantification for multiple tracer data at multiple locations and times. Prior information and observation errors could be incorporated into the weighted nonlinear least squares method with a penalty function. Users are able to change selected parameter values and view the results via embedded graphics, resulting in a flexible tool applicable to modeling transport processes and to teaching students about parameter estimation. The code was verified by comparing to a number of benchmarks with CXTFIT 2.0. It was applied to improve parameter estimation for four typical tracer experiment data sets in the literature using multi-model evaluation and comparison. Additional examples were included to illustrate the flexibilities and advantages of CXTFIT/Excel. The VBA macros were designed for general purpose and could be used for any parameter estimation/model calibration when the forward solution is implemented in Excel. A step-by-step tutorial, example Excel files and the code are provided as supplemental material.« less

Independent Orbiter Assessment (IOA): Analysis of the auxiliary power unit

NASA Technical Reports Server (NTRS)

Barnes, J. E.

1986-01-01

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Orbiter Auxiliary Power Unit (APU). The APUs are required to provide power to the Orbiter hydraulics systems during ascent and entry flight phases for aerosurface actuation, main engine gimballing, landing gear extension, and other vital functions. For analysis purposes, the APU system was broken down into ten functional subsystems. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode. A preponderance of 1/1 criticality items were related to failures that allowed the hydrazine fuel to escape into the Orbiter aft compartment, creating a severe fire hazard, and failures that caused loss of the gas generator injector cooling system.

Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means

PubMed Central

2014-01-01

In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878

A Comparison of Functional Models for Use in the Function-Failure Design Method

NASA Technical Reports Server (NTRS)

Stock, Michael E.; Stone, Robert B.; Tumer, Irem Y.

2006-01-01

When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized functional and failure mode vocabularies are used. Two separate function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed functional models.

Stimulus-related independent component and voxel-wise analysis of human brain activity during free viewing of a feature film.

PubMed

Lahnakoski, Juha M; Salmi, Juha; Jääskeläinen, Iiro P; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

2012-01-01

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments.

Stimulus-Related Independent Component and Voxel-Wise Analysis of Human Brain Activity during Free Viewing of a Feature Film

PubMed Central

Lahnakoski, Juha M.; Salmi, Juha; Jääskeläinen, Iiro P.; Lampinen, Jouko; Glerean, Enrico; Tikka, Pia; Sams, Mikko

2012-01-01

Understanding how the brain processes stimuli in a rich natural environment is a fundamental goal of neuroscience. Here, we showed a feature film to 10 healthy volunteers during functional magnetic resonance imaging (fMRI) of hemodynamic brain activity. We then annotated auditory and visual features of the motion picture to inform analysis of the hemodynamic data. The annotations were fitted to both voxel-wise data and brain network time courses extracted by independent component analysis (ICA). Auditory annotations correlated with two independent components (IC) disclosing two functional networks, one responding to variety of auditory stimulation and another responding preferentially to speech but parts of the network also responding to non-verbal communication. Visual feature annotations correlated with four ICs delineating visual areas according to their sensitivity to different visual stimulus features. In comparison, a separate voxel-wise general linear model based analysis disclosed brain areas preferentially responding to sound energy, speech, music, visual contrast edges, body motion and hand motion which largely overlapped the results revealed by ICA. Differences between the results of IC- and voxel-based analyses demonstrate that thorough analysis of voxel time courses is important for understanding the activity of specific sub-areas of the functional networks, while ICA is a valuable tool for revealing novel information about functional connectivity which need not be explained by the predefined model. Our results encourage the use of naturalistic stimuli and tasks in cognitive neuroimaging to study how the brain processes stimuli in rich natural environments. PMID:22496909

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

PubMed

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

2000-01-01

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

Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis

PubMed Central

Sato, João Ricardo; Balardin, Joana; Vidal, Maciel Calebe; Fujita, André

2016-01-01

Background Several neuroimaging studies support the model of abnormal development of brain connectivity in patients with autism-spectrum disorders (ASD). In this study, we aimed to test the hypothesis of reduced functional network segregation in autistic patients compared with controls. Methods Functional MRI data from children acquired under a resting-state protocol (Autism Brain Imaging Data Exchange [ABIDE]) were submitted to both fuzzy spectral clustering (FSC) with entropy analysis and graph modularity analysis. Results We included data from 814 children in our analysis. We identified 5 regions of interest comprising the motor, temporal and occipito-temporal cortices with increased entropy (p < 0.05) in the clustering structure (i.e., more segregation in the controls). Moreover, we noticed a statistically reduced modularity (p < 0.001) in the autistic patients compared with the controls. Significantly reduced eigenvector centrality values (p < 0.05) in the patients were observed in the same regions that were identified in the FSC analysis. Limitations There is considerable heterogeneity in the fMRI acquisition protocols among the sites that contributed to the ABIDE data set (e.g., scanner type, pulse sequence, duration of scan and resting-state protocol). Moreover, the sites differed in many variables related to sample characterization (e.g., age, IQ and ASD diagnostic criteria). Therefore, we cannot rule out the possibility that additional differences in functional network organization would be found in a more homogeneous data sample of individuals with ASD. Conclusion Our results suggest that the organization of the whole-brain functional network in patients with ASD is different from that observed in controls, which implies a reduced modularity of the brain functional networks involved in sensorimotor, social, affective and cognitive processing. PMID:26505141

DFT Study of Small Gold Clusters, Au n (2≤ n ≤ 6): Stability and Charge Distribution Using M08-SO Functional

NASA Astrophysics Data System (ADS)

Carvalho, F. S.; Braga, J. P.

2018-05-01

We have investigated the more stable structures for small gold clusters, Aun (2≤ n ≤ 6), using the density functional theory method. Two functionals used in the literature, the well-known B3LYP and M06-L, were compared with the one that has not been used for this system yet, M08-SO, and the results for dimer were compared with experimental data. It was found that M08-SO gives the best results for the effective core potential and basis set tested. Therefore, the functional M08-SO was used for other structures. The planar geometries were found to have the lowest energies. After the geometry optimization, Mulliken populational analysis (MPA) and natural populational analysis (NPA) were carried out and the results for charge distribution in gold trimer and tetramer were compared with data found in literature. The MPA calculation does not give results in agreement with the literature. On the other hand, the NPA calculation gives coherent data. The results showed that the charge distribution will not always predict the more favorable site of interaction.

Macroevolutionary trends of atomic composition and related functional group proportion in eukaryotic and prokaryotic proteins.

PubMed

Zhang, Yu-Juan; Yang, Chun-Lin; Hao, You-Jin; Li, Ying; Chen, Bin; Wen, Jian-Fan

2014-01-25

To fully explore the trends of atomic composition during the macroevolution from prokaryote to eukaryote, five atoms (oxygen, sulfur, nitrogen, carbon, hydrogen) and related functional groups in prokaryotic and eukaryotic proteins were surveyed and compared. Genome-wide analysis showed that eukaryotic proteins have more oxygen, sulfur and nitrogen atoms than prokaryotes do. Clusters of Orthologous Groups (COG) analysis revealed that oxygen, sulfur, carbon and hydrogen frequencies are higher in eukaryotic proteins than in their prokaryotic orthologs. Furthermore, functional group analysis demonstrated that eukaryotic proteins tend to have higher proportions of sulfhydryl, hydroxyl and acylamino, but lower of sulfide and carboxyl. Taken together, an apparent trend of increase was observed for oxygen and sulfur atoms in the macroevolution; the variation of oxygen and sulfur compositions and their related functional groups in macroevolution made eukaryotic proteins carry more useful functional groups. These results will be helpful for better understanding the functional significances of atomic composition evolution. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

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

Orms, Natalie; Rehn, Dirk; Dreuw, Andreas

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such asmore » polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.« less

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

DOE PAGES

Orms, Natalie; Rehn, Dirk; Dreuw, Andreas; ...

2017-12-21

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such asmore » polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.« less

Functional approach in estimation of cultural ecosystem services of recreational areas

NASA Astrophysics Data System (ADS)

Sautkin, I. S.; Rogova, T. V.

2018-01-01

The article is devoted to the identification and analysis of cultural ecosystem services of recreational areas from the different forest plant functional groups in the suburbs of Kazan. The study explored two cultural ecosystem services supplied by forest plants by linking these services to different plant functional traits. Information on the functional traits of 76 plants occurring in the forest ecosystems of the investigated area was collected from reference books on the biological characteristics of plant species. Analysis of these species and traits with the Ward clustering method yielded four functional groups with different potentials for delivering ecosystem services. The results show that the contribution of species diversity to services can be characterized through the functional traits of plants. This proves that there is a stable relationship between biodiversity and the quality and quantity of ecosystem services. The proposed method can be extended to other types of services (regulating and supporting). The analysis can be used in the socio-economic assessment of natural ecosystems for recreation and other uses.

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia.

PubMed

Li, Tao; Wang, Qiang; Zhang, Jie; Rolls, Edmund T; Yang, Wei; Palaniyappan, Lena; Zhang, Lu; Cheng, Wei; Yao, Ye; Liu, Zhaowen; Gong, Xiaohong; Luo, Qiang; Tang, Yanqing; Crow, Timothy J; Broome, Matthew R; Xu, Ke; Li, Chunbo; Wang, Jijun; Liu, Zhening; Lu, Guangming; Wang, Fei; Feng, Jianfeng

2017-03-01

Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functional-connectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functional-connectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functional-connectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Distinct Aging Effects on Functional Networks in Good and Poor Cognitive Performers

PubMed Central

Lee, Annie; Tan, Mingzhen; Qiu, Anqi

2016-01-01

Brain network hubs are susceptible to normal aging processes and disruptions of their functional connectivity are detrimental to decline in cognitive functions in older adults. However, it remains unclear how the functional connectivity of network hubs cope with cognitive heterogeneity in an aging population. This study utilized cognitive and resting-state functional magnetic resonance imaging data, cluster analysis, and graph network analysis to examine age-related alterations in the network hubs’ functional connectivity of good and poor cognitive performers. Our results revealed that poor cognitive performers showed age-dependent disruptions in the functional connectivity of the right insula and posterior cingulate cortex (PCC), while good cognitive performers showed age-related disruptions in the functional connectivity of the left insula and PCC. Additionally, the left PCC had age-related declines in the functional connectivity with the left medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC). Most interestingly, good cognitive performers showed age-related declines in the functional connectivity of the left insula and PCC with their right homotopic structures. These results may provide insights of neuronal correlates for understanding individual differences in aging. In particular, our study suggests prominent protection roles of the left insula and PCC and bilateral ACC in good performers. PMID:27667972

A Cognitive Engineering Analysis of the Vertical Navigation (VNAV) Function

NASA Technical Reports Server (NTRS)

Sherry, Lance; Feary, Michael; Polson, Peter; Mumaw, Randall; Palmer, Everett

2001-01-01

A cognitive engineering analysis of the Flight Management System (FMS) Vertical Navigation (VNAV) function has identified overloading of the VNAV button and overloading of the Flight Mode Annunciator (FMA) used by the VNAV function. These two types of overloading, resulting in modal input devices and ambiguous feedback, are well known sources of operator confusion, and explain, in part, the operational issues experienced by airline pilots using VNAV in descent and approach. A proposal to modify the existing VNAV design to eliminate the overloading is discussed. The proposed design improves pilot's situational awareness of the VNAV function, and potentially reduces the cost of software development and improves safety.

Properties of dust and clouds in the Mars atmosphere: Analysis of Viking IRTM emission phase function sequences

NASA Technical Reports Server (NTRS)

Clancy, R. T.; Lee, S. W.

1991-01-01

An analysis of emission-phase-function (EPF) observations from the Viking Orbiter Infrared Thermal Mapper (IRTM) yields a wide variety of results regarding dust and cloud scattering in the Mars atmosphere and atmospheric-corrected albedos for the surface of Mars. A multiple scattering radiative transfer model incorporating a bidirectional phase function for the surface and atmospheric scattering by dust and clouds is used to derive surface albedos and dust and ice optical properties and optical depths for these various conditions on Mars.

Functional analysis and treatment of the diurnal bruxism of a 16-year-old girl with autism.

PubMed

Armstrong, Amy; Knapp, Vicki Madaus; McAdam, David B

2014-01-01

Bruxism is defined as the clenching and grinding of teeth. This study used a functional analysis to examine whether the bruxism of a 16-year-old girl with autism was maintained by automatic reinforcement or social consequences. A subsequent component analysis of the intervention package described by Barnoy, Najdowski, Tarbox, Wilke, and Nollet (2009) showed that a vocal reprimand (e.g., "stop grinding") effectively reduced the participant's bruxism. Results were maintained across time, and effects extended to novel staff members. © Society for the Experimental Analysis of Behavior.

Projection-based motion estimation for cardiac functional analysis with high temporal resolution: a proof-of-concept study with digital phantom experiment

NASA Astrophysics Data System (ADS)

Suzuki, Yuki; Fung, George S. K.; Shen, Zeyang; Otake, Yoshito; Lee, Okkyun; Ciuffo, Luisa; Ashikaga, Hiroshi; Sato, Yoshinobu; Taguchi, Katsuyuki

2017-03-01

Cardiac motion (or functional) analysis has shown promise not only for non-invasive diagnosis of cardiovascular diseases but also for prediction of cardiac future events. Current imaging modalities has limitations that could degrade the accuracy of the analysis indices. In this paper, we present a projection-based motion estimation method for x-ray CT that estimates cardiac motion with high spatio-temporal resolution using projection data and a reference 3D volume image. The experiment using a synthesized digital phantom showed promising results for motion analysis.

An approach to functionally relevant clustering of the protein universe: Active site profile‐based clustering of protein structures and sequences

PubMed Central

Knutson, Stacy T.; Westwood, Brian M.; Leuthaeuser, Janelle B.; Turner, Brandon E.; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D.; Harper, Angela F.; Brown, Shoshana D.; Morris, John H.; Ferrin, Thomas E.; Babbitt, Patricia C.

2017-01-01

Abstract Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification—amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two‐Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure‐Function Linkage Database, SFLD) self‐identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self‐identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well‐curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP‐identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F‐measure and performance analysis on the enolase search results and comparison to GEMMA and SCI‐PHY demonstrate that TuLIP avoids the over‐division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. PMID:28054422

An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.

PubMed

Knutson, Stacy T; Westwood, Brian M; Leuthaeuser, Janelle B; Turner, Brandon E; Nguyendac, Don; Shea, Gabrielle; Kumar, Kiran; Hayden, Julia D; Harper, Angela F; Brown, Shoshana D; Morris, John H; Ferrin, Thomas E; Babbitt, Patricia C; Fetrow, Jacquelyn S

2017-04-01

Protein function identification remains a significant problem. Solving this problem at the molecular functional level would allow mechanistic determinant identification-amino acids that distinguish details between functional families within a superfamily. Active site profiling was developed to identify mechanistic determinants. DASP and DASP2 were developed as tools to search sequence databases using active site profiling. Here, TuLIP (Two-Level Iterative clustering Process) is introduced as an iterative, divisive clustering process that utilizes active site profiling to separate structurally characterized superfamily members into functionally relevant clusters. Underlying TuLIP is the observation that functionally relevant families (curated by Structure-Function Linkage Database, SFLD) self-identify in DASP2 searches; clusters containing multiple functional families do not. Each TuLIP iteration produces candidate clusters, each evaluated to determine if it self-identifies using DASP2. If so, it is deemed a functionally relevant group. Divisive clustering continues until each structure is either a functionally relevant group member or a singlet. TuLIP is validated on enolase and glutathione transferase structures, superfamilies well-curated by SFLD. Correlation is strong; small numbers of structures prevent statistically significant analysis. TuLIP-identified enolase clusters are used in DASP2 GenBank searches to identify sequences sharing functional site features. Analysis shows a true positive rate of 96%, false negative rate of 4%, and maximum false positive rate of 4%. F-measure and performance analysis on the enolase search results and comparison to GEMMA and SCI-PHY demonstrate that TuLIP avoids the over-division problem of these methods. Mechanistic determinants for enolase families are evaluated and shown to correlate well with literature results. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Application of modified profile analysis to function testing of the motion/no-motion issue in an aircraft ground-handling simulation. [statistical analysis procedure for man machine systems flight simulation

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Mckissick, B. T.; Steinmetz, G. G.

1979-01-01

A recent modification of the methodology of profile analysis, which allows the testing for differences between two functions as a whole with a single test, rather than point by point with multiple tests is discussed. The modification is applied to the examination of the issue of motion/no motion conditions as shown by the lateral deviation curve as a function of engine cut speed of a piloted 737-100 simulator. The results of this application are presented along with those of more conventional statistical test procedures on the same simulator data.

Blind source separation in retinal videos

NASA Astrophysics Data System (ADS)

Barriga, Eduardo S.; Truitt, Paul W.; Pattichis, Marios S.; Tüso, Dan; Kwon, Young H.; Kardon, Randy H.; Soliz, Peter

2003-05-01

An optical imaging device of retina function (OID-RF) has been developed to measure changes in blood oxygen saturation due to neural activity resulting from visual stimulation of the photoreceptors in the human retina. The video data that are collected represent a mixture of the functional signal in response to the retinal activation and other signals from undetermined physiological activity. Measured changes in reflectance in response to the visual stimulus are on the order of 0.1% to 1.0% of the total reflected intensity level which makes the functional signal difficult to detect by standard methods since it is masked by the other signals that are present. In this paper, we apply principal component analysis (PCA), blind source separation (BSS), using Extended Spatial Decorrelation (ESD) and independent component analysis (ICA) using the Fast-ICA algorithm to extract the functional signal from the retinal videos. The results revealed that the functional signal in a stimulated retina can be detected through the application of some of these techniques.

Morphological and functional diversity in therizinosaur claws and the implications for theropod claw evolution.

PubMed

Lautenschlager, Stephan

2014-06-22

Therizinosaurs are a group of herbivorous theropod dinosaurs from the Cretaceous of North America and Asia, best known for their iconically large and elongate manual claws. However, among Therizinosauria, ungual morphology is highly variable, reflecting a general trend found in derived theropod dinosaurs (Maniraptoriformes). A combined approach of shape analysis to characterize changes in manual ungual morphology across theropods and finite-element analysis to assess the biomechanical properties of different ungual shapes in therizinosaurs reveals a functional diversity related to ungual morphology. While some therizinosaur taxa used their claws in a generalist fashion, other taxa were functionally adapted to use the claws as grasping hooks during foraging. Results further indicate that maniraptoriform dinosaurs deviated from the plesiomorphic theropod ungual morphology resulting in increased functional diversity. This trend parallels modifications of the cranial skeleton in derived theropods in response to dietary adaptation, suggesting that dietary diversification was a major driver for morphological and functional disparity in theropod evolution.

Uses, misuses, new uses and fundamental limitations of magnetic resonance imaging in cognitive science

PubMed Central

2016-01-01

When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574303

Uses, misuses, new uses and fundamental limitations of magnetic resonance imaging in cognitive science.

PubMed

Turner, Robert

2016-10-05

When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Authors.

Effect of exercise on cognitive function in chronic disease patients: a meta-analysis and systematic review of randomized controlled trials

PubMed Central

Cai, Hong; Li, Guichen; Hua, Shanshan; Liu, Yufei; Chen, Li

2017-01-01

Background The purpose of this study was to conduct a meta-analysis and systematic review to assess the effect of exercise on cognitive function in people with chronic diseases. Methods PubMed, Web of Science, Embase, the Cochrane Library, CINAHL, PsycINFO, and three Chinese databases were electronically searched for papers that were published until September 2016. This meta-analysis and systematic review included randomized controlled trials that evaluated the effect of exercise on cognitive function compared with control group for people with chronic diseases. Results Totally, 35 studies met the inclusion criteria, with 3,113 participants. The main analysis revealed a positive overall random effect of exercise intervention on cognitive function in patients with chronic diseases. The secondary analysis revealed that aerobic exercise interventions and aerobic included exercise interventions had a positive effect on cognition in patients with chronic diseases. The intervention offering low frequency had a positive effect on cognitive function in patients with chronic diseases. Finally, we found that interventions offered at both low exercise intensity and moderate exercise intensity had a positive effect on cognitive function in patients with chronic diseases. The secondary analysis also revealed that exercise interventions were beneficial in Alzheimer’s disease patients when grouped by disease type. Conclusion This meta-analysis and systematic review suggests that exercise interventions positively influence cognitive function in patients with chronic diseases. Beneficial effect was independent of the type of disease, type of exercise, frequency, and the intensity of the exercise intervention. PMID:28546744

The most common technologies and tools for functional genome analysis.

PubMed

Gasperskaja, Evelina; Kučinskas, Vaidutis

2017-01-01

Since the sequence of the human genome is complete, the main issue is how to understand the information written in the DNA sequence. Despite numerous genome-wide studies that have already been performed, the challenge to determine the function of genes, gene products, and also their interaction is still open. As changes in the human genome are highly likely to cause pathological conditions, functional analysis is vitally important for human health. For many years there have been a variety of technologies and tools used in functional genome analysis. However, only in the past decade there has been rapid revolutionizing progress and improvement in high-throughput methods, which are ranging from traditional real-time polymerase chain reaction to more complex systems, such as next-generation sequencing or mass spectrometry. Furthermore, not only laboratory investigation, but also accurate bioinformatic analysis is required for reliable scientific results. These methods give an opportunity for accurate and comprehensive functional analysis that involves various fields of studies: genomics, epigenomics, proteomics, and interactomics. This is essential for filling the gaps in the knowledge about dynamic biological processes at both cellular and organismal level. However, each method has both advantages and limitations that should be taken into account before choosing the right method for particular research in order to ensure successful study. For this reason, the present review paper aims to describe the most frequent and widely-used methods for the comprehensive functional analysis.

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods.

PubMed

Salvatore, Stefania; Bramness, Jørgen Gustav; Reid, Malcolm J; Thomas, Kevin Victor; Harman, Christopher; Røislien, Jo

2015-01-01

Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities' scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

An arc tangent function demodulation method of fiber-optic Fabry-Perot high-temperature pressure sensor

NASA Astrophysics Data System (ADS)

Ren, Qianyu; Li, Junhong; Hong, Yingping; Jia, Pinggang; Xiong, Jijun

2017-09-01

A new demodulation algorithm of the fiber-optic Fabry-Perot cavity length based on the phase generated carrier (PGC) is proposed in this paper, which can be applied in the high-temperature pressure sensor. This new algorithm based on arc tangent function outputs two orthogonal signals by utilizing an optical system, which is designed based on the field-programmable gate array (FPGA) to overcome the range limit of the original PGC arc tangent function demodulation algorithm. The simulation and analysis are also carried on. According to the analysis of demodulation speed and precision, the simulation of different numbers of sampling points, and measurement results of the pressure sensor, the arc tangent function demodulation method has good demodulation results: 1 MHz processing speed of single data and less than 1% error showing practical feasibility in the fiber-optic Fabry-Perot cavity length demodulation of the Fabry-Perot high-temperature pressure sensor.

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

PubMed Central

Seeley, Matthew K.; Francom, Devin; Reese, C. Shane; Hopkins, J. Ty

2017-01-01

Abstract In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function. PMID:29339984

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach.

PubMed

Park, Jihong; Seeley, Matthew K; Francom, Devin; Reese, C Shane; Hopkins, J Ty

2017-12-01

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

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

Park, Jihong; Seeley, Matthew K.; Francom, Devin

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle,more » knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. Thus when using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.« less

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

DOE PAGES

Park, Jihong; Seeley, Matthew K.; Francom, Devin; ...

2017-12-28

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle,more » knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. Thus when using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.« less

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results

PubMed Central

Morelli, Maria Sole; Giannoni, Alberto; Passino, Claudio; Landini, Luigi; Emdin, Michele; Vanello, Nicola

2016-01-01

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings. PMID:27809243

ReSeqTools: an integrated toolkit for large-scale next-generation sequencing based resequencing analysis.

PubMed

He, W; Zhao, S; Liu, X; Dong, S; Lv, J; Liu, D; Wang, J; Meng, Z

2013-12-04

Large-scale next-generation sequencing (NGS)-based resequencing detects sequence variations, constructs evolutionary histories, and identifies phenotype-related genotypes. However, NGS-based resequencing studies generate extraordinarily large amounts of data, making computations difficult. Effective use and analysis of these data for NGS-based resequencing studies remains a difficult task for individual researchers. Here, we introduce ReSeqTools, a full-featured toolkit for NGS (Illumina sequencing)-based resequencing analysis, which processes raw data, interprets mapping results, and identifies and annotates sequence variations. ReSeqTools provides abundant scalable functions for routine resequencing analysis in different modules to facilitate customization of the analysis pipeline. ReSeqTools is designed to use compressed data files as input or output to save storage space and facilitates faster and more computationally efficient large-scale resequencing studies in a user-friendly manner. It offers abundant practical functions and generates useful statistics during the analysis pipeline, which significantly simplifies resequencing analysis. Its integrated algorithms and abundant sub-functions provide a solid foundation for special demands in resequencing projects. Users can combine these functions to construct their own pipelines for other purposes.

Benchmarking the Performance of Exchange-Correlation Functionals for Predicting Two-Photon Absorption Strengths.

PubMed

Beerepoot, Maarten T P; Alam, Md Mehboob; Bednarska, Joanna; Bartkowiak, Wojciech; Ruud, Kenneth; Zaleśny, Robert

2018-06-15

The present work investigates the performance of exchange-correlation functionals in the prediction of two-photon absorption (2PA) strengths. For this purpose, we considered six common functionals used for studying 2PA processes and tested these on six organoboron chelates. The set consisted of two semilocal (PBE and BLYP), two hybrid (B3LYP and PBE0), and two range-separated (LC-BLYP and CAM-B3LYP) functionals. The RI-CC2 method was chosen as a reference level and was found to give results consistent with the experimental data that are available for three of the molecules considered. Of the six exchange-correlation functionals studied, only the range-separated functionals predict an ordering of the 2PA strengths that is consistent with experimental and RI-CC2 results. Even though the range-separated functionals predict correct relative trends, the absolute values for the 2PA strengths are underestimated by a factor of 2-6 for the molecules considered. An in-depth analysis, on the basis of the derived generalized few-state model expression for the 2PA strength for a coupled-cluster wave function, reveals that the problem with these functionals can be linked to underestimated excited-state dipole moments and, to a lesser extent, overestimated excitation energies. The semilocal and hybrid functionals exhibit less predictable errors and a variation in the 2PA strengths in disagreement with the reference results. The semilocal and hybrid functionals show smaller average errors than the range-separated functionals, but our analysis reveals that this is due to fortuitous error cancellation between excitation energies and the transition dipole moments. Our results constitute a warning against using currently available exchange-correlation functionals in the prediction of 2PA strengths and highlight the need for functionals that correctly describe the electron density of excited electronic states.

Adverbials of Result: Phraseology and Functions in the Problem-Solution Pattern

ERIC Educational Resources Information Center

Charles, Maggie

2011-01-01

This paper combines the use of corpus techniques with discourse analysis in order to investigate adverbials of result in the writing of advanced academic student writers. It focuses in detail on the phraseology and functions of "thus," "therefore," "then," "hence," "so" and "consequently." Two corpora of native-speaker theses are examined: 190,000…

In vivo microvascular and macrovascular endothelial function is not associated with circulating dimethylarginines in patients with rheumatoid arthritis: a prospective analysis of the DRACCO cohort.

PubMed

Dimitroulas, Theodoros; Sandoo, Aamer; Hodson, James; Smith, Jacqueline P; Kitas, George D

2016-07-01

To examine associations between asymmetric (ADMA), symmetric dimethylarginine (SDMA) and ADMA:SDMA ratio with assessments of endothelial function and coronary artery perfusion in RA patients. ADMA and SDMA levels were measured in 197 RA individuals [144 (77.4%) females, median age: 66 years (quartiles: 59-73)]. Patients underwent assessments of microvascular endothelium-dependent and endothelium-independent function, macrovascular endothelium-dependent and endothelium-independent function and vascular morphology (pulse wave analysis, carotid intima-media thickness (cIMT), and carotid plaque). Coronary perfusion was assessed by subendocardial viability ratio (SEVR). SEVR correlated with SDMA (r = 0.172, p = 0.026) and ADMA:SDMA (r = -0.160, p = 0.041) in univariable analysis, but not in multivariable analysis accounting for confounding factors. Neither ADMA:SDMA ratio nor SDMA were significantly correlated with microvascular or macrovascular endothelial function, or with arterial stiffness and cIMT. Within subgroup of patients (n = 26) with high inflammatory markers, a post-hoc analysis showed that SDMA and the ADMA:SDMA ratio were significantly associated with endothelium-dependent microvascular function in univariable analysis, with Pearson's r correlation coefficients of -0.440 (p = 0.031) and 0.511 (p = 0.011), respectively. Similar finding were established between ADMA:SDMA ratio and arterial stiffness in univariable analysis, with Pearson's r of 0.493, (p = 0.024). Dimethylarginines were not found to be significantly associated with several assessments of vascular function and morphology in patients with RA, however, post-hoc analysis indicates that there may be associations in patients with raised inflammatory markers. Our results suggest that dysregulated NO metabolism may not be the sole mechanism for the development of preclinical atherosclerosis in RA.

Semi-supervised clustering for parcellating brain regions based on resting state fMRI data

NASA Astrophysics Data System (ADS)

Cheng, Hewei; Fan, Yong

2014-03-01

Many unsupervised clustering techniques have been adopted for parcellating brain regions of interest into functionally homogeneous subregions based on resting state fMRI data. However, the unsupervised clustering techniques are not able to take advantage of exiting knowledge of the functional neuroanatomy readily available from studies of cytoarchitectonic parcellation or meta-analysis of the literature. In this study, we propose a semi-supervised clustering method for parcellating amygdala into functionally homogeneous subregions based on resting state fMRI data. Particularly, the semi-supervised clustering is implemented under the framework of graph partitioning, and adopts prior information and spatial consistent constraints to obtain a spatially contiguous parcellation result. The graph partitioning problem is solved using an efficient algorithm similar to the well-known weighted kernel k-means algorithm. Our method has been validated for parcellating amygdala into 3 subregions based on resting state fMRI data of 28 subjects. The experiment results have demonstrated that the proposed method is more robust than unsupervised clustering and able to parcellate amygdala into centromedial, laterobasal, and superficial parts with improved functionally homogeneity compared with the cytoarchitectonic parcellation result. The validity of the parcellation results is also supported by distinctive functional and structural connectivity patterns of the subregions and high consistency between coactivation patterns derived from a meta-analysis and functional connectivity patterns of corresponding subregions.

Zebra: a web server for bioinformatic analysis of diverse protein families.

PubMed

Suplatov, Dmitry; Kirilin, Evgeny; Takhaveev, Vakil; Svedas, Vytas

2014-01-01

During evolution of proteins from a common ancestor, one functional property can be preserved while others can vary leading to functional diversity. A systematic study of the corresponding adaptive mutations provides a key to one of the most challenging problems of modern structural biology - understanding the impact of amino acid substitutions on protein function. The subfamily-specific positions (SSPs) are conserved within functional subfamilies but are different between them and, therefore, seem to be responsible for functional diversity in protein superfamilies. Consequently, a corresponding method to perform the bioinformatic analysis of sequence and structural data has to be implemented in the common laboratory practice to study the structure-function relationship in proteins and develop novel protein engineering strategies. This paper describes Zebra web server - a powerful remote platform that implements a novel bioinformatic analysis algorithm to study diverse protein families. It is the first application that provides specificity determinants at different levels of functional classification, therefore addressing complex functional diversity of large superfamilies. Statistical analysis is implemented to automatically select a set of highly significant SSPs to be used as hotspots for directed evolution or rational design experiments and analyzed studying the structure-function relationship. Zebra results are provided in two ways - (1) as a single all-in-one parsable text file and (2) as PyMol sessions with structural representation of SSPs. Zebra web server is available at http://biokinet.belozersky.msu.ru/zebra .

A new feedback image encryption scheme based on perturbation with dynamical compound chaotic sequence cipher generator

NASA Astrophysics Data System (ADS)

Tong, Xiaojun; Cui, Minggen; Wang, Zhu

2009-07-01

The design of the new compound two-dimensional chaotic function is presented by exploiting two one-dimensional chaotic functions which switch randomly, and the design is used as a chaotic sequence generator which is proved by Devaney's definition proof of chaos. The properties of compound chaotic functions are also proved rigorously. In order to improve the robustness against difference cryptanalysis and produce avalanche effect, a new feedback image encryption scheme is proposed using the new compound chaos by selecting one of the two one-dimensional chaotic functions randomly and a new image pixels method of permutation and substitution is designed in detail by array row and column random controlling based on the compound chaos. The results from entropy analysis, difference analysis, statistical analysis, sequence randomness analysis, cipher sensitivity analysis depending on key and plaintext have proven that the compound chaotic sequence cipher can resist cryptanalytic, statistical and brute-force attacks, and especially it accelerates encryption speed, and achieves higher level of security. By the dynamical compound chaos and perturbation technology, the paper solves the problem of computer low precision of one-dimensional chaotic function.

Discriminant analysis in wildlife research: Theory and applications

USGS Publications Warehouse

Williams, B.K.; Capen, D.E.

1981-01-01

Discriminant analysis, a method of analyzing grouped multivariate data, is often used in ecological investigations. It has both a predictive and an explanatory function, the former aiming at classification of individuals of unknown group membership. The goal of the latter function is to exhibit group separation by means of linear transforms, and the corresponding method is called canonical analysis. This discussion focuses on the application of canonical analysis in ecology. In order to clarify its meaning, a parametric approach is taken instead of the usual data-based formulation. For certain assumptions the data-based canonical variates are shown to result from maximum likelihood estimation, thus insuring consistency and asymptotic efficiency. The distorting effects of covariance heterogeneity are examined, as are certain difficulties which arise in interpreting the canonical functions. A 'distortion metric' is defined, by means of which distortions resulting from the canonical transformation can be assessed. Several sampling problems which arise in ecological applications are considered. It is concluded that the method may prove valuable for data exploration, but is of limited value as an inferential procedure.

Poly(styrene-co-N-methacryloyl-l-phenylalanine methyl ester)-functionalized magnetic nanoparticles as sorbents for the analysis of sodium benzoate in beverages.

PubMed

Ji, Shilei; Li, Nan; Qi, Li; Wang, Minglin

2017-01-01

In this study, poly(styrene-co-N-methacryloyl-l-phenylalanine methyl ester)-functionalized magnetic nanoparticles were constructed and used as magnetic solid-phase extraction sorbents for analysis of food preservatives in beverages. To prepare the poly(amino acid)-based sorbents, N-methacryloyl-l-phenylalanine methyl ester, and styrene served as the functional monomers and modified onto the magnetic nanoparticles via free radical polymerization. Interestingly, compared with propylparaben and potassium sorbate, the proposed poly(amino acid)-based sorbents showed a good selectivity to sodium benzoate. The adsorption capacity of the sorbents to sodium benzoate was 6.08 ± 0.31 mg/g. Moreover, the fast adsorption equilibrium could be reached within 5 min. Further, the resultant poly(amino acid)-based sorbents were applied in the analysis of sodium benzoate in real beverage samples. The results proved that the proposed magnetic solid-phase extraction sorbents have a great potential for the analysis of preservatives in food samples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effects of Different Levels of Intra-Abdominal Pressure on the Postoperative Hepatic Function of Patients Undergoing Laparoscopic Cholecystectomy: A Systematic Review and Meta-Analysis.

PubMed

Cheng, Zheng-Jun; Wang, Yun-Bing; Chen, Long; Gong, Jian-Ping; Zhang, Wei

2018-04-18

The aim of this meta-analysis is to compare the differences in postoperative markers of the hepatic function under different intra-abdominal pressures in laparoscopic cholecystectomy (LC). Several databases were searched for control studies, and then the weighted data were pooled with random-effect models. A total of 11 studies involving 865 patients were included. The meta-analysis reveals that the level of the aspartate aminotransferase and alanine transaminase of the low-pressure group has a lower postoperative increase than the moderate-pressure group (P<0.001). The level of the aspartate aminotransferase and alanine transaminase of the moderate-pressure group has a lower postoperative increase than the high-pressure group (P<0.001). Totally, the effect of lower pressure LC on postoperative hepatic functions is less significant than that of the higher one. Potential subgroup analysis does not modify these results. The recommended pressure in LC is suggested to be lower so as to result in a better surgical safety, especially for special populations.

Functional Communication Training and Chained Schedules of Reinforcement to Treat Challenging Behavior Maintained by Terminations of Activity Interruptions

ERIC Educational Resources Information Center

Falcomata, Terry S.; Roane, Henry S.; Muething, Colin S.; Stephenson, Kasey M.; Ing, Anna D.

2012-01-01

In this article, the authors evaluated functional communication training (FCT) and a chained schedule of reinforcement for the treatment of challenging behavior exhibited by two individuals diagnosed with Asperger syndrome and autism, respectively. Following a functional analysis with undifferentiated results, the authors demonstrated that…

Functional Analysis Identified Habit Reversal Components for the Treatment of Motor Tics

ERIC Educational Resources Information Center

Dufrene, Brad A.; Harpole, Lauren Lestremau; Sterling, Heather E.; Perry, Erin J.; Burton, Britney; Zoder-Martell, Kimberly

2013-01-01

This study included brief functional analyses and treatment for motor tics exhibited by two children with Tourette Syndrome. Brief functional analyses were conducted in an outpatient treatment center and results were used to develop individualized habit reversal procedures. Treatment data were collected in clinic for one child and in clinic and…

ANALYSES OF RESPONSE–STIMULUS SEQUENCES IN DESCRIPTIVE OBSERVATIONS

PubMed Central

Samaha, Andrew L; Vollmer, Timothy R; Borrero, Carrie; Sloman, Kimberly; Pipkin, Claire St. Peter; Bourret, Jason

2009-01-01

Descriptive observations were conducted to record problem behavior displayed by participants and to record antecedents and consequences delivered by caregivers. Next, functional analyses were conducted to identify reinforcers for problem behavior. Then, using data from the descriptive observations, lag-sequential analyses were conducted to examine changes in the probability of environmental events across time in relation to occurrences of problem behavior. The results of the lag-sequential analyses were interpreted in light of the results of functional analyses. Results suggested that events identified as reinforcers in a functional analysis followed behavior in idiosyncratic ways: after a range of delays and frequencies. Thus, it is possible that naturally occurring reinforcement contingencies are arranged in ways different from those typically evaluated in applied research. Further, these complex response–stimulus relations can be represented by lag-sequential analyses. However, limitations to the lag-sequential analysis are evident. PMID:19949537

Non-Inferential Multi-Subject Study of Functional Connectivity during Visual Stimulation.

PubMed

Esposito, F; Cirillo, M; Aragri, A; Caranci, F; Cirillo, L; Di Salle, F; Cirillo, S

2007-01-31

Independent component analysis (ICA) is a powerful technique for the multivariate, non-inferential, data-driven analysis of functional magnetic resonance imaging (fMRI) data-sets. The non-inferential nature of ICA makes this a suitable technique for the study of complex mental states whose temporal evolution would be difficult to describe analytically in terms of classical statistical regressors. Taking advantage of this feature, ICA can extract a number of functional connectivity patterns regardless of the task executed by the subject. The technique is so powerful that functional connectivity patterns can be derived even when the subject is just resting in the scanner, opening the opportunity for functional investigation of the human mind at its basal "default" state, which has been proposed to be altered in several brain disorders. However, one major drawback of ICA consists in the difficulty of managing its results, which are not represented by a single functional image as in inferential studies. This produces the need for a classification of ICA results and exacerbates the difficulty of obtaining group "averaged" functional connectivity patterns, while preserving the interpretation of individual differences. Addressing the subject-level variability in the very same framework of "grouping" appears to be a favourable approach towards the clinical evaluation and application of ICA-based methodologies. Here we present a novel strategy for group-level ICA analyses, namely the self-organizing group-level ICA (sog-ICA), which is used on visual activation fMRI data from a block-design experiment repeated on six subjects. We propose the sog-ICA as a multi-subject analysis tool for grouping ICA data while assessing the similarity and variability of the fMRI results of individual subject decompositions.

Sampling with poling-based flux balance analysis: optimal versus sub-optimal flux space analysis of Actinobacillus succinogenes.

PubMed

Binns, Michael; de Atauri, Pedro; Vlysidis, Anestis; Cascante, Marta; Theodoropoulos, Constantinos

2015-02-18

Flux balance analysis is traditionally implemented to identify the maximum theoretical flux for some specified reaction and a single distribution of flux values for all the reactions present which achieve this maximum value. However it is well known that the uncertainty in reaction networks due to branches, cycles and experimental errors results in a large number of combinations of internal reaction fluxes which can achieve the same optimal flux value. In this work, we have modified the applied linear objective of flux balance analysis to include a poling penalty function, which pushes each new set of reaction fluxes away from previous solutions generated. Repeated poling-based flux balance analysis generates a sample of different solutions (a characteristic set), which represents all the possible functionality of the reaction network. Compared to existing sampling methods, for the purpose of generating a relatively "small" characteristic set, our new method is shown to obtain a higher coverage than competing methods under most conditions. The influence of the linear objective function on the sampling (the linear bias) constrains optimisation results to a subspace of optimal solutions all producing the same maximal fluxes. Visualisation of reaction fluxes plotted against each other in 2 dimensions with and without the linear bias indicates the existence of correlations between fluxes. This method of sampling is applied to the organism Actinobacillus succinogenes for the production of succinic acid from glycerol. A new method of sampling for the generation of different flux distributions (sets of individual fluxes satisfying constraints on the steady-state mass balances of intermediates) has been developed using a relatively simple modification of flux balance analysis to include a poling penalty function inside the resulting optimisation objective function. This new methodology can achieve a high coverage of the possible flux space and can be used with and without linear bias to show optimal versus sub-optimal solution spaces. Basic analysis of the Actinobacillus succinogenes system using sampling shows that in order to achieve the maximal succinic acid production CO₂ must be taken into the system. Solutions involving release of CO₂ all give sub-optimal succinic acid production.

Experimental support for the foldability-function tradeoff hypothesis: segregation of the folding nucleus and functional regions in fibroblast growth factor-1.

PubMed

Longo, Liam; Lee, Jihun; Blaber, Michael

2012-12-01

The acquisition of function is often associated with destabilizing mutations, giving rise to the stability-function tradeoff hypothesis. To test whether function is also accommodated at the expense of foldability, fibroblast growth factor-1 (FGF-1) was subjected to a comprehensive φ-value analysis at each of the 11 turn regions. FGF-1, a β-trefoil fold, represents an excellent model system with which to evaluate the influence of function on foldability: because of its threefold symmetric structure, analysis of FGF-1 allows for direct comparisons between symmetry-related regions of the protein that are associated with function to those that are not; thus, a structural basis for regions of foldability can potentially be identified. The resulting φ-value distribution of FGF-1 is highly polarized, with the majority of positions described as either folded-like or denatured-like in the folding transition state. Regions important for folding are shown to be asymmetrically distributed within the protein architecture; furthermore, regions associated with function (i.e., heparin-binding affinity and receptor-binding affinity) are localized to regions of the protein that fold after barrier crossing (late in the folding pathway). These results provide experimental support for the foldability-function tradeoff hypothesis in the evolution of FGF-1. Notably, the results identify the potential for folding redundancy in symmetric protein architecture with important implications for protein evolution and design. Copyright © 2012 The Protein Society.

A framework for joint image-and-shape analysis

NASA Astrophysics Data System (ADS)

Gao, Yi; Tannenbaum, Allen; Bouix, Sylvain

2014-03-01

Techniques in medical image analysis are many times used for the comparison or regression on the intensities of images. In general, the domain of the image is a given Cartesian grids. Shape analysis, on the other hand, studies the similarities and differences among spatial objects of arbitrary geometry and topology. Usually, there is no function defined on the domain of shapes. Recently, there has been a growing needs for defining and analyzing functions defined on the shape space, and a coupled analysis on both the shapes and the functions defined on them. Following this direction, in this work we present a coupled analysis for both images and shapes. As a result, the statistically significant discrepancies in both the image intensities as well as on the underlying shapes are detected. The method is applied on both brain images for the schizophrenia and heart images for atrial fibrillation patients.

A Meta-Analysis of Differences in IQ Profiles between Individuals with Asperger's Disorder and High-Functioning Autism

ERIC Educational Resources Information Center

Chiang, Hsu-Min; Tsai, Luke Y.; Cheung, Ying Kuen; Brown, Alice; Li, Huacheng

2014-01-01

A meta-analysis was performed to examine differences in IQ profiles between individuals with Asperger's disorder (AspD) and high-functioning autism (HFA). Fifty-two studies were included for this study. The results showed that (a) individuals with AspD had significantly higher full-scale IQ, verbal IQ (VIQ), and performance IQ (PIQ) than did…

Model-Based Segmentation of Cortical Regions of Interest for Multi-subject Analysis of fMRI Data

NASA Astrophysics Data System (ADS)

Engel, Karin; Brechmann, Andr'e.; Toennies, Klaus

The high inter-subject variability of human neuroanatomy complicates the analysis of functional imaging data across subjects. We propose a method for the correct segmentation of cortical regions of interest based on the cortical surface. First results on the segmentation of Heschl's gyrus indicate the capability of our approach for correct comparison of functional activations in relation to individual cortical patterns.

Noncoding sequence classification based on wavelet transform analysis: part II

NASA Astrophysics Data System (ADS)

Paredes, O.; Strojnik, M.; Romo-Vázquez, R.; Vélez-Pérez, H.; Ranta, R.; Garcia-Torales, G.; Scholl, M. K.; Morales, J. A.

2017-09-01

DNA sequences in human genome can be divided into the coding and noncoding ones. We hypothesize that the characteristic periodicities of the noncoding sequences are related to their function. We describe the procedure to identify these characteristic periodicities using the wavelet analysis. Our results show that three groups of noncoding sequences, each one with different biological function, may be differentiated by their wavelet coefficients within specific frequency range.

Availability Estimate of a Conceptual ESM System.

DTIC Science & Technology

1979-06-01

affect mission operation.t A functional block level failure modes and effects analysis ( FMEA ) performed on the filter resulted in an assessed failure rate...is based on an FMEA of failures that disable the function (see Appendix A). A further 29 examination of the filter piece-parts reveals that the driver...Digital-to-analog converter DC Direct current DF Direction finding ESM Electronic Support Measures FMEA Failure modes and effects analysis FMPO

Dark Energy Survey Year 1 Results: Methodology and Projections for Joint Analysis of Galaxy Clustering, Galaxy Lensing, and CMB Lensing Two-point Functions

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

Giannantonio, T.; et al.

Optical imaging surveys measure both the galaxy density and the gravitational lensing-induced shear fields across the sky. Recently, the Dark Energy Survey (DES) collaboration used a joint fit to two-point correlations between these observables to place tight constraints on cosmology (DES Collaboration et al. 2017). In this work, we develop the methodology to extend the DES Collaboration et al. (2017) analysis to include cross-correlations of the optical survey observables with gravitational lensing of the cosmic microwave background (CMB) as measured by the South Pole Telescope (SPT) and Planck. Using simulated analyses, we show how the resulting set of five two-pointmore » functions increases the robustness of the cosmological constraints to systematic errors in galaxy lensing shear calibration. Additionally, we show that contamination of the SPT+Planck CMB lensing map by the thermal Sunyaev-Zel'dovich effect is a potentially large source of systematic error for two-point function analyses, but show that it can be reduced to acceptable levels in our analysis by masking clusters of galaxies and imposing angular scale cuts on the two-point functions. The methodology developed here will be applied to the analysis of data from the DES, the SPT, and Planck in a companion work.« less

A proteome view of structural, functional, and taxonomic characteristics of major protein domain clusters.

PubMed

Sun, Chia-Tsen; Chiang, Austin W T; Hwang, Ming-Jing

2017-10-27

Proteome-scale bioinformatics research is increasingly conducted as the number of completely sequenced genomes increases, but analysis of protein domains (PDs) usually relies on similarity in their amino acid sequences and/or three-dimensional structures. Here, we present results from a bi-clustering analysis on presence/absence data for 6,580 unique PDs in 2,134 species with a sequenced genome, thus covering a complete set of proteins, for the three superkingdoms of life, Bacteria, Archaea, and Eukarya. Our analysis revealed eight distinctive PD clusters, which, following an analysis of enrichment of Gene Ontology functions and CATH classification of protein structures, were shown to exhibit structural and functional properties that are taxa-characteristic. For examples, the largest cluster is ubiquitous in all three superkingdoms, constituting a set of 1,472 persistent domains created early in evolution and retained in living organisms and characterized by basic cellular functions and ancient structural architectures, while an Archaea and Eukarya bi-superkingdom cluster suggests its PDs may have existed in the ancestor of the two superkingdoms, and others are single superkingdom- or taxa (e.g. Fungi)-specific. These results contribute to increase our appreciation of PD diversity and our knowledge of how PDs are used in species, yielding implications on species evolution.

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis.

PubMed

Quintela-del-Río, Alejandro; Francisco-Fernández, Mario

2011-02-01

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Mixed kernel function support vector regression for global sensitivity analysis

NASA Astrophysics Data System (ADS)

Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

2017-11-01

Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

An Analysis of Risk and Function Information in Early Stage Design

NASA Technical Reports Server (NTRS)

Barrientos, Francesca; Tumer, Irem; Grantham, Katie; VanWie, Michael; Stone, Robert

2005-01-01

The concept of function offers a high potential for thinking and reasoning about designs as well as providing a common thread for relating together other design information. This paper focuses specifically on the relation between function and risk by examining how this information is addressed for a design team conducting early stage design for space missions. Risk information is decomposed into a set of key attributes which are then used to scrutinize the risk information using three approaches from the pragmatics sub-field of linguistics: i) Gricean, ii) Relevance Theory, and Functional Analysis. Results of this linguistics-based approach descriptively account for the context of designer communication with respect to function and risk, and offer prescriptive guidelines for improving designer communication.

On the Power of Abstract Interpretation

NASA Technical Reports Server (NTRS)

Reddy, Uday S.; Kamin, Samuel N.

1991-01-01

Increasingly sophisticated applications of static analysis place increased burden on the reliability of the analysis techniques. Often, the failure of the analysis technique to detect some information my mean that the time or space complexity of the generated code would be altered. Thus, it is important to precisely characterize the power of static analysis techniques. We follow the approach of Selur et. al. who studied the power of strictness analysis techniques. Their result can be summarized by saying 'strictness analysis is perfect up to variations in constants.' In other words, strictness analysis is as good as it could be, short of actually distinguishing between concrete values. We use this approach to characterize a broad class of analysis techniques based on abstract interpretation including, but not limited to, strictness analysis. For the first-order case, we consider abstract interpretations where the abstract domain for data values is totally ordered. This condition is satisfied by Mycroft's strictness analysis that of Sekar et. al. and Wadler's analysis of list-strictness. For such abstract interpretations, we show that the analysis is complete in the sense that, short of actually distinguishing between concrete values with the same abstraction, it gives the best possible information. We further generalize these results to typed lambda calculus with pairs and higher-order functions. Note that products and function spaces over totally ordered domains are not totally ordered. In fact, the notion of completeness used in the first-order case fails if product domains or function spaces are added. We formulate a weaker notion of completeness based on observability of values. Two values (including pairs and functions) are considered indistinguishable if their observable components are indistinguishable. We show that abstract interpretation of typed lambda calculus programs is complete up to this notion of indistinguishability. We use denotationally-oriented arguments instead of the detailed operational arguments used by Selur et. al.. Hence, our proofs are much simpler. They should be useful for further future improvements.

Differential expression of pancreatic protein and chemosensing receptor mRNAs in NKCC1-null intestine

PubMed Central

Bradford, Emily M; Vairamani, Kanimozhi; Shull, Gary E

2016-01-01

AIM: To investigate the intestinal functions of the NKCC1 Na+-K+-2Cl cotransporter (SLC12a2 gene), differential mRNA expression changes in NKCC1-null intestine were analyzed. METHODS: Microarray analysis of mRNA from intestines of adult wild-type mice and gene-targeted NKCC1-null mice (n = 6 of each genotype) was performed to identify patterns of differential gene expression changes. Differential expression patterns were further examined by Gene Ontology analysis using the online Gorilla program, and expression changes of selected genes were verified using northern blot analysis and quantitative real time-polymerase chain reaction. Histological staining and immunofluorescence were performed to identify cell types in which upregulated pancreatic digestive enzymes were expressed. RESULTS: Genes typically associated with pancreatic function were upregulated. These included lipase, amylase, elastase, and serine proteases indicative of pancreatic exocrine function, as well as insulin and regenerating islet genes, representative of endocrine function. Northern blot analysis and immunohistochemistry showed that differential expression of exocrine pancreas mRNAs was specific to the duodenum and localized to a subset of goblet cells. In addition, a major pattern of changes involving differential expression of olfactory receptors that function in chemical sensing, as well as other chemosensing G-protein coupled receptors, was observed. These changes in chemosensory receptor expression may be related to the failure of intestinal function and dependency on parenteral nutrition observed in humans with SLC12a2 mutations. CONCLUSION: The results suggest that loss of NKCC1 affects not only secretion, but also goblet cell function and chemosensing of intestinal contents via G-protein coupled chemosensory receptors. PMID:26909237

Valuing the visual impact of wind farms: A calculus method for synthesizing choice experiments studies.

PubMed

Wen, Cheng; Dallimer, Martin; Carver, Steve; Ziv, Guy

2018-05-06

Despite the great potential of mitigating carbon emission, development of wind farms is often opposed by local communities due to the visual impact on landscape. A growing number of studies have applied nonmarket valuation methods like Choice Experiments (CE) to value the visual impact by eliciting respondents' willingness to pay (WTP) or willingness to accept (WTA) for hypothetical wind farms through survey questions. Several meta-analyses have been found in the literature to synthesize results from different valuation studies, but they have various limitations related to the use of the prevailing multivariate meta-regression analysis. In this paper, we propose a new meta-analysis method to establish general functions for the relationships between the estimated WTP or WTA and three wind farm attributes, namely the distance to residential/coastal areas, the number of turbines and turbine height. This method involves establishing WTA or WTP functions for individual studies, fitting the average derivative functions and deriving the general integral functions of WTP or WTA against wind farm attributes. Results indicate that respondents in different studies consistently showed increasing WTP for moving wind farms to greater distances, which can be fitted by non-linear (natural logarithm) functions. However, divergent preferences for the number of turbines and turbine height were found in different studies. We argue that the new analysis method proposed in this paper is an alternative to the mainstream multivariate meta-regression analysis for synthesizing CE studies and the general integral functions of WTP or WTA against wind farm attributes are useful for future spatial modelling and benefit transfer studies. We also suggest that future multivariate meta-analyses should include non-linear components in the regression functions. Copyright © 2018. Published by Elsevier B.V.

Persistence and withdrawal by students in a preservice science and mathematics teacher education course

NASA Astrophysics Data System (ADS)

Tulip, David F.; Lucas, Keith B.

1991-12-01

At a time when recruitment into preservice teacher education courses in mathematics and science is difficult, one strategy to increase the number of graduates is to minimise the number of students who fail to complete their university courses. This study sought to determine factors which distinguish withdrawers from persisters in the first semester of a B.Ed course. Discriminant analysis was employed; a discriminant function employing seven factors resulted in correct classification in 81% of cases. Further analysis distinguishing between dropouts and transferees resulted in two discriminant functions with some common variables.

Sound attenuation and preferred music in the treatment of problem behavior maintained by escape from noise.

PubMed

Kettering, Tracy L; Fisher, Wayne W; Kelley, Michael E; LaRue, Robert H

2018-06-06

We examined the extent to which different sounds functioned as motivating operations (MO) that evoked problem behavior during a functional analysis for two participants. Results suggested that escape from loud noises reinforced the problem behavior for one participant and escape from arguing reinforced problem behavior for the other participant. Noncontingent delivery of preferred music through sound-attenuating headphones decreased problem behavior without the use of extinction for both participants. We discuss the results in terms of the abolishing effects of the intervention. © 2018 Society for the Experimental Analysis of Behavior.

Using scale and feather traits for module construction provides a functional approach to chicken epidermal development.

PubMed

Bao, Weier; Greenwold, Matthew J; Sawyer, Roger H

2017-11-01

Gene co-expression network analysis has been a research method widely used in systematically exploring gene function and interaction. Using the Weighted Gene Co-expression Network Analysis (WGCNA) approach to construct a gene co-expression network using data from a customized 44K microarray transcriptome of chicken epidermal embryogenesis, we have identified two distinct modules that are highly correlated with scale or feather development traits. Signaling pathways related to feather development were enriched in the traditional KEGG pathway analysis and functional terms relating specifically to embryonic epidermal development were also enriched in the Gene Ontology analysis. Significant enrichment annotations were discovered from customized enrichment tools such as Modular Single-Set Enrichment Test (MSET) and Medical Subject Headings (MeSH). Hub genes in both trait-correlated modules showed strong specific functional enrichment toward epidermal development. Also, regulatory elements, such as transcription factors and miRNAs, were targeted in the significant enrichment result. This work highlights the advantage of this methodology for functional prediction of genes not previously associated with scale- and feather trait-related modules.

Resting State Network Topology of the Ferret Brain

PubMed Central

Zhou, Zhe Charles; Salzwedel, Andrew P.; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K.; Gilmore, John H.; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-01-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. PMID:27596024

Functional analysis and intervention for perseverative verbal behaviour of an older adult with traumatic brain injury.

PubMed

Quearry, Amy Garcia; Lundervold, Duane A

2016-01-01

A functional analysis of behaviour was conducted to determine the controlling variables related to the perseverative verbal behaviour (PBV) of a 60-year-old female with a long-standing traumatic brain injury receiving educational assistance. Functional analyses (FA) of antecedent and consequent conditions related to PCB were conducted to determine controlling influence of: (a) content of verbal interaction and, (b) social reinforcement. After isolating the controlling variables, the functioned-based intervention was implemented in 60 minute tutoring sessions. A reversal condition was used to demonstrate experimental control of the behavior during tutoring sessions. PVB which occurred in the context of tutoring for an undergraduate course significantly interfered with the delivery of instruction. Multiple replications of the functional relation between social reinforcement and PVB duration was demonstrated using an A-B-A-B reversal design during functional analysis and tutoring conditions. PVB markedly declined, but did not extinguish over the course of weekly tutoring (extinction) sessions, most likely due to 'bootleg reinforcement' occurring in other situations. Results indicate that perseverative verbal behaviour following closed head injury may be strongly influenced by the social contingencies operating in various contexts and is amenable to applied behaviour analysis interventions.

Studying hemispheric lateralization during a Stroop task through near-infrared spectroscopy-based connectivity

NASA Astrophysics Data System (ADS)

Zhang, Lei; Sun, Jinyan; Sun, Bailei; Luo, Qingming; Gong, Hui

2014-05-01

Near-infrared spectroscopy (NIRS) is a developing and promising functional brain imaging technology. Developing data analysis methods to effectively extract meaningful information from collected data is the major bottleneck in popularizing this technology. In this study, we measured hemodynamic activity of the prefrontal cortex (PFC) during a color-word matching Stroop task using NIRS. Hemispheric lateralization was examined by employing traditional activation and novel NIRS-based connectivity analyses simultaneously. Wavelet transform coherence was used to assess intrahemispheric functional connectivity. Spearman correlation analysis was used to examine the relationship between behavioral performance and activation/functional connectivity, respectively. In agreement with activation analysis, functional connectivity analysis revealed leftward lateralization for the Stroop effect and correlation with behavioral performance. However, functional connectivity was more sensitive than activation for identifying hemispheric lateralization. Granger causality was used to evaluate the effective connectivity between hemispheres. The results showed increased information flow from the left to the right hemispheres for the incongruent versus the neutral task, indicating a leading role of the left PFC. This study demonstrates that the NIRS-based connectivity can reveal the functional architecture of the brain more comprehensively than traditional activation, helping to better utilize the advantages of NIRS.

MetaNET--a web-accessible interactive platform for biological metabolic network analysis.

PubMed

Narang, Pankaj; Khan, Shawez; Hemrom, Anmol Jaywant; Lynn, Andrew Michael

2014-01-01

Metabolic reactions have been extensively studied and compiled over the last century. These have provided a theoretical base to implement models, simulations of which are used to identify drug targets and optimize metabolic throughput at a systemic level. While tools for the perturbation of metabolic networks are available, their applications are limited and restricted as they require varied dependencies and often a commercial platform for full functionality. We have developed MetaNET, an open source user-friendly platform-independent and web-accessible resource consisting of several pre-defined workflows for metabolic network analysis. MetaNET is a web-accessible platform that incorporates a range of functions which can be combined to produce different simulations related to metabolic networks. These include (i) optimization of an objective function for wild type strain, gene/catalyst/reaction knock-out/knock-down analysis using flux balance analysis. (ii) flux variability analysis (iii) chemical species participation (iv) cycles and extreme paths identification and (v) choke point reaction analysis to facilitate identification of potential drug targets. The platform is built using custom scripts along with the open-source Galaxy workflow and Systems Biology Research Tool as components. Pre-defined workflows are available for common processes, and an exhaustive list of over 50 functions are provided for user defined workflows. MetaNET, available at http://metanet.osdd.net , provides a user-friendly rich interface allowing the analysis of genome-scale metabolic networks under various genetic and environmental conditions. The framework permits the storage of previous results, the ability to repeat analysis and share results with other users over the internet as well as run different tools simultaneously using pre-defined workflows, and user-created custom workflows.

ANTONIA perfusion and stroke. A software tool for the multi-purpose analysis of MR perfusion-weighted datasets and quantitative ischemic stroke assessment.

PubMed

Forkert, N D; Cheng, B; Kemmling, A; Thomalla, G; Fiehler, J

2014-01-01

The objective of this work is to present the software tool ANTONIA, which has been developed to facilitate a quantitative analysis of perfusion-weighted MRI (PWI) datasets in general as well as the subsequent multi-parametric analysis of additional datasets for the specific purpose of acute ischemic stroke patient dataset evaluation. Three different methods for the analysis of DSC or DCE PWI datasets are currently implemented in ANTONIA, which can be case-specifically selected based on the study protocol. These methods comprise a curve fitting method as well as a deconvolution-based and deconvolution-free method integrating a previously defined arterial input function. The perfusion analysis is extended for the purpose of acute ischemic stroke analysis by additional methods that enable an automatic atlas-based selection of the arterial input function, an analysis of the perfusion-diffusion and DWI-FLAIR mismatch as well as segmentation-based volumetric analyses. For reliability evaluation, the described software tool was used by two observers for quantitative analysis of 15 datasets from acute ischemic stroke patients to extract the acute lesion core volume, FLAIR ratio, perfusion-diffusion mismatch volume with manually as well as automatically selected arterial input functions, and follow-up lesion volume. The results of this evaluation revealed that the described software tool leads to highly reproducible results for all parameters if the automatic arterial input function selection method is used. Due to the broad selection of processing methods that are available in the software tool, ANTONIA is especially helpful to support image-based perfusion and acute ischemic stroke research projects.

Optimization Based Efficiencies in First Order Reliability Analysis

NASA Technical Reports Server (NTRS)

Peck, Jeffrey A.; Mahadevan, Sankaran

2003-01-01

This paper develops a method for updating the gradient vector of the limit state function in reliability analysis using Broyden's rank one updating technique. In problems that use commercial code as a black box, the gradient calculations are usually done using a finite difference approach, which becomes very expensive for large system models. The proposed method replaces the finite difference gradient calculations in a standard first order reliability method (FORM) with Broyden's Quasi-Newton technique. The resulting algorithm of Broyden updates within a FORM framework (BFORM) is used to run several example problems, and the results compared to standard FORM results. It is found that BFORM typically requires fewer functional evaluations that FORM to converge to the same answer.

Locomotive cab design development. Volume 1 : analysis of locomotive cab environment & development of cab design alternatives

DOT National Transportation Integrated Search

1976-10-01

This report presents an analysis of the line haul freight : engineer's working and living environment, the resultant locomotive : cab design and design alternatives. The analysis is based on a : delineation of functional requirements found in current...

Functions of behavior change interventions when implementing multi-professional teamwork at an emergency department: a comparative case study

PubMed Central

2014-01-01

Background While there is strong support for the benefits of working in multi-professional teams in health care, the implementation of multi-professional teamwork is reported to be complex and challenging. Implementation strategies combining multiple behavior change interventions are recommended, but the understanding of how and why the behavior change interventions influence staff behavior is limited. There is a lack of studies focusing on the functions of different behavior change interventions and the mechanisms driving behavior change. In this study, applied behavior analysis is used to analyze the function and impact of different behavior change interventions when implementing multi-professional teamwork. Methods A comparative case study design was applied. Two sections of an emergency department implemented multi-professional teamwork involving changes in work processes, aimed at increasing inter-professional collaboration. Behavior change interventions and staff behavior change were studied using observations, interviews and document analysis. Using a hybrid thematic analysis, the behavior change interventions were categorized according to the DCOM® model. The functions of the behavior change interventions were then analyzed using applied behavior analysis. Results The two sections used different behavior change interventions, resulting in a large difference in the degree of staff behavior change. The successful section enabled staff performance of teamwork behaviors with a strategy based on ongoing problem-solving and frequent clarification of directions. Managerial feedback initially played an important role in motivating teamwork behaviors. Gradually, as staff started to experience positive outcomes of the intervention, motivation for teamwork behaviors was replaced by positive task-generated feedback. Conclusions The functional perspective of applied behavior analysis offers insight into the behavioral mechanisms that describe how and why behavior change interventions influence staff behavior. The analysis demonstrates how enabling behavior change interventions, managerial feedback and task-related feedback interact in their influence on behavior and have complementary functions during different stages of implementation. PMID:24885212

Clinical interpretation of the Spinal Cord Injury Functional Index (SCI-FI)

PubMed Central

Fyffe, Denise; Kalpakjian, Claire Z.; Slavin, Mary; Kisala, Pamela; Ni, Pengsheng; Kirshblum, Steven C.; Tulsky, David S.; Jette, Alan M.

2016-01-01

Objective: To provide validation of functional ability levels for the Spinal Cord Injury – Functional Index (SCI-FI). Design: Cross-sectional. Setting: Inpatient rehabilitation hospital and community settings. Participants: A sample of 855 individuals with traumatic spinal cord injury enrolled in 6 rehabilitation centers participating in the National Spinal Cord Injury Model Systems Network. Interventions: Not Applicable. Main Outcome Measures: Spinal Cord Injury-Functional Index (SCI-FI). Results: Cluster analyses identified three distinct groups that represent low, mid-range and high SCI-FI functional ability levels. Comparison of clusters on personal and other injury characteristics suggested some significant differences between groups. Conclusions: These results strongly support the use of SCI-FI functional ability levels to document the perceived functional abilities of persons with SCI. Results of the cluster analysis suggest that the SCI-FI functional ability levels capture function by injury characteristics. Clinical implications regarding tracking functional activity trajectories during follow-up visits are discussed. PMID:26781769

Medial prefrontal functional connectivity--relation to memory self-appraisal accuracy in older adults with and without memory disorders.

PubMed

Ries, Michele L; McLaren, Donald G; Bendlin, Barbara B; Guofanxu; Rowley, Howard A; Birn, Rasmus; Kastman, Erik K; Sager, Mark A; Asthana, Sanjay; Johnson, Sterling C

2012-04-01

It is tentatively estimated that 25% of people with early Alzheimer's disease (AD) show impaired awareness of disease-related changes in their own cognition. Research examining both normative self-awareness and altered awareness resulting from brain disease or injury points to the central role of the medial prefrontal cortex (MPFC) in generating accurate self-appraisals. The current project builds on this work - examining changes in MPFC functional connectivity that correspond to impaired self-appraisal accuracy early in the AD time course. Our behavioral focus was self-appraisal accuracy for everyday memory function, and this was measured using the Memory Function Scale of the Memory Awareness Rating Scale - an instrument psychometrically validated for this purpose. Using regression analysis of data from people with healthy memory (n=12) and people with impaired memory due to amnestic mild cognitive impairment or early AD (n=12), we tested the hypothesis that altered MPFC functional connectivity - particularly with other cortical midline structures and dorsolateral prefrontal cortex - explains variation in memory self-appraisal accuracy. We spatially constrained (i.e., explicitly masked) our regression analyses to those regions that work in conjunction with the MPFC to evoke self-appraisals in a normative group. This empirically derived explicit mask was generated from the result of a psychophysiological interaction analysis of fMRI self-appraisal task data in a separate, large group of cognitively healthy individuals. Results of our primary analysis (i.e., the regression of memory self-appraisal accuracy on MPFC functional connectivity) were generally consistent with our hypothesis: people who were less accurate in making memory self-appraisals showed attenuated functional connectivity between the MPFC seed region and proximal areas within the MPFC (including subgenual anterior cingulate cortex), bilateral dorsolateral prefrontal cortex, bilateral caudate, and left posterior hippocampus. Contrary to our expectations, MPFC functional connectivity with the posterior cingulate was not significantly related to accuracy of memory self-appraisals. Results reported here corroborate findings of variable memory self-appraisal accuracy during the earliest emergence of AD symptoms and reveal alterations in MPFC functional connectivity that correspond to impaired memory self-appraisal. Copyright © 2012 Elsevier Ltd. All rights reserved.

Transdiagnostic differences in the resting-state functional connectivity of the prefrontal cortex in depression and schizophrenia.

PubMed

Chen, Xi; Liu, Chang; He, Hui; Chang, Xin; Jiang, Yuchao; Li, Yingjia; Duan, Mingjun; Li, Jianfu; Luo, Cheng; Yao, Dezhong

2017-08-01

Depression and schizophrenia are two of the most serious psychiatric disorders. They share similar symptoms but the pathology-specific commonalities and differences remain unknown. This study was conducted to acquire a full picture of the functional alterations in schizophrenia and depression patients. The resting-state fMRI data from 20 patients with schizophrenia, 20 patients with depression and 20 healthy control subjects were collected. A data-driven approach that included local functional connectivity density (FCD) analysis combined with multivariate pattern analysis (MVPA) was used to compare the three groups. Based on the results of the MVPA, the local FCD value in the orbitofrontal cortex (OFC) can differentiate depression patients from schizophrenia patients. The patients with depression had a higher local FCD value in the medial and anterior parts of the OFC than the subjects in the other two groups, which suggested altered abstract and reward reinforces processing in depression patients. Subsequent functional connectivity analysis indicated that the connection in the prefrontal cortex was significantly lower in people with schizophrenia compared to people with depression and healthy controls. The systematically different medications for schizophrenia and depression may have different effects on functional connectivity. These results suggested that the resting-state functional connectivity pattern in the prefrontal cortex may be a transdiagnostic difference between depression and schizophrenia patients. Copyright © 2017 Elsevier B.V. All rights reserved.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

PubMed

Harper, Angela F; Leuthaeuser, Janelle B; Babbitt, Patricia C; Morris, John H; Ferrin, Thomas E; Poole, Leslie B; Fetrow, Jacquelyn S

2017-02-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins

PubMed Central

Babbitt, Patricia C.; Ferrin, Thomas E.

2017-01-01

Peroxiredoxins (Prxs or Prdxs) are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique). MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially—MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method’s novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is demonstrated by the Prx superfamily results, laying the foundation for potential functionally relevant clustering of the universe of protein sequences. PMID:28187133

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity. Copyright © 2017 Elsevier Inc. All rights reserved.

Global analyses of Ceratocystis cacaofunesta mitochondria: from genome to proteome

PubMed Central

2013-01-01

Background The ascomycete fungus Ceratocystis cacaofunesta is the causal agent of wilt disease in cacao, which results in significant economic losses in the affected producing areas. Despite the economic importance of the Ceratocystis complex of species, no genomic data are available for any of its members. Given that mitochondria play important roles in fungal virulence and the susceptibility/resistance of fungi to fungicides, we performed the first functional analysis of this organelle in Ceratocystis using integrated “omics” approaches. Results The C. cacaofunesta mitochondrial genome (mtDNA) consists of a single, 103,147-bp circular molecule, making this the second largest mtDNA among the Sordariomycetes. Bioinformatics analysis revealed the presence of 15 conserved genes and 37 intronic open reading frames in C. cacaofunesta mtDNA. Here, we predicted the mitochondrial proteome (mtProt) of C. cacaofunesta, which is comprised of 1,124 polypeptides - 52 proteins that are mitochondrially encoded and 1,072 that are nuclearly encoded. Transcriptome analysis revealed 33 probable novel genes. Comparisons among the Gene Ontology results of the predicted mtProt of C. cacaofunesta, Neurospora crassa and Saccharomyces cerevisiae revealed no significant differences. Moreover, C. cacaofunesta mitochondria were isolated, and the mtProt was subjected to mass spectrometric analysis. The experimental proteome validated 27% of the predicted mtProt. Our results confirmed the existence of 110 hypothetical proteins and 7 novel proteins of which 83 and 1, respectively, had putative mitochondrial localization. Conclusions The present study provides the first partial genomic analysis of a species of the Ceratocystis genus and the first predicted mitochondrial protein inventory of a phytopathogenic fungus. In addition to the known mitochondrial role in pathogenicity, our results demonstrated that the global function analysis of this organelle is similar in pathogenic and non-pathogenic fungi, suggesting that its relevance in the lifestyle of these organisms should be based on a small number of specific proteins and/or with respect to differential gene regulation. In this regard, particular interest should be directed towards mitochondrial proteins with unknown function and the novel protein that might be specific to this species. Further functional characterization of these proteins could enhance our understanding of the role of mitochondria in phytopathogenicity. PMID:23394930

MALDI MS-based Composition Analysis of the Polymerization Reaction of Toluene Diisocyanate (TDI) and Ethylene Glycol (EG).

PubMed

Ahn, Yeong Hee; Lee, Yeon Jung; Kim, Sung Ho

2015-01-01

This study describes an MS-based analysis method for monitoring changes in polymer composition during the polyaddition polymerization reaction of toluene diisocyanate (TDI) and ethylene glycol (EG). The polymerization was monitored as a function of reaction time using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS). The resulting series of polymer adducts terminated with various end-functional groups were precisely identified and the relative compositions of those series were estimated. A new MALDI MS data interpretation method was developed, consisting of a peak-resolving algorithm for overlapping peaks in MALDI MS spectra, a retrosynthetic analysis for the generation of reduced unit mass peaks, and a Gaussian fit-based selection of the most prominent polymer series among the reconstructed unit mass peaks. This method of data interpretation avoids errors originating from side reactions due to the presence of trace water in the reaction mixture or MALDI analysis. Quantitative changes in the relative compositions of the resulting polymer products were monitored as a function of reaction time. These results demonstrate that the mass data interpretation method described herein can be a powerful tool for estimating quantitative changes in the compositions of polymer products arising during a polymerization reaction.

A study on quantifying COPD severity by combining pulmonary function tests and CT image analysis

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2011-03-01

This paper describes a novel method that can evaluate chronic obstructive pulmonary disease (COPD) severity by combining measurements of pulmonary function tests and measurements obtained from CT image analysis. There is no cure for COPD. However, with regular medical care and consistent patient compliance with treatments and lifestyle changes, the symptoms of COPD can be minimized and progression of the disease can be slowed. Therefore, many diagnosis methods based on CT image analysis have been proposed for quantifying COPD. Most of diagnosis methods for COPD extract the lesions as low-attenuation areas (LAA) by thresholding and evaluate the COPD severity by calculating the LAA in the lung (LAA%). However, COPD is usually the result of a combination of two conditions, emphysema and chronic obstructive bronchitis. Therefore, the previous methods based on only LAA% do not work well. The proposed method utilizes both of information including the measurements of pulmonary function tests and the results of the chest CT image analysis to evaluate the COPD severity. In this paper, we utilize a multi-class AdaBoost to combine both of information and classify the COPD severity into five stages automatically. The experimental results revealed that the accuracy rate of the proposed method was 88.9% (resubstitution scheme) and 64.4% (leave-one-out scheme).

Adding results to a meta-analysis: Theory and example

NASA Astrophysics Data System (ADS)

Willson, Victor L.

Meta-analysis has been used as a research method to describe bodies of research data. It promotes hypothesis formation and the development of science education laws. A function overlooked, however, is the role it plays in updating research. Methods to integrate new research with meta-analysis results need explication. A procedure is presented using Bayesian analysis. Research in science education attitude correlation with achievement has been published after a recent meta-analysis of the topic. The results show how new findings complement the previous meta-analysis and extend its conclusions. Additional methodological questions adddressed are how studies are to be weighted, which variables are to be examined, and how often meta-analysis are to be updated.

[Formula: see text] regularity properties of singular parameterizations in isogeometric analysis.

PubMed

Takacs, T; Jüttler, B

2012-11-01

Isogeometric analysis (IGA) is a numerical simulation method which is directly based on the NURBS-based representation of CAD models. It exploits the tensor-product structure of 2- or 3-dimensional NURBS objects to parameterize the physical domain. Hence the physical domain is parameterized with respect to a rectangle or to a cube. Consequently, singularly parameterized NURBS surfaces and NURBS volumes are needed in order to represent non-quadrangular or non-hexahedral domains without splitting, thereby producing a very compact and convenient representation. The Galerkin projection introduces finite-dimensional spaces of test functions in the weak formulation of partial differential equations. In particular, the test functions used in isogeometric analysis are obtained by composing the inverse of the domain parameterization with the NURBS basis functions. In the case of singular parameterizations, however, some of the resulting test functions do not necessarily fulfill the required regularity properties. Consequently, numerical methods for the solution of partial differential equations cannot be applied properly. We discuss the regularity properties of the test functions. For one- and two-dimensional domains we consider several important classes of singularities of NURBS parameterizations. For specific cases we derive additional conditions which guarantee the regularity of the test functions. In addition we present a modification scheme for the discretized function space in case of insufficient regularity. It is also shown how these results can be applied for computational domains in higher dimensions that can be parameterized via sweeping.

Critique and sensitivity analysis of the compensation function used in the LMS Hudson River striped bass models. Environmental Sciences Division publication No. 944

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

Van Winkle, W.; Christensen, S.W.; Kauffman, G.

1976-12-01

The description and justification for the compensation function developed and used by Lawler, Matusky and Skelly Engineers (LMS) (under contract to Consolidated Edison Company of New York) in their Hudson River striped bass models are presented. A sensitivity analysis of this compensation function is reported, based on computer runs with a modified version of the LMS completely mixed (spatially homogeneous) model. Two types of sensitivity analysis were performed: a parametric study involving at least five levels for each of the three parameters in the compensation function, and a study of the form of the compensation function itself, involving comparison ofmore » the LMS function with functions having no compensation at standing crops either less than or greater than the equilibrium standing crops. For the range of parameter values used in this study, estimates of percent reduction are least sensitive to changes in YS, the equilibrium standing crop, and most sensitive to changes in KXO, the minimum mortality rate coefficient. Eliminating compensation at standing crops either less than or greater than the equilibrium standing crops results in higher estimates of percent reduction. For all values of KXO and for values of YS and KX at and above the baseline values, eliminating compensation at standing crops less than the equilibrium standing crops results in a greater increase in percent reduction than eliminating compensation at standing crops greater than the equilibrium standing crops.« less

Multivariate geomorphic analysis of forest streams: Implications for assessment of land use impacts on channel condition

Treesearch

Richard. D. Wood-Smith; John M. Buffington

1996-01-01

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10...

Agreement between Descriptive and Experimental Analyses of Behavior under Naturalistic Test Conditions

ERIC Educational Resources Information Center

Martens, Brian K.; Gertz, Lynne E.; Werder, Candace Susan de Lacy; Rymanowski, Jennifer L.

2010-01-01

We compared the results of a contingency space analysis (CSA) of behavior-consequence recordings to the results of functional analysis (FA) test conditions involving antecedent stimuli and verbal statements that both differed from and mimicked those in the natural environment. Three preschool children with autism spectrum disorder participated.…

Standardized residual as response function for order identification of multi input intervention analysis

NASA Astrophysics Data System (ADS)

Suhartono, Lee, Muhammad Hisyam; Rezeki, Sri

2017-05-01

Intervention analysis is a statistical model in the group of time series analysis which is widely used to describe the effect of an intervention caused by external or internal factors. An example of external factors that often occurs in Indonesia is a disaster, both natural or man-made disaster. The main purpose of this paper is to provide the results of theoretical studies on identification step for determining the order of multi inputs intervention analysis for evaluating the magnitude and duration of the impact of interventions on time series data. The theoretical result showed that the standardized residuals could be used properly as response function for determining the order of multi inputs intervention model. Then, these results are applied for evaluating the impact of a disaster on a real case in Indonesia, i.e. the magnitude and duration of the impact of the Lapindo mud on the volume of vehicles on the highway. Moreover, the empirical results showed that the multi inputs intervention model can describe and explain accurately the magnitude and duration of the impact of disasters on a time series data.

GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis.

PubMed

Zheng, Qi; Wang, Xiu-Jie

2008-07-01

Gene Ontology (GO) analysis has become a commonly used approach for functional studies of large-scale genomic or transcriptomic data. Although there have been a lot of software with GO-related analysis functions, new tools are still needed to meet the requirements for data generated by newly developed technologies or for advanced analysis purpose. Here, we present a Gene Ontology Enrichment Analysis Software Toolkit (GOEAST), an easy-to-use web-based toolkit that identifies statistically overrepresented GO terms within given gene sets. Compared with available GO analysis tools, GOEAST has the following improved features: (i) GOEAST displays enriched GO terms in graphical format according to their relationships in the hierarchical tree of each GO category (biological process, molecular function and cellular component), therefore, provides better understanding of the correlations among enriched GO terms; (ii) GOEAST supports analysis for data from various sources (probe or probe set IDs of Affymetrix, Illumina, Agilent or customized microarrays, as well as different gene identifiers) and multiple species (about 60 prokaryote and eukaryote species); (iii) One unique feature of GOEAST is to allow cross comparison of the GO enrichment status of multiple experiments to identify functional correlations among them. GOEAST also provides rigorous statistical tests to enhance the reliability of analysis results. GOEAST is freely accessible at http://omicslab.genetics.ac.cn/GOEAST/

Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

NASA Astrophysics Data System (ADS)

Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

2012-10-01

In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

Big Bang Bifurcation Analysis and Allee Effect in Generic Growth Functions

NASA Astrophysics Data System (ADS)

Leonel Rocha, J.; Taha, Abdel-Kaddous; Fournier-Prunaret, D.

2016-06-01

The main purpose of this work is to study the dynamics and bifurcation properties of generic growth functions, which are defined by the population size functions of the generic growth equation. This family of unimodal maps naturally incorporates a principal focus of ecological and biological research: the Allee effect. The analysis of this kind of extinction phenomenon allows to identify a class of Allee’s functions and characterize the corresponding Allee’s effect region and Allee’s bifurcation curve. The bifurcation analysis is founded on the performance of fold and flip bifurcations. The dynamical behavior is rich with abundant complex bifurcation structures, the big bang bifurcations of the so-called “box-within-a-box” fractal type being the most outstanding. Moreover, these bifurcation cascades converge to different big bang bifurcation curves with distinct kinds of boxes, where for the corresponding parameter values several attractors are associated. To the best of our knowledge, these results represent an original contribution to clarify the big bang bifurcation analysis of continuous 1D maps.

Parameter Estimation of Actuators for Benchmark Active Control Technology (BACT) Wind Tunnel Model with Analysis of Wear and Aerodynamic Loading Effects

NASA Technical Reports Server (NTRS)

Waszak, Martin R.; Fung, Jimmy

1998-01-01

This report describes the development of transfer function models for the trailing-edge and upper and lower spoiler actuators of the Benchmark Active Control Technology (BACT) wind tunnel model for application to control system analysis and design. A simple nonlinear least-squares parameter estimation approach is applied to determine transfer function parameters from frequency response data. Unconstrained quasi-Newton minimization of weighted frequency response error was employed to estimate the transfer function parameters. An analysis of the behavior of the actuators over time to assess the effects of wear and aerodynamic load by using the transfer function models is also presented. The frequency responses indicate consistent actuator behavior throughout the wind tunnel test and only slight degradation in effectiveness due to aerodynamic hinge loading. The resulting actuator models have been used in design, analysis, and simulation of controllers for the BACT to successfully suppress flutter over a wide range of conditions.

Biosignals Analysis for Kidney Function Effect Analysis of Fennel Aromatherapy

PubMed Central

Kim, Bong-Hyun; Cho, Dong-Uk; Seo, Ssang-Hee

2015-01-01

Human effort in order to enjoy a healthy life is diverse. IT technology to these analyzes, the results of development efforts, it has been applied. Therefore, I use the care and maintenance diagnostic health management and prevention than treatment. In particular, the aromatherapy treatment easy to use without the side effects there is no irritation, are widely used in modern society. In this paper, we measured the aroma effect by applying a biosignal analysis techniques; an experiment was performed to analyze. In particular, we design methods and processes of research based on the theory aroma that affect renal function. Therefore, in this paper, measuring the biosignals and after fennel aromatherapy treatment prior to the enforcement of the mutual comparison, through the analysis, studies were carried out to analyze the effect of fennel aromatherapy therapy on kidney function. PMID:25977696

Basis Function Approximation of Transonic Aerodynamic Influence Coefficient Matrix

NASA Technical Reports Server (NTRS)

Li, Wesley Waisang; Pak, Chan-Gi

2010-01-01

A technique for approximating the modal aerodynamic influence coefficients [AIC] matrices by using basis functions has been developed and validated. An application of the resulting approximated modal AIC matrix for a flutter analysis in transonic speed regime has been demonstrated. This methodology can be applied to the unsteady subsonic, transonic and supersonic aerodynamics. The method requires the unsteady aerodynamics in frequency-domain. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root-locus et cetera. The unsteady aeroelastic analysis for design optimization using unsteady transonic aerodynamic approximation is being demonstrated using the ZAERO(TradeMark) flutter solver (ZONA Technology Incorporated, Scottsdale, Arizona). The technique presented has been shown to offer consistent flutter speed prediction on an aerostructures test wing [ATW] 2 configuration with negligible loss in precision in transonic speed regime. These results may have practical significance in the analysis of aircraft aeroelastic calculation and could lead to a more efficient design optimization cycle

Application of Approximate Unsteady Aerodynamics for Flutter Analysis

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Li, Wesley W.

2010-01-01

A technique for approximating the modal aerodynamic influence coefficient (AIC) matrices by using basis functions has been developed. A process for using the resulting approximated modal AIC matrix in aeroelastic analysis has also been developed. The method requires the unsteady aerodynamics in frequency domain, and this methodology can be applied to the unsteady subsonic, transonic, and supersonic aerodynamics. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root locus et cetera. The unsteady aeroelastic analysis using unsteady subsonic aerodynamic approximation is demonstrated herein. The technique presented is shown to offer consistent flutter speed prediction on an aerostructures test wing (ATW) 2 and a hybrid wing body (HWB) type of vehicle configuration with negligible loss in precision. This method computes AICs that are functions of the changing parameters being studied and are generated within minutes of CPU time instead of hours. These results may have practical application in parametric flutter analyses as well as more efficient multidisciplinary design and optimization studies.

Basis Function Approximation of Transonic Aerodynamic Influence Coefficient Matrix

NASA Technical Reports Server (NTRS)

Li, Wesley W.; Pak, Chan-gi

2011-01-01

A technique for approximating the modal aerodynamic influence coefficients matrices by using basis functions has been developed and validated. An application of the resulting approximated modal aerodynamic influence coefficients matrix for a flutter analysis in transonic speed regime has been demonstrated. This methodology can be applied to the unsteady subsonic, transonic, and supersonic aerodynamics. The method requires the unsteady aerodynamics in frequency-domain. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root-locus et cetera. The unsteady aeroelastic analysis for design optimization using unsteady transonic aerodynamic approximation is being demonstrated using the ZAERO flutter solver (ZONA Technology Incorporated, Scottsdale, Arizona). The technique presented has been shown to offer consistent flutter speed prediction on an aerostructures test wing 2 configuration with negligible loss in precision in transonic speed regime. These results may have practical significance in the analysis of aircraft aeroelastic calculation and could lead to a more efficient design optimization cycle.

Lower cognitive function in patients with age-related macular degeneration: a meta-analysis

PubMed Central

Zhou, Li-Xiao; Sun, Cheng-Lin; Wei, Li-Juan; Gu, Zhi-Min; Lv, Liang; Dang, Yalong

2016-01-01

Objective To investigate the cognitive impairment in patients with age-related macular degeneration (AMD). Methods Relevant articles were identified through a search of the following electronic databases through October 2015, without language restriction: 1) PubMed; 2) the Cochrane Library; 3) EMBASE; 4) ScienceDirect. Meta-analysis was conducted using STATA 12.0 software. Standardized mean differences with corresponding 95% confidence intervals were calculated. All of the included studies met the following four criteria: 1) the study design was a case–control or randomized controlled trial (RCT) study; 2) the study investigated cognitive function in the patient with AMD; 3) the diagnoses of AMD must be provided; 4) there were sufficient scores data to extract for evaluating cognitive function between cases and controls. The Newcastle–Ottawa Scale criteria were used to assess the methodological quality of the studies. Results Of the initial 278 literatures, only six case–control and one RCT studies met all of the inclusion criteria. A total of 794 AMD patients and 1,227 controls were included in this study. Five studies were performed with mini-mental state examination (MMSE), two studies with animal fluency, two studies with trail making test (TMT)-A and -B, one study with Mini-Cog. Results of the meta-analysis revealed lower cognitive function test scores in patients with AMD, especially with MMSE and Mini-Cog test (P≤0.001 for all). The results also showed that differences in the TMT-A (except AMD [total] vs controls) and TMT-B test had no statistical significance (P>0.01). The Newcastle–Ottawa Scale score was ≥5 for all of the included studies. Based on the sensitivity analysis, no single study influenced the overall pooled estimates. Conclusion This meta-analysis suggests lower cognitive function test scores in patients with AMD, especially with MMSE and Mini-Cog test. The other cognitive impairment screening tests, such as animal fluency test and TMT, need more studies to assess. PMID:26966358

Visual target modulation of functional connectivity networks revealed by self-organizing group ICA.

PubMed

van de Ven, Vincent; Bledowski, Christoph; Prvulovic, David; Goebel, Rainer; Formisano, Elia; Di Salle, Francesco; Linden, David E J; Esposito, Fabrizio

2008-12-01

We applied a data-driven analysis based on self-organizing group independent component analysis (sogICA) to fMRI data from a three-stimulus visual oddball task. SogICA is particularly suited to the investigation of the underlying functional connectivity and does not rely on a predefined model of the experiment, which overcomes some of the limitations of hypothesis-driven analysis. Unlike most previous applications of ICA in functional imaging, our approach allows the analysis of the data at the group level, which is of particular interest in high order cognitive studies. SogICA is based on the hierarchical clustering of spatially similar independent components, derived from single subject decompositions. We identified four main clusters of components, centered on the posterior cingulate, bilateral insula, bilateral prefrontal cortex, and right posterior parietal and prefrontal cortex, consistently across all participants. Post hoc comparison of time courses revealed that insula, prefrontal cortex and right fronto-parietal components showed higher activity for targets than for distractors. Activation for distractors was higher in the posterior cingulate cortex, where deactivation was observed for targets. While our results conform to previous neuroimaging studies, they also complement conventional results by showing functional connectivity networks with unique contributions to the task that were consistent across subjects. SogICA can thus be used to probe functional networks of active cognitive tasks at the group-level and can provide additional insights to generate new hypotheses for further study. Copyright 2007 Wiley-Liss, Inc.

Delay differential equations via the matrix Lambert W function and bifurcation analysis: application to machine tool chatter.

PubMed

Yi, Sun; Nelson, Patrick W; Ulsoy, A Galip

2007-04-01

In a turning process modeled using delay differential equations (DDEs), we investigate the stability of the regenerative machine tool chatter problem. An approach using the matrix Lambert W function for the analytical solution to systems of delay differential equations is applied to this problem and compared with the result obtained using a bifurcation analysis. The Lambert W function, known to be useful for solving scalar first-order DDEs, has recently been extended to a matrix Lambert W function approach to solve systems of DDEs. The essential advantages of the matrix Lambert W approach are not only the similarity to the concept of the state transition matrix in lin ear ordinary differential equations, enabling its use for general classes of linear delay differential equations, but also the observation that we need only the principal branch among an infinite number of roots to determine the stability of a system of DDEs. The bifurcation method combined with Sturm sequences provides an algorithm for determining the stability of DDEs without restrictive geometric analysis. With this approach, one can obtain the critical values of delay, which determine the stability of a system and hence the preferred operating spindle speed without chatter. We apply both the matrix Lambert W function and the bifurcation analysis approach to the problem of chatter stability in turning, and compare the results obtained to existing methods. The two new approaches show excellent accuracy and certain other advantages, when compared to traditional graphical, computational and approximate methods.

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family.

PubMed

Danisman, Selahattin; van Dijk, Aalt D J; Bimbo, Andrea; van der Wal, Froukje; Hennig, Lars; de Folter, Stefan; Angenent, Gerco C; Immink, Richard G H

2013-12-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein-protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein-protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family.

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family

PubMed Central

Danisman, Selahattin; de Folter, Stefan; Immink, Richard G. H.

2013-01-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein–protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein–protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family. PMID:24129704

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

An Investigation of Document Partitions.

ERIC Educational Resources Information Center

Shaw, W. M., Jr.

1986-01-01

Empirical significance of document partitions is investigated as a function of index term-weight and similarity thresholds. Results show the same empirically preferred partitions can be detected by two independent strategies: an analysis of cluster-based retrieval analysis and an analysis of regularities in the underlying structure of the document…

The Effects of Conducting a Functional Analysis on Problem Behavior in Other Settings

ERIC Educational Resources Information Center

Call, Nathan A.; Findley, Addie J.; Reavis, Andrea R.

2012-01-01

It has been suggested that reinforcing problem behavior during functional analyses (FAs) may be unethical (e.g., Carr, 1977), the implication being that doing so may result in an increase in problem behavior outside of FA sessions. The current study assessed whether conducting a FA resulted in increases in problem behavior outside of the FA…

Longitudinal structure function from logarithmic slopes of F2 at low x

NASA Astrophysics Data System (ADS)

Boroun, G. R.

2018-01-01

Using Laplace transform techniques, I calculate the longitudinal structure function FL(x ,Q2) from the scaling violations of the proton structure function F2(x ,Q2) and make a critical study of this relationship between the structure functions at leading order (LO) up to next-to-next-to leading order (NNLO) analysis at small x . Furthermore, I consider heavy quark contributions to the relation between the structure functions, which leads to compact formula for Nf=3 +Heavy . The nonlinear corrections to the longitudinal structure function at LO up to NNLO analysis are shown in the Nf=4 (light quark flavor) based on the nonlinear corrections at R =2 and R =4 GeV-1 . The results are compared with experimental data of the longitudinal proton structure function FL in the range of 6.5 ≤Q2≤800 GeV2 .

Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

PubMed

Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

2014-02-01

Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

A contour for the entanglement entropies in harmonic lattices

NASA Astrophysics Data System (ADS)

Coser, Andrea; De Nobili, Cristiano; Tonni, Erik

2017-08-01

We construct a contour function for the entanglement entropies in generic harmonic lattices. In one spatial dimension, numerical analysis are performed by considering harmonic chains with either periodic or Dirichlet boundary conditions. In the massless regime and for some configurations where the subsystem is a single interval, the numerical results for the contour function are compared to the inverse of the local weight function which multiplies the energy-momentum tensor in the corresponding entanglement hamiltonian, found through conformal field theory methods, and a good agreement is observed. A numerical analysis of the contour function for the entanglement entropy is performed also in a massless harmonic chain for a subsystem made by two disjoint intervals.

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

Wixson, J. R.

Root cause analysis (RCA) is an important methodology that can be integrated with the VE Job Plan to generate superior results from the VE Methodology. The point at which RCA is most appropriate is after the function analysis and FAST Model have been built and functions for improvement have been chosen. These functions are then subjected to a simple, but, rigorous RCA to get to the root cause of their deficiencies, whether it is high cost/poor value, poor quality, or poor reliability. Once the most probable causes for these problems have been arrived at, better solutions for improvement can bemore » developed in the creativity phase because the team better understands the problems associated with these functions.« less

Estimating errors in least-squares fitting

NASA Technical Reports Server (NTRS)

Richter, P. H.

1995-01-01

While least-squares fitting procedures are commonly used in data analysis and are extensively discussed in the literature devoted to this subject, the proper assessment of errors resulting from such fits has received relatively little attention. The present work considers statistical errors in the fitted parameters, as well as in the values of the fitted function itself, resulting from random errors in the data. Expressions are derived for the standard error of the fit, as a function of the independent variable, for the general nonlinear and linear fitting problems. Additionally, closed-form expressions are derived for some examples commonly encountered in the scientific and engineering fields, namely ordinary polynomial and Gaussian fitting functions. These results have direct application to the assessment of the antenna gain and system temperature characteristics, in addition to a broad range of problems in data analysis. The effects of the nature of the data and the choice of fitting function on the ability to accurately model the system under study are discussed, and some general rules are deduced to assist workers intent on maximizing the amount of information obtained form a given set of measurements.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Propositions for the Analysis of Commutation Phenomena and Modeling of Universal Motors Using the State Function Method

NASA Astrophysics Data System (ADS)

Niwa, Yuta; Akiyama, Yuji; Naruta, Tomokazu

We carried out FEM simulations for modeling ultra-high-speed universal motors by using the state function method and analyzed the phenomenon of commutator sparking, the characteristics of the air gap surface, and the contact condition or contact resistance of the brushes and commutator bars. Thus, we could quantitatively analyze commutator sparking and investigate the configuration of the iron core. The results of FEM analysis were used to develop a model for predicting the configuration of the iron core and for estimating the electromotive force generated by the transformer, armature reaction field, spark voltage, contact resistance between the rotating brushes, and changes in the gap permeance. The results of our simulation were experimental results. This confirmed the validity of our analysis method. Thus, an ultra-high-speed, high-capacity of 1.5kw motor rotating at 30,000rpm can be designed for use in vacuum cleaners.

A Prototype System for Retrieval of Gene Functional Information

PubMed Central

Folk, Lillian C.; Patrick, Timothy B.; Pattison, James S.; Wolfinger, Russell D.; Mitchell, Joyce A.

2003-01-01

Microarrays allow researchers to gather data about the expression patterns of thousands of genes simultaneously. Statistical analysis can reveal which genes show statistically significant results. Making biological sense of those results requires the retrieval of functional information about the genes thus identified, typically a manual gene-by-gene retrieval of information from various on-line databases. For experiments generating thousands of genes of interest, retrieval of functional information can become a significant bottleneck. To address this issue, we are currently developing a prototype system to automate the process of retrieval of functional information from multiple on-line sources. PMID:14728346

[Soft tissue sarcoma of the upper extremities. Analysis of factors relevant for prognosis in 160 patients].

PubMed

Lehnhardt, M; Hirche, C; Daigeler, A; Goertz, O; Ring, A; Hirsch, T; Drücke, D; Hauser, J; Steinau, H U

2012-02-01

Soft tissue sarcomas (STS) are a rare entity with reduced prognosis due to their aggressive biology. For an optimal treatment of STS identification of independent prognostic factors is crucial in order to reduce tumor-related mortality and recurrence rates. The surgical oncological concept includes wide excisions with resection safety margins >1 cm which enables acceptable functional results and reduced rates of amputation of the lower extremities. In contrast, individual anatomy of the upper extremities, in particular of the hand, leads to an intentional reduction of resection margins in order to preserve the extremity and its function with the main intention of tumor-free resection margins. In this study, the oncological safety and outcome as well as functional results were validated by a retrospective analysis of survival rate, recurrence rate and potential prognostic factors. A total of 160 patients who had been treated for STS of the upper extremities were retrospectively included. Independent prognostic factors were analyzed (primary versus recurrent tumor, tumor size, resection status, grade of malignancy, additional therapy, localization in the upper extremity). Kaplan-Meier analyses for survival rate and local control were calculated. Further outcome measures were functional results validated by the DASH score and rate of amputation. In 130 patients (81%) wide tumor excision (R0) was performed and in 19 patients (12%) an amputation was necessary. The 5-year overall survival rate was 70% and the 5-year survival rate in primary tumors was 81% whereas in recurrences 55% relapsed locally. The 10-year overall survival rate was 45% and the 5-year recurrence rate was 18% for primary STS and 43% for recurrent STS. Variance analysis revealed primary versus recurrent tumor, tumor size, resection status and grade of malignancy as independent prognostic factors. Analysis of functional results showed a median DASH score of 37 (0-100; 0=contralateral extremity). The 5-year survival and local recurrence rates are comparable to STS wide resections with safety margins >1 cm for the lower extremities and the trunk. Analysis of prognostic factors revealed resection status and the tumor-free resection margins to be the main goals in STS resection of upper extremity.

Meta-analysis of neuropsychological measures of executive functioning in children and adolescents with high-functioning autism spectrum disorder.

PubMed

Lai, Chun Lun Eric; Lau, Zoe; Lui, Simon S Y; Lok, Eugenia; Tam, Venus; Chan, Quinney; Cheng, Koi Man; Lam, Siu Man; Cheung, Eric F C

2017-05-01

Existing literature on the profile of executive dysfunction in autism spectrum disorder showed inconsistent results. Age, comorbid attention-deficit/hyperactivity disorder (ADHD) and cognitive abilities appeared to play a role in confounding the picture. Previous meta-analyses have focused on a few components of executive functions. This meta-analysis attempted to delineate the profile of deficit in several components of executive functioning in children and adolescents with high-functioning autism spectrum disorder (HFASD). Ninety-eight English published case-control studies comparing children and adolescents with HFASD with typically developing controls using well-known neuropsychological measures to assess executive functions were included. Results showed that children and adolescents with HFASD were moderately impaired in verbal working memory (g = 0.67), spatial working memory (g = 0.58), flexibility (g = 0.59), planning (g = 0.62), and generativity (g = 0.60) except for inhibition (g = 0.41). Subgroup analysis showed that impairments were still significant for flexibility (g = 0.57-0.61), generativity (g = 0.52-0.68), and working memory (g = 0.49-0.56) in a sample of autism spectrum disorder (ASD) subjects without comorbid ADHD or when the cognitive abilities of the ASD group and the control group were comparable. This meta-analysis confirmed the presence of executive dysfunction in children and adolescents with HFASD. These deficits are not solely accounted for by the effect of comorbid ADHD and the general cognitive abilities. Our results support the executive dysfunction hypothesis and contribute to the clinical understanding and possible development of interventions to alleviate these deficits in children and adolescents with HFASD. Autism Res 2017, 10: 911-939. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

PubMed Central

Wild, Philipp S.; Felix, Janine F.; Schillert, Arne; Chen, Ming-Huei; Leening, Maarten J.G.; Völker, Uwe; Großmann, Vera; Brody, Jennifer A.; Irvin, Marguerite R.; Shah, Sanjiv J.; Pramana, Setia; Lieb, Wolfgang; Schmidt, Reinhold; Stanton, Alice V.; Malzahn, Dörthe; Lyytikäinen, Leo-Pekka; Tiller, Daniel; Smith, J. Gustav; Di Tullio, Marco R.; Musani, Solomon K.; Morrison, Alanna C.; Pers, Tune H.; Morley, Michael; Kleber, Marcus E.; Aragam, Jayashri; Bis, Joshua C.; Bisping, Egbert; Broeckel, Ulrich; Cheng, Susan; Deckers, Jaap W.; Del Greco M, Fabiola; Edelmann, Frank; Fornage, Myriam; Franke, Lude; Friedrich, Nele; Harris, Tamara B.; Hofer, Edith; Hofman, Albert; Huang, Jie; Hughes, Alun D.; Kähönen, Mika; investigators, KNHI; Kruppa, Jochen; Lackner, Karl J.; Lannfelt, Lars; Laskowski, Rafael; Launer, Lenore J.; Lindgren, Cecilia M.; Loley, Christina; Mayet, Jamil; Medenwald, Daniel; Morris, Andrew P.; Müller, Christian; Müller-Nurasyid, Martina; Nappo, Stefania; Nilsson, Peter M.; Nuding, Sebastian; Nutile, Teresa; Peters, Annette; Pfeufer, Arne; Pietzner, Diana; Pramstaller, Peter P.; Raitakari, Olli T.; Rice, Kenneth M.; Rotter, Jerome I.; Ruohonen, Saku T.; Sacco, Ralph L.; Samdarshi, Tandaw E.; Sharp, Andrew S.P.; Shields, Denis C.; Sorice, Rossella; Sotoodehnia, Nona; Stricker, Bruno H.; Surendran, Praveen; Töglhofer, Anna M.; Uitterlinden, André G.; Völzke, Henry; Ziegler, Andreas; Münzel, Thomas; März, Winfried; Cappola, Thomas P.; Hirschhorn, Joel N.; Mitchell, Gary F.; Smith, Nicholas L.; Fox, Ervin R.; Dueker, Nicole D.; Jaddoe, Vincent W.V.; Melander, Olle; Lehtimäki, Terho; Ciullo, Marina; Hicks, Andrew A.; Lind, Lars; Gudnason, Vilmundur; Pieske, Burkert; Barron, Anthony J.; Zweiker, Robert; Schunkert, Heribert; Ingelsson, Erik; Liu, Kiang; Arnett, Donna K.; Psaty, Bruce M.; Blankenberg, Stefan; Larson, Martin G.; Felix, Stephan B.; Franco, Oscar H.; Zeller, Tanja; Vasan, Ramachandran S.; Dörr, Marcus

2017-01-01

BACKGROUND. Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS. A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS. The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION. The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING. For detailed information per study, see Acknowledgments. PMID:28394258

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform

PubMed Central

Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features. PMID:27304979

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

PubMed

Wu, Hau-Tieng; Wu, Han-Kuei; Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.

Memory-focused interventions for people with cognitive disorders: A systematic review and meta-analysis of randomized controlled studies.

PubMed

Yang, Hui-Ling; Chan, Pi-Tuan; Chang, Pi-Chen; Chiu, Huei-Ling; Sheen Hsiao, Shu-Tai; Chu, Hsin; Chou, Kuei-Ru

2018-02-01

A better understanding of people with cognitive disorders improves performance on memory tasks through memory-focused interventions are needed. The purpose of this study was to assess the effect of memoryfocused interventions on cognitive disorders through a meta-analysis. Systematic review and meta-analysis. The online electronic databases PubMed, the Cochrane Library, Ovid-Medline, CINHAL, PsycINFO, Ageline, and Embase (up to May 2017) were used in this study. No language restriction was applied to the search. Objective memory (learning and memory function, immediate recall, delayed recall, and recognition) was the primary indicator and subjective memory performance, global cognitive function, and depression were the secondary indicators. The Hedges' g of change, subgroup analyses, and meta-regression were analyzed on the basis of the characteristics of people with cognitive disorders. A total of 27 studies (2177 participants, mean age=75.80) reporting RCTs were included in the meta-analysis. The results indicated a medium-to-large effect of memory-focused interventions on learning and memory function (Hedges' g=0.62) and subjective memory performance (Hedges' g=0.67), a small-to-medium effect on delayed recall and depression, and a small effect on immediate recall and global cognitive function (all p<0.05) compared with the control. Subgroup analysis and meta-regression indicated that the effects on learning and memory function were more profound in the format of memory training, individual training, shorter treatment duration, and more than eight treatment sessions, and the effect size indicated the MMSE score was the most crucial indicator (β=-0.06, p=0.04). This is first comprehensive meta-analysis of special memory domains in people with cognitive disorders. The results revealed that memory-focused interventions effectively improved memory-related performance in people with cognitive disorders. An appropriately designed intervention can effectively improve memory function, reduce disability progression, and improve mood state in people with cognitive disorders. Additional randomized controlled trials including measures of recognition, global cognitive function, and depression should be conducted and analyzed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stretched hydrogen molecule from a constrained-search density-functional perspective

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

Valone, Steven M; Levy, Mel

2009-01-01

Constrained-search density functional theory gives valuable insights into the fundamentals of density functional theory. It provides exact results and bounds on the ground- and excited-state density functionals. An important advantage of the theory is that it gives guidance in the construction of functionals. Here they engage constrained search theory to explore issues associated with the functional behavior of 'stretched bonds' in molecular hydrogen. A constrained search is performed with familiar valence bond wavefunctions ordinarily used to describe molecular hydrogen. The effective, one-electron hamiltonian is computed and compared to the corresponding uncorrelated, Hartree-Fock effective hamiltonian. Analysis of the functional suggests themore » need to construct different functionals for the same density and to allow a competition among these functions. As a result the correlation energy functional is composed explicitly of energy gaps from the different functionals.« less

Nonparametric Bayesian inference for mean residual life functions in survival analysis.

PubMed

Poynor, Valerie; Kottas, Athanasios

2018-01-19

Modeling and inference for survival analysis problems typically revolves around different functions related to the survival distribution. Here, we focus on the mean residual life (MRL) function, which provides the expected remaining lifetime given that a subject has survived (i.e. is event-free) up to a particular time. This function is of direct interest in reliability, medical, and actuarial fields. In addition to its practical interpretation, the MRL function characterizes the survival distribution. We develop general Bayesian nonparametric inference for MRL functions built from a Dirichlet process mixture model for the associated survival distribution. The resulting model for the MRL function admits a representation as a mixture of the kernel MRL functions with time-dependent mixture weights. This model structure allows for a wide range of shapes for the MRL function. Particular emphasis is placed on the selection of the mixture kernel, taken to be a gamma distribution, to obtain desirable properties for the MRL function arising from the mixture model. The inference method is illustrated with a data set of two experimental groups and a data set involving right censoring. The supplementary material available at Biostatistics online provides further results on empirical performance of the model, using simulated data examples. © The Author 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Trade-off of cerebello-cortical and cortico-cortical functional networks for planning in 6-year-old children.

PubMed

Kipping, Judy A; Margulies, Daniel S; Eickhoff, Simon B; Lee, Annie; Qiu, Anqi

2018-08-01

Childhood is a critical period for the development of cognitive planning. There is a lack of knowledge on its neural mechanisms in children. This study aimed to examine cerebello-cortical and cortico-cortical functional connectivity in association with planning skills in 6-year-olds (n = 76). We identified the cerebello-cortical and cortico-cortical functional networks related to cognitive planning using activation likelihood estimation (ALE) meta-analysis on existing functional imaging studies on spatial planning, and data-driven independent component analysis (ICA) of children's resting-state functional MRI (rs-fMRI). We investigated associations of cerebello-cortical and cortico-cortical functional connectivity with planning ability in 6-year-olds, as assessed using the Stockings of Cambridge task. Long-range functional connectivity of two cerebellar networks (lobules VI and lateral VIIa) with the prefrontal and premotor cortex were greater in children with poorer planning ability. In contrast, cortico-cortical association networks were not associated with the performance of planning in children. These results highlighted the key contribution of the lateral cerebello-frontal functional connectivity, but not cortico-cortical association functional connectivity, for planning ability in 6-year-olds. Our results suggested that brain adaptation to the acquisition of planning ability during childhood is partially achieved through the engagement of the cerebello-cortical functional connectivity. Copyright © 2018 Elsevier Inc. All rights reserved.

Advances in the indirect, descriptive, and experimental approaches to the functional analysis of problem behavior.

PubMed

Wightman, Jade; Julio, Flávia; Virués-Ortega, Javier

2014-05-01

Experimental functional analysis is an assessment methodology to identify the environmental factors that maintain problem behavior in individuals with developmental disabilities and in other populations. Functional analysis provides the basis for the development of reinforcement-based approaches to treatment. This article reviews the procedures, validity, and clinical implementation of the methodological variations of functional analysis and function-based interventions. We present six variations of functional analysis methodology in addition to the typical functional analysis: brief functional analysis, single-function tests, latency-based functional analysis, functional analysis of precursors, and trial-based functional analysis. We also present the three general categories of function-based interventions: extinction, antecedent manipulation, and differential reinforcement. Functional analysis methodology is a valid and efficient approach to the assessment of problem behavior and the selection of treatment strategies.

The Application of Nonstandard Analysis to the Study of Inviscid Shock Wave Jump Conditions

NASA Technical Reports Server (NTRS)

Farassat, F.; Baty, R. S.

1998-01-01

The use of conservation laws in nonconservative form for deriving shock jump conditions by Schwartz distribution theory leads to ambiguous products of generalized functions. Nonstandard analysis is used to define a class of Heaviside functions where the jump from zero to one occurs on an infinitesimal interval. These Heaviside functions differ by their microstructure near x = 0, i.e., by the nature of the rise within the infinitesimal interval it is shown that the conservation laws in nonconservative form can relate the different Heaviside functions used to define jumps in different flow parameters. There are no mathematical or logical ambiguities in the derivation of the jump conditions. An important result is that the microstructure of the Heaviside function of the jump in entropy has a positive peak greater than one within the infinitesimal interval where the jump occurs. This phenomena is known from more sophisticated studies of the structure of shock waves using viscous fluid assumption. However, the present analysis is simpler and more direct.

A human functional protein interaction network and its application to cancer data analysis

PubMed Central

2010-01-01

Background One challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system. Results We have constructed a protein functional interaction network by extending curated pathways with non-curated sources of information, including protein-protein interactions, gene coexpression, protein domain interaction, Gene Ontology (GO) annotations and text-mined protein interactions, which cover close to 50% of the human proteome. By applying this network to two glioblastoma multiforme (GBM) data sets and projecting cancer candidate genes onto the network, we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance, and the majority of GBM samples have sequence-altered genes in two network modules, one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane, and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes, tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast, colorectal and pancreatic cancers. Conclusions We have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases. PMID:20482850

Plate fixation versus intramedullary fixation for midshaft clavicle fractures: Meta-analysis of complications and functional outcomes

PubMed Central

Xiao, Hao; Gao, Hengbo; Zheng, Tuokang; Zhao, Jianhui

2016-01-01

Objective This analysis critically compares publications discussing complications and functional outcomes of plate fixation (PF) versus intramedullary fixation (IF) for midshaft clavicle fractures. Methods Relevant studies published between January 1990 and October 2014, without language restrictions, were identified in database searches of PubMed®, Medline®, Embase and the Chinese National Knowledge Infrastructure (CNKI). Studies that compared postoperative complications and functional outcomes between PF and IF for midshaft clavicle fractures, and provided sufficient data for analysis, were included in this meta-analysis. Results After strict evaluation, 12 studies were included in this meta-analysis. Studies encompassed 462 participants in the PF group and 440 in the IF group. Study participants were followed up for ≥1 year. Outcomes were superior with IF compared with PF in terms of shoulder constant score at 6-month follow-up, fewer symptomatic hardware complications, lower rate of refracture after hardware removal and less hypertrophic scarring. In other aspects, such as functional recovery at 12-months and 24-months, Disability of Arm, Shoulder and Hand (DASH) questionnaire results at 12-month follow-up, shoulder motion range, rates of superficial infection, temporary brachial plexus lesion, nonunion, malunion, delayed union, implant failure and need for major revision, both techniques were similar. Conclusions Findings of this meta-analysis suggest that, in many respects, IF was superior to PF for the management of midshaft clavicle fractures. This finding could aid surgeons in making decisions on the optimum internal fixation pattern for midshaft clavicular fractures. PMID:26880791

The Convergent Validity of the Questions about Behavioral Function Scale and Functional Analysis for Problem Behavior Displayed by Individuals with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Watkins, Nicholas; Rapp, John T.

2013-01-01

Only a few studies have compared the convergent validity of the Questions About Behavioral Function (QABF) scale to the results of functional analyses (FA). In the current study, six participants who emitted problem behaviors participated in either a brief, or a no-interaction-series FA, while each participant's parent completed the QABF. The…

Influence of Cognitive Functioning on Age-Related Performance Declines in Visuospatial Sequence Learning.

PubMed

Krüger, Melanie; Hinder, Mark R; Puri, Rohan; Summers, Jeffery J

2017-01-01

Objectives: The aim of this study was to investigate how age-related performance differences in a visuospatial sequence learning task relate to age-related declines in cognitive functioning. Method: Cognitive functioning of 18 younger and 18 older participants was assessed using a standardized test battery. Participants then undertook a perceptual visuospatial sequence learning task. Various relationships between sequence learning and participants' cognitive functioning were examined through correlation and factor analysis. Results: Older participants exhibited significantly lower performance than their younger counterparts in the sequence learning task as well as in multiple cognitive functions. Factor analysis revealed two independent subsets of cognitive functions associated with performance in the sequence learning task, related to either the processing and storage of sequence information (first subset) or problem solving (second subset). Age-related declines were only found for the first subset of cognitive functions, which also explained a significant degree of the performance differences in the sequence learning task between age-groups. Discussion: The results suggest that age-related performance differences in perceptual visuospatial sequence learning can be explained by declines in the ability to process and store sequence information in older adults, while a set of cognitive functions related to problem solving mediates performance differences independent of age.

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction.

PubMed

Abulnaga, S Mazdak; Yang, Zhen; Carass, Aaron; Kansal, Kalyani; Jedynak, Bruno M; Onyike, Chiadi U; Ying, Sarah H; Prince, Jerry L

2016-02-27

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction

NASA Astrophysics Data System (ADS)

Abulnaga, S. Mazdak; Yang, Zhen; Carass, Aaron; Kansal, Kalyani; Jedynak, Bruno M.; Onyike, Chiadi U.; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

Scaling characteristics of one-dimensional fractional diffusion processes in the presence of power-law distributed random noise

NASA Astrophysics Data System (ADS)

Nezhadhaghighi, Mohsen Ghasemi

2017-08-01

Here, we present results of numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy-tailed probability distribution functions. Assuming that the distribution function of the random fluctuations obeys Lévy statistics with a power-law scaling exponent, we investigate the fractional diffusion equation in the presence of μ -stable Lévy noise. We study the scaling properties of the global width and two-point correlation functions and then compare the analytical and numerical results for the growth exponent β and the roughness exponent α . We also investigate the fractional Fokker-Planck equation for heavy-tailed random fluctuations. We show that the fractional diffusion processes in the presence of μ -stable Lévy noise display special scaling properties in the probability distribution function (PDF). Finally, we numerically study the scaling properties of the heavy-tailed random fluctuations by using the diffusion entropy analysis. This method is based on the evaluation of the Shannon entropy of the PDF generated by the random fluctuations, rather than on the measurement of the global width of the process. We apply the diffusion entropy analysis to extract the growth exponent β and to confirm the validity of our numerical analysis.

HUNT: launch of a full-length cDNA database from the Helix Research Institute.

PubMed

Yudate, H T; Suwa, M; Irie, R; Matsui, H; Nishikawa, T; Nakamura, Y; Yamaguchi, D; Peng, Z Z; Yamamoto, T; Nagai, K; Hayashi, K; Otsuki, T; Sugiyama, T; Ota, T; Suzuki, Y; Sugano, S; Isogai, T; Masuho, Y

2001-01-01

The Helix Research Institute (HRI) in Japan is releasing 4356 HUman Novel Transcripts and related information in the newly established HUNT database. The institute is a joint research project principally funded by the Japanese Ministry of International Trade and Industry, and the clones were sequenced in the governmental New Energy and Industrial Technology Development Organization (NEDO) Human cDNA Sequencing Project. The HUNT database contains an extensive amount of annotation from advanced analysis and represents an essential bioinformatics contribution towards understanding of the gene function. The HRI human cDNA clones were obtained from full-length enriched cDNA libraries constructed with the oligo-capping method and have resulted in novel full-length cDNA sequences. A large fraction has little similarity to any proteins of known function and to obtain clues about possible function we have developed original analysis procedures. Any putative function deduced here can be validated or refuted by complementary analysis results. The user can also extract information from specific categories like PROSITE patterns, PFAM domains, PSORT localization, transmembrane helices and clones with GENIUS structure assignments. The HUNT database can be accessed at http://www.hri.co.jp/HUNT.

Scaling characteristics of one-dimensional fractional diffusion processes in the presence of power-law distributed random noise.

PubMed

Nezhadhaghighi, Mohsen Ghasemi

2017-08-01

Here, we present results of numerical simulations and the scaling characteristics of one-dimensional random fluctuations with heavy-tailed probability distribution functions. Assuming that the distribution function of the random fluctuations obeys Lévy statistics with a power-law scaling exponent, we investigate the fractional diffusion equation in the presence of μ-stable Lévy noise. We study the scaling properties of the global width and two-point correlation functions and then compare the analytical and numerical results for the growth exponent β and the roughness exponent α. We also investigate the fractional Fokker-Planck equation for heavy-tailed random fluctuations. We show that the fractional diffusion processes in the presence of μ-stable Lévy noise display special scaling properties in the probability distribution function (PDF). Finally, we numerically study the scaling properties of the heavy-tailed random fluctuations by using the diffusion entropy analysis. This method is based on the evaluation of the Shannon entropy of the PDF generated by the random fluctuations, rather than on the measurement of the global width of the process. We apply the diffusion entropy analysis to extract the growth exponent β and to confirm the validity of our numerical analysis.

Partial correlation-based functional connectivity analysis for functional near-infrared spectroscopy signals

NASA Astrophysics Data System (ADS)

Akın, Ata

2017-12-01

A theoretical framework, a partial correlation-based functional connectivity (PC-FC) analysis to functional near-infrared spectroscopy (fNIRS) data, is proposed. This is based on generating a common background signal from a high passed version of fNIRS data averaged over all channels as the regressor in computing the PC between pairs of channels. This approach has been employed to real data collected during a Stroop task. The results show a strong significance in the global efficiency (GE) metric computed by the PC-FC analysis for neutral, congruent, and incongruent stimuli (NS, CS, IcS; GEN=0.10±0.009, GEC=0.11±0.01, GEIC=0.13±0.015, p=0.0073). A positive correlation (r=0.729 and p=0.0259) is observed between the interference of reaction times (incongruent-neutral) and interference of GE values (GEIC-GEN) computed from [HbO] signals.

Cluster analysis differentiates high and low community functioning in schizophrenia: Subgroups differ on working memory but not other neurocognitive domains.

PubMed

Alden, Eva C; Cobia, Derin J; Reilly, James L; Smith, Matthew J

2015-10-01

Schizophrenia is characterized by impairment in multiple aspects of community functioning. Available literature suggests that community functioning may be enhanced through cognitive remediation, however, evidence is limited regarding whether specific neurocognitive domains may be treatment targets. We characterized schizophrenia subjects based on their level of community functioning through cluster analysis in an effort to identify whether specific neurocognitive domains were associated with variation in functioning. Schizophrenia (SCZ, n=60) and control (CON, n=45) subjects completed a functional capacity task, social competence role-play, functional attainment interview, and a neuropsychological battery. Multiple cluster analytic techniques were used on the measures of functioning in the schizophrenia subjects to generate functionally-defined subgroups. MANOVA evaluated between-group differences in neurocognition. The cluster analysis revealed two distinct groups, consisting of 36 SCZ characterized by high levels of community functioning (HF-SCZ) and 24 SCZ with low levels of community functioning (LF-SCZ). There was a main group effect for neurocognitive performance (p<0.001) with CON outperforming both SCZ groups in all neurocognitive domains. Post-hoc tests revealed that HF-SCZ had higher verbal working memory compared to LF-SCZ (p≤0.05, Cohen's d=0.78) but the two groups did not differ in remaining domains. The cluster analysis classified schizophrenia subjects in HF-SCZ and LF-SCZ using a multidimensional assessment of community functioning. Moreover, HF-SCZ demonstrated rather preserved verbal working memory relative to LF-SCZ. The results suggest that verbal working memory may play a critical role in community functioning, and is a potential cognitive treatment target for schizophrenia subjects. Copyright © 2015 Elsevier B.V. All rights reserved.

Revisiting Interpretation of Canonical Correlation Analysis: A Tutorial and Demonstration of Canonical Commonality Analysis

ERIC Educational Resources Information Center

Nimon, Kim; Henson, Robin K.; Gates, Michael S.

2010-01-01

In the face of multicollinearity, researchers face challenges interpreting canonical correlation analysis (CCA) results. Although standardized function and structure coefficients provide insight into the canonical variates produced, they fall short when researchers want to fully report canonical effects. This article revisits the interpretation of…

UK audit of analysis of quantitative parameters from renography data generated using a physical phantom.

PubMed

Nijran, Kuldip S; Houston, Alex S; Fleming, John S; Jarritt, Peter H; Heikkinen, Jari O; Skrypniuk, John V

2014-07-01

In this second UK audit of quantitative parameters obtained from renography, phantom simulations were used in cases in which the 'true' values could be estimated, allowing the accuracy of the parameters measured to be assessed. A renal physical phantom was used to generate a set of three phantom simulations (six kidney functions) acquired on three different gamma camera systems. A total of nine phantom simulations and three real patient studies were distributed to UK hospitals participating in the audit. Centres were asked to provide results for the following parameters: relative function and time-to-peak (whole kidney and cortical region). As with previous audits, a questionnaire collated information on methodology. Errors were assessed as the root mean square deviation from the true value. Sixty-one centres responded to the audit, with some hospitals providing multiple sets of results. Twenty-one centres provided a complete set of parameter measurements. Relative function and time-to-peak showed a reasonable degree of accuracy and precision in most UK centres. The overall average root mean squared deviation of the results for (i) the time-to-peak measurement for the whole kidney and (ii) the relative function measurement from the true value was 7.7 and 4.5%, respectively. These results showed a measure of consistency in the relative function and time-to-peak that was similar to the results reported in a previous renogram audit by our group. Analysis of audit data suggests a reasonable degree of accuracy in the quantification of renography function using relative function and time-to-peak measurements. However, it is reasonable to conclude that the objectives of the audit could not be fully realized because of the limitations of the mechanical phantom in providing true values for renal parameters.

76 FR 72493 - ITS Joint Program Office Webinar on Alternative Organizational Structures for a Certificate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-23

... over time. (This study is an institutional analysis only, not a technical analysis, and it is not... Adam Hopps at (202) 680-0091. The ITS JPO will present results from an early analysis of organizational models. This analysis will describe the functions that need to be performed by a CME; identify key...

QCD analysis of neutrino charged current structure function F2 in deep inelastic scattering

NASA Technical Reports Server (NTRS)

Saleem, M.; Aleem, F.

1985-01-01

An analytic expression for the neutrino charged current structure function F sub 2 (x, Q sup 2) in deep inelastic scattering, consistent with quantum chromodynamics, is proposed. The calculated results are in good agreement with experiment.

Assignment of functional activations to probabilistic cytoarchitectonic areas revisited.

PubMed

Eickhoff, Simon B; Paus, Tomas; Caspers, Svenja; Grosbras, Marie-Helene; Evans, Alan C; Zilles, Karl; Amunts, Katrin

2007-07-01

Probabilistic cytoarchitectonic maps in standard reference space provide a powerful tool for the analysis of structure-function relationships in the human brain. While these microstructurally defined maps have already been successfully used in the analysis of somatosensory, motor or language functions, several conceptual issues in the analysis of structure-function relationships still demand further clarification. In this paper, we demonstrate the principle approaches for anatomical localisation of functional activations based on probabilistic cytoarchitectonic maps by exemplary analysis of an anterior parietal activation evoked by visual presentation of hand gestures. After consideration of the conceptual basis and implementation of volume or local maxima labelling, we comment on some potential interpretational difficulties, limitations and caveats that could be encountered. Extending and supplementing these methods, we then propose a supplementary approach for quantification of structure-function correspondences based on distribution analysis. This approach relates the cytoarchitectonic probabilities observed at a particular functionally defined location to the areal specific null distribution of probabilities across the whole brain (i.e., the full probability map). Importantly, this method avoids the need for a unique classification of voxels to a single cortical area and may increase the comparability between results obtained for different areas. Moreover, as distribution-based labelling quantifies the "central tendency" of an activation with respect to anatomical areas, it will, in combination with the established methods, allow an advanced characterisation of the anatomical substrates of functional activations. Finally, the advantages and disadvantages of the various methods are discussed, focussing on the question of which approach is most appropriate for a particular situation.

Association of presence/absence and on/off patterns of Helicobacter pylori oipA gene with peptic ulcer disease and gastric cancer risks: a meta-analysis.

PubMed

Liu, Jingwei; He, Caiyun; Chen, Moye; Wang, Zhenning; Xing, Chengzhong; Yuan, Yuan

2013-11-20

There are increasing studies examining the relationship between the status of H. pylori oipA gene and peptic ulcer disease (PUD) and gastric cancer (GC) but the results turn out to be controversial. We attempted to clarify whether oipA gene status is linked with PUD and/or GC risks. A systematically literature search was performed through four electronic databases. According to the specific inclusion and exclusion criteria, seven articles were ultimately available for the meta-analysis of oipA presence/absence with PUD and GC, and eleven articles were included for the meta-analysis of oipA on/off status with PUD and GC. For the on/off functional status analysis of oipA gene, the "on" status showed significant associations with increased risks of PUD (OR = 3.97, 95% CI: 2.89, 5.45; P < 0.001) and GC (OR = 2.43, 95% CI: 1.45, 4.07; P = 0.001) compared with gastritis and functional dyspepsia controls. Results of the homogeneity test indicated different effects of oipA "on" status on PUD risk between children and adult subgroups and on GC risk between PCR-sequencing and immunoblot subgroups. For the presence/absence analysis of oipA gene, we found null association of the presence of oipA gene with the risks of PUD (OR = 1.93, 95% CI: 0.60, 6.25; P = 0.278) and GC (OR = 2.09, 95% CI: 0.51, 8.66; P = 0.308) compared with gastritis and functional dyspepsia controls. To be concluded, when oipA exists, the functional "on" status of this gene showed association with increased risks for PUD and GC compared with gastritis and FD controls. However, merely investigating the presence/absence of oipA would overlook the importance of its functional on/off status and would not be reliable to predict risks of PUD and GC. Further large-scale and well-designed studies concerning on/off status of oipA are required to confirm our meta-analysis results.

Specific cognitive functions and depressive symptoms as predictors of activities of daily living in older adults with heterogeneous cognitive backgrounds

PubMed Central

de Paula, Jonas J.; Diniz, Breno S.; Bicalho, Maria A.; Albuquerque, Maicon Rodrigues; Nicolato, Rodrigo; de Moraes, Edgar N.; Romano-Silva, Marco A.; Malloy-Diniz, Leandro F.

2015-01-01

Cognitive functioning influences activities of daily living (ADL). However, studies reporting the association between ADL and neuropsychological performance show inconsistent results regarding what specific cognitive domains are related to each specific functional domains. Additionally, whether depressive symptoms are associated with a worse functional performance in older adults is still under explored. We investigated if specific cognitive domains and depressive symptoms would affect different aspects of ADL. Participants were 274 older adults (96 normal aging participants, 85 patients with mild cognitive impairment, and 93 patients probable with mild Alzheimer’s disease dementia) with low formal education (∼4 years). Measures of ADL included three complexity levels: Self-care, Instrumental-Domestic, and Instrumental-Complex. The specific cognitive functions were evaluated through a factorial strategy resulting in four cognitive domains: Executive Functions, Language/Semantic Memory, Episodic Memory, and Visuospatial Abilities. The Geriatric Depression Scale measured depressive symptoms. Multiple linear regression analysis showed executive functions and episodic memory as significant predictors of Instrumental-Domestic ADL, and executive functions, episodic memory and language/semantic memory as predictors of Instrumental-Complex ADL (22 and 28% of explained variance, respectively). Ordinal regression analysis showed the influence of specific cognitive functions and depressive symptoms on each one of the instrumental ADL. We observed a heterogeneous pattern of association with explained variance ranging from 22 to 38%. Different instrumental ADL had specific cognitive predictors and depressive symptoms were predictive of ADL involving social contact. Our results suggest a specific pattern of influence depending on the specific instrumental daily living activity. PMID:26257644

Influence of CT-based depth correction of renal scintigraphy in evaluation of living kidney donors on side selection and postoperative renal function: is it necessary to know the relative renal function?

PubMed

Weinberger, Sarah; Klarholz-Pevere, Carola; Liefeldt, Lutz; Baeder, Michael; Steckhan, Nico; Friedersdorff, Frank

2018-03-22

To analyse the influence of CT-based depth correction in the assessment of split renal function in potential living kidney donors. In 116 consecutive living kidney donors preoperative split renal function was assessed using the CT-based depth correction. Influence on donor side selection and postoperative renal function of the living kidney donors were analyzed. Linear regression analysis was performed to identify predictors of postoperative renal function. A left versus right kidney depth variation of more than 1 cm was found in 40/114 donors (35%). 11 patients (10%) had a difference of more than 5% in relative renal function after depth correction. Kidney depth variation and changes in relative renal function after depth correction would have had influence on side selection in 30 of 114 living kidney donors. CT depth correction did not improve the predictability of postoperative renal function of the living kidney donor. In general, it was not possible to predict the postoperative renal function from preoperative total and relative renal function. In multivariate linear regression analysis, age and BMI were identified as most important predictors for postoperative renal function of the living kidney donors. Our results clearly indicate that concerning the postoperative renal function of living kidney donors, the relative renal function of the donated kidney seems to be less important than other factors. A multimodal assessment with consideration of all available results including kidney size, location of the kidney and split renal function remains necessary.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

Clinical interpretation of the Spinal Cord Injury Functional Index (SCI-FI).

PubMed

Fyffe, Denise; Kalpakjian, Claire Z; Slavin, Mary; Kisala, Pamela; Ni, Pengsheng; Kirshblum, Steven C; Tulsky, David S; Jette, Alan M

2016-09-01

To provide validation of functional ability levels for the Spinal Cord Injury - Functional Index (SCI-FI). Cross-sectional. Inpatient rehabilitation hospital and community settings. A sample of 855 individuals with traumatic spinal cord injury enrolled in 6 rehabilitation centers participating in the National Spinal Cord Injury Model Systems Network. Not Applicable. Spinal Cord Injury-Functional Index (SCI-FI). Cluster analyses identified three distinct groups that represent low, mid-range and high SCI-FI functional ability levels. Comparison of clusters on personal and other injury characteristics suggested some significant differences between groups. These results strongly support the use of SCI-FI functional ability levels to document the perceived functional abilities of persons with SCI. Results of the cluster analysis suggest that the SCI-FI functional ability levels capture function by injury characteristics. Clinical implications regarding tracking functional activity trajectories during follow-up visits are discussed.

Optimization of structures on the basis of fracture mechanics and reliability criteria

NASA Technical Reports Server (NTRS)

Heer, E.; Yang, J. N.

1973-01-01

Systematic summary of factors which are involved in optimization of given structural configuration is part of report resulting from study of analysis of objective function. Predicted reliability of performance of finished structure is sharply dependent upon results of coupon tests. Optimization analysis developed by study also involves expected cost of proof testing.

Functional diversity of fish in tropical estuaries: A traits-based approach of communities in Pernambuco, Brazil

NASA Astrophysics Data System (ADS)

Silva-Júnior, C. A. B.; Mérigot, B.; Lucena-Frédou, F.; Ferreira, B. P.; Coxey, M. S.; Rezende, S. M.; Frédou, T.

2017-11-01

Environmental changes and human activities may have strong impacts on biodiversity and ecosystem functioning. While biodiversity is traditionally based on species richness and composition, there is a growing concern to take into account functional diversity to assess and manage species communities. In spite of their economic importance, functional diversity quantified by a traits-based approach is still poorly documented in tropical estuaries. In this study, the functional diversity of fishes was investigated within four estuaries in Pernambuco state, northeast of Brazil. These areas are subject to different levels of human impact (e.g. mangrove deforestation, shrimp farming, fishing etc.) and environmental conditions. Fishes were collected during 34 scientific surveys. A total of 122 species were identified and 12 functional traits were quantified describing two main functions: food acquisition and locomotion. Fish abundance and functional dissimilarities data were combined into a multivariate analysis, the Double Principal Coordinate Analysis, to identify the functional typology of fish assemblages according to the estuary. Results showed that Itapissuma, the largest estuary with a wider mangrove forest area, differs from the other three estuaries, showing higher mean values per samples of species richness S and quadratic entropy Q. Similarly, it presented a different functional typology (the first two axes of the DPCoA account for 68.7% of total inertia, while those of a traditional PCA based solely on species abundances provided only 17.4%). Conversely, Suape, Sirinhaém, and to a lower extent Rio Formoso, showed more similarity in their diversity. This result was attributed to their predominantly marine influenced hydrological features, and similar levels of species abundances and in morphological traits. Overall, this study, combining diversity indices and a recent multivariate analysis to access species contribution to functional typology, allows to deepen diversity assessment by providing additional information regarding the functional pattern of fish assemblages.

Assessment of protein set coherence using functional annotations

PubMed Central

Chagoyen, Monica; Carazo, Jose M; Pascual-Montano, Alberto

2008-01-01

Background Analysis of large-scale experimental datasets frequently produces one or more sets of proteins that are subsequently mined for functional interpretation and validation. To this end, a number of computational methods have been devised that rely on the analysis of functional annotations. Although current methods provide valuable information (e.g. significantly enriched annotations, pairwise functional similarities), they do not specifically measure the degree of homogeneity of a protein set. Results In this work we present a method that scores the degree of functional homogeneity, or coherence, of a set of proteins on the basis of the global similarity of their functional annotations. The method uses statistical hypothesis testing to assess the significance of the set in the context of the functional space of a reference set. As such, it can be used as a first step in the validation of sets expected to be homogeneous prior to further functional interpretation. Conclusion We evaluate our method by analysing known biologically relevant sets as well as random ones. The known relevant sets comprise macromolecular complexes, cellular components and pathways described for Saccharomyces cerevisiae, which are mostly significantly coherent. Finally, we illustrate the usefulness of our approach for validating 'functional modules' obtained from computational analysis of protein-protein interaction networks. Matlab code and supplementary data are available at PMID:18937846

Delaying Surgical Treatment of Penile Fracture Results in Poor Functional Outcomes: Results from a Large Retrospective Multicenter European Study.

PubMed

Bozzini, Giorgio; Albersen, Maarten; Otero, Javier Romero; Margreiter, Markus; Cruz, Eduard Garcia; Mueller, Alexander; Gratzke, Christian; Serefoglu, Ege Can; Salamanca, Juan Ignacio Martinez; Verze, Paolo

2018-01-01

Penile fracture is a rare clinical entity that represents a urologic emergency. It involves traumatic rupture of the tunica albuginea of the corpora cavernosa due to twisting or bending of the penile shaft during erection. To determine the differences in preoperative diagnostic evaluation patterns and outcomes of penile fracture patients to investigate the impact of surgical delay on functional outcomes. A retrospective analysis was performed using data obtained from 137 patients presenting with penile fracture at seven different European academic medical centers between 1996 and 2013. Age, imaging modalities used, timing of surgical intervention, length of tunica albuginea defect, and surgical technique were recorded. Postoperative erectile function outcomes were assessed with the International Index of Erectile Function (IIEF-5), and the presence of postoperative penile curvature was noted. The association between timing of surgical intervention and postoperative IIEF-5 results was evaluated with discriminant function analysis. The median age of the patients was 34.50 yr (interquartile range [IQR]: 28.0-46.5 yr). Of the 137 patients, 82 (59.85%) underwent penile Doppler ultrasound, and 5 patients (3.64%) were evaluated with magnetic resonance imaging. All patients were treated surgically, and the duration between emergency room admission and surgical intervention was 5.0h (IQR: 3.6-8.0h). The median length of tunica albuginea defect was 10mm (IQR: 8-20mm). Postoperative IIEF-5 scores were 21 (IQR: 12-23) and 23 (IQR: 15-24) at the first and third postoperative months, respectively. Discriminant function analysis revealed that if the surgical intervention was performed >8.23hours after emergency room admission, postoperative erectile function was significantly worse (p=0.0051 at first month and p=0.0057 at third month postoperatively). Our multicenter study showed that delaying surgical intervention results in significantly impaired erectile function. Surgical treatment must be planned as soon as possible to avoid postoperative erectile dysfunction. We looked at sexual outcomes following the repair of penile fracture in a large European population. We found that outcomes worsened if surgical repair was delayed. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

A novel method for calculating relative free energy of similar molecules in two environments

NASA Astrophysics Data System (ADS)

Farhi, Asaf; Singh, Bipin

2017-03-01

Calculating relative free energies is a topic of substantial interest and has many applications including solvation and binding free energies, which are used in computational drug discovery. However, there remain the challenges of accuracy, simple implementation, robustness and efficiency, which prevent the calculations from being automated and limit their use. Here we present an exact and complete decoupling analysis in which the partition functions of the compared systems decompose into the partition functions of the common and different subsystems. This decoupling analysis is applicable to submolecules with coupled degrees of freedom such as the methyl group and to any potential function (including the typical dihedral potentials), enabling to remove less terms in the transformation which results in a more efficient calculation. Then we show mathematically, in the context of partition function decoupling, that the two compared systems can be simulated separately, eliminating the need to design a composite system. We demonstrate the decoupling analysis and the separate transformations in a relative free energy calculation using MD simulations for a general force field and compare to another calculation and to experimental results. We present a unified soft-core technique that ensures the monotonicity of the numerically integrated function (analytical proof) which is important for the selection of intermediates. We show mathematically that in this soft-core technique the numerically integrated function can be non-steep only when we transform the systems separately, which can simplify the numerical integration. Finally, we show that when the systems have rugged energy landscape they can be equilibrated without introducing another sampling dimension which can also enable to use the simulation results for other free energy calculations.

Finite element analysis of a composite wheelchair wheel design

NASA Technical Reports Server (NTRS)

Ortega, Rene

1994-01-01

The finite element analysis of a composite wheelchair wheel design is presented. The design is the result of a technology utilization request. The designer's intent is to soften the riding feeling by incorporating a mechanism attaching the wheel rim to the spokes that would allow considerable deflection upon compressive loads. A finite element analysis was conducted to verify proper structural function. Displacement and stress results are presented and conclusions are provided.

A novel analysis method for near infrared spectroscopy based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Zhou, Zhenyu; Yang, Hongyu; Liu, Yun; Ruan, Zongcai; Luo, Qingming; Gong, Hui; Lu, Zuhong

2007-05-01

Near Infrared Imager (NIRI) has been widely used to access the brain functional activity non-invasively. We use a portable, multi-channel and continuous-wave NIR topography instrument to measure the concentration changes of each hemoglobin species and map cerebral cortex functional activation. By extracting some essential features from the BOLD signals, optical tomography is able to be a new way of neuropsychological studies. Fourier spectral analysis provides a common framework for examining the distribution of global energy in the frequency domain. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. The hemoglobin species concentration changes are of such kind. In this work we develop a new signal processing method using Hilbert-Huang transform to perform spectral analysis of the functional NIRI signals. Compared with wavelet based multi-resolution analysis (MRA), we demonstrated the extraction of task related signal for observation of activation in the prefrontal cortex (PFC) in vision stimulation experiment. This method provides a new analysis tool for functional NIRI signals. Our experimental results show that the proposed approach provides the unique method for reconstructing target signal without losing original information and enables us to understand the episode of functional NIRI more precisely.

Statin Treatment and Functional Outcome after Ischemic Stroke: Case-control and Meta-analysis

PubMed Central

Biffi, A; Devan, WJ; Anderson, CD; Cortellini, L; Furie, KL; Rosand, J; Rost, NS

2011-01-01

Background and Purpose Multiple studies suggest that statin use prior to acute ischemic stroke (AIS) is associated with improved functional outcome. However, available evidence is conflicting, and several published reports are limited by small sample sizes. We therefore investigated the effect of antecedent use of statins on stroke outcome by performing a meta-analysis of all results from published studies as well as our own unpublished data. Methods We performed a systematic literature search and meta-analysis of studies investigating the association between pre-stroke statin use and clinical outcome, and included additional data from 126 pre-stroke statin users and 767 non-users enrolled at our Institution. A total of 12 studies, comprising 2013 statin users and 9682 non- users were meta-analyzed using a random effects model. We also meta-analyzed results for individual TOAST stroke subtypes to determine whether the effect of statin use differed across subtypes, using the Breslow-Day (BD) test. Results Meta-analysis of all available data identified an association between pre-stroke statin use and improved functional outcome (Odds Ratio = 1.62, 95% Confidence Interval: 1.39 -1.88), but we uncovered evidence of publication bias. The effect of statin use on functional outcome was found to be larger for small vessel strokes compared to other subtypes (BD p = 0.008). Conclusions Antecedent use of statins is associated with improved outcome in AIS patients. This association appears to be stronger in patients with small vessel stroke subtype. However, evidence of publication bias in the existing literature suggests these findings should be interpreted with caution. PMID:21415396

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia.

PubMed

Damaraju, E; Allen, E A; Belger, A; Ford, J M; McEwen, S; Mathalon, D H; Mueller, B A; Pearlson, G D; Potkin, S G; Preda, A; Turner, J A; Vaidya, J G; van Erp, T G; Calhoun, V D

2014-01-01

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical-subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivity with sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences.

Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

PubMed Central

Damaraju, E.; Allen, E.A.; Belger, A.; Ford, J.M.; McEwen, S.; Mathalon, D.H.; Mueller, B.A.; Pearlson, G.D.; Potkin, S.G.; Preda, A.; Turner, J.A.; Vaidya, J.G.; van Erp, T.G.; Calhoun, V.D.

2014-01-01

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical–subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivity with sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences. PMID:25161896

Functional network connectivity analysis based on partial correlation in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Zhang, Nan; Guan, Xiaoting; Zhang, Yumei; Li, Jingjing; Chen, Hongyan; Chen, Kewei; Fleisher, Adam; Yao, Li; Wu, Xia

2009-02-01

Functional network connectivity (FNC) measures the temporal dependency among the time courses of functional networks. However, the marginal correlation between two networks used in the classic FNC analysis approach doesn't separate the FNC from the direct/indirect effects of other networks. In this study, we proposed an alternative approach based on partial correlation to evaluate the FNC, since partial correlation based FNC can reveal the direct interaction between a pair of networks, removing dependencies or influences from others. Previous studies have demonstrated less task-specific activation and less rest-state activity in Alzheimer's disease (AD). We applied present approach to contrast FNC differences of resting state network (RSN) between AD and normal controls (NC). The fMRI data under resting condition were collected from 15 AD and 16 NC. FNC was calculated for each pair of six RSNs identified using Group ICA, thus resulting in 15 (2 out of 6) pairs for each subject. Partial correlation based FNC analysis indicated 6 pairs significant differences between groups, while marginal correlation only revealed 2 pairs (involved in the partial correlation results). Additionally, patients showed lower correlation than controls among most of the FNC differences. Our results provide new evidences for the disconnection hypothesis in AD.

Factors affecting quality of social interaction park in Jakarta

NASA Astrophysics Data System (ADS)

Mangunsong, N. I.

2018-01-01

The existence of social interactions park in Jakarta is an oasis in the middle of a concrete jungle. Parks is a response to the need for open space as a place of recreation and community interaction. Often the social interaction parks built by the government does not function as expected, but other functions such as a place to sell, trash, unsafe so be rarely visited by visitors. The purpose of this study was to analyze the factors that affect the quality of social interaction parks in Jakarta by conducting descriptive analysis and correlation analysis of the variables assessment. The results of the analysis can give an idea of social interactions park based on community needs and propose the development of social interactioncity park. The object of study are 25 social interaction parks in 5 municipalities of Jakarta. The method used is descriptive analysis method, correlation analysis using SPSS 19 and using crosstab, chi-square tests. The variables are 5 aspects of Design, Plants composition: Selection type of plant (D); the beauty and harmony (Ind); Maintenance and fertility (P); Cleanliness and Environmental Health (BS); Specificity (Drainage, Multi Function garden, Means, Concern/Mutual cooperation, in dense settlements) (K). The results of analysis show that beauty is the most significant correlation with the value of the park followed by specificity, cleanliness and maintenance. Design was not the most significant variable affecting the quality of the park. The results of this study can be used by the Department of Parks and Cemeteries as input in managing park existing or to be developed and to improve the quality of social interaction park in Jakarta.

The level crossing rates and associated statistical properties of a random frequency response function

NASA Astrophysics Data System (ADS)

Langley, Robin S.

2018-03-01

This work is concerned with the statistical properties of the frequency response function of the energy of a random system. Earlier studies have considered the statistical distribution of the function at a single frequency, or alternatively the statistics of a band-average of the function. In contrast the present analysis considers the statistical fluctuations over a frequency band, and results are obtained for the mean rate at which the function crosses a specified level (or equivalently, the average number of times the level is crossed within the band). Results are also obtained for the probability of crossing a specified level at least once, the mean rate of occurrence of peaks, and the mean trough-to-peak height. The analysis is based on the assumption that the natural frequencies and mode shapes of the system have statistical properties that are governed by the Gaussian Orthogonal Ensemble (GOE), and the validity of this assumption is demonstrated by comparison with numerical simulations for a random plate. The work has application to the assessment of the performance of dynamic systems that are sensitive to random imperfections.

Detailed Wave Function Analysis for Multireference Methods: Implementation in the Molcas Program Package and Applications to Tetracene.

PubMed

Plasser, Felix; Mewes, Stefanie A; Dreuw, Andreas; González, Leticia

2017-11-14

High-level multireference computations on electronically excited and charged states of tetracene are performed, and the results are analyzed using an extensive wave function analysis toolbox that has been newly implemented in the Molcas program package. Aside from verifying the strong effect of dynamic correlation, this study reveals an unexpected critical influence of the atomic orbital basis set. It is shown that different polarized double-ζ basis sets produce significantly different results for energies, densities, and overall wave functions, with the best performance obtained for the atomic natural orbital (ANO) basis set by Pierloot et al. Strikingly, the ANO basis set not only reproduces the energies but also performs exceptionally well in terms of describing the diffuseness of the different states and of their attachment/detachment densities. This study, thus, not only underlines the fact that diffuse basis functions are needed for an accurate description of the electronic wave functions but also shows that, at least for the present example, it is enough to include them implicitly in the contraction scheme.

Discriminant analysis of functional optical topography for schizophrenia diagnosis

NASA Astrophysics Data System (ADS)

Chuang, Ching-Cheng; Nakagome, Kazuyuki; Pu, Shenghong; Lan, Tsuo-Hung; Lee, Chia-Yen; Sun, Chia-Wei

2014-01-01

Abnormal prefrontal function plays a central role in the cognition deficits of schizophrenic patients; however, the character of the relationship between discriminant analysis and prefrontal activation remains undetermined. Recently, evidence of low prefrontal cortex (PFC) activation in individuals with schizophrenia has also been found during verbal fluency tests (VFT) and other cognitive tests with several neuroimaging methods. The purpose of this study is to assess the hemodynamic changes of the PFC and discriminant analysis between schizophrenia patients and healthy controls during VFT task by utilizing functional optical topography. A total of 99 subjects including 53 schizophrenic patients and 46 age- and gender-matched healthy controls were studied. The results showed that the healthy group had larger activation in the right and left PFC than in the middle PFC. Besides, the schizophrenic group showed weaker task performance and lower activation in the whole PFC than the healthy group. The result of the discriminant analysis showed a significant difference with P value <0.001 in six channels (CH 23, 29, 31, 40, 42, 52) between the schizophrenic and healthy groups. Finally, 68.69% and 71.72% of subjects are correctly classified as being schizophrenic or healthy with all 52 channels and six significantly different channels, respectively. Our findings suggest that the left PFC can be a feature region for discriminant analysis of schizophrenic diagnosis.

Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study

PubMed Central

Liu, Peng; Qin, Wei; Wang, Jingjing; Zeng, Fang; Zhou, Guangyu; Wen, Haixia; von Deneen, Karen M.; Liang, Fanrong; Gong, Qiyong; Tian, Jie

2013-01-01

Background Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neural basis of FD. The main purpose of the current study was thereby to characterize the distinct patterns of resting-state function between FD patients and healthy controls (HCs). Methodology/Principal Findings Thirty FD patients and thirty HCs were enrolled and experienced 5-mintue resting-state scanning. Based on the support vector machine (SVM), we applied multivariate pattern analysis (MVPA) to investigate the differences of resting-state function mapped by regional homogeneity (ReHo). A classifier was designed by using the principal component analysis and the linear SVM. Permutation test was then employed to identify the significant contribution to the final discrimination. The results displayed that the mean classifier accuracy was 86.67%, and highly discriminative brain regions mainly included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), supplementary motor area (SMA), temporal pole (TP), insula, anterior/middle cingulate cortex (ACC/MCC), thalamus, hippocampus (HIPP)/parahippocamus (ParaHIPP) and cerebellum. Correlation analysis revealed significant correlations between ReHo values in certain regions of interest (ROI) and the FD symptom severity and/or duration, including the positive correlations between the dmPFC, pACC and the symptom severity; whereas, the positive correlations between the MCC, OFC, insula, TP and FD duration. Conclusions These findings indicated that significantly distinct patterns existed between FD patients and HCs during the resting-state, which could expand our understanding of the neural basis of FD. Meanwhile, our results possibly showed potential feasibility of functional magnetic resonance imaging diagnostic assay for FD. PMID:23874543

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

Boroun, G. R., E-mail: grboroun@gmail.com, E-mail: boroun@razi.ac.ir; Zarrin, S.

We derive a general scheme for the evolution of the nonsinglet structure function at the leadingorder (LO) and next-to-leading-order (NLO) by using the Laplace-transform technique. Results for the nonsinglet structure function are compared with MSTW2008, GRV, and CKMT parameterizations and also EMC experimental data in the LO and NLO analysis. The results are in good agreement with the experimental data and other parameterizations in the low- and large-x regions.

Evaluating the Accuracy of Results for Teacher Implemented Trial-Based Functional Analyses.

PubMed

Rispoli, Mandy; Ninci, Jennifer; Burke, Mack D; Zaini, Samar; Hatton, Heather; Sanchez, Lisa

2015-09-01

Trial-based functional analysis (TBFA) allows for the systematic and experimental assessment of challenging behavior in applied settings. The purposes of this study were to evaluate a professional development package focused on training three Head Start teachers to conduct TBFAs with fidelity during ongoing classroom routines. To assess the accuracy of the TBFA results, the effects of a function-based intervention derived from the TBFA were compared with the effects of a non-function-based intervention. Data were collected on child challenging behavior and appropriate communication. An A-B-A-C-D design was utilized in which A represented baseline, and B and C consisted of either function-based or non-function-based interventions counterbalanced across participants, and D represented teacher implementation of the most effective intervention. Results showed that the function-based intervention produced greater decreases in challenging behavior and greater increases in appropriate communication than the non-function-based intervention for all three children. © The Author(s) 2015.

Improved dynamical scaling analysis using the kernel method for nonequilibrium relaxation.

PubMed

Echinaka, Yuki; Ozeki, Yukiyasu

2016-10-01

The dynamical scaling analysis for the Kosterlitz-Thouless transition in the nonequilibrium relaxation method is improved by the use of Bayesian statistics and the kernel method. This allows data to be fitted to a scaling function without using any parametric model function, which makes the results more reliable and reproducible and enables automatic and faster parameter estimation. Applying this method, the bootstrap method is introduced and a numerical discrimination for the transition type is proposed.

Modified Gaussian influence function of deformable mirror actuators.

PubMed

Huang, Linhai; Rao, Changhui; Jiang, Wenhan

2008-01-07

A new deformable mirror influence function based on a Gaussian function is introduced to analyze the fitting capability of a deformable mirror. The modified expressions for both azimuthal and radial directions are presented based on the analysis of the residual error between a measured influence function and a Gaussian influence function. With a simplex search method, we further compare the fitting capability of our proposed influence function to fit the data produced by a Zygo interferometer with that of a Gaussian influence function. The result indicates that the modified Gaussian influence function provides much better performance in data fitting.

User's Manual and Final Report for Hot-SMAC GUI Development

NASA Technical Reports Server (NTRS)

Yarrington, Phil

2001-01-01

A new software package called Higher Order Theory-Structural/Micro Analysis Code (HOT-SMAC) has been developed as an effective alternative to the finite element approach for Functionally Graded Material (FGM) modeling. HOT-SMAC is a self-contained package including pre- and post-processing through an intuitive graphical user interface, along with the well-established Higher Order Theory for Functionally Graded Materials (HOTFGM) thermomechanical analysis engine. This document represents a Getting Started/User's Manual for HOT-SMAC and a final report for its development. First, the features of the software are presented in a simple step-by-step example where a HOT-SMAC model representing a functionally graded material is created, mechanical and thermal boundary conditions are applied, the model is analyzed and results are reviewed. In a second step-by-step example, a HOT-SMAC model of an actively cooled metallic channel with ceramic thermal barrier coating is built and analyzed. HOT-SMAC results from this model are compared to recently published results (NASA/TM-2001-210702) for two grid densities. Finally, a prototype integration of HOTSMAC with the commercially available HyperSizer(R) structural analysis and sizing software is presented. In this integration, local strain results from HyperSizer's structural analysis are fed to a detailed HOT-SMAC model of the flange-to-facesheet bond region of a stiffened panel. HOT-SMAC is then used to determine the peak shear and peel (normal) stresses between the facesheet and bonded flange of the panel and determine the "free edge" effects.

Complete 3D kinematics of upper extremity functional tasks.

PubMed

van Andel, Carolien J; Wolterbeek, Nienke; Doorenbosch, Caroline A M; Veeger, DirkJan H E J; Harlaar, Jaap

2008-01-01

Upper extremity (UX) movement analysis by means of 3D kinematics has the potential to become an important clinical evaluation method. However, no standardized protocol for clinical application has yet been developed, that includes the whole upper limb. Standardization problems include the lack of a single representative function, the wide range of motion of joints and the complexity of the anatomical structures. A useful protocol would focus on the functional status of the arm and particularly the orientation of the hand. The aim of this work was to develop a standardized measurement method for unconstrained movement analysis of the UX that includes hand orientation, for a set of functional tasks for the UX and obtain normative values. Ten healthy subjects performed four representative activities of daily living (ADL). In addition, six standard active range of motion (ROM) tasks were executed. Joint angles of the wrist, elbow, shoulder and scapula were analyzed throughout each ADL task and minimum/maximum angles were determined from the ROM tasks. Characteristic trajectories were found for the ADL tasks, standard deviations were generally small and ROM results were consistent with the literature. The results of this study could form the normative basis for the development of a 'UX analysis report' equivalent to the 'gait analysis report' and would allow for future comparisons with pediatric and/or pathologic movement patterns.

Analysis of Real Ship Rolling Dynamics under Wave Excitement Force Composed of Sums of Cosine Functions

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

Zhang, Y. S.; Cai, F.; Xu, W. M.

2011-09-28

The ship motion equation with a cosine wave excitement force describes the slip moments in regular waves. A new kind of wave excitement force model, with the form as sums of cosine functions was proposed to describe ship rolling in irregular waves. Ship rolling time series were obtained by solving the ship motion equation with the fourth-order-Runger-Kutta method. These rolling time series were synthetically analyzed with methods of phase-space track, power spectrum, primary component analysis, and the largest Lyapunove exponent. Simulation results show that ship rolling presents some chaotic characteristic when the wave excitement force was applied by sums ofmore » cosine functions. The result well explains the course of ship rolling's chaotic mechanism and is useful for ship hydrodynamic study.« less

Impact of Missing Data on the Detection of Differential Item Functioning: The Case of Mantel-Haenszel and Logistic Regression Analysis

ERIC Educational Resources Information Center

Robitzsch, Alexander; Rupp, Andre A.

2009-01-01

This article describes the results of a simulation study to investigate the impact of missing data on the detection of differential item functioning (DIF). Specifically, it investigates how four methods for dealing with missing data (listwise deletion, zero imputation, two-way imputation, response function imputation) interact with two methods of…

Cost Function and Its Use for Intergovernmental Educational Transfers in Vietnam

ERIC Educational Resources Information Center

Nguyen-Hoang, Phuong

2012-01-01

The purpose of this paper is twofold. First, although many cost function studies have been done in developed countries, there has been no such study for the developing countries such as Vietnam. This paper will make the first attempt at conducting a cost function analysis for Vietnam. Second, it also demonstrates how the results of the cost…

Tropospheric Delay Raytracing Applied in VLBI Analysis

NASA Astrophysics Data System (ADS)

MacMillan, D. S.; Eriksson, D.; Gipson, J. M.

2013-12-01

Tropospheric delay modeling error continues to be one of the largest sources of error in VLBI analysis. For standard operational solutions, we use the VMF1 elevation-dependent mapping functions derived from ECMWF data. These mapping functions assume that tropospheric delay at a site is azimuthally symmetric. As this assumption does not reflect reality, we have determined the raytrace delay along the signal path through the troposphere for each VLBI quasar observation. We determined the troposphere refractivity fields from the pressure, temperature, specific humidity and geopotential height fields of the NASA GSFC GEOS-5 numerical weather model. We discuss results from analysis of the CONT11 R&D and the weekly operational R1+R4 experiment sessions. When applied in VLBI analysis, baseline length repeatabilities were better for 66-72% of baselines with raytraced delays than with VMF1 mapping functions. Vertical repeatabilities were better for 65% of sites.

An Overview of R in Health Decision Sciences.

PubMed

Jalal, Hawre; Pechlivanoglou, Petros; Krijkamp, Eline; Alarid-Escudero, Fernando; Enns, Eva; Hunink, M G Myriam

2017-10-01

As the complexity of health decision science applications increases, high-level programming languages are increasingly adopted for statistical analyses and numerical computations. These programming languages facilitate sophisticated modeling, model documentation, and analysis reproducibility. Among the high-level programming languages, the statistical programming framework R is gaining increased recognition. R is freely available, cross-platform compatible, and open source. A large community of users who have generated an extensive collection of well-documented packages and functions supports it. These functions facilitate applications of health decision science methodology as well as the visualization and communication of results. Although R's popularity is increasing among health decision scientists, methodological extensions of R in the field of decision analysis remain isolated. The purpose of this article is to provide an overview of existing R functionality that is applicable to the various stages of decision analysis, including model design, input parameter estimation, and analysis of model outputs.

Introducing linear functions: an alternative statistical approach

NASA Astrophysics Data System (ADS)

Nolan, Caroline; Herbert, Sandra

2015-12-01

The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be `threshold concepts'. There is recognition that linear functions can be taught in context through the exploration of linear modelling examples, but this has its limitations. Currently, statistical data is easily attainable, and graphics or computer algebra system (CAS) calculators are common in many classrooms. The use of this technology provides ease of access to different representations of linear functions as well as the ability to fit a least-squares line for real-life data. This means these calculators could support a possible alternative approach to the introduction of linear functions. This study compares the results of an end-of-topic test for two classes of Australian middle secondary students at a regional school to determine if such an alternative approach is feasible. In this study, test questions were grouped by concept and subjected to concept by concept analysis of the means of test results of the two classes. This analysis revealed that the students following the alternative approach demonstrated greater competence with non-standard questions.

Mining dynamic noteworthy functions in software execution sequences.

PubMed

Zhang, Bing; Huang, Guoyan; Wang, Yuqian; He, Haitao; Ren, Jiadong

2017-01-01

As the quality of crucial entities can directly affect that of software, their identification and protection become an important premise for effective software development, management, maintenance and testing, which thus contribute to improving the software quality and its attack-defending ability. Most analysis and evaluation on important entities like codes-based static structure analysis are on the destruction of the actual software running. In this paper, from the perspective of software execution process, we proposed an approach to mine dynamic noteworthy functions (DNFM)in software execution sequences. First, according to software decompiling and tracking stack changes, the execution traces composed of a series of function addresses were acquired. Then these traces were modeled as execution sequences and then simplified so as to get simplified sequences (SFS), followed by the extraction of patterns through pattern extraction (PE) algorithm from SFS. After that, evaluating indicators inner-importance and inter-importance were designed to measure the noteworthiness of functions in DNFM algorithm. Finally, these functions were sorted by their noteworthiness. Comparison and contrast were conducted on the experiment results from two traditional complex network-based node mining methods, namely PageRank and DegreeRank. The results show that the DNFM method can mine noteworthy functions in software effectively and precisely.

Functional brain networks in healthy subjects under acupuncture stimulation: An EEG study based on nonlinear synchronization likelihood analysis

NASA Astrophysics Data System (ADS)

Yu, Haitao; Liu, Jing; Cai, Lihui; Wang, Jiang; Cao, Yibin; Hao, Chongqing

2017-02-01

Electroencephalogram (EEG) signal evoked by acupuncture stimulation at "Zusanli" acupoint is analyzed to investigate the modulatory effect of manual acupuncture on the functional brain activity. Power spectral density of EEG signal is first calculated based on the autoregressive Burg method. It is shown that the EEG power is significantly increased during and after acupuncture in delta and theta bands, but decreased in alpha band. Furthermore, synchronization likelihood is used to estimate the nonlinear correlation between each pairwise EEG signals. By applying a threshold to resulting synchronization matrices, functional networks for each band are reconstructed and further quantitatively analyzed to study the impact of acupuncture on network structure. Graph theoretical analysis demonstrates that the functional connectivity of the brain undergoes obvious change under different conditions: pre-acupuncture, acupuncture, and post-acupuncture. The minimum path length is largely decreased and the clustering coefficient keeps increasing during and after acupuncture in delta and theta bands. It is indicated that acupuncture can significantly modulate the functional activity of the brain, and facilitate the information transmission within different brain areas. The obtained results may facilitate our understanding of the long-lasting effect of acupuncture on the brain function.

Computational analysis of microRNA function in heart development.

PubMed

Liu, Ganqiang; Ding, Min; Chen, Jiajia; Huang, Jinyan; Wang, Haiyun; Jing, Qing; Shen, Bairong

2010-09-01

Emerging evidence suggests that specific spatio-temporal microRNA (miRNA) expression is required for heart development. In recent years, hundreds of miRNAs have been discovered. In contrast, functional annotations are available only for a very small fraction of these regulatory molecules. In order to provide a global perspective for the biologists who study the relationship between differentially expressed miRNAs and heart development, we employed computational analysis to uncover the specific cellular processes and biological pathways targeted by miRNAs in mouse heart development. Here, we utilized Gene Ontology (GO) categories, KEGG Pathway, and GeneGo Pathway Maps as a gene functional annotation system for miRNA target enrichment analysis. The target genes of miRNAs were found to be enriched in functional categories and pathway maps in which miRNAs could play important roles during heart development. Meanwhile, we developed miRHrt (http://sysbio.suda.edu.cn/mirhrt/), a database aiming to provide a comprehensive resource of miRNA function in regulating heart development. These computational analysis results effectively illustrated the correlation of differentially expressed miRNAs with cellular functions and heart development. We hope that the identified novel heart development-associated pathways and the database presented here would facilitate further understanding of the roles and mechanisms of miRNAs in heart development.

Design for cyclic loading endurance of composites

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Murthy, Pappu L. N.; Chamis, Christos C.; Liaw, Leslie D. G.

1993-01-01

The application of the computer code IPACS (Integrated Probabilistic Assessment of Composite Structures) to aircraft wing type structures is described. The code performs a complete probabilistic analysis for composites taking into account the uncertainties in geometry, boundary conditions, material properties, laminate lay-ups, and loads. Results of the analysis are presented in terms of cumulative distribution functions (CDF) and probability density function (PDF) of the fatigue life of a wing type composite structure under different hygrothermal environments subjected to the random pressure. The sensitivity of the fatigue life to a number of critical structural/material variables is also computed from the analysis.

Identification and expression profiling analysis of TCP family genes involved in growth and development in maize.

PubMed

Chai, Wenbo; Jiang, Pengfei; Huang, Guoyu; Jiang, Haiyang; Li, Xiaoyu

2017-10-01

The TCP family is a group of plant-specific transcription factors. TCP genes encode proteins harboring bHLH structure, which is implicated in DNA binding and protein-protein interactions and known as the TCP domain. TCP genes play important roles in plant development and have been evolutionarily and functionally elaborated in various plants, however, no overall phylogenetic analysis or expression profiling of TCP genes in Zea mays has been reported. In the present study, a systematic analysis of molecular evolution and functional prediction of TCP family genes in maize ( Z . mays L.) has been conducted. We performed a genome-wide survey of TCP genes in maize, revealing the gene structure, chromosomal location and phylogenetic relationship of family members. Microsynteny between grass species and tissue-specific expression profiles were also investigated. In total, 29 TCP genes were identified in the maize genome, unevenly distributed on the 10 maize chromosomes. Additionally, ZmTCP genes were categorized into nine classes based on phylogeny and purifying selection may largely be responsible for maintaining the functions of maize TCP genes. What's more, microsynteny analysis suggested that TCP genes have been conserved during evolution. Finally, expression analysis revealed that most TCP genes are expressed in the stem and ear, which suggests that ZmTCP genes influence stem and ear growth. This result is consistent with the previous finding that maize TCP genes represses the growth of axillary organs and enables the formation of female inflorescences. Altogether, this study presents a thorough overview of TCP family in maize and provides a new perspective on the evolution of this gene family. The results also indicate that TCP family genes may be involved in development stage in plant growing conditions. Additionally, our results will be useful for further functional analysis of the TCP gene family in maize.

Domain fusion analysis by applying relational algebra to protein sequence and domain databases

PubMed Central

Truong, Kevin; Ikura, Mitsuhiko

2003-01-01

Background Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful. Results This paper proposes a computational method employing relational algebra to find domain fusions in protein sequence databases. The feasibility of this method was illustrated on the SWISS-PROT+TrEMBL sequence database using domain predictions from the Pfam HMM (hidden Markov model) database. We identified 235 and 189 putative functionally linked protein partners in H. sapiens and S. cerevisiae, respectively. From scientific literature, we were able to confirm many of these functional linkages, while the remainder offer testable experimental hypothesis. Results can be viewed at . Conclusion As the analysis can be computed quickly on any relational database that supports standard SQL (structured query language), it can be dynamically updated along with the sequence and domain databases, thereby improving the quality of predictions over time. PMID:12734020

Neurological soft signs are not "soft" in brain structure and functional networks: evidence from ALE meta-analysis.

PubMed

Zhao, Qing; Li, Zhi; Huang, Jia; Yan, Chao; Dazzan, Paola; Pantelis, Christos; Cheung, Eric F C; Lui, Simon S Y; Chan, Raymond C K

2014-05-01

Neurological soft signs (NSS) are associated with schizophrenia and related psychotic disorders. NSS have been conventionally considered as clinical neurological signs without localized brain regions. However, recent brain imaging studies suggest that NSS are partly localizable and may be associated with deficits in specific brain areas. We conducted an activation likelihood estimation meta-analysis to quantitatively review structural and functional imaging studies that evaluated the brain correlates of NSS in patients with schizophrenia and other psychotic disorders. Six structural magnetic resonance imaging (sMRI) and 15 functional magnetic resonance imaging (fMRI) studies were included. The results from meta-analysis of the sMRI studies indicated that NSS were associated with atrophy of the precentral gyrus, the cerebellum, the inferior frontal gyrus, and the thalamus. The results from meta-analysis of the fMRI studies demonstrated that the NSS-related task was significantly associated with altered brain activation in the inferior frontal gyrus, bilateral putamen, the cerebellum, and the superior temporal gyrus. Our findings from both sMRI and fMRI meta-analyses further support the conceptualization of NSS as a manifestation of the "cerebello-thalamo-prefrontal" brain network model of schizophrenia and related psychotic disorders.

Functional approach to high-throughput plant growth analysis

PubMed Central

2013-01-01

Method Taking advantage of the current rapid development in imaging systems and computer vision algorithms, we present HPGA, a high-throughput phenotyping platform for plant growth modeling and functional analysis, which produces better understanding of energy distribution in regards of the balance between growth and defense. HPGA has two components, PAE (Plant Area Estimation) and GMA (Growth Modeling and Analysis). In PAE, by taking the complex leaf overlap problem into consideration, the area of every plant is measured from top-view images in four steps. Given the abundant measurements obtained with PAE, in the second module GMA, a nonlinear growth model is applied to generate growth curves, followed by functional data analysis. Results Experimental results on model plant Arabidopsis thaliana show that, compared to an existing approach, HPGA reduces the error rate of measuring plant area by half. The application of HPGA on the cfq mutant plants under fluctuating light reveals the correlation between low photosynthetic rates and small plant area (compared to wild type), which raises a hypothesis that knocking out cfq changes the sensitivity of the energy distribution under fluctuating light conditions to repress leaf growth. Availability HPGA is available at http://www.msu.edu/~jinchen/HPGA. PMID:24565437

Environmental drivers of heterogeneity in the trophic-functional structure of protozoan communities during an annual cycle in a coastal ecosystem.

PubMed

Xu, Guangjian; Yang, Eun Jin; Xu, Henglong

2017-08-15

Trophic-functional groupings are an important biological trait to summarize community structure in functional space. The heterogeneity of the tropic-functional pattern of protozoan communities and its environmental drivers were studied in coastal waters of the Yellow Sea during a 1-year cycle. Samples were collected using the glass slide method at four stations within a water pollution gradient. A second-stage matrix-based analysis was used to summarize spatial variation in the annual pattern of the functional structure. A clustering analysis revealed significant variability in the trophic-functional pattern among the four stations during the 1-year cycle. The heterogeneity in the trophic-functional pattern of the communities was significantly related to changes in environmental variables, particularly ammonium-nitrogen and nitrates, alone or in combination with dissolved oxygen. These results suggest that the heterogeneity in annual patterns of protozoan trophic-functional structure may reflect water quality status in coastal ecosystems. Copyright © 2017. Published by Elsevier Ltd.

[The operative functioning of maternity hospital].

PubMed

2011-01-01

The analysis of operative functioning of maternity hospital is presented. The study results characterize the work loads, the level of professional qualification of medical personnel, the level of pathology of delivery demanding an operative invasion. The conditions of effective decision making in financial issues are discussed.

Coexistence and local μ-stability of multiple equilibrium points for memristive neural networks with nonmonotonic piecewise linear activation functions and unbounded time-varying delays.

PubMed

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2016-12-01

In this paper, the coexistence and dynamical behaviors of multiple equilibrium points are discussed for a class of memristive neural networks (MNNs) with unbounded time-varying delays and nonmonotonic piecewise linear activation functions. By means of the fixed point theorem, nonsmooth analysis theory and rigorous mathematical analysis, it is proven that under some conditions, such n-neuron MNNs can have 5 n equilibrium points located in ℜ n , and 3 n of them are locally μ-stable. As a direct application, some criteria are also obtained on the multiple exponential stability, multiple power stability, multiple log-stability and multiple log-log-stability. All these results reveal that the addressed neural networks with activation functions introduced in this paper can generate greater storage capacity than the ones with Mexican-hat-type activation function. Numerical simulations are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of earing behaviour in deep drawing of ASS 304 at elevated temperature

NASA Astrophysics Data System (ADS)

Gupta, Amit Kumar; Deole, Aditya; Kotkunde, Nitin; Singh, Swadesh Kumar; jella, Gangadhar

2016-08-01

Earing tendency in a deep drawn cup of circular blanks is one the most prominent characteristics observed due to anisotropy in a metal sheet. Such formation of uneven rim is mainly due to dissimilarity in yield stress as well as Lankford parameter (r- value) in different orientations. In this paper, an analytical function coupled with different yield functions viz., Hill 1948, Barlat 1989 and Barlat Yld 2000-2d has been used to provide an approximation of earing profile. In order to validate the results, material parameters for yield functions and hardening rule have been calibrated for ASS 304 at 250°C and deep drawing experiment is conducted to measure the earing profile. The predicted earing profiles based on analytical results have been validated using experimental earing profile. Based on this analysis, Barlat Yld 2000-2d has been observed to be a well suited yield model for deep drawing of ASS 304, which also confirms the reliability of analytical function for earing profile estimation.

Characteristics of locomotion, muscle strength, and muscle tissue in regenerating rat skeletal muscles.

PubMed

Iwata, Akira; Fuchioka, Satoshi; Hiraoka, Koichi; Masuhara, Mitsuhiko; Kami, Katsuya

2010-05-01

Although numerous studies have aimed to elucidate the mechanisms used to repair the structure and function of injured skeletal muscles, it remains unclear how and when movement recovers following damage. We performed a temporal analysis to characterize the changes in movement, muscle function, and muscle structure after muscle injury induced by the drop-mass technique. At each time-point, movement recovery was determined by ankle kinematic analysis of locomotion, and functional recovery was represented by isometric force. As a histological analysis, the cross-sectional area of myotubes was measured to examine structural regeneration. The dorsiflexion angle of the ankle, as assessed by kinematic analysis of locomotion, increased after injury and then returned to control levels by day 14 post-injury. The isometric force returned to normal levels by day 21 post-injury. However, the size of the myotubes did not reach normal levels, even at day 21 post-injury. These results indicate that recovery of locomotion occurs prior to recovery of isometric force and that functional recovery occurs earlier than structural regeneration. Thus, it is suggested that recovery of the movement and function of injured skeletal muscles might be insufficient as markers for estimating the degree of neuromuscular system reconstitution.

Resting state network topology of the ferret brain.

PubMed

Zhou, Zhe Charles; Salzwedel, Andrew P; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K; Gilmore, John H; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-12-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. Copyright © 2016 Elsevier Inc. All rights reserved.

Functional relevance for type 1 diabetes mellitus-associated genetic variants by using integrative analyses.

PubMed

Qiu, Ying-Hua; Deng, Fei-Yan; Tang, Zai-Xiang; Jiang, Zhen-Huan; Lei, Shu-Feng

2015-10-01

Type 1 diabetes mellitus (type 1 DM) is an autoimmune disease. Although genome-wide association studies (GWAS) and meta-analyses have successfully identified numerous type 1 DM-associated susceptibility loci, the underlying mechanisms for these susceptibility loci are currently largely unclear. Based on publicly available datasets, we performed integrative analyses (i.e., integrated gene relationships among implicated loci, differential gene expression analysis, functional prediction and functional annotation clustering analysis) and combined with expression quantitative trait loci (eQTL) results to further explore function mechanisms underlying the associations between genetic variants and type 1 DM. Among a total of 183 type 1 DM-associated SNPs, eQTL analysis showed that 17 SNPs with cis-regulated eQTL effects on 9 genes. All the 9 eQTL genes enrich in immune-related pathways or Gene Ontology (GO) terms. Functional prediction analysis identified 5 SNPs located in transcription factor (TF) binding sites. Of the 9 eQTL genes, 6 (TAP2, HLA-DOB, HLA-DQB1, HLA-DQA1, HLA-DRB5 and CTSH) were differentially expressed in type 1 DM-associated related cells. Especially, rs3825932 in CTSH has integrative functional evidence supporting the association with type 1 DM. These findings indicated that integrative analyses can yield important functional information to link genetic variants and type 1 DM. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Metagenomic analysis reveals significant changes of microbial compositions and protective functions during drinking water treatment.

PubMed

Chao, Yuanqing; Ma, Liping; Yang, Ying; Ju, Feng; Zhang, Xu-Xiang; Wu, Wei-Min; Zhang, Tong

2013-12-19

The metagenomic approach was applied to characterize variations of microbial structure and functions in raw (RW) and treated water (TW) in a drinking water treatment plant (DWTP) at Pearl River Delta, China. Microbial structure was significantly influenced by the treatment processes, shifting from Gammaproteobacteria and Betaproteobacteria in RW to Alphaproteobacteria in TW. Further functional analysis indicated the basic metabolic functions of microorganisms in TW did not vary considerably. However, protective functions, i.e. glutathione synthesis genes in 'oxidative stress' and 'detoxification' subsystems, significantly increased, revealing the surviving bacteria may have higher chlorine resistance. Similar results were also found in glutathione metabolism pathway, which identified the major reaction for glutathione synthesis and supported more genes for glutathione metabolism existed in TW. This metagenomic study largely enhanced our knowledge about the influences of treatment processes, especially chlorination, on bacterial community structure and protective functions (e.g. glutathione metabolism) in ecosystems of DWTPs.

VALUING BENEFITS FROM WATER QUALITY IMPROVEMENTS USING KUHN TUCKER MODEL - A COMPARATIVE ANALYSIS ON UTILITY FUNCTIONAL FORMS-

NASA Astrophysics Data System (ADS)

Okuyama, Tadahiro

Kuhn-Tucker model, which has studied in recent years, is a benefit valuation technique using the revealed-preference data, and the feature is to treatvarious patterns of corner solutions flexibly. It is widely known for the benefit calculation using the revealed-preference data that a value of a benefit changes depending on a functional form. However, there are little studies which examine relationship between utility functions and values of benefits in Kuhn-Tucker model. The purpose of this study is to analysis an influence of the functional form to the value of a benefit. Six types of utility functions are employed for benefit calculations. The data of the recreational activity of 26 beaches of Miyagi Prefecture were employed. Calculation results indicated that Phaneuf and Siderelis (2003) and Whitehead et al.(2010)'s functional forms are useful for benefit calculations.

An evaluation of generalization of mands during functional communication training.

PubMed

Falcomata, Terry S; Wacker, David P; Ringdahl, Joel E; Vinquist, Kelly; Dutt, Anuradha

2013-01-01

The primary purpose of this study was to evaluate the generalization of mands during functional communication training (FCT) and sign language training across functional contexts (i.e., positive reinforcement, negative reinforcement). A secondary purpose was to evaluate a training procedure based on stimulus control to teach manual signs. During the treatment evaluation, we implemented sign language training in 1 functional context (e.g., positive reinforcement by attention) while continuing the functional analysis conditions in 2 other contexts (e.g., positive reinforcement by tangible item; negative reinforcement by escape). During the generalization evaluation, we tested for the generalization of trained mands across functional contexts (i.e., positive reinforcement; negative reinforcement) by implementing extinction in the 2 nontarget contexts. The results suggested that the stimulus control training procedure effectively taught manual signs and treated destructive behavior. Specific patterns of generalization of trained mands and destructive behavior also were observed. © Society for the Experimental Analysis of Behavior.

The convergence of the order sequence and the solution function sequence on fractional partial differential equation

NASA Astrophysics Data System (ADS)

Rusyaman, E.; Parmikanti, K.; Chaerani, D.; Asefan; Irianingsih, I.

2018-03-01

One of the application of fractional ordinary differential equation is related to the viscoelasticity, i.e., a correlation between the viscosity of fluids and the elasticity of solids. If the solution function develops into function with two or more variables, then its differential equation must be changed into fractional partial differential equation. As the preliminary study for two variables viscoelasticity problem, this paper discusses about convergence analysis of function sequence which is the solution of the homogenous fractional partial differential equation. The method used to solve the problem is Homotopy Analysis Method. The results show that if given two real number sequences (αn) and (βn) which converge to α and β respectively, then the solution function sequences of fractional partial differential equation with order (αn, βn) will also converge to the solution function of fractional partial differential equation with order (α, β).

An analysis of maintenance following functional communication training.

PubMed Central

Durand, V M; Carr, E G

1992-01-01

The multiple and long-term effects of functional communication training relative to a common reductive procedure (time-out from positive reinforcement) were evaluated. Twelve children participated in a functional analysis of their challenging behaviors (Study 1), which implicated adult attention as a maintaining variable. The children were then matched for chronological age, mental age, and language age and assigned to two groups. One group received functional communication training as an intervention for their challenging behavior, and the second group received time-out as a contrast. Both interventions were initially successful (Study 2), but durable results were achieved only with the group that received functional communication training across different stimulus conditions (Study 3). Students whose challenging behaviors were previously reduced with time-out resumed these behaviors in the presence of naive teachers unaware of the children's intervention history. The value of teaching communicative responses to promote maintenance is discussed as it relates to the concept of functional equivalence. PMID:1478902

Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations

PubMed Central

Beleva Guthrie, Violeta; Masica, David L; Fraser, Andrew; Federico, Joseph; Fan, Yunfan; Camps, Manel; Karchin, Rachel

2018-01-01

Abstract The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure. PMID:29522102

How a submarine returns to periscope depth: analysing complex socio-technical systems using Cognitive Work Analysis.

PubMed

Stanton, Neville A; Bessell, Kevin

2014-01-01

This paper presents the application of Cognitive Work Analysis to the description of the functions, situations, activities, decisions, strategies, and competencies of a Trafalgar class submarine when performing the function of returning to periscope depth. All five phases of Cognitive Work Analysis are presented, namely: Work Domain Analysis, Control Task Analysis, Strategies Analysis, Social Organisation and Cooperation Analysis, and Worker Competencies Analysis. Complex socio-technical systems are difficult to analyse but Cognitive Work Analysis offers an integrated way of analysing complex systems with the core of functional means-ends analysis underlying all of the other representations. The joined-up analysis offers a coherent framework for understanding how socio-technical systems work. Data were collected through observation and interviews at different sites across the UK. The resultant representations present a statement of how the work domain and current activities are configured in this complex socio-technical system. This is intended to provide a baseline, from which all future conceptions of the domain may be compared. The strength of the analysis is in the multiple representations from which the constraints acting on the work may be analysed. Future research needs to challenge the assumptions behind these constraints in order to develop new ways of working. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology

PubMed Central

2011-01-01

Background The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. Methods In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. Results The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server database. The internet platform was tested on PC Intel Core2 Duo T9600 2.8GHz 4GB RAM server with 768x576 pixel size, 1.28Mb tiff format images reffering to meningioma tumour (x400, Ki-67/MIB-1). The time consumption was as following: at analysis by CAMI, locally on a server – 3.5 seconds, at remote analysis – 26 seconds, from which 22 seconds were used for data transfer via internet connection. At jpg format image (102 Kb) the consumption time was reduced to 14 seconds. Conclusions The results have confirmed that designed remote platform can be useful for pathology image analysis. The time consumption is depended mainly on the image size and speed of the internet connections. The presented implementation can be used for many types of analysis at different staining, tissue, morphometry approaches, etc. The significant problem is the implementation of the JSP page in the multithread form, that can be used parallelly by many users. The presented platform for image analysis in pathology can be especially useful for small laboratory without its own image analysis system. PMID:21489188

Global analyses of Ceratocystis cacaofunesta mitochondria: from genome to proteome.

PubMed

Ambrosio, Alinne Batista; do Nascimento, Leandro Costa; Oliveira, Bruno V; Teixeira, Paulo José P L; Tiburcio, Ricardo A; Toledo Thomazella, Daniela P; Leme, Adriana F P; Carazzolle, Marcelo F; Vidal, Ramon O; Mieczkowski, Piotr; Meinhardt, Lyndel W; Pereira, Gonçalo A G; Cabrera, Odalys G

2013-02-11

The ascomycete fungus Ceratocystis cacaofunesta is the causal agent of wilt disease in cacao, which results in significant economic losses in the affected producing areas. Despite the economic importance of the Ceratocystis complex of species, no genomic data are available for any of its members. Given that mitochondria play important roles in fungal virulence and the susceptibility/resistance of fungi to fungicides, we performed the first functional analysis of this organelle in Ceratocystis using integrated "omics" approaches. The C. cacaofunesta mitochondrial genome (mtDNA) consists of a single, 103,147-bp circular molecule, making this the second largest mtDNA among the Sordariomycetes. Bioinformatics analysis revealed the presence of 15 conserved genes and 37 intronic open reading frames in C. cacaofunesta mtDNA. Here, we predicted the mitochondrial proteome (mtProt) of C. cacaofunesta, which is comprised of 1,124 polypeptides - 52 proteins that are mitochondrially encoded and 1,072 that are nuclearly encoded. Transcriptome analysis revealed 33 probable novel genes. Comparisons among the Gene Ontology results of the predicted mtProt of C. cacaofunesta, Neurospora crassa and Saccharomyces cerevisiae revealed no significant differences. Moreover, C. cacaofunesta mitochondria were isolated, and the mtProt was subjected to mass spectrometric analysis. The experimental proteome validated 27% of the predicted mtProt. Our results confirmed the existence of 110 hypothetical proteins and 7 novel proteins of which 83 and 1, respectively, had putative mitochondrial localization. The present study provides the first partial genomic analysis of a species of the Ceratocystis genus and the first predicted mitochondrial protein inventory of a phytopathogenic fungus. In addition to the known mitochondrial role in pathogenicity, our results demonstrated that the global function analysis of this organelle is similar in pathogenic and non-pathogenic fungi, suggesting that its relevance in the lifestyle of these organisms should be based on a small number of specific proteins and/or with respect to differential gene regulation. In this regard, particular interest should be directed towards mitochondrial proteins with unknown function and the novel protein that might be specific to this species. Further functional characterization of these proteins could enhance our understanding of the role of mitochondria in phytopathogenicity.

Security Analysis of Selected AMI Failure Scenarios Using Agent Based Game Theoretic Simulation

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

Abercrombie, Robert K; Schlicher, Bob G; Sheldon, Frederick T

Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our analysis on the Advanced Metering Infrastructure (AMI) functional domain which the National Electric Sector Cyber security Organization Resource (NESCOR) working group has currently documented 29 failure scenarios. The strategy for the game was developed by analyzing five electric sector representative failure scenarios contained in the AMI functional domain. From thesemore » five selected scenarios, we characterize them into three specific threat categories affecting confidentiality, integrity and availability (CIA). The analysis using our ABGT simulation demonstrates how to model the AMI functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the AMI network with respect to CIA.« less

The Researches on Damage Detection Method for Truss Structures

NASA Astrophysics Data System (ADS)

Wang, Meng Hong; Cao, Xiao Nan

2018-06-01

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

Inverse Thermal Analysis of Titanium GTA Welds Using Multiple Constraints

NASA Astrophysics Data System (ADS)

Lambrakos, S. G.; Shabaev, A.; Huang, L.

2015-06-01

Inverse thermal analysis of titanium gas-tungsten-arc welds using multiple constraint conditions is presented. This analysis employs a methodology that is in terms of numerical-analytical basis functions for inverse thermal analysis of steady-state energy deposition in plate structures. The results of this type of analysis provide parametric representations of weld temperature histories that can be adopted as input data to various types of computational procedures, such as those for prediction of solid-state phase transformations. In addition, these temperature histories can be used to construct parametric function representations for inverse thermal analysis of welds corresponding to other process parameters or welding processes whose process conditions are within similar regimes. The present study applies an inverse thermal analysis procedure that provides for the inclusion of constraint conditions associated with both solidification and phase transformation boundaries.

Impact Factors and Risk Analysis of Tropical Cyclones on a Highway Network.

PubMed

Yang, Saini; Hu, Fuyu; Jaeger, Carlo

2016-02-01

Coastal areas typically have high social and economic development and are likely to suffer huge losses due to tropical cyclones. These cyclones have a great impact on the transportation network, but there have been a limited number of studies about tropical-cyclone-induced transportation network functional damages, especially in Asia. This study develops an innovative measurement and analytical tool for highway network functional damage and risk in the context of a tropical cyclone, with which we explored the critical spatial characteristics of tropical cyclones with regard to functional damage to a highway network by developing linear regression models to quantify their relationship. Furthermore, we assessed the network's functional risk and calculated the return periods under different damage levels. In our analyses, we consider the real-world highway network of Hainan province, China. Our results illustrate that the most important spatial characteristics were location (in particular, the midlands), travel distance, landfalling status, and origin coordinates. However, the trajectory direction did not obviously affect the results. Our analyses indicate that the highway network of Hainan province may suffer from a 90% functional damage scenario every 4.28 years. These results have critical policy implications for the transport sector in reference to emergency planning and disaster reduction. © 2015 Society for Risk Analysis.

Aminopropyl groups of the functionalized Mobil Crystalline Material 41 as a carrier for controlled diclofenac sodium and piroxicam delivery

PubMed Central

Khodaverdi, Elham; Ahmadi, Mina; Kamali, Hossein; Hadizadeh, Farzin

2017-01-01

Objective: Synthetic Mobil Crystalline Material 41 (MCM-41) as a mesoporous material and functionalized MCM-41 using aminopropyl groups were studied in order to investigate their ability to encapsulate and to control the release of diclofenac sodium and piroxicam. Materials and Methods: MCM-41 was synthesized through sol–gel procedure and functionalized with aminopropyl groups. The physicochemical properties of MCM-41 were studied through particle size analysis, infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, and carbon–hydrogen–nitrogen analysis. Diclofenac sodium and piroxicam were loaded into the MCM-41 matrix using the filtration and solvent evaporation methods. The drug-loading capacity was determined by ultraviolet, Fourier transform infrared, X-ray diffraction, and Brunauer–Emmett–Teller analysis. Results: According to the results for pure drug release, >57% was released in the 1st h, but when these drugs were loaded into pure Mobil Crystalline Material 41 (MCM-41) and functionalized MCM-41, the release into the simulated gastrointestinal medium was less, continuous, and slower. The release of piroxicam from functionalized MCM-41 was slower than that from MCM-41 in the simulated intestinal medium because of the formation of electrostatic bonds between piroxicam and the aminopropyl groups of the functionalized MCM-41. However, in the case of diclofenac sodium, there was no significant difference between pure MCM-41 and functionalized MCM-41. The difference between piroxicam and diclofenac sodium was due to the high solubility of diclofenac sodium in the intestinal medium (pH 6.8), which caused more rapid release from the matrixes than for piroxicam. Conclusion: Our findings indicate that, after functionalization of MCM-41, it could offer a good means of delivering controlled diclofenac sodium and piroxicam. PMID:29692976

A Meta-analysis of Cerebellar Contributions to Higher Cognition from PET and fMRI studies

PubMed Central

Keren-Happuch, E; Chen, Shen-Hsing Annabel; Ho, Moon-Ho Ringo; Desmond, John E.

2013-01-01

A growing interest in cerebellar function and its involvement in higher cognition have prompted much research in recent years. Cerebellar presence in a wide range of cognitive functions examined within an increasing body of neuroimaging literature has been observed. We applied a meta-analytic approach, which employed the activation likelihood estimate method, to consolidate results of cerebellar involvement accumulated in different cognitive tasks of interest and systematically identified similarities among the studies. The current analysis included 88 neuroimaging studies demonstrating cerebellar activations in higher cognitive domains involving emotion, executive function, language, music, timing and working memory. While largely consistent with a prior meta-analysis by Stoodley and Schmahmann (2009), our results extended their findings to include music and timing domains to provide further insights into cerebellar involvement and elucidate its role in higher cognition. In addition, we conducted inter- and intra-domain comparisons for the cognitive domains of emotion, language and working memory. We also considered task differences within the domain of verbal working memory by conducting a comparison of the Sternberg with the n-back task, as well as an analysis of the differential components within the Sternberg task. Results showed a consistent cerebellar presence in the timing domain, providing evidence for a role in time keeping. Unique clusters identified within the domain further refine the topographic organization of the cerebellum. PMID:23125108

Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

PubMed

Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

2018-06-13

To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

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

Megala, M.; Rajkumar, Beulah J. M., E-mail: beulah-rajkumar@yahoo.co.in

The electronic and optical transfer properties of Benzene, Benzoic Acid (BA), Nitrobenzene (NB) and Para Nitro Benzoic Acid (PNBA) at ground and first excited state has been investigated by the Density functional theory (DFT)and Time Dependent Density Functional Theory (TDDFT) using SVWN functional/3-21G basis set respectively. Possible intra-molecular charge transfer and n to π* transitions in the ground and the first excitation states have been predicted by the molecular orbitals and the Natural Bond Orbital (NBO) analysis. The simulated absorption spectra have been generated and the result compared with existing experimental results.

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

Representation of analysis results involving aleatory and epistemic uncertainty.

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

Johnson, Jay Dean; Helton, Jon Craig; Oberkampf, William Louis

2008-08-01

Procedures are described for the representation of results in analyses that involve both aleatory uncertainty and epistemic uncertainty, with aleatory uncertainty deriving from an inherent randomness in the behavior of the system under study and epistemic uncertainty deriving from a lack of knowledge about the appropriate values to use for quantities that are assumed to have fixed but poorly known values in the context of a specific study. Aleatory uncertainty is usually represented with probability and leads to cumulative distribution functions (CDFs) or complementary cumulative distribution functions (CCDFs) for analysis results of interest. Several mathematical structures are available for themore » representation of epistemic uncertainty, including interval analysis, possibility theory, evidence theory and probability theory. In the presence of epistemic uncertainty, there is not a single CDF or CCDF for a given analysis result. Rather, there is a family of CDFs and a corresponding family of CCDFs that derive from epistemic uncertainty and have an uncertainty structure that derives from the particular uncertainty structure (i.e., interval analysis, possibility theory, evidence theory, probability theory) used to represent epistemic uncertainty. Graphical formats for the representation of epistemic uncertainty in families of CDFs and CCDFs are investigated and presented for the indicated characterizations of epistemic uncertainty.« less

Towards tests of quark-hadron duality with functional analysis and spectral function data

NASA Astrophysics Data System (ADS)

Boito, Diogo; Caprini, Irinel

2017-04-01

The presence of terms that violate quark-hadron duality in the expansion of QCD Green's functions is a generally accepted fact. Recently, a new approach was proposed for the study of duality violations (DVs), which exploits the existence of a rigorous lower bound on the functional distance, measured in a certain norm, between a "true" correlator and its approximant calculated theoretically along a contour in the complex energy plane. In the present paper, we pursue the investigation of functional-analysis-based tests towards their application to real spectral function data. We derive a closed analytic expression for the minimal functional distance based on the general weighted L2 norm and discuss its relation with the distance measured in the L∞ norm. Using fake data sets obtained from a realistic toy model in which we allow for covariances inspired from the publicly available ALEPH spectral functions, we obtain, by Monte Carlo simulations, the statistical distribution of the strength parameter that measures the magnitude of the DV term added to the usual operator product expansion. The results show that, if the region with large errors near the end point of the spectrum in τ decays is excluded, the functional-analysis-based tests using either L2 or L∞ norms are able to detect, in a statistically significant way, the presence of DVs in realistic spectral function pseudodata.

A Rasch-validated version of the upper extremity functional index for interval-level measurement of upper extremity function.

PubMed

Hamilton, Clayon B; Chesworth, Bert M

2013-11-01

The original 20-item Upper Extremity Functional Index (UEFI) has not undergone Rasch validation. The purpose of this study was to determine whether Rasch analysis supports the UEFI as a measure of a single construct (ie, upper extremity function) and whether a Rasch-validated UEFI has adequate reproducibility for individual-level patient evaluation. This was a secondary analysis of data from a repeated-measures study designed to evaluate the measurement properties of the UEFI over a 3-week period. Patients (n=239) with musculoskeletal upper extremity disorders were recruited from 17 physical therapy clinics across 4 Canadian provinces. Rasch analysis of the UEFI measurement properties was performed. If the UEFI did not fit the Rasch model, misfitting patients were deleted, items with poor response structure were corrected, and misfitting items and redundant items were deleted. The impact of differential item functioning on the ability estimate of patients was investigated. A 15-item modified UEFI was derived to achieve fit to the Rasch model where the total score was supported as a measure of upper extremity function only. The resultant UEFI-15 interval-level scale (0-100, worst to best state) demonstrated excellent internal consistency (person separation index=0.94) and test-retest reliability (intraclass correlation coefficient [2,1]=.95). The minimal detectable change at the 90% confidence interval was 8.1. Patients who were ambidextrous or bilaterally affected were excluded to allow for the analysis of differential item functioning due to limb involvement and arm dominance. Rasch analysis did not support the validity of the 20-item UEFI. However, the UEFI-15 was a valid and reliable interval-level measure of a single dimension: upper extremity function. Rasch analysis supports using the UEFI-15 in physical therapist practice to quantify upper extremity function in patients with musculoskeletal disorders of the upper extremity.

KWICgrouper--Designing a Tool for Corpus-Driven Concordance Analysis

ERIC Educational Resources Information Center

O'Donnell, Matthew Brook

2008-01-01

The corpus-driven analysis of concordance data often results in the identification of groups of lines in which repeated patterns around the node item establish membership in a particular function meaning group (Mahlberg, 2005). This paper explains the KWICgrouper, a concept designed to support this kind of concordance analysis. Groups are defined…

The effects of whole body vibration on mobility and balance in children with cerebral palsy: a systematic review with meta-analysis

PubMed Central

Saquetto, M.; Carvalho, V.; Silva, C.; Conceição, C.; Gomes-Neto, M.

2015-01-01

Objective: We performed a meta-analysis to evaluate the effects of whole-body vibration on physiologic and functional measurements in children with cerebral palsy. Design and methods: We searched MEDLINE, Cochrane Controlled Trials Register, EMBASE, Scielo, CINAHL (from the earliest date available to November 2014) for randomized controlled trials, that aimed to investigate the effects of whole-body vibration versus exercise and/or versus control on physiologic and functional measurements in children with cerebral palsy. Two reviewers independently selected the studies. Weighted mean differences (WMDs) and 95% confidence intervals (CIs) were calculated. Results: Six studies with 176 patients comparing whole-body vibration to exercise and/or control were included. Whole-body vibration resulted in improvement in: gait speed WMDs (0.13 95% CI:0.05 to 0.20); gross motor function dimension E WMDs (2.97 95% CI:0.07 to 5.86) and femur bone density (1.32 95% CI:0.28 to 2.36). The meta-analysis also showed a nonsignificant difference in muscle strength and gross motor function dimension D for participants in the whole-body vibration compared with control group. No serious adverse events were reported. Conclusions: Whole-body vibration may improve gait speed and standing function in children with cerebral palsy and could be considered for inclusion in rehabilitation programs. PMID:26032205

Computer analysis of protein functional sites projection on exon structure of genes in Metazoa

PubMed Central

2015-01-01

Background Study of the relationship between the structural and functional organization of proteins and their coding genes is necessary for an understanding of the evolution of molecular systems and can provide new knowledge for many applications for designing proteins with improved medical and biological properties. It is well known that the functional properties of proteins are determined by their functional sites. Functional sites are usually represented by a small number of amino acid residues that are distantly located from each other in the amino acid sequence. They are highly conserved within their functional group and vary significantly in structure between such groups. According to this facts analysis of the general properties of the structural organization of the functional sites at the protein level and, at the level of exon-intron structure of the coding gene is still an actual problem. Results One approach to this analysis is the projection of amino acid residue positions of the functional sites along with the exon boundaries to the gene structure. In this paper, we examined the discontinuity of the functional sites in the exon-intron structure of genes and the distribution of lengths and phases of the functional site encoding exons in vertebrate genes. We have shown that the DNA fragments coding the functional sites were in the same exons, or in close exons. The observed tendency to cluster the exons that code functional sites which could be considered as the unit of protein evolution. We studied the characteristics of the structure of the exon boundaries that code, and do not code, functional sites in 11 Metazoa species. This is accompanied by a reduced frequency of intercodon gaps (phase 0) in exons encoding the amino acid residue functional site, which may be evidence of the existence of evolutionary limitations to the exon shuffling. Conclusions These results characterize the features of the coding exon-intron structure that affect the functionality of the encoded protein and allow a better understanding of the emergence of biological diversity. PMID:26693737

Effects of Heterogeniety on Spatial Pattern Analysis of Wild Pistachio Trees in Zagros Woodlands, Iran

NASA Astrophysics Data System (ADS)

Erfanifard, Y.; Rezayan, F.

2014-10-01

Vegetation heterogeneity biases second-order summary statistics, e.g., Ripley's K-function, applied for spatial pattern analysis in ecology. Second-order investigation based on Ripley's K-function and related statistics (i.e., L- and pair correlation function g) is widely used in ecology to develop hypothesis on underlying processes by characterizing spatial patterns of vegetation. The aim of this study was to demonstrate effects of underlying heterogeneity of wild pistachio (Pistacia atlantica Desf.) trees on the second-order summary statistics of point pattern analysis in a part of Zagros woodlands, Iran. The spatial distribution of 431 wild pistachio trees was accurately mapped in a 40 ha stand in the Wild Pistachio & Almond Research Site, Fars province, Iran. Three commonly used second-order summary statistics (i.e., K-, L-, and g-functions) were applied to analyse their spatial pattern. The two-sample Kolmogorov-Smirnov goodness-of-fit test showed that the observed pattern significantly followed an inhomogeneous Poisson process null model in the study region. The results also showed that heterogeneous pattern of wild pistachio trees biased the homogeneous form of K-, L-, and g-functions, demonstrating a stronger aggregation of the trees at the scales of 0-50 m than actually existed and an aggregation at scales of 150-200 m, while regularly distributed. Consequently, we showed that heterogeneity of point patterns may bias the results of homogeneous second-order summary statistics and we also suggested applying inhomogeneous summary statistics with related null models for spatial pattern analysis of heterogeneous vegetations.

Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder.

PubMed

Xing, Mengqi; Tadayonnejad, Reza; MacNamara, Annmarie; Ajilore, Olusola; DiGangi, Julia; Phan, K Luan; Leow, Alex; Klumpp, Heide

2017-01-01

Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state. Resting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks. WPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC. Theta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD.

Genomic survey, expression profile and co-expression network analysis of OsWD40 family in rice

PubMed Central

2012-01-01

Background WD40 proteins represent a large family in eukaryotes, which have been involved in a broad spectrum of crucial functions. Systematic characterization and co-expression analysis of OsWD40 genes enable us to understand the networks of the WD40 proteins and their biological processes and gene functions in rice. Results In this study, we identify and analyze 200 potential OsWD40 genes in rice, describing their gene structures, genome localizations, and evolutionary relationship of each member. Expression profiles covering the whole life cycle in rice has revealed that transcripts of OsWD40 were accumulated differentially during vegetative and reproductive development and preferentially up or down-regulated in different tissues. Under phytohormone treatments, 25 OsWD40 genes were differentially expressed with treatments of one or more of the phytohormone NAA, KT, or GA3 in rice seedlings. We also used a combined analysis of expression correlation and Gene Ontology annotation to infer the biological role of the OsWD40 genes in rice. The results suggested that OsWD40 genes may perform their diverse functions by complex network, thus were predictive for understanding their biological pathways. The analysis also revealed that OsWD40 genes might interact with each other to take part in metabolic pathways, suggesting a more complex feedback network. Conclusions All of these analyses suggest that the functions of OsWD40 genes are diversified, which provide useful references for selecting candidate genes for further functional studies. PMID:22429805

New whole-body sensory-motor gradients revealed using phase-locked analysis and verified using multivoxel pattern analysis and functional connectivity.

PubMed

Zeharia, Noa; Hertz, Uri; Flash, Tamar; Amedi, Amir

2015-02-18

Topographic organization is one of the main principles of organization in the human brain. Specifically, whole-brain topographic mapping using spectral analysis is responsible for one of the greatest advances in vision research. Thus, it is intriguing that although topography is a key feature also in the motor system, whole-body somatosensory-motor mapping using spectral analysis has not been conducted in humans outside M1/SMA. Here, using this method, we were able to map a homunculus in the globus pallidus, a key target area for deep brain stimulation, which has not been mapped noninvasively or in healthy subjects. The analysis clarifies contradictory and partial results regarding somatotopy in the caudal-cingulate zone and rostral-cingulate zone in the medial wall and in the putamen. Most of the results were confirmed at the single-subject level and were found to be compatible with results from animal studies. Using multivoxel pattern analysis, we could predict movements of individual body parts in these homunculi, thus confirming that they contain somatotopic information. Using functional connectivity, we demonstrate interhemispheric functional somatotopic connectivity of these homunculi, such that the somatotopy in one hemisphere could have been found given the connectivity pattern of the corresponding regions of interest in the other hemisphere. When inspecting the somatotopic and nonsomatotopic connectivity patterns, a similarity index indicated that the pattern of connected and nonconnected regions of interest across different homunculi is similar for different body parts and hemispheres. The results show that topographical gradients are even more widespread than previously assumed in the somatosensory-motor system. Spectral analysis can thus potentially serve as a gold standard for defining somatosensory-motor system areas for basic research and clinical applications. Copyright © 2015 the authors 0270-6474/15/352845-15$15.00/0.

Quantitative trait nucleotide analysis using Bayesian model selection.

PubMed

Blangero, John; Goring, Harald H H; Kent, Jack W; Williams, Jeff T; Peterson, Charles P; Almasy, Laura; Dyer, Thomas D

2005-10-01

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

Using machine-learning methods to analyze economic loss function of quality management processes

NASA Astrophysics Data System (ADS)

Dzedik, V. A.; Lontsikh, P. A.

2018-05-01

During analysis of quality management systems, their economic component is often analyzed insufficiently. To overcome this issue, it is necessary to withdraw the concept of economic loss functions from tolerance thinking and address it. Input data about economic losses in processes have a complex form, thus, using standard tools to solve this problem is complicated. Use of machine learning techniques allows one to obtain precise models of the economic loss function based on even the most complex input data. Results of such analysis contain data about the true efficiency of a process and can be used to make investment decisions.

Quantitative proteomic analysis of intact plastids.

PubMed

Shiraya, Takeshi; Kaneko, Kentaro; Mitsui, Toshiaki

2014-01-01

Plastids are specialized cell organelles in plant cells that are differentiated into various forms including chloroplasts, chromoplasts, and amyloplasts, and fulfill important functions in maintaining the overall cell metabolism and sensing environmental factors such as sunlight. It is therefore important to grasp the mechanisms of differentiation and functional changes of plastids in order to enhance the understanding of vegetality. In this chapter, details of a method for the extraction of intact plastids that makes analysis possible while maintaining the plastid functions are provided; in addition, a quantitative shotgun method for analyzing the composition and changes in the content of proteins in plastids as a result of environmental impacts is described.

Assaying gene function by growth competition experiment.

PubMed

Merritt, Joshua; Edwards, Jeremy S

2004-07-01

High-throughput screening and analysis is one of the emerging paradigms in biotechnology. In particular, high-throughput methods are essential in the field of functional genomics because of the vast amount of data generated in recent and ongoing genome sequencing efforts. In this report we discuss integrated functional analysis methodologies which incorporate both a growth competition component and a highly parallel assay used to quantify results of the growth competition. Several applications of the two most widely used technologies in the field, i.e., transposon mutagenesis and deletion strain library growth competition, and individual applications of several developing or less widely reported technologies are presented.

Psychological and functional effect of different primary treatments for prostate cancer: A comparative prospective analysis.

PubMed

Sciarra, Alessandro; Gentilucci, Alessandro; Salciccia, Stefano; Von Heland, Magnus; Ricciuti, Giam Piero; Marzio, Vittorio; Pierella, Federico; Musio, Daniela; Tombolini, Vincenzo; Frantellizzi, Viviana; Pasquini, Massimo; Maraone, Annalisa; Guandalini, Alessio; Maggi, Martina

2018-04-26

The aim of the study was to comparatively evaluate the psychological and functional effect of different primary treatments in patients with prostate cancer. We conducted a single-center prospective non randomized study in a real-life setting using functional and psychological questionnaires in prostate cancer cases submitted to radical prostatectomy, external radiotherapy, or active surveillance. Totally, 220 cases were evaluated at baseline and during the follow-up at 1-, 3-, 6-, and 12-month interval after therapy. Patients self-completed questionnaires on urinary symptoms and incontinence, erectile and bowel function, psychological distress (PD), anxiety, and depression. Several significant differences among the three groups of treatment were found regarding the total score of the functional questionnaires. Regarding PD, cases submitted to radical prostatectomy showed stable scores during all the 12 months of follow-up whereas cases submitted to radiotherapy showed a rapid significant worsening of scores at 1-month interval and persistent also at 6- and 12-month interval. Cases submitted to active surveillance showed a slight and slow worsening of scores only at 12-month interval. PD and depression resulted to be more associated with urinary symptoms than sexual function worsening whereas anxiety resulted to be associated either with urinary symptoms or sexual function worsening. The results of our comparative and prospective analysis could be used to better inform treatment decision-making. Patients and their teams might wish to know how functional and psychological aspects may differently be influenced by treatment choice. Copyright © 2018 Elsevier Inc. All rights reserved.

Isogeometric analysis of free-form Timoshenko curved beams including the nonlinear effects of large deformations

NASA Astrophysics Data System (ADS)

Hosseini, Seyed Farhad; Hashemian, Ali; Moetakef-Imani, Behnam; Hadidimoud, Saied

2018-03-01

In the present paper, the isogeometric analysis (IGA) of free-form planar curved beams is formulated based on the nonlinear Timoshenko beam theory to investigate the large deformation of beams with variable curvature. Based on the isoparametric concept, the shape functions of the field variables (displacement and rotation) in a finite element analysis are considered to be the same as the non-uniform rational basis spline (NURBS) basis functions defining the geometry. The validity of the presented formulation is tested in five case studies covering a wide range of engineering curved structures including from straight and constant curvature to variable curvature beams. The nonlinear deformation results obtained by the presented method are compared to well-established benchmark examples and also compared to the results of linear and nonlinear finite element analyses. As the nonlinear load-deflection behavior of Timoshenko beams is the main topic of this article, the results strongly show the applicability of the IGA method to the large deformation analysis of free-form curved beams. Finally, it is interesting to notice that, until very recently, the large deformations analysis of free-form Timoshenko curved beams has not been considered in IGA by researchers.

Using digital photogrammetry to conduct an anthropometric analysis of wheelchair users.

PubMed

Barros, Helda Oliveira; Soares, Marcelomárcio

2012-01-01

This study deals with using digital photogrammetry to make an anthropometric analysis of wheelchair users. To analyse the data, Digita software was used, which was made available by means of the agreement of the Design Department of the Federal University of Pernambuco--Brazil--with the Department of Ergonomics of the Technical University of Lisbon--Portugal. Data collection involved a random sample of 18 subjects and occurred in the Biomechanics Laboratory of the Maurice of Nassau Faculty, located in Recife, Pernambuco. The methodology applied comprises the steps of Ergonomic Assessment, Configuration of the Data Base, Taking Digital Photographs, Digitalising the Coordinates and Presentation of Results. 15 structural variables related to static anthropometry were analysed, and 4 functional range variables relating to dynamic anthropometry. The results were presented by analysing personal data, classified by gender, ethnicity and age; by functional analysis of the sample, classified by clinical diagnosis, results of assessing the joints, results of the evaluation through motion and postural evaluation; and of the analysis of the anthropometric sample, which indicated for each variable the number of people, the mean, the standard deviation, and the minimum, median and maximum values.

Characterization of bioplastic based from cassava crisp home industrial waste incorporated with chitosan and liquid smoke

NASA Astrophysics Data System (ADS)

Fathanah, U.; Lubis, M. R.; Nasution, F.; Masyawi, M. S.

2018-03-01

Cassava peel (Manihot utilissima) is waste of agricultural result that is much potential as raw material of bioplastic making. This research focuses on bioplastic making from cassava peel. It aims to characterize the resulted bioplastic (mechanical and physical properties, SEM analysis, FTIR analysis and time test of bioplastic degradation). The bioplastic preparation takes place by mixing starch of cassava peel and chitosan (20, 30, 40 and 50% w/w), glycerol 30% w/w as plasticizer, and liquid smoke (0, 1 and 2 mL) as antimicrobial agent. The research result shows the highest value of tensile strength is 96.04 MPa, the highest elongation at break is 52.27%, and the value of water-resistant test is 22.68%. Morphology analysis by using SEM shows uneven surface and there is fracture in its cross-section. The analysis of functional group by FTIR shows the presence of functional groups of O–H (hydroxyl), N–H (amine), dan CH3–O (ether). The fastest complete degradation of bioplastic occurs in 45 days, and the longest occurs in 57 days.

[Critic analysis of a comparative meta-analysis on the morbidity, functional and carcinologic results after radical prostatectomy according to surgical approach. Work of cancerology committee of the French urological association].

PubMed

Bastide, C; Rozet, F; Salomon, L; Mongiat-Artus, P; Beuzeboc, P; Cormier, L; Eiss, D; Gaschignard, N; Peyromaure, M; Richaud, P; Soulié, M

2010-09-01

Surgical approach for radical prostatectomy is even today a subject of debate in the urologic community. Many comparative studies between retropubic and laparoscopic approach (robotic assisted or not) were reported since 10 years without being able to decide between the supporters of retropubic or laparoscopic approach. The committee of cancer research of the French urological association took hold this question after a recent meta-analysis publication on this subject. Although imperfect, this meta-analysis exists and permits to conclude partially on the advantages and the inconveniences supposed for each surgical approach. Regarding morbidity after radical prostatectomy, the only significant difference reported concerns the hemorrhagic risk in favour of the laparoscopic approach. Regarding oncologic results, the only exploitable data concern positive surgical margins rate, which is identical whatever surgical approach. Concerning the functional results, no difference was reported in the literature between different surgical approaches. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

The effect of preoperative training on functional recovery in patients undergoing total knee arthroplasty: A systematic review and meta-analysis.

PubMed

Ma, Jian-Xiong; Zhang, Lu-Kai; Kuang, Ming-Jie; Zhao, Jie; Wang, Ying; Lu, Bin; Sun, Lei; Ma, Xin-Long

2018-03-01

A meta-analysis to evaluate the efficacy of preoperative training on functional recovery in patients undergoing total knee arthroplasty. Randomized controlled trials (RCTs) about relevant studies were searched from PubMed (1996-2017.4), Embase (1980-2017.4), and the Cochrane Library (CENTRAL 2017.4). Nine studies which evaluated the effect of preoperative training on functional recovery in patients undergoing TKA were included in our meta-analysis. Meta-analysis results were collected and analyzed by Review Manager 5.3 (Copenhagen: The Nordic Cochrane Center the Collaboration 2014). Nine studies containing 777 patients meet the inclusion criteria. Our pooled data analysis indicated that preoperative training was as effective as the control group in terms of visual analogue scale(VAS) score at ascend stairs (P = 0.41) and descend stars (P = 0.80), rang of motion (ROM) of flexion (P = 0.86) and extension (P = 0.60), short form 36 (SF-36) of physical function score (P = 0.07) and bodily pain score (P = 0.39), western Ontario and Macmaster universities osteoarthritis index (WOMAC) function score (P = 0.10), and time up and go (P = 0.28). While differences were found in length of stay (P < 0.05). Our meta-analysis demonstrated that preoperative training have the similar efficacy on functional recovery in patients following total knee arthroplasty compared with control group. However, high quality studies with more patients were needed in future. Copyright © 2018 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

PubMed

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

TAM 2.0: tool for MicroRNA set analysis.

PubMed

Li, Jianwei; Han, Xiaofen; Wan, Yanping; Zhang, Shan; Zhao, Yingshu; Fan, Rui; Cui, Qinghua; Zhou, Yuan

2018-06-06

With the rapid accumulation of high-throughput microRNA (miRNA) expression profile, the up-to-date resource for analyzing the functional and disease associations of miRNAs is increasingly demanded. We here describe the updated server TAM 2.0 for miRNA set enrichment analysis. Through manual curation of over 9000 papers, a more than two-fold growth of reference miRNA sets has been achieved in comparison with previous TAM, which covers 9945 and 1584 newly collected miRNA-disease and miRNA-function associations, respectively. Moreover, TAM 2.0 allows users not only to test the functional and disease annotations of miRNAs by overrepresentation analysis, but also to compare the input de-regulated miRNAs with those de-regulated in other disease conditions via correlation analysis. Finally, the functions for miRNA set query and result visualization are also enabled in the TAM 2.0 server to facilitate the community. The TAM 2.0 web server is freely accessible at http://www.scse.hebut.edu.cn/tam/ or http://www.lirmed.com/tam2/.

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.

PubMed

Chao-Gan, Yan; Yu-Feng, Zang

2010-01-01

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for "pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for "pipeline" data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.

Enhanced cardio vascular image analysis by combined representation of results from dynamic MRI and anatomic CTA

NASA Astrophysics Data System (ADS)

Kuehnel, C.; Hennemuth, A.; Oeltze, S.; Boskamp, T.; Peitgen, H.-O.

2008-03-01

The diagnosis support in the field of coronary artery disease (CAD) is very complex due to the numerous symptoms and performed studies leading to the final diagnosis. CTA and MRI are on their way to replace invasive catheter angiography. Thus, there is a need for sophisticated software tools that present the different analysis results, and correlate the anatomical and dynamic image information. We introduce a new software assistant for the combined result visualization of CTA and MR images, in which a dedicated concept for the structured presentation of original data, segmentation results, and individual findings is realized. Therefore, we define a comprehensive class hierarchy and assign suitable interaction functions. User guidance is coupled as closely as possible with available data, supporting a straightforward workflow design. The analysis results are extracted from two previously developed software assistants, providing coronary artery analysis and measurements, function analysis as well as late enhancement data investigation. As an extension we introduce a finding concept directly relating suspicious positions to the underlying data. An affine registration of CT and MR data in combination with the AHA 17-segment model enables the coupling of local findings to positions in all data sets. Furthermore, sophisticated visualization in 2D and 3D and interactive bull's eye plots facilitate a correlation of coronary stenoses and physiology. The software has been evaluated on 20 patient data sets.

Functional Impairment and Changes in Depression Subtypes for Women in STAR*D: A Latent Transition Analysis

PubMed Central

Rothschild, Anthony J.; Lapane, Kate L.

2016-01-01

Abstract Objective: To characterize the association between functional impairment and major depression subtypes at baseline and to characterize changes in subtypes by functional impairment level in women receiving citalopram in level 1 of the Sequenced Treatment Alternatives to Relieve Depression trial. Method: Women who completed baseline and week 12 study visits were included. Items from the self-reported Quick Inventory of Depressive Symptomatology were used to define the latent depression subtypes. The Work and Social Adjustment Scale was used to classify baseline functional impairment. A latent transition analysis model provided estimates of the prevalence of subtype membership and transition probabilities by functional impairment level. Results: Of the 755 women included, 69% had major functional impairment at baseline. Regardless of functional impairment level, the subtypes were differentiated by depression severity, appetite changes, psychomotor disturbances, and insomnia. Sixty-seven percent of women with normal/significant functional impairment and 60% of women with major impairment were likely to transition to a symptom resolution subtype at week 12. Women with baseline major impairment who were in the severe with psychomotor agitation subtype at the beginning of the study were least likely to transition to the symptom resolution subtype (4% chance). Conclusions: Functional impairment level was related to both the baseline depression subtype and the likelihood of moving to a different subtype. These results underscore the need to incorporate not only depression symptoms but also functioning in the assessment and treatment of depression. PMID:26488110

Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function.

PubMed

Guo, Qian; Zhou, Tiantong; Li, Wenjie; Dong, Li; Wang, Suhong; Zou, Ling

2017-07-01

Executive function refers to conscious control in psychological process which relates to thinking and action. Emotional decision is a part of hot executive function and contains emotion and logic elements. As a kind of important social adaptation ability, more and more attention has been paid in recent years. Gambling task can be well performed in the study of emotional decision. As fMRI researches focused on gambling task show not completely consistent brain activation regions, this study adopted EEG-fMRI fusion technology to reveal brain neural activity related with feedback stimuli. In this study, an EEG-informed fMRI analysis was applied to process simultaneous EEG-fMRI data. First, relative power-spectrum analysis and K-means clustering method were performed separately to extract EEG-fMRI features. Then, Generalized linear models were structured using fMRI data and using different EEG features as regressors. The results showed that in the win versus loss stimuli, the activated regions almost covered the caudate, the ventral striatum (VS), the orbital frontal cortex (OFC), and the cingulate. Wide activation areas associated with reward and punishment were revealed by the EEG-fMRI integration analysis than the conventional fMRI results, such as the posterior cingulate and the OFC. The VS and the medial prefrontal cortex (mPFC) were found when EEG power features were performed as regressors of GLM compared with results entering the amplitudes of feedback-related negativity (FRN) as regressors. Furthermore, the brain region activation intensity was the strongest when theta-band power was used as a regressor compared with the other two fusion results. The EEG-based fMRI analysis can more accurately depict the whole-brain activation map and analyze emotional decision problems.

Multilayer motif analysis of brain networks

NASA Astrophysics Data System (ADS)

Battiston, Federico; Nicosia, Vincenzo; Chavez, Mario; Latora, Vito

2017-04-01

In the last decade, network science has shed new light both on the structural (anatomical) and on the functional (correlations in the activity) connectivity among the different areas of the human brain. The analysis of brain networks has made possible to detect the central areas of a neural system and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on anatomical and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows us to perform an analysis of the human brain where the structural and functional layers are considered together. In this work, we describe how to classify the subgraphs of a multiplex network, and we extend the motif analysis to networks with an arbitrary number of layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, anatomical and functional, respectively, obtained from diffusion and functional magnetic resonance imaging. Results indicate that subgraphs in which the presence of a physical connection between brain areas (links at the structural layer) coexists with a non-trivial positive correlation in their activities are statistically overabundant. Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the probability to find a link in one layer depends on the intensity of the connection in the other one. Showing that functional connectivity is non-trivially constrained by the underlying anatomical network, our work contributes to a better understanding of the interplay between the structure and function in the human brain.

Effect of Increased Intensity of Physiotherapy on Patient Outcomes After Stroke: An Economic Literature Review and Cost-Effectiveness Analysis

PubMed Central

Chan, B

2015-01-01

Background Functional improvements have been seen in stroke patients who have received an increased intensity of physiotherapy. This requires additional costs in the form of increased physiotherapist time. Objectives The objective of this economic analysis is to determine the cost-effectiveness of increasing the intensity of physiotherapy (duration and/or frequency) during inpatient rehabilitation after stroke, from the perspective of the Ontario Ministry of Health and Long-term Care. Data Sources The inputs for our economic evaluation were extracted from articles published in peer-reviewed journals and from reports from government sources or the Canadian Stroke Network. Where published data were not available, we sought expert opinion and used inputs based on the experts' estimates. Review Methods The primary outcome we considered was cost per quality-adjusted life-year (QALY). We also evaluated functional strength training because of its similarities to physiotherapy. We used a 2-state Markov model to evaluate the cost-effectiveness of functional strength training and increased physiotherapy intensity for stroke inpatient rehabilitation. The model had a lifetime timeframe with a 5% annual discount rate. We then used sensitivity analyses to evaluate uncertainty in the model inputs. Results We found that functional strength training and higher-intensity physiotherapy resulted in lower costs and improved outcomes over a lifetime. However, our sensitivity analyses revealed high levels of uncertainty in the model inputs, and therefore in the results. Limitations There is a high level of uncertainty in this analysis due to the uncertainty in model inputs, with some of the major inputs based on expert panel consensus or expert opinion. In addition, the utility outcomes were based on a clinical study conducted in the United Kingdom (i.e., 1 study only, and not in an Ontario or Canadian setting). Conclusions Functional strength training and higher-intensity physiotherapy may result in lower costs and improved health outcomes. However, these results should be interpreted with caution. PMID:26366241

The effects of sex hormones on immune function: a meta-analysis.

PubMed

Foo, Yong Zhi; Nakagawa, Shinichi; Rhodes, Gillian; Simmons, Leigh W

2017-02-01

The effects of sex hormones on immune function have received much attention, especially following the proposal of the immunocompetence handicap hypothesis. Many studies, both experimental and correlational, have been conducted to test the relationship between immune function and the sex hormones testosterone in males and oestrogen in females. However, the results are mixed. We conducted four cross-species meta-analyses to investigate the relationship between sex hormones and immune function: (i) the effect of testosterone manipulation on immune function in males, (ii) the correlation between circulating testosterone level and immune function in males, (iii) the effect of oestrogen manipulation on immune function in females, and (iv) the correlation between circulating oestrogen level and immune function in females. The results from the experimental studies showed that testosterone had a medium-sized immunosuppressive effect on immune function. The effect of oestrogen, on the other hand, depended on the immune measure used. Oestrogen suppressed cell-mediated immune function while reducing parasite loads. The overall correlation (meta-analytic relationship) between circulating sex hormone level and immune function was not statistically significant for either testosterone or oestrogen despite the power of meta-analysis. These results suggest that correlational studies have limited value for testing the effects of sex hormones on immune function. We found little evidence of publication bias in the four data sets using indirect tests. There was a weak and positive relationship between year of publication and effect size for experimental studies of testosterone that became non-significant after we controlled for castration and immune measure, suggesting that the temporal trend was due to changes in these moderators over time. Graphical analyses suggest that the temporal trend was due to an increased use of cytokine measures across time. We found substantial heterogeneity in effect sizes, except in correlational studies of testosterone, even after we accounted for the relevant random and fixed factors. In conclusion, our results provide good evidence that testosterone suppresses immune function and that the effect of oestrogen varies depending on the immune measure used. © 2016 Cambridge Philosophical Society.

A Short Note on the Scaling Function Constant Problem in the Two-Dimensional Ising Model

NASA Astrophysics Data System (ADS)

Bothner, Thomas

2018-02-01

We provide a simple derivation of the constant factor in the short-distance asymptotics of the tau-function associated with the 2-point function of the two-dimensional Ising model. This factor was first computed by Tracy (Commun Math Phys 142:297-311, 1991) via an exponential series expansion of the correlation function. Further simplifications in the analysis are due to Tracy and Widom (Commun Math Phys 190:697-721, 1998) using Fredholm determinant representations of the correlation function and Wiener-Hopf approximation results for the underlying resolvent operator. Our method relies on an action integral representation of the tau-function and asymptotic results for the underlying Painlevé-III transcendent from McCoy et al. (J Math Phys 18:1058-1092, 1977).

A new set of ESTs and cDNA clones from full-length and normalized libraries for gene discovery and functional characterization in citrus

PubMed Central

Marques, M Carmen; Alonso-Cantabrana, Hugo; Forment, Javier; Arribas, Raquel; Alamar, Santiago; Conejero, Vicente; Perez-Amador, Miguel A

2009-01-01

Background Interpretation of ever-increasing raw sequence information generated by modern genome sequencing technologies faces multiple challenges, such as gene function analysis and genome annotation. Indeed, nearly 40% of genes in plants encode proteins of unknown function. Functional characterization of these genes is one of the main challenges in modern biology. In this regard, the availability of full-length cDNA clones may fill in the gap created between sequence information and biological knowledge. Full-length cDNA clones facilitate functional analysis of the corresponding genes enabling manipulation of their expression in heterologous systems and the generation of a variety of tagged versions of the native protein. In addition, the development of full-length cDNA sequences has the power to improve the quality of genome annotation. Results We developed an integrated method to generate a new normalized EST collection enriched in full-length and rare transcripts of different citrus species from multiple tissues and developmental stages. We constructed a total of 15 cDNA libraries, from which we isolated 10,898 high-quality ESTs representing 6142 different genes. Percentages of redundancy and proportion of full-length clones range from 8 to 33, and 67 to 85, respectively, indicating good efficiency of the approach employed. The new EST collection adds 2113 new citrus ESTs, representing 1831 unigenes, to the collection of citrus genes available in the public databases. To facilitate functional analysis, cDNAs were introduced in a Gateway-based cloning vector for high-throughput functional analysis of genes in planta. Herein, we describe the technical methods used in the library construction, sequence analysis of clones and the overexpression of CitrSEP, a citrus homolog to the Arabidopsis SEP3 gene, in Arabidopsis as an example of a practical application of the engineered Gateway vector for functional analysis. Conclusion The new EST collection denotes an important step towards the identification of all genes in the citrus genome. Furthermore, public availability of the cDNA clones generated in this study, and not only their sequence, enables testing of the biological function of the genes represented in the collection. Expression of the citrus SEP3 homologue, CitrSEP, in Arabidopsis results in early flowering, along with other phenotypes resembling the over-expression of the Arabidopsis SEPALLATA genes. Our findings suggest that the members of the SEP gene family play similar roles in these quite distant plant species. PMID:19747386

Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

PubMed

Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

2016-09-01

In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control and disease groups through the average curves in each group. Such group differences, however, neglect the variability in the sample of connectivity curves. In this article, the use of functional principal component analysis (FPCA) is demonstrated to enrich functional connectivity studies by providing increased power and flexibility for statistical inference. Specifically, individual connectivity curves are related to individual characteristics such as age and measures of cognitive function, thus providing a tool to relate brain connectivity with these variables at the individual level. This individual level analysis opens a new perspective that goes beyond previous group level comparisons. Using a large data set of resting-state functional magnetic resonance imaging scans, relationships between connectivity and two measures of cognitive function-episodic memory and executive function-were investigated. The group-based approach was implemented by dichotomizing the continuous cognitive variable and testing for group differences, resulting in no statistically significant findings. To demonstrate the new approach, FPCA was implemented, followed by linear regression models with cognitive scores as responses, identifying significant associations of connectivity in the right middle temporal region with both cognitive scores.

Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function

PubMed Central

2009-01-01

Background A central task in contemporary biosciences is the identification of biological processes showing response in genome-wide differential gene expression experiments. Two types of analysis are common. Either, one generates an ordered list based on the differential expression values of the probed genes and examines the tail areas of the list for over-representation of various functional classes. Alternatively, one monitors the average differential expression level of genes belonging to a given functional class. So far these two types of method have not been combined. Results We introduce a scoring function, Gene Set Z-score (GSZ), for the analysis of functional class over-representation that combines two previous analysis methods. GSZ encompasses popular functions such as correlation, hypergeometric test, Max-Mean and Random Sets as limiting cases. GSZ is stable against changes in class size as well as across different positions of the analysed gene list in tests with randomized data. GSZ shows the best overall performance in a detailed comparison to popular functions using artificial data. Likewise, GSZ stands out in a cross-validation of methods using split real data. A comparison of empirical p-values further shows a strong difference in favour of GSZ, which clearly reports better p-values for top classes than the other methods. Furthermore, GSZ detects relevant biological themes that are missed by the other methods. These observations also hold when comparing GSZ with popular program packages. Conclusion GSZ and improved versions of earlier methods are a useful contribution to the analysis of differential gene expression. The methods and supplementary material are available from the website http://ekhidna.biocenter.helsinki.fi/users/petri/public/GSZ/GSZscore.html. PMID:19775443

Microbial community analysis using MEGAN.

PubMed

Huson, Daniel H; Weber, Nico

2013-01-01

Metagenomics, the study of microbes in the environment using DNA sequencing, depends upon dedicated software tools for processing and analyzing very large sequencing datasets. One such tool is MEGAN (MEtaGenome ANalyzer), which can be used to interactively analyze and compare metagenomic and metatranscriptomic data, both taxonomically and functionally. To perform a taxonomic analysis, the program places the reads onto the NCBI taxonomy, while functional analysis is performed by mapping reads to the SEED, COG, and KEGG classifications. Samples can be compared taxonomically and functionally, using a wide range of different charting and visualization techniques. PCoA analysis and clustering methods allow high-level comparison of large numbers of samples. Different attributes of the samples can be captured and used within analysis. The program supports various input formats for loading data and can export analysis results in different text-based and graphical formats. The program is designed to work with very large samples containing many millions of reads. It is written in Java and installers for the three major computer operating systems are available from http://www-ab.informatik.uni-tuebingen.de. © 2013 Elsevier Inc. All rights reserved.

Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy

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

Dean, Jamie A., E-mail: jamie.dean@icr.ac.uk; Wong, Kee H.; Gay, Hiram

Purpose: Current normal tissue complication probability modeling using logistic regression suffers from bias and high uncertainty in the presence of highly correlated radiation therapy (RT) dose data. This hinders robust estimates of dose-response associations and, hence, optimal normal tissue–sparing strategies from being elucidated. Using functional data analysis (FDA) to reduce the dimensionality of the dose data could overcome this limitation. Methods and Materials: FDA was applied to modeling of severe acute mucositis and dysphagia resulting from head and neck RT. Functional partial least squares regression (FPLS) and functional principal component analysis were used for dimensionality reduction of the dose-volume histogrammore » data. The reduced dose data were input into functional logistic regression models (functional partial least squares–logistic regression [FPLS-LR] and functional principal component–logistic regression [FPC-LR]) along with clinical data. This approach was compared with penalized logistic regression (PLR) in terms of predictive performance and the significance of treatment covariate–response associations, assessed using bootstrapping. Results: The area under the receiver operating characteristic curve for the PLR, FPC-LR, and FPLS-LR models was 0.65, 0.69, and 0.67, respectively, for mucositis (internal validation) and 0.81, 0.83, and 0.83, respectively, for dysphagia (external validation). The calibration slopes/intercepts for the PLR, FPC-LR, and FPLS-LR models were 1.6/−0.67, 0.45/0.47, and 0.40/0.49, respectively, for mucositis (internal validation) and 2.5/−0.96, 0.79/−0.04, and 0.79/0.00, respectively, for dysphagia (external validation). The bootstrapped odds ratios indicated significant associations between RT dose and severe toxicity in the mucositis and dysphagia FDA models. Cisplatin was significantly associated with severe dysphagia in the FDA models. None of the covariates was significantly associated with severe toxicity in the PLR models. Dose levels greater than approximately 1.0 Gy/fraction were most strongly associated with severe acute mucositis and dysphagia in the FDA models. Conclusions: FPLS and functional principal component analysis marginally improved predictive performance compared with PLR and provided robust dose-response associations. FDA is recommended for use in normal tissue complication probability modeling.« less

Objective analysis of pseudostress over the Indian Ocean using a direct-minimization approach

NASA Technical Reports Server (NTRS)

Legler, David M.; Navon, I. M.; O'Brien, James J.

1989-01-01

A technique not previously used in objective analysis of meteorological data is used here to produce monthly average surface pseudostress data over the Indian Ocean. An initial guess field is derived and a cost functional is constructed with five terms: approximation to initial guess, approximation to climatology, a smoothness parameter, and two kinematic terms. The functional is minimized using a conjugate-gradient technique, and the weight for the climatology term controls the overall balance of influence between the climatology and the initial guess. Results from various weight combinations are presented for January and July 1984. Quantitative and qualitative comparisons to the subject analysis are made to find which weight combination provides the best results. The weight on the approximation to climatology is found to balance the influence of the original field and climatology.

Self-Organizing Maps and Parton Distribution Functions

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

K. Holcomb, Simonetta Liuti, D. Z. Perry

2011-05-01

We present a new method to extract parton distribution functions from high energy experimental data based on a specific type of neural networks, the Self-Organizing Maps. We illustrate the features of our new procedure that are particularly useful for an anaysis directed at extracting generalized parton distributions from data. We show quantitative results of our initial analysis of the parton distribution functions from inclusive deep inelastic scattering.

Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data.

PubMed

Salvatore, Stefania; Røislien, Jo; Baz-Lomba, Jose A; Bramness, Jørgen G

2017-03-01

Wastewater-based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential: methadone, oxazepam and methylphenidate, comparing them to positive and negative control drugs. Sewage samples were collected in February 2014 from a wastewater treatment plant in Oslo, Norway. The weekly pattern of each drug was extracted by fitting of generalized additive models, using trigonometric functions to model the cyclic behaviour. From the weekly component, the main temporal features were then extracted using functional principal component analysis. Results are presented through the functional principal components (FPCs) and corresponding FPC scores. Clinically, the most important weekly feature of the wastewater-based epidemiology data was the second FPC, representing the difference between average midweek level and a peak during the weekend, representing possible recreational use of a drug in the weekend. Estimated scores on this FPC indicated recreational use of methylphenidate, with a high weekend peak, but not for methadone and oxazepam. The functional principal component analysis uncovered clinically important temporal features of the weekly patterns of the use of prescription drugs detected from wastewater analysis. This may be used as a post-marketing surveillance method to monitor prescription drugs with abuse potential. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Extending bicluster analysis to annotate unclassified ORFs and predict novel functional modules using expression data

PubMed Central

Bryan, Kenneth; Cunningham, Pádraig

2008-01-01

Background Microarrays have the capacity to measure the expressions of thousands of genes in parallel over many experimental samples. The unsupervised classification technique of bicluster analysis has been employed previously to uncover gene expression correlations over subsets of samples with the aim of providing a more accurate model of the natural gene functional classes. This approach also has the potential to aid functional annotation of unclassified open reading frames (ORFs). Until now this aspect of biclustering has been under-explored. In this work we illustrate how bicluster analysis may be extended into a 'semi-supervised' ORF annotation approach referred to as BALBOA. Results The efficacy of the BALBOA ORF classification technique is first assessed via cross validation and compared to a multi-class k-Nearest Neighbour (kNN) benchmark across three independent gene expression datasets. BALBOA is then used to assign putative functional annotations to unclassified yeast ORFs. These predictions are evaluated using existing experimental and protein sequence information. Lastly, we employ a related semi-supervised method to predict the presence of novel functional modules within yeast. Conclusion In this paper we demonstrate how unsupervised classification methods, such as bicluster analysis, may be extended using of available annotations to form semi-supervised approaches within the gene expression analysis domain. We show that such methods have the potential to improve upon supervised approaches and shed new light on the functions of unclassified ORFs and their co-regulation. PMID:18831786

Phylogenetic versus functional signals in the evolution of form-function relationships in terrestrial vision.

PubMed

Motani, Ryosuke; Schmitz, Lars

2011-08-01

Phylogeny is deeply pertinent to evolutionary studies. Traits that perform a body function are expected to be strongly influenced by physical "requirements" of the function. We investigated if such traits exhibit phylogenetic signals, and, if so, how phylogenetic noises bias quantification of form-function relationships. A form-function system that is strongly influenced by physics, namely the relationship between eye morphology and visual optics in amniotes, was used. We quantified the correlation between form (i.e., eye morphology) and function (i.e., ocular optics) while varying the level of phylogenetic bias removal through adjusting Pagel's λ. Ocular soft-tissue dimensions exhibited the highest correlation with ocular optics when 1% of phylogenetic bias expected from Brownian motion was removed (i.e., λ= 0.01); the value for hard-tissue data were 8%. A small degree of phylogenetic bias therefore exists in morphology despite of the stringent functional constraints. We also devised a phylogenetically informed discriminant analysis and recorded the effects of phylogenetic bias on this method using the same data. Use of proper λ values during phylogenetic bias removal improved misidentification rates in resulting classifications when prior probabilities were assumed to be equal. Even a small degree of phylogenetic bias affected the classification resulting from phylogenetically informed discriminant analysis. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Discovering the Deregulated Molecular Functions Involved in Malignant Transformation of Endometriosis to Endometriosis-Associated Ovarian Carcinoma Using a Data-Driven, Function-Based Analysis

PubMed Central

Chang, Chia-Ming; Yang, Yi-Ping; Chuang, Jen-Hua; Chuang, Chi-Mu; Lin, Tzu-Wei; Wang, Peng-Hui; Yu, Mu-Hsien

2017-01-01

The clinical characteristics of clear cell carcinoma (CCC) and endometrioid carcinoma EC) are concomitant with endometriosis (ES), which leads to the postulation of malignant transformation of ES to endometriosis-associated ovarian carcinoma (EAOC). Different deregulated functional areas were proposed accounting for the pathogenesis of EAOC transformation, and there is still a lack of a data-driven analysis with the accumulated experimental data in publicly-available databases to incorporate the deregulated functions involved in the malignant transformation of EOAC. We used the microarray gene expression datasets of ES, CCC and EC downloaded from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) database. Then, we investigated the pathogenesis of EAOC by a data-driven, function-based analytic model with the quantified molecular functions defined by 1454 Gene Ontology (GO) term gene sets. This model converts the gene expression profiles to the functionome consisting of 1454 quantified GO functions, and then, the key functions involving the malignant transformation of EOAC can be extracted by a series of filters. Our results demonstrate that the deregulated oxidoreductase activity, metabolism, hormone activity, inflammatory response, innate immune response and cell-cell signaling play the key roles in the malignant transformation of EAOC. These results provide the evidence supporting the specific molecular pathways involved in the malignant transformation of EAOC. PMID:29113136

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

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

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

DOE PAGES

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.; ...

2016-06-24

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

Nonlinear Poisson Equation for Heterogeneous Media

PubMed Central

Hu, Langhua; Wei, Guo-Wei

2012-01-01

The Poisson equation is a widely accepted model for electrostatic analysis. However, the Poisson equation is derived based on electric polarizations in a linear, isotropic, and homogeneous dielectric medium. This article introduces a nonlinear Poisson equation to take into consideration of hyperpolarization effects due to intensive charges and possible nonlinear, anisotropic, and heterogeneous media. Variational principle is utilized to derive the nonlinear Poisson model from an electrostatic energy functional. To apply the proposed nonlinear Poisson equation for the solvation analysis, we also construct a nonpolar solvation energy functional based on the nonlinear Poisson equation by using the geometric measure theory. At a fixed temperature, the proposed nonlinear Poisson theory is extensively validated by the electrostatic analysis of the Kirkwood model and a set of 20 proteins, and the solvation analysis of a set of 17 small molecules whose experimental measurements are also available for a comparison. Moreover, the nonlinear Poisson equation is further applied to the solvation analysis of 21 compounds at different temperatures. Numerical results are compared to theoretical prediction, experimental measurements, and those obtained from other theoretical methods in the literature. A good agreement between our results and experimental data as well as theoretical results suggests that the proposed nonlinear Poisson model is a potentially useful model for electrostatic analysis involving hyperpolarization effects. PMID:22947937

Health-related Quality of Life After Radical Cystectomy: A Cross-sectional Study With Matched-pair Analysis on Ileal Conduit vs Ileal Orthotopic Neobladder Diversion.

PubMed

Cerruto, Maria Angela; D'Elia, Carolina; Siracusano, Salvatore; Saleh, Omar; Gacci, Mauro; Cacciamani, Giovanni; De Marco, Vincenzo; Porcaro, Antonio Benito; Balzarro, Matteo; Niero, Mauro; Lonardi, Cristina; Iafrate, Massimo; Bassi, Pierfrancesco; Imbimbo, Ciro; Racioppi, Marco; Talamini, Renato; Ciciliato, Stefano; Serni, Sergio; Carini, Marco; Verze, Paolo; Artibani, Walter

2017-10-01

To examine the different and health-related quality of life (HR-QoL) outcomes between ileal conduit (IC) and ileal orthotopic neobladder (IONB) in patients who underwent radical cystectomy (RC), by using validated self-reported cancer-specific instruments. This retrospective, cross-sectional, multicenter cohort study included 148 and 171 patients with either IC or IONB. HR-QoL was evaluated with Quality of Life Core Questionnaire and bladder module (BLM)-30 European Organisation for Research and Treatment of Cancer questionnaires. Baseline HR-QoL scores were dichotomized at the median to give "good" or "poor" score profiles. A matched-pair analysis compared HR-QoL aspects between 79 IC patients and 79 IONB patients. At univariate analysis IONB resulted favorable for physical functioning, emotional functioning, cognitive functioning (CF), fatigue, dyspnea, appetite loss, constipation (CO), and abdominal bloating flatulence (AB). At multivariate analyses, IONB showed better scores for emotional functioning (85 vs 79, P = .023), CF (93 vs 85, P <.001), CO (16 vs 31, P <.001), and AB (12 vs 25, P <.001). A significant worsening of sexual and urinary function was observed for IONB patients in the long-term. At matched-pair analysis, global health status was similar (65 vs 62, P = .385). Significantly better scores were observed in the IONB group for the following items: CF (P = .007), fatigue (P = .003), pain (P = .019), dyspnea (P = .016), CO (P = .001), and AB (P = .00). IONB and IC after RC were similar in terms of global health status. IONB provides better results in some aspects of HR-QoL related to bowel function, but a worsening of urinary and sexual functions. Further randomized controlled trials are needed to confirm these data. Copyright © 2017 Elsevier Inc. All rights reserved.

Stability of individual loudness functions obtained by magnitude estimation and production

NASA Technical Reports Server (NTRS)

Hellman, R. P.

1981-01-01

A correlational analysis of individual magnitude estimation and production exponents at the same frequency is performed, as is an analysis of individual exponents produced in different sessions by the same procedure across frequency (250, 1000, and 3000 Hz). Taken as a whole, the results show that individual exponent differences do not decrease by counterbalancing magnitude estimation with magnitude production and that individual exponent differences remain stable over time despite changes in stimulus frequency. Further results show that although individual magnitude estimation and production exponents do not necessarily obey the .6 power law, it is possible to predict the slope of an equal-sensation function averaged for a group of listeners from individual magnitude estimation and production data. On the assumption that individual listeners with sensorineural hearing also produce stable and reliable magnitude functions, it is also shown that the slope of the loudness-recruitment function measured by magnitude estimation and production can be predicted for individuals with bilateral losses of long duration. Results obtained in normal and pathological ears thus suggest that individual listeners can produce loudness judgements that reveal, although indirectly, the input-output characteristic of the auditory system.

Factor Analysis of the Modified Sexual Adjustment Questionnaire-Male

PubMed Central

Wilmoth, Margaret C.; Hanlon, Alexandra L.; Ng, Lit Soo; Bruner, Debra W.

2015-01-01

Background and Purpose The Sexual Adjustment Questionnaire (SAQ) is used in National Cancer Institute–sponsored clinical trials as an outcome measure for sexual functioning. The tool was revised to meet the needs for a clinically useful, theory-based outcome measure for use in both research and clinical settings. This report describes the modifications and validity testing of the modified Sexual Adjustment Questionnaire-Male (mSAQ-Male). Methods This secondary analysis of data from a large Radiation Therapy Oncology Group trial employed principal axis factor analytic techniques in estimating validity of the revised tool. The sample size was 686; most subjects were White, older than the age 60 years, and with a high school education and a Karnofsky performance scale (KPS) score of greater than 90. Results A 16-item, 3-factor solution resulted from the factor analysis. The mSAQ-Male was also found to be sensitive to changes in physical sexual functioning as measured by the KPS. Conclusion The mSAQ-Male is a valid self-report measure of sexuality that can be used clinically to detect changes in male sexual functioning. PMID:25255676

Analysis of the respirogram phase of Korean wrestling athletes compared with nonathletes for sports physiotherapy research.

PubMed

Shin, Yong-Sub; Yang, Seung-Min; Kim, Mee-Young; Lee, Lim-Kyu; Park, Byoung-Sun; Lee, Won-Deok; Noh, Ji-Woong; Kim, Ju-Hyun; Lee, Jeong-Uk; Kwak, Taek-Yong; Lee, Tae-Hyun; Kim, Ju-Young; Park, Jaehong; Kim, Junghwan

2016-01-01

[Purpose] Respiratory function is important for patients including athletes who require physical therapy for respiratory dysfunction. The purpose of the present study was to analyze the differences in the respirograms between Korean wrestling athletes and nonathletes according to phase for the study of sports physiotherapy. [Subjects and Methods] Respiratory function was measured using spirometry in both the athletes and nonathletes while they were in a sitting position. [Results] Spirometry parameters in the athletes were significantly higher than in the nonathletes. In respirogram phasic analysis, the expiratory area and total area of forced vital capacity were significantly increased in the athletes compared with the nonathletes. The slopes of the forced vital capacity for athletes at slopes 1, 2, and 3 of the A area were significantly increased. In correlative analysis, chest circumference was significantly correlated with slope 3 of the A area of the forced vital capacity. [Conclusion] The results suggest that the differences in changes in the phases of the respirogram between the Korean wrestling athletes and nonathletes may in part contribute to our understanding of respiratory function in sports physiotherapy research.

Changes in functional connectivity within the fronto-temporal brain network induced by regular and irregular Russian verb production

PubMed Central

Kireev, Maxim; Slioussar, Natalia; Korotkov, Alexander D.; Chernigovskaya, Tatiana V.; Medvedev, Svyatoslav V.

2015-01-01

Functional connectivity between brain areas involved in the processing of complex language forms remains largely unexplored. Contributing to the debate about neural mechanisms underlying regular and irregular inflectional morphology processing in the mental lexicon, we conducted an fMRI experiment in which participants generated forms from different types of Russian verbs and nouns as well as from nonce stimuli. The data were subjected to a whole brain voxel-wise analysis of context dependent changes in functional connectivity [the so-called psychophysiological interaction (PPI) analysis]. Unlike previously reported subtractive results that reveal functional segregation between brain areas, PPI provides complementary information showing how these areas are functionally integrated in a particular task. To date, PPI evidence on inflectional morphology has been scarce and only available for inflectionally impoverished English verbs in a same-different judgment task. Using PPI here in conjunction with a production task in an inflectionally rich language, we found that functional connectivity between the left inferior frontal gyrus (LIFG) and bilateral superior temporal gyri (STG) was significantly greater for regular real verbs than for irregular ones. Furthermore, we observed a significant positive covariance between the number of mistakes in irregular real verb trials and the increase in functional connectivity between the LIFG and the right anterior cingulate cortex in these trails, as compared to regular ones. Our results therefore allow for dissociation between regularity and processing difficulty effects. These results, on the one hand, shed new light on the functional interplay within the LIFG-bilateral STG language-related network and, on the other hand, call for partial reconsideration of some of the previous findings while stressing the role of functional temporo-frontal connectivity in complex morphological processes. PMID:25741262

The Angular Correlation Function of Galaxies from Early Sloan Digital Sky Survey Data

NASA Astrophysics Data System (ADS)

Connolly, Andrew J.; Scranton, Ryan; Johnston, David; Dodelson, Scott; Eisenstein, Daniel J.; Frieman, Joshua A.; Gunn, James E.; Hui, Lam; Jain, Bhuvnesh; Kent, Stephen; Loveday, Jon; Nichol, Robert C.; O'Connell, Liam; Postman, Marc; Scoccimarro, Roman; Sheth, Ravi K.; Stebbins, Albert; Strauss, Michael A.; Szalay, Alexander S.; Szapudi, István; Tegmark, Max; Vogeley, Michael S.; Zehavi, Idit; Annis, James; Bahcall, Neta; Brinkmann, J.; Csabai, István; Doi, Mamoru; Fukugita, Masataka; Hennessy, G. S.; Hindsley, Robert; Ichikawa, Takashi; Ivezić, Željko; Kim, Rita S. J.; Knapp, Gillian R.; Kunszt, Peter; Lamb, D. Q.; Lee, Brian C.; Lupton, Robert H.; McKay, Timothy A.; Munn, Jeff; Peoples, John; Pier, Jeff; Rockosi, Constance; Schlegel, David; Stoughton, Christopher; Tucker, Douglas L.; Yanny, Brian; York, Donald G.

2002-11-01

The Sloan Digital Sky Survey is one of the first multicolor photometric and spectroscopic surveys designed to measure the statistical properties of galaxies within the local universe. In this paper we present some of the initial results on the angular two-point correlation function measured from the early SDSS galaxy data. The form of the correlation function, over the magnitude interval 18

Sex differences in the development of neuroanatomical functional connectivity underlying intelligence found using Bayesian connectivity analysis.

PubMed

Schmithorst, Vincent J; Holland, Scott K

2007-03-01

A Bayesian method for functional connectivity analysis was adapted to investigate between-group differences. This method was applied in a large cohort of almost 300 children to investigate differences in boys and girls in the relationship between intelligence and functional connectivity for the task of narrative comprehension. For boys, a greater association was shown between intelligence and the functional connectivity linking Broca's area to auditory processing areas, including Wernicke's areas and the right posterior superior temporal gyrus. For girls, a greater association was shown between intelligence and the functional connectivity linking the left posterior superior temporal gyrus to Wernicke's areas bilaterally. A developmental effect was also seen, with girls displaying a positive correlation with age in the association between intelligence and the functional connectivity linking the right posterior superior temporal gyrus to Wernicke's areas bilaterally. Our results demonstrate a sexual dimorphism in the relationship of functional connectivity to intelligence in children and an increasing reliance on inter-hemispheric connectivity in girls with age.

Comparative study of popular objective functions for damping power system oscillations in multimachine system.

PubMed

Islam, Naz Niamul; Hannan, M A; Shareef, Hussain; Mohamed, Azah; Salam, M A

2014-01-01

Power oscillation damping controller is designed in linearized model with heuristic optimization techniques. Selection of the objective function is very crucial for damping controller design by optimization algorithms. In this research, comparative analysis has been carried out to evaluate the effectiveness of popular objective functions used in power system oscillation damping. Two-stage lead-lag damping controller by means of power system stabilizers is optimized using differential search algorithm for different objective functions. Linearized model simulations are performed to compare the dominant mode's performance and then the nonlinear model is continued to evaluate the damping performance over power system oscillations. All the simulations are conducted in two-area four-machine power system to bring a detailed analysis. Investigated results proved that multiobjective D-shaped function is an effective objective function in terms of moving unstable and lightly damped electromechanical modes into stable region. Thus, D-shape function ultimately improves overall system damping and concurrently enhances power system reliability.

Application and interpretation of functional data analysis techniques to differential scanning calorimetry data from lupus patients.

PubMed

Kendrick, Sarah K; Zheng, Qi; Garbett, Nichola C; Brock, Guy N

2017-01-01

DSC is used to determine thermally-induced conformational changes of biomolecules within a blood plasma sample. Recent research has indicated that DSC curves (or thermograms) may have different characteristics based on disease status and, thus, may be useful as a monitoring and diagnostic tool for some diseases. Since thermograms are curves measured over a range of temperature values, they are considered functional data. In this paper we apply functional data analysis techniques to analyze differential scanning calorimetry (DSC) data from individuals from the Lupus Family Registry and Repository (LFRR). The aim was to assess the effect of lupus disease status as well as additional covariates on the thermogram profiles, and use FD analysis methods to create models for classifying lupus vs. control patients on the basis of the thermogram curves. Thermograms were collected for 300 lupus patients and 300 controls without lupus who were matched with diseased individuals based on sex, race, and age. First, functional regression with a functional response (DSC) and categorical predictor (disease status) was used to determine how thermogram curve structure varied according to disease status and other covariates including sex, race, and year of birth. Next, functional logistic regression with disease status as the response and functional principal component analysis (FPCA) scores as the predictors was used to model the effect of thermogram structure on disease status prediction. The prediction accuracy for patients with Osteoarthritis and Rheumatoid Arthritis but without Lupus was also calculated to determine the ability of the classifier to differentiate between Lupus and other diseases. Data were divided 1000 times into separate 2/3 training and 1/3 test data for evaluation of predictions. Finally, derivatives of thermogram curves were included in the models to determine whether they aided in prediction of disease status. Functional regression with thermogram as a functional response and disease status as predictor showed a clear separation in thermogram curve structure between cases and controls. The logistic regression model with FPCA scores as the predictors gave the most accurate results with a mean 79.22% correct classification rate with a mean sensitivity = 79.70%, and specificity = 81.48%. The model correctly classified OA and RA patients without Lupus as controls at a rate of 75.92% on average with a mean sensitivity = 79.70% and specificity = 77.6%. Regression models including FPCA scores for derivative curves did not perform as well, nor did regression models including covariates. Changes in thermograms observed in the disease state likely reflect covalent modifications of plasma proteins or changes in large protein-protein interacting networks resulting in the stabilization of plasma proteins towards thermal denaturation. By relating functional principal components from thermograms to disease status, our Functional Principal Component Analysis model provides results that are more easily interpretable compared to prior studies. Further, the model could also potentially be coupled with other biomarkers to improve diagnostic classification for lupus.

Parameter identification for nonlinear aerodynamic systems

NASA Technical Reports Server (NTRS)

Pearson, Allan E.

1992-01-01

Continuing work on frequency analysis for transfer function identification is discussed. A new study was initiated into a 'weighted' least squares algorithm within the context of the Fourier modulating function approach. The first phase of applying these techniques to the F-18 flight data is nearing completion, and these results are summarized.

Automation Applications in an Advanced Air Traffic Management System : Volume 2D. Functional Analysis of Air Traffic Management (Concluded)

DOT National Transportation Integrated Search

1974-08-01

The technical report presents a detailed description of the strategic control functional objectives, followed by a presentation of the basic strategic control algorithm and how it evolved. Contained in this discussion are the results of analyses that...

False-Positive Tangible Outcomes of Functional Analyses

ERIC Educational Resources Information Center

Rooker, Griffin W.; Iwata, Brian A.; Harper, Jill M.; Fahmie, Tara A.; Camp, Erin M.

2011-01-01

Functional analysis (FA) methodology is the most precise method for identifying variables that maintain problem behavior. Occasionally, however, results of an FA may be influenced by idiosyncratic sensitivity to aspects of the assessment conditions. For example, data from several studies suggest that inclusion of a tangible condition during an FA…

Therapist Effects on Functional Analysis Outcomes with Young Children

ERIC Educational Resources Information Center

Huete, John M.; Kurtz, Patricia F.

2010-01-01

Analog functional analyses (FAs) are commonly used to assess factors that maintain problem behavior of individuals with intellectual disabilities. These analyses are usually conducted by trained staff in clinic settings. However, recent research suggests that FAs conducted by unfamiliar individuals, such as hospital or clinic staff, may result in…

Bayesian analysis of spatially-dependent functional responses with spatially-dependent multi-dimensional functional predictors

USDA-ARS?s Scientific Manuscript database

Recent advances in technology have led to the collection of high-dimensional data not previously encountered in many scientific environments. As a result, scientists are often faced with the challenging task of including these high-dimensional data into statistical models. For example, data from sen...

Permutation methods for the structured exploratory data analysis (SEDA) of familial trait values.

PubMed

Karlin, S; Williams, P T

1984-07-01

A collection of functions that contrast familial trait values between and across generations is proposed for studying transmission effects and other collateral influences in nuclear families. Two classes of structured exploratory data analysis (SEDA) statistics are derived from ratios of these functions. SEDA-functionals are the empirical cumulative distributions of the ratio of the two contrasts computed within each family. SEDA-indices are formed by first averaging the numerator and denominator contrasts separately over the population and then forming their ratio. The significance of SEDA results are determined by a spectrum of permutation techniques that selectively shuffle the trait values across families. The process systematically alters certain family structure relationships while keeping other familial relationships intact. The methodology is applied to five data examples of plasma total cholesterol concentrations, reported height values, dermatoglyphic pattern intensity index scores, measurements of dopamine-beta-hydroxylase activity, and psychometric cognitive test results.

Advanced Techniques in Pulmonary Function Test Analysis Interpretation and Diagnosis

PubMed Central

Gildea, T.J.; Bell, C. William

1980-01-01

The Pulmonary Functions Analysis and Diagnostic System is an advanced clinical processing system developed for use at the Pulmonary Division, Department of Medicine at the University of Nebraska Medical Center. The system generates comparative results and diagnostic impressions for a variety of routine and specialized pulmonary functions test data. Routine evaluation deals with static lung volumes, breathing mechanics, diffusing capacity, and blood gases while specialized tests include lung compliance studies, small airways dysfunction studies and dead space to tidal volume ratios. Output includes tabular results of normal vs. observed values, clinical impressions and commentary and, where indicated, a diagnostic impression. A number of pulmonary physiological and state variables are entered or sampled (A to D) with periodic status reports generated for the test supervisor. Among the various physiological variables sampled are respiratory frequency, minute ventilation, oxygen consumption, carbon dioxide production, and arterial oxygen saturation.

Analysis of an electrohydraulic aircraft control surface servo and comparison with test results

NASA Technical Reports Server (NTRS)

Edwards, J. W.

1972-01-01

An analysis of an electrohydraulic aircraft control-surface system is made in which the system is modeled as a lumped, two-mass, spring-coupled system controlled by a servo valve. Both linear and nonlinear models are developed, and the effects of hinge-moment loading are included. Transfer functions of the system and approximate literal factors of the transfer functions for several cases are presented. The damping action of dynamic pressure feedback is analyzed. Comparisons of the model responses with results from tests made on a highly resonant rudder control-surface servo indicate the adequacy of the model. The effects of variations in hinge-moment loading are illustrated.

Accuracy analysis of automodel solutions for Lévy flight-based transport: from resonance radiative transfer to a simple general model

NASA Astrophysics Data System (ADS)

Kukushkin, A. B.; Sdvizhenskii, P. A.

2017-12-01

The results of accuracy analysis of automodel solutions for Lévy flight-based transport on a uniform background are presented. These approximate solutions have been obtained for Green’s function of the following equations: the non-stationary Biberman-Holstein equation for three-dimensional (3D) radiative transfer in plasma and gases, for various (Doppler, Lorentz, Voigt and Holtsmark) spectral line shapes, and the 1D transport equation with a simple longtailed step-length probability distribution function with various power-law exponents. The results suggest the possibility of substantial extension of the developed method of automodel solution to other fields far beyond physics.

Recent Advances in Clinical Glycoproteomics of Immunoglobulins (Igs).

PubMed

Plomp, Rosina; Bondt, Albert; de Haan, Noortje; Rombouts, Yoann; Wuhrer, Manfred

2016-07-01

Antibody glycosylation analysis has seen methodological progress resulting in new findings with regard to antibody glycan structure and function in recent years. For example, antigen-specific IgG glycosylation analysis is now applicable for clinical samples because of the increased sensitivity of measurements, and this has led to new insights in the relationship between IgG glycosylation and various diseases. Furthermore, many new methods have been developed for the purification and analysis of IgG Fc glycopeptides, notably multiple reaction monitoring for high-throughput quantitative glycosylation analysis. In addition, new protocols for IgG Fab glycosylation analysis were established revealing autoimmune disease-associated changes. Functional analysis has shown that glycosylation of IgA and IgE is involved in transport across the intestinal epithelium and receptor binding, respectively. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Quantum trajectory analysis of multimode subsystem-bath dynamics.

PubMed

Wyatt, Robert E; Na, Kyungsun

2002-01-01

The dynamics of a swarm of quantum trajectories is investigated for systems involving the interaction of an active mode (the subsystem) with an M-mode harmonic reservoir (the bath). Equations of motion for the position, velocity, and action function for elements of the probability fluid are integrated in the Lagrangian (moving with the fluid) picture of quantum hydrodynamics. These fluid elements are coupled through the Bohm quantum potential and as a result evolve as a correlated ensemble. Wave function synthesis along the trajectories permits an exact description of the quantum dynamics for the evolving probability fluid. The approach is fully quantum mechanical and does not involve classical or semiclassical approximations. Computational results are presented for three systems involving the interaction on an active mode with M=1, 10, and 15 bath modes. These results include configuration space trajectory evolution, flux analysis of the evolving ensemble, wave function synthesis along trajectories, and energy partitioning along specific trajectories. These results demonstrate the feasibility of using a small number of quantum trajectories to obtain accurate quantum results on some types of open quantum systems that are not amenable to standard quantum approaches involving basis set expansions or Eulerian space-fixed grids.

Proteomic Analysis of the Arabidopsis Nucleolus Suggests Novel Nucleolar FunctionsD⃞

PubMed Central

Pendle, Alison F.; Clark, Gillian P.; Boon, Reinier; Lewandowska, Dominika; Lam, Yun Wah; Andersen, Jens; Mann, Matthias; Lamond, Angus I.; Brown, John W. S.; Shaw, Peter J.

2005-01-01

The eukaryotic nucleolus is involved in ribosome biogenesis and a wide range of other RNA metabolism and cellular functions. An important step in the functional analysis of the nucleolus is to determine the complement of proteins of this nuclear compartment. Here, we describe the first proteomic analysis of plant (Arabidopsis thaliana) nucleoli, in which we have identified 217 proteins. This allows a direct comparison of the proteomes of an important nuclear structure between two widely divergent species: human and Arabidopsis. The comparison identified many common proteins, plant-specific proteins, proteins of unknown function found in both proteomes, and proteins that were nucleolar in plants but nonnucleolar in human. Seventy-two proteins were expressed as GFP fusions and 87% showed nucleolar or nucleolar-associated localization. In a striking and unexpected finding, we have identified six components of the postsplicing exon-junction complex (EJC) involved in mRNA export and nonsense-mediated decay (NMD)/mRNA surveillance. This association was confirmed by GFP-fusion protein localization. These results raise the possibility that in plants, nucleoli may have additional functions in mRNA export or surveillance. PMID:15496452

Discrete-Time Deterministic $Q$ -Learning: A Novel Convergence Analysis.

PubMed

Wei, Qinglai; Lewis, Frank L; Sun, Qiuye; Yan, Pengfei; Song, Ruizhuo

2017-05-01

In this paper, a novel discrete-time deterministic Q -learning algorithm is developed. In each iteration of the developed Q -learning algorithm, the iterative Q function is updated for all the state and control spaces, instead of updating for a single state and a single control in traditional Q -learning algorithm. A new convergence criterion is established to guarantee that the iterative Q function converges to the optimum, where the convergence criterion of the learning rates for traditional Q -learning algorithms is simplified. During the convergence analysis, the upper and lower bounds of the iterative Q function are analyzed to obtain the convergence criterion, instead of analyzing the iterative Q function itself. For convenience of analysis, the convergence properties for undiscounted case of the deterministic Q -learning algorithm are first developed. Then, considering the discounted factor, the convergence criterion for the discounted case is established. Neural networks are used to approximate the iterative Q function and compute the iterative control law, respectively, for facilitating the implementation of the deterministic Q -learning algorithm. Finally, simulation results and comparisons are given to illustrate the performance of the developed algorithm.

Management and analysis of genomic functional and phenotypic controlled annotations to support biomedical investigation and practice.

PubMed

Masseroli, Marco

2007-07-01

The growing available genomic information provides new opportunities for novel research approaches and original biomedical applications that can provide effective data management and analysis support. In fact, integration and comprehensive evaluation of available controlled data can highlight information patterns leading to unveil new biomedical knowledge. Here, we describe Genome Function INtegrated Discover (GFINDer), a Web-accessible three-tier multidatabase system we developed to automatically enrich lists of user-classified genes with several functional and phenotypic controlled annotations, and to statistically evaluate them in order to identify annotation categories significantly over- or underrepresented in each considered gene class. Genomic controlled annotations from Gene Ontology (GO), KEGG, Pfam, InterPro, and Online Mendelian Inheritance in Man (OMIM) were integrated in GFINDer and several categorical tests were implemented for their analysis. A controlled vocabulary of inherited disorder phenotypes was obtained by normalizing and hierarchically structuring disease accompanying signs and symptoms from OMIM Clinical Synopsis sections. GFINDer modular architecture is well suited for further system expansion and for sustaining increasing workload. Testing results showed that GFINDer analyses can highlight gene functional and phenotypic characteristics and differences, demonstrating its value in supporting genomic biomedical approaches aiming at understanding the complex biomolecular mechanisms underlying patho-physiological phenotypes, and in helping the transfer of genomic results to medical practice.

A New Method for Nonlinear and Nonstationary Time Series Analysis and Its Application to the Earthquake and Building Response Records

NASA Technical Reports Server (NTRS)

Huang, Norden E.

1999-01-01

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum, Example of application of this method to earthquake and building response will be given. The results indicate those low frequency components, totally missed by the Fourier analysis, are clearly identified by the new method. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

Intrinsic Resting-State Functional Connectivity in the Human Spinal Cord at 3.0 T.

PubMed

San Emeterio Nateras, Oscar; Yu, Fang; Muir, Eric R; Bazan, Carlos; Franklin, Crystal G; Li, Wei; Li, Jinqi; Lancaster, Jack L; Duong, Timothy Q

2016-04-01

To apply resting-state functional magnetic resonance (MR) imaging to map functional connectivity of the human spinal cord. Studies were performed in nine self-declared healthy volunteers with informed consent and institutional review board approval. Resting-state functional MR imaging was performed to map functional connectivity of the human cervical spinal cord from C1 to C4 at 1 × 1 × 3-mm resolution with a 3.0-T clinical MR imaging unit. Independent component analysis (ICA) was performed to derive resting-state functional MR imaging z-score maps rendered on two-dimensional and three-dimensional images. Seed-based analysis was performed for cross validation with ICA networks by using Pearson correlation. Reproducibility analysis of resting-state functional MR imaging maps from four repeated trials in a single participant yielded a mean z score of 6 ± 1 (P < .0001). The centroid coordinates across the four trials deviated by 2 in-plane voxels ± 2 mm (standard deviation) and up to one adjacent image section ± 3 mm. ICA of group resting-state functional MR imaging data revealed prominent functional connectivity patterns within the spinal cord gray matter. There were statistically significant (z score > 3, P < .001) bilateral, unilateral, and intersegmental correlations in the ventral horns, dorsal horns, and central spinal cord gray matter. Three-dimensional surface rendering provided visualization of these components along the length of the spinal cord. Seed-based analysis showed that many ICA components exhibited strong and significant (P < .05) correlations, corroborating the ICA results. Resting-state functional MR imaging connectivity networks are qualitatively consistent with known neuroanatomic and functional structures in the spinal cord. Resting-state functional MR imaging of the human cervical spinal cord with a 3.0-T clinical MR imaging unit and standard MR imaging protocols and hardware reveals prominent functional connectivity patterns within the spinal cord gray matter, consistent with known functional and anatomic layouts of the spinal cord.

Religion, Spirituality, and Physical Health in Cancer Patients: A Meta-Analysis

PubMed Central

Jim, Heather S.L.; Pustejovsky, James; Park, Crystal L.; Danhauer, Suzanne C.; Sherman, Allen C.; Fitchett, George; Merluzzi, Thomas V.; Munoz, Alexis R.; George, Login; Snyder, Mallory A.; Salsman, John M.

2015-01-01

Background Whereas religion/spirituality (R/S) is important in its own right for many cancer patients, a large body of research has examined whether R/S is also associated with better physical health outcomes. This literature has been characterized by heterogeneity in sample composition, measures of R/S, and measures of physical health. In an effort to synthesize previous findings, we conducted a meta-analysis of the relationship between R/S and patient-reported physical health in cancer patients. Methods A search of PubMed, PsycInfo, CINAHL, and Cochrane Library yielded 2,073 abstracts, which were independently evaluated by pairs of raters. Meta-analysis was conducted on 497 effect sizes from 101 unique samples encompassing over 32,000 adult cancer patients. R/S measures were categorized into affective, behavioral, cognitive, and ‘other’ dimensions. Physical health measures were categorized into physical well-being, functional well-being, and physical symptoms. Average estimated correlations (Fisher's z) were calculated using generalized estimating equations with robust variance estimation. Results Overall R/S was associated with overall physical health (z=.153, p<.001); this relationship was not moderated by sociodemographic or clinical variables. Affective R/S was associated with physical well-being (z=.167, p<.001), functional well-being (z=.343, p<.001), and physical symptoms (z=.282, p<.001). Cognitive R/S was associated with physical well-being (z=.079, p<.05) and functional well-being (z=.090, p<.01). ‘Other’ R/S was associated with functional well-being (z=.100, p<.05). Conclusions Results of the current meta-analysis suggest that greater R/S is associated with better patient-reported physical health. These results underscore the importance of attending to patients’ religious and spiritual needs as part of comprehensive cancer care. PMID:26258868

Effects of Adjuvant Mental Practice on Affected Upper Limb Function Following a Stroke: Results of Three-Dimensional Motion Analysis, Fugl-Meyer Assessment of the Upper Extremity and Motor Activity Logs.

PubMed

Oh, Hyun Seung; Kim, Eun Joo; Kim, Doo Young; Kim, Soo Jeong

2016-06-01

To investigate the effects of adjuvant mental practice (MP) on affected upper limb function following a stroke using three-dimensional (3D) motion analysis. In this AB/BA crossover study, we studied 10 hemiplegic patients who had a stroke within the past 6 months. The patients were randomly allocated to two groups: one group received MP combined with conventional rehabilitation therapy for the first 3 weeks followed by conventional rehabilitation therapy alone for the final 3 weeks; the other group received the same therapy but in reverse order. The MP tasks included drinking from a cup and opening a door. MP was individually administered for 20 minutes, 3 days a week for 3 weeks. To assess the tasks, we used 3D motion analysis and three additional tests: the Fugl-Meyer Assessment of the upper extremity (FMA-UE) and the motor activity logs for amount of use (MAL-AOU) and quality of movement (MAL-QOM). Assessments were performed immediately before treatment (T0), 3 weeks into treatment (T1), and 6 weeks into treatment (T2). Based on the results of the 3D motion analysis and the FMA-UE index (p=0.106), the MAL-AOU scale (p=0.092), and MAL-QOM scale (p=0.273), adjuvant MP did not result in significant improvements. Adjuvant MP had no significant effect on upper limb function following a stroke, according to 3D motion analysis and three clinical assessment tools (the FMA-UE index and the two MAL scales). The importance of this study is its use of objective 3D motion analysis to evaluate the effects of MP. Further studies will be needed to validate these findings.

Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

PubMed Central

Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

2015-01-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

A quality function deployment framework for the service quality of health information websites.

PubMed

Chang, Hyejung; Kim, Dohoon

2010-03-01

This research was conducted to identify both the users' service requirements on health information websites (HIWs) and the key functional elements for running HIWs. With the quality function deployment framework, the derived service attributes (SAs) are mapped into the suppliers' functional characteristics (FCs) to derive the most critical FCs for the users' satisfaction. Using the survey data from 228 respondents, the SAs, FCs and their relationships were analyzed using various multivariate statistical methods such as principal component factor analysis, discriminant analysis, correlation analysis, etc. Simple and compound FC priorities were derived by matrix calculation. Nine factors of SAs and five key features of FCs were identified, and these served as the basis for the house of quality model. Based on the compound FC priorities, the functional elements pertaining to security and privacy, and usage support should receive top priority in the course of enhancing HIWs. The quality function deployment framework can improve the FCs of the HIWs in an effective, structured manner, and it can also be utilized for critical success factors together with their strategic implications for enhancing the service quality of HIWs. Therefore, website managers could efficiently improve website operations by considering this study's results.

Transforming User Needs into Functional Requirements for an Antibiotic Clinical Decision Support System

PubMed Central

Bright, T.J.

2013-01-01

Summary Background Many informatics studies use content analysis to generate functional requirements for system development. Explication of this translational process from qualitative data to functional requirements can strengthen the understanding and scientific rigor when applying content analysis in informatics studies. Objective To describe a user-centered approach transforming emergent themes derived from focus group data into functional requirements for informatics solutions and to illustrate these methods to the development of an antibiotic clinical decision support system (CDS). Methods The approach consisted of five steps: 1) identify unmet therapeutic planning information needs via Focus Group Study-I, 2) develop a coding framework of therapeutic planning themes to refine the domain scope to antibiotic therapeutic planning, 3) identify functional requirements of an antibiotic CDS system via Focus Group Study-II, 4) discover informatics solutions and functional requirements from coded data, and 5) determine the types of information needed to support the antibiotic CDS system and link with the identified informatics solutions and functional requirements. Results The coding framework for Focus Group Study-I revealed unmet therapeutic planning needs. Twelve subthemes emerged and were clustered into four themes; analysis indicated a need for an antibiotic CDS intervention. Focus Group Study-II included five types of information needs. Comments from the Barrier/Challenge to information access and Function/Feature themes produced three informatics solutions and 13 functional requirements of an antibiotic CDS system. Comments from the Patient, Institution, and Domain themes generated required data elements for each informatics solution. Conclusion This study presents one example explicating content analysis of focus group data and the analysis process to functional requirements from narrative data. Illustration of this 5-step method was used to develop an antibiotic CDS system, resolving unmet antibiotic prescribing needs. As a reusable approach, these techniques can be refined and applied to resolve unmet information needs with informatics interventions in additional domains. PMID:24454586

A proteomic analysis of leaf sheaths from rice.

PubMed

Shen, Shihua; Matsubae, Masami; Takao, Toshifumi; Tanaka, Naoki; Komatsu, Setsuko

2002-10-01

The proteins extracted from the leaf sheaths of rice seedlings were separated by 2-D PAGE, and analyzed by Edman sequencing and mass spectrometry, followed by database searching. Image analysis revealed 352 protein spots on 2-D PAGE after staining with Coomassie Brilliant Blue. The amino acid sequences of 44 of 84 proteins were determined; for 31 of these proteins, a clear function could be assigned, whereas for 12 proteins, no function could be assigned. Forty proteins did not yield amino acid sequence information, because they were N-terminally blocked, or the obtained sequences were too short and/or did not give unambiguous results. Fifty-nine proteins were analyzed by mass spectrometry; all of these proteins were identified by matching to the protein database. The amino acid sequences of 19 of 27 proteins analyzed by mass spectrometry were similar to the results of Edman sequencing. These results suggest that 2-D PAGE combined with Edman sequencing and mass spectrometry analysis can be effectively used to identify plant proteins.

Surface interaction of H2S, SO2, and SO3 on fullerene-like gallium nitride (GaN) nanostructure semiconductor

NASA Astrophysics Data System (ADS)

Salimifard, M.; Rad, A. Shokuhi; Mahanpoor, K.

2017-10-01

Density functional theory (DFT) using MPW1PW91 and B3LYP hybrid functionals was utilized for quantum-based investigations of three major sulfur compounds (H2S, SO2, and SO3) adsorption onto fullerene-like Ga12N12 nanocluster. All chemicals showed high chemisorption with the order of SO3>SO2>>H2S. Results of charge analysis showed that during adsorption, transfer of charge is from H2S to nanocluster while reverse direction of charge transfer is found for SO2 and SO3 molecules. Partial dissociation is found for adsorbates especially for SO2 and SO3 molecules. Results of thermochemistry analysis show negative values for enthalpy and Gibbs free energy of adsorption, confirming exothermic spontaneous process. Analysis of frontier molecular orbital (FMO) showed important role of orbital hybridizing towards formation of new bonds upon adsorption. As a result, we introduce Ga12N12 nanocluster as a strong adsorbent for sulfur compounds.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

Qualitative Organic Analysis: An Efficient, Safer, and Economical Approach to Preliminary Tests and Functional Group Analysis

ERIC Educational Resources Information Center

Dhingra, Sunita; Angrish, Chetna

2011-01-01

Qualitative organic analysis of an unknown compound is an integral part of the university chemistry laboratory curriculum. This type of training is essential as students learn to approach a problem systematically and to interpret the results logically. However, considerable quantities of waste are generated by using conventional methods of…

PresenceAbsence: An R package for presence absence analysis

Treesearch

Elizabeth A. Freeman; Gretchen Moisen

2008-01-01

The PresenceAbsence package for R provides a set of functions useful when evaluating the results of presence-absence analysis, for example, models of species distribution or the analysis of diagnostic tests. The package provides a toolkit for selecting the optimal threshold for translating a probability surface into presence-absence maps specifically tailored to their...

Poincaré chaos and unpredictable functions

NASA Astrophysics Data System (ADS)

Akhmet, Marat; Fen, Mehmet Onur

2017-07-01

The results of this study are continuation of the research of Poincaré chaos initiated in the papers (M. Akhmet and M.O. Fen, Commun Nonlinear Sci Numer Simulat 40 (2016) 1-5; M. Akhmet and M.O. Fen, Turk J Math, doi:10.3906/mat-1603-51, in press). We focus on the construction of an unpredictable function, continuous on the real axis. As auxiliary results, unpredictable orbits for the symbolic dynamics and the logistic map are obtained. By shaping the unpredictable function as well as Poisson function we have performed the first step in the development of the theory of unpredictable solutions for differential and discrete equations. The results are preliminary ones for deep analysis of chaos existence in differential and hybrid systems. Illustrative examples concerning unpredictable solutions of differential equations are provided.

Amide I vibrational circular dichroism of dipeptide: Conformation dependence and fragment analysis

NASA Astrophysics Data System (ADS)

Choi, Jun-Ho; Cho, Minhaeng

2004-03-01

The amide I vibrational circular dichroic response of alanine dipeptide analog (ADA) was theoretically investigated and the density functional theory calculation and fragment analysis results are presented. A variety of vibrational spectroscopic properties, local and normal mode frequencies, coupling constant, dipole, and rotational strengths, are calculated by varying two dihedral angles determining the three-dimensional ADA conformation. Considering two monopeptide fragments separately, we show that the amide I vibrational circular dichroism of the ADA can be quantitatively predicted. For several representative conformations of the model ADA, vibrational circular dichroism spectra are calculated by using both the density functional theory calculation and fragment analysis methods.

Distinct metabolites for photoreactive L-phenylalanine derivatives in Klebsiella sp. CK6 isolated from rhizosphere of a wild dipterocarp sapling.

PubMed

Wang, Lei; Hisano, Wataru; Murai, Yuta; Sakurai, Munenori; Muto, Yasuyuki; Ikemoto, Haruka; Okamoto, Masashi; Murotani, Takashi; Isoda, Reika; Kim, Dongyeop; Sakihama, Yasuko; Sitepu, Irnayuli R; Hashidoko, Yasuyuki; Hatanaka, Yasumaru; Hashimoto, Makoto

2013-07-16

Photoaffinity labeling is a reliable analytical method for biological functional analysis. Three major photophores--aryl azide, benzophenone and trifluoromethyldiazirine--are utilized in analysis. Photophore-bearing L-phenylalanine derivatives, which are used for biological functional analysis, were inoculated into a Klebsiella sp. isolated from the rhizosphere of a wild dipterocarp sapling in Central Kalimantan, Indonesia, under nitrogen-limiting conditions. The proportions of metabolites were quite distinct for each photophore. These results indicated that photophores affected substrate recognition in rhizobacterial metabolic pathways, and differential photoaffinity labeling could be achieved using different photophore-containing L-phenylalanine derivatives.

Evaluation of Contact Heat Transfer Coefficient and Phase Transformation during Hot Stamping of a Hat-Type Part

PubMed Central

Kim, Heung-Kyu; Lee, Seong Hyeon; Choi, Hyunjoo

2015-01-01

Using an inverse analysis technique, the heat transfer coefficient on the die-workpiece contact surface of a hot stamping process was evaluated as a power law function of contact pressure. This evaluation was to determine whether the heat transfer coefficient on the contact surface could be used for finite element analysis of the entire hot stamping process. By comparing results of the finite element analysis and experimental measurements of the phase transformation, an evaluation was performed to determine whether the obtained heat transfer coefficient function could provide reasonable finite element prediction for workpiece properties affected by the hot stamping process. PMID:28788046

Using the Rasch Measurement Model in Psychometric Analysis of the Family Effectiveness Measure

PubMed Central

McCreary, Linda L.; Conrad, Karen M.; Conrad, Kendon J.; Scott, Christy K; Funk, Rodney R.; Dennis, Michael L.

2013-01-01

Background Valid assessment of family functioning can play a vital role in optimizing client outcomes. Because family functioning is influenced by family structure, socioeconomic context, and culture, existing measures of family functioning--primarily developed with nuclear, middle class European American families--may not be valid assessments of families in diverse populations. The Family Effectiveness Measure was developed to address this limitation. Objectives To test the Family Effectiveness Measure with data from a primarily low-income African American convenience sample, using the Rasch measurement model. Method A sample of 607 adult women completed the measure. Rasch analysis was used to assess unidimensionality, response category functioning, item fit, person reliability, differential item functioning by race and parental status, and item hierarchy. Criterion-related validity was tested using correlations with five other variables related to family functioning. Results The Family Effectiveness Measure measures two separate constructs: The effective family functioning construct was a psychometrically sound measure of the target construct that was more efficient due to the deletion of 22 items. The ineffective family functioning construct consisted of 16 of those deleted items but was not as strong psychometrically. Items in both constructs evidenced no differential item functioning by race. Criterion-related validity was supported for both. Discussion In contrast to the prevailing conceptualization that family functioning is a single construct, assessed by positively and negatively worded items, use of the Rasch analysis suggested the existence of two constructs. While the effective family functioning is a strong and efficient measure of family functioning, the ineffective family functioning will require additional item development and psychometric testing. PMID:23636342

Photon wave function formalism for analysis of Mach–Zehnder interferometer and sum-frequency generation

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

Ritboon, Atirach, E-mail: atirach.3.14@gmail.com; Department of Physics, Faculty of Science, Prince of Songkla University, Hat Yai 90112; Daengngam, Chalongrat, E-mail: chalongrat.d@psu.ac.th

2016-08-15

Biakynicki-Birula introduced a photon wave function similar to the matter wave function that satisfies the Schrödinger equation. Its second quantization form can be applied to investigate nonlinear optics at nearly full quantum level. In this paper, we applied the photon wave function formalism to analyze both linear optical processes in the well-known Mach–Zehnder interferometer and nonlinear optical processes for sum-frequency generation in dispersive and lossless medium. Results by photon wave function formalism agree with the well-established Maxwell treatments and existing experimental verifications.

Platform for combined analysis of functional and biomolecular phenotypes of the same cell.

PubMed

Kelbauskas, L; Ashili, S; Zeng, J; Rezaie, A; Lee, K; Derkach, D; Ueberroth, B; Gao, W; Paulson, T; Wang, H; Tian, Y; Smith, D; Reid, B; Meldrum, Deirdre R

2017-03-16

Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression.

Self spectrum window method in wigner-ville distribution.

PubMed

Liu, Zhongguo; Liu, Changchun; Liu, Boqiang; Lv, Yangsheng; Lei, Yinsheng; Yu, Mengsun

2005-01-01

Wigner-Ville distribution (WVD) is an important type of time-frequency analysis in biomedical signal processing. The cross-term interference in WVD has a disadvantageous influence on its application. In this research, the Self Spectrum Window (SSW) method was put forward to suppress the cross-term interference, based on the fact that the cross-term and auto-WVD- terms in integral kernel function are orthogonal. With the Self Spectrum Window (SSW) algorithm, a real auto-WVD function was used as a template to cross-correlate with the integral kernel function, and the Short Time Fourier Transform (STFT) spectrum of the signal was used as window function to process the WVD in time-frequency plane. The SSW method was confirmed by computer simulation with good analysis results. Satisfactory time- frequency distribution was obtained.

Time correlation functions of simple liquids: A new insight on the underlying dynamical processes

NASA Astrophysics Data System (ADS)

Garberoglio, Giovanni; Vallauri, Renzo; Bafile, Ubaldo

2018-05-01

Extensive molecular dynamics simulations of liquid sodium have been carried out to evaluate correlation functions of several dynamical quantities. We report the results of a novel analysis of the longitudinal and transverse correlation functions obtained by evaluating directly their self- and distinct contributions at different wavevectors k. It is easily recognized that the self-contribution remains close to its k → 0 limit, which turns out to be exactly the autocorrelation function of the single particle velocity. The wavevector dependence of the longitudinal and transverse spectra and their self- and distinct parts is also presented. By making use of the decomposition of the velocity autocorrelation spectrum in terms of longitudinal and transverse parts, our analysis is able to recognize the effect of different dynamical processes in different frequency ranges.

Distant Massive Clusters and Cosmology

NASA Technical Reports Server (NTRS)

Donahue, Megan

1999-01-01

We present a status report of our X-ray study and analysis of a complete sample of distant (z=0.5-0.8), X-ray luminous clusters of galaxies. We have obtained ASCA and ROSAT observations of the five brightest Extended Medium Sensitivity (EMSS) clusters with z > 0.5. We have constructed an observed temperature function for these clusters, and measured iron abundances for all of these clusters. We have developed an analytic expression for the behavior of the mass-temperature relation in a low-density universe. We use this mass-temperature relation together with a Press-Schechter-based model to derive the expected temperature function for different values of Omega-M. We combine this analysis with the observed temperature functions at redshifts from 0 - 0.8 to derive maximum likelihood estimates for the value of Omega-M. We report preliminary results of this analysis.

Predicting the Influence of Nano-Scale Material Structure on the In-Plane Buckling of Orthotropic Plates

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Odegard, Gregory M.; Nemeth, Michael P.; Frankland, Sarah-Jane V.

2004-01-01

A multi-scale analysis of the structural stability of a carbon nanotube-polymer composite material is developed. The influence of intrinsic molecular structure, such as nanotube length, volume fraction, orientation and chemical functionalization, is investigated by assessing the relative change in critical, in-plane buckling loads. The analysis method relies on elastic properties predicted using the hierarchical, constitutive equations developed from the equivalent-continuum modeling technique applied to the buckling analysis of an orthotropic plate. The results indicate that for the specific composite materials considered in this study, a composite with randomly orientated carbon nanotubes consistently provides the highest values of critical buckling load and that for low volume fraction composites, the non-functionalized nanotube material provides an increase in critical buckling stability with respect to the functionalized system.

Detecting phase separation of freeze-dried binary amorphous systems using pair-wise distribution function and multivariate data analysis.

PubMed

Chieng, Norman; Trnka, Hjalte; Boetker, Johan; Pikal, Michael; Rantanen, Jukka; Grohganz, Holger

2013-09-15

The purpose of this study is to investigate the use of multivariate data analysis for powder X-ray diffraction-pair-wise distribution function (PXRD-PDF) data to detect phase separation in freeze-dried binary amorphous systems. Polymer-polymer and polymer-sugar binary systems at various ratios were freeze-dried. All samples were analyzed by PXRD, transformed to PDF and analyzed by principal component analysis (PCA). These results were validated by differential scanning calorimetry (DSC) through characterization of glass transition of the maximally freeze-concentrate solute (Tg'). Analysis of PXRD-PDF data using PCA provides a more clear 'miscible' or 'phase separated' interpretation through the distribution pattern of samples on a score plot presentation compared to residual plot method. In a phase separated system, samples were found to be evenly distributed around the theoretical PDF profile. For systems that were miscible, a clear deviation of samples away from the theoretical PDF profile was observed. Moreover, PCA analysis allows simultaneous analysis of replicate samples. Comparatively, the phase behavior analysis from PXRD-PDF-PCA method was in agreement with the DSC results. Overall, the combined PXRD-PDF-PCA approach improves the clarity of the PXRD-PDF results and can be used as an alternative explorative data analytical tool in detecting phase separation in freeze-dried binary amorphous systems. Copyright © 2013 Elsevier B.V. All rights reserved.

Functional data analysis of sleeping energy expenditure.

PubMed

Lee, Jong Soo; Zakeri, Issa F; Butte, Nancy F

2017-01-01

Adequate sleep is crucial during childhood for metabolic health, and physical and cognitive development. Inadequate sleep can disrupt metabolic homeostasis and alter sleeping energy expenditure (SEE). Functional data analysis methods were applied to SEE data to elucidate the population structure of SEE and to discriminate SEE between obese and non-obese children. Minute-by-minute SEE in 109 children, ages 5-18, was measured in room respiration calorimeters. A smoothing spline method was applied to the calorimetric data to extract the true smoothing function for each subject. Functional principal component analysis was used to capture the important modes of variation of the functional data and to identify differences in SEE patterns. Combinations of functional principal component analysis and classifier algorithm were used to classify SEE. Smoothing effectively removed instrumentation noise inherent in the room calorimeter data, providing more accurate data for analysis of the dynamics of SEE. SEE exhibited declining but subtly undulating patterns throughout the night. Mean SEE was markedly higher in obese than non-obese children, as expected due to their greater body mass. SEE was higher among the obese than non-obese children (p<0.01); however, the weight-adjusted mean SEE was not statistically different (p>0.1, after post hoc testing). Functional principal component scores for the first two components explained 77.8% of the variance in SEE and also differed between groups (p = 0.037). Logistic regression, support vector machine or random forest classification methods were able to distinguish weight-adjusted SEE between obese and non-obese participants with good classification rates (62-64%). Our results implicate other factors, yet to be uncovered, that affect the weight-adjusted SEE of obese and non-obese children. Functional data analysis revealed differences in the structure of SEE between obese and non-obese children that may contribute to disruption of metabolic homeostasis.

Local linear regression for function learning: an analysis based on sample discrepancy.

PubMed

Cervellera, Cristiano; Macciò, Danilo

2014-11-01

Local linear regression models, a kind of nonparametric structures that locally perform a linear estimation of the target function, are analyzed in the context of empirical risk minimization (ERM) for function learning. The analysis is carried out with emphasis on geometric properties of the available data. In particular, the discrepancy of the observation points used both to build the local regression models and compute the empirical risk is considered. This allows to treat indifferently the case in which the samples come from a random external source and the one in which the input space can be freely explored. Both consistency of the ERM procedure and approximating capabilities of the estimator are analyzed, proving conditions to ensure convergence. Since the theoretical analysis shows that the estimation improves as the discrepancy of the observation points becomes smaller, low-discrepancy sequences, a family of sampling methods commonly employed for efficient numerical integration, are also analyzed. Simulation results involving two different examples of function learning are provided.

The Geometry of Selected U.S. Tidal Inlets.

DTIC Science & Technology

1980-05-01

wrong cluster. Table 6. Descriminant analysis results for three variables (DCC, EM2, and EM3). a. Coefficients for di i iminant functions based on three...47.95/ 3 07.72 0.975, 4,1 0 .310. 1 C1297 0,)1r, 55,94 o, D, C 24.07: 1. C5, 75 Iable-9. Descriminant analysis results for six variables (DMX, DMA, W

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

PubMed

Doborjeh, Maryam Gholami; Wang, Grace Y; Kasabov, Nikola K; Kydd, Robert; Russell, Bruce

2016-09-01

This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case study, the method was applied to electroencephalography (EEG) data collected during a GO/NOGO cognitive task performed by untreated opiate addicts, those undergoing methadone maintenance treatment (MMT) for opiate dependence and a healthy control group. the method is based on an SNN architecture called NeuCube, trained on spatiotemporal EEG data. NeuCube was used to classify EEG data across subject groups and across GO versus NOGO trials, but also facilitated a deeper comparative analysis of the dynamic brain processes. This analysis results in a better understanding of human brain functioning across subject groups when performing a cognitive task. In terms of the EEG data classification, a NeuCube model obtained better results (the maximum obtained accuracy: 90.91%) when compared with traditional statistical and artificial intelligence methods (the maximum obtained accuracy: 50.55%). more importantly, new information about the effects of MMT on cognitive brain functions is revealed through the analysis of the SNN model connectivity and its dynamics. this paper presented a new method for EEG data modeling and revealed new knowledge on brain functions associated with mental activity which is different from the brain activity observed in a resting state of the same subjects.

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

Adare, A.

PHENIX measurements are presented for the cross section and double-helicity asymmetry (ALL) in inclusive π⁰ production at midrapidity from p+p collisions at √s = 510 GeV from data taken in 2012 and 2013 at the Relativistic Heavy Ion Collider. The next-to-leading-order perturbativequantum- chromodynamics theory calculation is in excellent agreement with the presented cross section results. The calculation utilized parton-to-pion fragmentation functions from the recent DSS14 global analysis, which prefer a smaller gluon-to-pion fragmentation function. The π⁰A LL results follow an increasingly positive asymmetry trend with pT and √s with respect to the predictions and are in excellent agreement with themore » latest global analysis results. This analysis incorporated earlier results on π0 and jet A LL, and suggested a positive contribution of gluon polarization to the spin of the proton ΔG for the gluon momentum fraction range x > 0.05. The data presented here extend to a currently unexplored region, down to x 0.01, and thus provide additional constraints on the value of ΔG.« less

[Research on Time-frequency Characteristics of Magneto-acoustic Signal of Different Thickness Medium Based on Wave Summing Method].

PubMed

Zhang, Shunqi; Yin, Tao; Ma, Ren; Liu, Zhipeng

2015-08-01

Functional imaging method of biological electrical characteristics based on magneto-acoustic effect gives valuable information of tissue in early tumor diagnosis, therein time and frequency characteristics analysis of magneto-acoustic signal is important in image reconstruction. This paper proposes wave summing method based on Green function solution for acoustic source of magneto-acoustic effect. Simulations and analysis under quasi 1D transmission condition are carried out to time and frequency characteristics of magneto-acoustic signal of models with different thickness. Simulation results of magneto-acoustic signal were verified through experiments. Results of the simulation with different thickness showed that time-frequency characteristics of magneto-acoustic signal reflected thickness of sample. Thin sample, which is less than one wavelength of pulse, and thick sample, which is larger than one wavelength, showed different summed waveform and frequency characteristics, due to difference of summing thickness. Experimental results verified theoretical analysis and simulation results. This research has laid a foundation for acoustic source and conductivity reconstruction to the medium with different thickness in magneto-acoustic imaging.

ANCAC: amino acid, nucleotide, and codon analysis of COGs – a tool for sequence bias analysis in microbial orthologs

PubMed Central

2012-01-01

Background The COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG) within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins. Results Here we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC’s NUCOCOG dataset as the largest one available for that purpose thus far. Conclusions Using the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills. PMID:22958836

Development of Welding Fumes Health Index (WFHI) for Welding Workplace’s Safety and Health Assessment

PubMed Central

HARIRI, Azian; PAIMAN, Nuur Azreen; LEMAN, Abdul Mutalib; MD. YUSOF, Mohammad Zainal

2014-01-01

Abstract Background This study aimed to develop an index that can rank welding workplace that associate well with possible health risk of welders. Methods Welding Fumes Health Index (WFHI) were developed based on data from case studies conducted in Plant 1 and Plant 2. Personal sampling of welding fumes to assess the concentration of metal constituents along with series of lung function tests was conducted. Fifteen metal constituents were investigated in each case study. Index values were derived from aggregation analysis of metal constituent concentration while significant lung functions were recognized through statistical analysis in each plant. Results The results showed none of the metal constituent concentration was exceeding the permissible exposure limit (PEL) for all plants. However, statistical analysis showed significant mean differences of lung functions between welders and non-welders. The index was then applied to one of the welding industry (Plant 3) for verification purpose. The developed index showed its promising ability to rank welding workplace, according to the multiple constituent concentrations of welding fumes that associates well with lung functions of the investigated welders. Conclusion There was possibility that some of the metal constituents were below the detection limit leading to ‘0’ value of sub index, thus the multiplicative form of aggregation model was not suitable for analysis. On the other hand, maximum or minimum operator forms suffer from compensation issues and were not considered in this study. PMID:25927034

Measurement of influence function using swing arm profilometer and laser tracker.

PubMed

Jing, Hongwei; King, Christopher; Walker, David

2010-03-01

We present a novel method to accurately measure 3D polishing influence functions by using a swing arm profilometer (SAP) and a laser tracker. The laser tracker is used to align the SAP and measure the parameters of the SAP setup before measuring the influence function. The instruments and the measurement method are described, together with measurement uncertainty analysis. An influence function deliberately produced with asymmetric form in order to create a challenging test is measured, and compared with that of a commercial 3D profilometer. The SAP result is 48.2 microm in PV, 7.271 mm(3) in volume. The 3D profilometer result is 48.4 microm in PV, 7.289 mm(3) in volume. The forms of the two results show excellent correlation. This gives confidence of the viability of the SAP method for larger influence functions out of range of the commercial instrument.

Differential and Conditional Activation of PKC-Isoforms Dictates Cardiac Adaptation during Physiological to Pathological Hypertrophy

PubMed Central

Naskar, Shaon; Datta, Kaberi; Mitra, Arkadeep; Pathak, Kanchan; Datta, Ritwik; Bansal, Trisha; Sarkar, Sagartirtha

2014-01-01

A cardiac hypertrophy is defined as an increase in heart mass which may either be beneficial (physiological hypertrophy) or detrimental (pathological hypertrophy). This study was undertaken to establish the role of different protein kinase-C (PKC) isoforms in the regulation of cardiac adaptation during two types of cardiac hypertrophy. Phosphorylation of specific PKC-isoforms and expression of their downstream proteins were studied during physiological and pathological hypertrophy in 24 week male Balb/c mice (Mus musculus) models, by reverse transcriptase-PCR, western blot analysis and M-mode echocardiography for cardiac function analysis. PKC-δ was significantly induced during pathological hypertrophy while PKC-α was exclusively activated during physiological hypertrophy in our study. PKC-δ activation during pathological hypertrophy resulted in cardiomyocyte apoptosis leading to compromised cardiac function and on the other hand, activation of PKC-α during physiological hypertrophy promoted cardiomyocyte growth but down regulated cellular apoptotic load resulting in improved cardiac function. Reversal in PKC-isoform with induced activation of PKC-δ and simultaneous inhibition of phospho-PKC-α resulted in an efficient myocardium to deteriorate considerably resulting in compromised cardiac function during physiological hypertrophy via augmentation of apoptotic and fibrotic load. This is the first report where PKC-α and -δ have been shown to play crucial role in cardiac adaptation during physiological and pathological hypertrophy respectively thereby rendering compromised cardiac function to an otherwise efficient heart by conditional reversal of their activation. PMID:25116170

Introduction to Generalized Functions with Applications in Aerodynamics and Aeroacoustics

NASA Technical Reports Server (NTRS)

Farassat, F.

1994-01-01

Generalized functions have many applications in science and engineering. One useful aspect is that discontinuous functions can be handled as easily as continuous or differentiable functions and provide a powerful tool in formulating and solving many problems of aerodynamics and acoustics. Furthermore, generalized function theory elucidates and unifies many ad hoc mathematical approaches used by engineers and scientists. We define generalized functions as continuous linear functionals on the space of infinitely differentiable functions with compact support, then introduce the concept of generalized differentiation. Generalized differentiation is the most important concept in generalized function theory and the applications we present utilize mainly this concept. First, some results of classical analysis, are derived with the generalized function theory. Other applications of the generalized function theory in aerodynamics discussed here are the derivations of general transport theorems for deriving governing equations of fluid mechanics, the interpretation of the finite part of divergent integrals, the derivation of the Oswatitsch integral equation of transonic flow, and the analysis of velocity field discontinuities as sources of vorticity. Applications in aeroacoustics include the derivation of the Kirchhoff formula for moving surfaces, the noise from moving surfaces, and shock noise source strength based on the Ffowcs Williams-Hawkings equation.

Evaluating linguistic equivalence of patient-reported outcomes in a cancer clinical trial.

PubMed

Hahn, Elizabeth A; Bode, Rita K; Du, Hongyan; Cella, David

2006-01-01

In order to make meaningful cross-cultural or cross-linguistic comparisons of health-related quality of life (HRQL) or to pool international research data, it is essential to create unbiased measures that can detect clinically important differences. When HRQL scores differ between cultural/linguistic groups, it is important to determine whether this reflects real group differences, or is the result of systematic measurement variability. To investigate the linguistic measurement equivalence of a cancer-specific HRQL questionnaire, and to conduct a sensitivity analysis of treatment differences in HRQL in a clinical trial. Patients with newly diagnosed chronic myelogenous leukemia (n = 1049) completed serial HRQL assessments in an international Phase III trial. Two types of differential item functioning (uniform and non-uniform) were evaluated using item response theory and classical test theory approaches. A sensitivity analysis was conducted to compare HRQL between treatment arms using items without evidence of differential functioning. Among 27 items, nine (33%) did not exhibit any evidence of differential functioning in both linguistic comparisons (English versus French, English versus German). Although 18 items functioned differently, there was no evidence of systematic bias. In a sensitivity analysis, adjustment for differential functioning affected the magnitude, but not the direction or interpretation of clinical trial treatment arm differences. Sufficient sample sizes were available for only three of the eight language groups. Identification of differential functioning in two-thirds of the items suggests that current psychometric methods may be too sensitive. Enhanced methodologies are needed to differentiate trivial from substantive differential item functioning. Systematic variability in HRQL across different groups can be evaluated for its effect upon clinical trial results; a practice recommended when data are pooled across cultural or linguistic groups to make conclusions about treatment effects.

Executive Dysfunction in OSA Before and After Treatment: A Meta-Analysis

PubMed Central

Olaithe, Michelle; Bucks, Romola S.

2013-01-01

Study Objectives: Obstructive sleep apnea (OSA) is a frequent and often underdiagnosed condition that is associated with upper airway collapse, oxygen desaturation, and sleep fragmentation leading to cognitive dysfunction. There is meta-analytic evidence that subdomains of attention and memory are affected by OSA. However, a thorough investigation of the impact of OSA on different subdomains of executive function is yet to be conducted. This report investigates the impact of OSA and its treatment, in adult patients, on 5 theorized subdomains of executive function. Design: An extensive literature search was conducted of published and unpublished materials, returning 35 studies that matched selection criteria. Meta-analysis was used to synthesize the results from studies examining the impact of OSA on executive functioning compared to controls (21 studies), and before and after treatment (19 studies); 5 studies met inclusion in both categories. Measurements: Research papers were selected which assessed 5 subdomains of executive function: Shifting, Updating, Inhibition, Generativity, and Fluid Reasoning. Results: All 5 domains of executive function demonstrated medium to very large impairments in OSA independent of age and disease severity. Furthermore, all subdomains of executive function demonstrated small to medium improvements with CPAP treatment. Discussion: Executive function is impaired across all five domains in OSA; these difficulties improved with CPAP treatment. Age and disease severity did not moderate the effects found; however, further studies are needed to explore the extent of primary and secondary effects, and the impact of age and premorbid intellectual ability (cognitive reserve). Citation: Olaithe M; Bucks RS. Executive dysfunction in OSA before and after treatment: a meta-analysis. SLEEP 2013;36(9):1297-1305. PMID:23997362

Elliptic supersymmetric integrable model and multivariable elliptic functions

NASA Astrophysics Data System (ADS)

Motegi, Kohei

2017-12-01

We investigate the elliptic integrable model introduced by Deguchi and Martin [Int. J. Mod. Phys. A 7, Suppl. 1A, 165 (1992)], which is an elliptic extension of the Perk-Schultz model. We introduce and study a class of partition functions of the elliptic model by using the Izergin-Korepin analysis. We show that the partition functions are expressed as a product of elliptic factors and elliptic Schur-type symmetric functions. This result resembles recent work by number theorists in which the correspondence between the partition functions of trigonometric models and the product of the deformed Vandermonde determinant and Schur functions were established.

The Relationship Between Body Image and Sexual Function in Middle-Aged Women.

PubMed

Afshari, Poorandokht; Houshyar, Zeinab; Javadifar, Nahid; Pourmotahari, Fatemeh; Jorfi, Maryam

2016-11-01

An individual's social and marital function, interpersonal relationships, and quality of life may, sometimes be affected by negative body image. This study is aimed at determining the relationship between body image and sexual function in middle-aged women. In this cross-sectional study, 437 middle-aged women, who were referred to various public healthcare centers in Ahvaz, Iran during 2014-2015, were selected. The Female Sexual Function Index (FSFI) and Body Shape Questionnaire (BSQ) were used for data collection. Chi-square, one-way analysis of variance, Spearman's correlation test, and logistic regression analysis were performed for statistical analysis. Approximately 58% of the participants expressed satisfaction with their body image, 35% were mildly dissatisfied, and 7% were moderately dissatisfied with their body image. Body image had a significant negative relationship with sexual satisfaction and sexual function (p=0.005). Furthermore, there was a significant relationship between body image and sexual desire (p=0.022), pain (p=0.001), sexual arousal (p<0.0005), sexual orgasm (p=0.001), and sexual satisfaction (p<0.0005). As the results indicated, body image is an important aspect of sexual health. In this study, women with a positive body image had higher sexual function valuation, compared to women with a negative body image. Also, body shape satisfaction was a predictor of sexual function.

Dynamic biochemical tissue analysis detects functional L-selectin ligands on colon cancer tissues

PubMed Central

Carlson, Grady E.; Martin, Eric W.; Shirure, Venktesh S.; Malgor, Ramiro; Resto, Vicente A.; Goetz, Douglas J.; Burdick, Monica M.

2017-01-01

A growing body of evidence suggests that L-selectin ligands presented on circulating tumor cells facilitate metastasis by binding L-selectin presented on leukocytes. Commonly used methods for detecting L-selectin ligands on tissues, e.g., immunostaining, are performed under static, no-flow conditions. However, such analysis does not assay for functional L-selectin ligands, specifically those ligands that promote adhesion under shear flow conditions. Recently our lab developed a method, termed dynamic biochemical tissue analysis (DBTA), to detect functional selectin ligands in situ by probing tissues with L-selectin-coated microspheres under hemodynamic flow conditions. In this investigation, DBTA was used to probe human colon tissues for L-selectin ligand activity. The detection of L-selectin ligands using DBTA was highly specific. Furthermore, DBTA reproducibly detected functional L-selectin ligands on diseased, e.g., cancerous or inflamed, tissues but not on noncancerous tissues. In addition, DBTA revealed a heterogeneous distribution of functional L-selectin ligands on colon cancer tissues. Most notably, detection of L-selectin ligands by immunostaining using HECA-452 antibody only partially correlated with functional L-selectin ligands detected by DBTA. In summation, the results of this study demonstrate that DBTA detects functional selectin ligands to provide a unique characterization of pathological tissue. PMID:28282455

Compensation through Functional Hyperconnectivity: A Longitudinal Connectome Assessment of Mild Traumatic Brain Injury

PubMed Central

Iraji, Armin; Chen, Hanbo; Wiseman, Natalie; Welch, Robert D.; O'Neil, Brian J.; Haacke, E. Mark; Liu, Tianming; Kou, Zhifeng

2016-01-01

Mild traumatic brain injury (mTBI) is a major public health concern. Functional MRI has reported alterations in several brain networks following mTBI. However, the connectome-scale brain network changes are still unknown. In this study, sixteen mTBI patients were prospectively recruited from an emergency department and followed up at 4–6 weeks after injury. Twenty-four healthy controls were also scanned twice with the same time interval. Three hundred fifty-eight brain landmarks that preserve structural and functional correspondence of brain networks across individuals were used to investigate longitudinal brain connectivity. Network-based statistic (NBS) analysis did not find significant difference in the group-by-time interaction and time effects. However, 258 functional pairs show group differences in which mTBI patients have higher functional connectivity. Meta-analysis showed that “Action” and “Cognition” are the most affected functional domains. Categorization of connectomic signatures using multiview group-wise cluster analysis identified two patterns of functional hyperconnectivity among mTBI patients: (I) between the posterior cingulate cortex and the association areas of the brain and (II) between the occipital and the frontal lobes of the brain. Our results demonstrate that brain concussion renders connectome-scale brain network connectivity changes, and the brain tends to be hyperactivated to compensate the pathophysiological disturbances. PMID:26819765

Compensation through Functional Hyperconnectivity: A Longitudinal Connectome Assessment of Mild Traumatic Brain Injury.

PubMed

Iraji, Armin; Chen, Hanbo; Wiseman, Natalie; Welch, Robert D; O'Neil, Brian J; Haacke, E Mark; Liu, Tianming; Kou, Zhifeng

2016-01-01

Mild traumatic brain injury (mTBI) is a major public health concern. Functional MRI has reported alterations in several brain networks following mTBI. However, the connectome-scale brain network changes are still unknown. In this study, sixteen mTBI patients were prospectively recruited from an emergency department and followed up at 4-6 weeks after injury. Twenty-four healthy controls were also scanned twice with the same time interval. Three hundred fifty-eight brain landmarks that preserve structural and functional correspondence of brain networks across individuals were used to investigate longitudinal brain connectivity. Network-based statistic (NBS) analysis did not find significant difference in the group-by-time interaction and time effects. However, 258 functional pairs show group differences in which mTBI patients have higher functional connectivity. Meta-analysis showed that "Action" and "Cognition" are the most affected functional domains. Categorization of connectomic signatures using multiview group-wise cluster analysis identified two patterns of functional hyperconnectivity among mTBI patients: (I) between the posterior cingulate cortex and the association areas of the brain and (II) between the occipital and the frontal lobes of the brain. Our results demonstrate that brain concussion renders connectome-scale brain network connectivity changes, and the brain tends to be hyperactivated to compensate the pathophysiological disturbances.

Dynamic biochemical tissue analysis detects functional L-selectin ligands on colon cancer tissues.

PubMed

Carlson, Grady E; Martin, Eric W; Shirure, Venktesh S; Malgor, Ramiro; Resto, Vicente A; Goetz, Douglas J; Burdick, Monica M

2017-01-01

A growing body of evidence suggests that L-selectin ligands presented on circulating tumor cells facilitate metastasis by binding L-selectin presented on leukocytes. Commonly used methods for detecting L-selectin ligands on tissues, e.g., immunostaining, are performed under static, no-flow conditions. However, such analysis does not assay for functional L-selectin ligands, specifically those ligands that promote adhesion under shear flow conditions. Recently our lab developed a method, termed dynamic biochemical tissue analysis (DBTA), to detect functional selectin ligands in situ by probing tissues with L-selectin-coated microspheres under hemodynamic flow conditions. In this investigation, DBTA was used to probe human colon tissues for L-selectin ligand activity. The detection of L-selectin ligands using DBTA was highly specific. Furthermore, DBTA reproducibly detected functional L-selectin ligands on diseased, e.g., cancerous or inflamed, tissues but not on noncancerous tissues. In addition, DBTA revealed a heterogeneous distribution of functional L-selectin ligands on colon cancer tissues. Most notably, detection of L-selectin ligands by immunostaining using HECA-452 antibody only partially correlated with functional L-selectin ligands detected by DBTA. In summation, the results of this study demonstrate that DBTA detects functional selectin ligands to provide a unique characterization of pathological tissue.

Design oriented structural analysis

NASA Technical Reports Server (NTRS)

Giles, Gary L.

1994-01-01

Desirable characteristics and benefits of design oriented analysis methods are described and illustrated by presenting a synoptic description of the development and uses of the Equivalent Laminated Plate Solution (ELAPS) computer code. ELAPS is a design oriented structural analysis method which is intended for use in the early design of aircraft wing structures. Model preparation is minimized by using a few large plate segments to model the wing box structure. Computational efficiency is achieved by using a limited number of global displacement functions that encompass all segments over the wing planform. Coupling with other codes is facilitated since the output quantities such as deflections and stresses are calculated as continuous functions over the plate segments. Various aspects of the ELAPS development are discussed including the analytical formulation, verification of results by comparison with finite element analysis results, coupling with other codes, and calculation of sensitivity derivatives. The effectiveness of ELAPS for multidisciplinary design application is illustrated by describing its use in design studies of high speed civil transport wing structures.

Three-Dimensional Field Solutions for Multi-Pole Cylindrical Halbach Arrays in an Axial Orientation

NASA Technical Reports Server (NTRS)

Thompson, William K.

2006-01-01

This article presents three-dimensional B field solutions for the cylindrical Halbach array in an axial orientation. This arrangement has applications in the design of axial motors and passive axial magnetic bearings and couplers. The analytical model described here assumes ideal magnets with fixed and uniform magnetization. The field component functions are expressed as sums of 2-D definite integrals that are easily computed by a number of mathematical analysis software packages. The analysis is verified with sample calculations and the results are compared to equivalent results from traditional finite-element analysis (FEA). The field solutions are then approximated for use in flux linkage and induced EMF calculations in nearby stator windings by expressing the field variance with angular displacement as pure sinusoidal function whose amplitude depends on radial and axial position. The primary advantage of numerical implementation of the analytical approach presented in the article is that it lends itself more readily to parametric analysis and design tradeoffs than traditional FEA models.

ISAP: ISO Spectral Analysis Package

NASA Astrophysics Data System (ADS)

Ali, Babar; Bauer, Otto; Brauher, Jim; Buckley, Mark; Harwood, Andrew; Hur, Min; Khan, Iffat; Li, Jing; Lord, Steve; Lutz, Dieter; Mazzarella, Joe; Molinari, Sergio; Morris, Pat; Narron, Bob; Seidenschwang, Karla; Sidher, Sunil; Sturm, Eckhard; Swinyard, Bruce; Unger, Sarah; Verstraete, Laurent; Vivares, Florence; Wieprecht, Ecki

2014-03-01

ISAP, written in IDL, simplifies the process of visualizing, subsetting, shifting, rebinning, masking, combining scans with weighted means or medians, filtering, and smoothing Auto Analysis Results (AARs) from post-pipeline processing of the Infrared Space Observatory's (ISO) Short Wavelength Spectrometer (SWS) and Long Wavelength Spectrometer (LWS) data. It can also be applied to PHOT-S and CAM-CVF data, and data from practically any spectrometer. The result of a typical ISAP session is expected to be a "simple spectrum" (single-valued spectrum which may be resampled to a uniform wavelength separation if desired) that can be further analyzed and measured either with other ISAP functions, native IDL functions, or exported to other analysis package (e.g., IRAF, MIDAS) if desired. ISAP provides many tools for further analysis, line-fitting, and continuum measurements, such as routines for unit conversions, conversions from wavelength space to frequency space, line and continuum fitting, flux measurement, synthetic photometry and models such as a zodiacal light model to predict and subtract the dominant foreground at some wavelengths.

Detecting social-cognitive deficits after traumatic brain injury: An ALE meta-analysis of fMRI studies.

PubMed

Xiao, Hui; Jacobsen, Andre; Chen, Ziqian; Wang, Yang

2017-01-01

Traumatic brain injury (TBI) can result in significant social dysfunction, which is represented by impairment to social-cognitive abilities (i.e. social cognition, social attention/executive function and communication). This study is aimed to explore brain networks mediating the social dysfunction after TBI and its underlying mechanisms. We performed a quantitative meta-analysis using the activation likelihood estimation (ALE) approach on functional magnetic resonance imaging (fMRI) studies of social-cognitive abilities following TBI. Sixteen studies fulfilled the inclusion criteria resulting in a total of 190 patients with TBI and 206 controls enrolled in the ALE meta-analysis. The temporoparietal junction (TPJ) and the medial prefrontal cortex (mPFC) were the specific regions that social cognition predominantly engaged. The cingulate gyrus, frontal gyrus and inferior parietal lobule were the main regions related to social attention/executive functions. Communication dysfunction, especially related to language deficits, was found to show greater activation of the temporal gyrus and fusiform gyrus in TBI. The current ALE meta-analytic findings provide evidence that patients have significant social-cognitive disabilities following TBI. The relatively limited pool of literature and the varied fMRI results from published studies indicate that social-cognitive abilities following TBI is an area that would greatly benefit from further investigation.

The Meditative Mind: A Comprehensive Meta-Analysis of MRI Studies

PubMed Central

2015-01-01

Over the past decade mind and body practices, such as yoga and meditation, have raised interest in different scientific fields; in particular, the physiological mechanisms underlying the beneficial effects observed in meditators have been investigated. Neuroimaging studies have studied the effects of meditation on brain structure and function and findings have helped clarify the biological underpinnings of the positive effects of meditation practice and the possible integration of this technique in standard therapy. The large amount of data collected thus far allows drawing some conclusions about the neural effects of meditation practice. In the present study we used activation likelihood estimation (ALE) analysis to make a coordinate-based meta-analysis of neuroimaging data on the effects of meditation on brain structure and function. Results indicate that meditation leads to activation in brain areas involved in processing self-relevant information, self-regulation, focused problem-solving, adaptive behavior, and interoception. Results also show that meditation practice induces functional and structural brain modifications in expert meditators, especially in areas involved in self-referential processes such as self-awareness and self-regulation. These results demonstrate that a biological substrate underlies the positive pervasive effect of meditation practice and suggest that meditation techniques could be adopted in clinical populations and to prevent disease. PMID:26146618

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

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

Benadjaoud, Mohamed Amine, E-mail: mohamedamine.benadjaoud@gustaveroussy.fr; Université Paris sud, Le Kremlin-Bicêtre; Institut Gustave Roussy, Villejuif

2014-11-01

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principalmore » components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.« less

Modular Digital Missile Guidance, Phase I2

DTIC Science & Technology

1976-01-28

at OMR. The revised study plan was fornally approved by ONR on 29 May 1975, confining the sinulatlon analysis work to a Class II missile with...functions analyzed in tne Phase I and Phase 11 studies . It can be seen thatf tnere practicable» (based on the results of function partitioning trade...llaillAU AS a result of this study » three generic missile families have oeen established and» relative to this classification» on