multiple method integration: Topics by Science.gov

Sample records for multiple method integration

Multiple methods integration for structural mechanics analysis and design

NASA Technical Reports Server (NTRS)

Housner, J. M.; Aminpour, M. A.

1991-01-01

A new research area of multiple methods integration is proposed for joining diverse methods of structural mechanics analysis which interact with one another. Three categories of multiple methods are defined: those in which a physical interface are well defined; those in which a physical interface is not well-defined, but selected; and those in which the interface is a mathematical transformation. Two fundamental integration procedures are presented that can be extended to integrate various methods (e.g., finite elements, Rayleigh Ritz, Galerkin, and integral methods) with one another. Since the finite element method will likely be the major method to be integrated, its enhanced robustness under element distortion is also examined and a new robust shell element is demonstrated.
Statistical Methods in Integrative Genomics

PubMed Central

Richardson, Sylvia; Tseng, George C.; Sun, Wei

2016-01-01

Statistical methods in integrative genomics aim to answer important biology questions by jointly analyzing multiple types of genomic data (vertical integration) or aggregating the same type of data across multiple studies (horizontal integration). In this article, we introduce different types of genomic data and data resources, and then review statistical methods of integrative genomics, with emphasis on the motivation and rationale of these methods. We conclude with some summary points and future research directions. PMID:27482531
On the method of Ermakov and Zolotukhin for multiple integration

NASA Technical Reports Server (NTRS)

Cranley, R.; Patterson, T. N. L.

1971-01-01

By introducing the idea of pseudo-implementation, a practical assessment of the method for multiple integration is made. The performance of the method is found to be unimpressive in comparison with a recent regression method.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Ochiai, Yoshihiro

Heat-conduction analysis under steady state without heat generation can easily be treated by the boundary element method. However, in the case with heat conduction with heat generation can approximately be solved without a domain integral by an improved multiple-reciprocity boundary element method. The convention multiple-reciprocity boundary element method is not suitable for complicated heat generation. In the improved multiple-reciprocity boundary element method, on the other hand, the domain integral in each step is divided into point, line, and area integrals. In order to solve the problem, the contour lines of heat generation, which approximate the actual heat generation, are used.
A comparative study of Conroy and Monte Carlo methods applied to multiple quadratures and multiple scattering

NASA Technical Reports Server (NTRS)

Deepak, A.; Fluellen, A.

1978-01-01

An efficient numerical method of multiple quadratures, the Conroy method, is applied to the problem of computing multiple scattering contributions in the radiative transfer through realistic planetary atmospheres. A brief error analysis of the method is given and comparisons are drawn with the more familiar Monte Carlo method. Both methods are stochastic problem-solving models of a physical or mathematical process and utilize the sampling scheme for points distributed over a definite region. In the Monte Carlo scheme the sample points are distributed randomly over the integration region. In the Conroy method, the sample points are distributed systematically, such that the point distribution forms a unique, closed, symmetrical pattern which effectively fills the region of the multidimensional integration. The methods are illustrated by two simple examples: one, of multidimensional integration involving two independent variables, and the other, of computing the second order scattering contribution to the sky radiance.
Integrative Analysis of “-Omics” Data Using Penalty Functions

PubMed Central

Zhao, Qing; Shi, Xingjie; Huang, Jian; Liu, Jin; Li, Yang; Ma, Shuangge

2014-01-01

In the analysis of omics data, integrative analysis provides an effective way of pooling information across multiple datasets or multiple correlated responses, and can be more effective than single-dataset (response) analysis. Multiple families of integrative analysis methods have been proposed in the literature. The current review focuses on the penalization methods. Special attention is paid to sparse meta-analysis methods that pool summary statistics across datasets, and integrative analysis methods that pool raw data across datasets. We discuss their formulation and rationale. Beyond “standard” penalized selection, we also review contrasted penalization and Laplacian penalization which accommodate finer data structures. The computational aspects, including computational algorithms and tuning parameter selection, are examined. This review concludes with possible limitations and extensions. PMID:25691921
A modified precise integration method for transient dynamic analysis in structural systems with multiple damping models

NASA Astrophysics Data System (ADS)

Ding, Zhe; Li, Li; Hu, Yujin

2018-01-01

Sophisticated engineering systems are usually assembled by subcomponents with significantly different levels of energy dissipation. Therefore, these damping systems often contain multiple damping models and lead to great difficulties in analyzing. This paper aims at developing a time integration method for structural systems with multiple damping models. The dynamical system is first represented by a generally damped model. Based on this, a new extended state-space method for the damped system is derived. A modified precise integration method with Gauss-Legendre quadrature is then proposed. The numerical stability and accuracy of the proposed integration method are discussed in detail. It is verified that the method is conditionally stable and has inherent algorithmic damping, period error and amplitude decay. Numerical examples are provided to assess the performance of the proposed method compared with other methods. It is demonstrated that the method is more accurate than other methods with rather good efficiency and the stable condition is easy to be satisfied in practice.
Structural reliability calculation method based on the dual neural network and direct integration method.

PubMed

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.
Method and system of integrating information from multiple sources

DOEpatents

Alford, Francine A [Livermore, CA; Brinkerhoff, David L [Antioch, CA

2006-08-15

A system and method of integrating information from multiple sources in a document centric application system. A plurality of application systems are connected through an object request broker to a central repository. The information may then be posted on a webpage. An example of an implementation of the method and system is an online procurement system.
Criteria for quantitative and qualitative data integration: mixed-methods research methodology.

PubMed

Lee, Seonah; Smith, Carrol A M

2012-05-01

Many studies have emphasized the need and importance of a mixed-methods approach for evaluation of clinical information systems. However, those studies had no criteria to guide integration of multiple data sets. Integrating different data sets serves to actualize the paradigm that a mixed-methods approach argues; thus, we require criteria that provide the right direction to integrate quantitative and qualitative data. The first author used a set of criteria organized from a literature search for integration of multiple data sets from mixed-methods research. The purpose of this article was to reorganize the identified criteria. Through critical appraisal of the reasons for designing mixed-methods research, three criteria resulted: validation, complementarity, and discrepancy. In applying the criteria to empirical data of a previous mixed methods study, integration of quantitative and qualitative data was achieved in a systematic manner. It helped us obtain a better organized understanding of the results. The criteria of this article offer the potential to produce insightful analyses of mixed-methods evaluations of health information systems.
A retrospective likelihood approach for efficient integration of multiple omics factors in case-control association studies.

PubMed

Balliu, Brunilda; Tsonaka, Roula; Boehringer, Stefan; Houwing-Duistermaat, Jeanine

2015-03-01

Integrative omics, the joint analysis of outcome and multiple types of omics data, such as genomics, epigenomics, and transcriptomics data, constitute a promising approach for powerful and biologically relevant association studies. These studies often employ a case-control design, and often include nonomics covariates, such as age and gender, that may modify the underlying omics risk factors. An open question is how to best integrate multiple omics and nonomics information to maximize statistical power in case-control studies that ascertain individuals based on the phenotype. Recent work on integrative omics have used prospective approaches, modeling case-control status conditional on omics, and nonomics risk factors. Compared to univariate approaches, jointly analyzing multiple risk factors with a prospective approach increases power in nonascertained cohorts. However, these prospective approaches often lose power in case-control studies. In this article, we propose a novel statistical method for integrating multiple omics and nonomics factors in case-control association studies. Our method is based on a retrospective likelihood function that models the joint distribution of omics and nonomics factors conditional on case-control status. The new method provides accurate control of Type I error rate and has increased efficiency over prospective approaches in both simulated and real data. © 2015 Wiley Periodicals, Inc.
A method for integrating multiple components in a decision support system

Treesearch

Donald Nute; Walter D. Potter; Zhiyuan Cheng; Mayukh Dass; Astrid Glende; Frederick Maierv; Cy Routh; Hajime Uchiyama; Jin Wang; Sarah Witzig; Mark Twery; Peter Knopp; Scott Thomasma; H. Michael Rauscher

2005-01-01

We present a flexible, extensible method for integrating multiple tools into a single large decision support system (DSS) using a forest ecosystem management DSS (NED-2) as an example. In our approach, a rich ontology for the target domain is developed and implemented in the internal data model for the DSS. Semi-autonomous agents control external components and...
Image sensor with high dynamic range linear output

NASA Technical Reports Server (NTRS)

Yadid-Pecht, Orly (Inventor); Fossum, Eric R. (Inventor)

2007-01-01

Designs and operational methods to increase the dynamic range of image sensors and APS devices in particular by achieving more than one integration times for each pixel thereof. An APS system with more than one column-parallel signal chains for readout are described for maintaining a high frame rate in readout. Each active pixel is sampled for multiple times during a single frame readout, thus resulting in multiple integration times. The operation methods can also be used to obtain multiple integration times for each pixel with an APS design having a single column-parallel signal chain for readout. Furthermore, analog-to-digital conversion of high speed and high resolution can be implemented.
Detecting submerged objects: the application of side scan sonar to forensic contexts.

PubMed

Schultz, John J; Healy, Carrie A; Parker, Kenneth; Lowers, Bim

2013-09-10

Forensic personnel must deal with numerous challenges when searching for submerged objects. While traditional water search methods have generally involved using dive teams, remotely operated vehicles (ROVs), and water scent dogs for cases involving submerged objects and bodies, law enforcement is increasingly integrating multiple methods that include geophysical technologies. There are numerous advantages for integrating geophysical technologies, such as side scan sonar and ground penetrating radar (GPR), with more traditional search methods. Overall, these methods decrease the time involved searching, in addition to increasing area searched. However, as with other search methods, there are advantages and disadvantages when using each method. For example, in instances with excessive aquatic vegetation or irregular bottom terrain, it may not be possible to discern a submersed body with side scan sonar. As a result, forensic personnel will have the highest rate of success during searches for submerged objects when integrating multiple search methods, including deploying multiple geophysical technologies. The goal of this paper is to discuss the methodology of various search methods that are employed for submerged objects and how these various methods can be integrated as part of a comprehensive protocol for water searches depending upon the type of underwater terrain. In addition, two successful case studies involving the search and recovery of a submerged human body using side scan sonar are presented to illustrate the successful application of integrating a geophysical technology with divers when searching for a submerged object. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

PubMed

Adhikari, Badri; Hou, Jie; Cheng, Jianlin

2018-03-01

In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on contact prediction. The first method (MULTICOM-NOVEL) uses only traditional features (sequence profile, secondary structure, and solvent accessibility) with deep learning to predict contacts and serves as a baseline. The second method (MULTICOM-CONSTRUCT) uses our new alignment algorithm to generate deep multiple sequence alignment to derive coevolution-based features, which are integrated by a neural network method to predict contacts. The third method (MULTICOM-CLUSTER) is a consensus combination of the predictions of the first two methods. We evaluated our methods on 94 CASP12 domains. On a subset of 38 free-modeling domains, our methods achieved an average precision of up to 41.7% for top L/5 long-range contact predictions. The comparison of the three methods shows that the quality and effective depth of multiple sequence alignments, coevolution-based features, and machine learning integration of coevolution-based features and traditional features drive the quality of predicted protein contacts. On the full CASP12 dataset, the coevolution-based features alone can improve the average precision from 28.4% to 41.6%, and the machine learning integration of all the features further raises the precision to 56.3%, when top L/5 predicted long-range contacts are evaluated. And the correlation between the precision of contact prediction and the logarithm of the number of effective sequences in alignments is 0.66. © 2017 Wiley Periodicals, Inc.
Multiple network interface core apparatus and method

DOEpatents

Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

2011-04-26

A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.
Ensemble positive unlabeled learning for disease gene identification.

PubMed

Yang, Peng; Li, Xiaoli; Chua, Hon-Nian; Kwoh, Chee-Keong; Ng, See-Kiong

2014-01-01

An increasing number of genes have been experimentally confirmed in recent years as causative genes to various human diseases. The newly available knowledge can be exploited by machine learning methods to discover additional unknown genes that are likely to be associated with diseases. In particular, positive unlabeled learning (PU learning) methods, which require only a positive training set P (confirmed disease genes) and an unlabeled set U (the unknown candidate genes) instead of a negative training set N, have been shown to be effective in uncovering new disease genes in the current scenario. Using only a single source of data for prediction can be susceptible to bias due to incompleteness and noise in the genomic data and a single machine learning predictor prone to bias caused by inherent limitations of individual methods. In this paper, we propose an effective PU learning framework that integrates multiple biological data sources and an ensemble of powerful machine learning classifiers for disease gene identification. Our proposed method integrates data from multiple biological sources for training PU learning classifiers. A novel ensemble-based PU learning method EPU is then used to integrate multiple PU learning classifiers to achieve accurate and robust disease gene predictions. Our evaluation experiments across six disease groups showed that EPU achieved significantly better results compared with various state-of-the-art prediction methods as well as ensemble learning classifiers. Through integrating multiple biological data sources for training and the outputs of an ensemble of PU learning classifiers for prediction, we are able to minimize the potential bias and errors in individual data sources and machine learning algorithms to achieve more accurate and robust disease gene predictions. In the future, our EPU method provides an effective framework to integrate the additional biological and computational resources for better disease gene predictions.
MSblender: A probabilistic approach for integrating peptide identifications from multiple database search engines.

PubMed

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I; Marcotte, Edward M

2011-07-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for every possible PSM and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for most proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses.
MSblender: a probabilistic approach for integrating peptide identifications from multiple database search engines

PubMed Central

Kwon, Taejoon; Choi, Hyungwon; Vogel, Christine; Nesvizhskii, Alexey I.; Marcotte, Edward M.

2011-01-01

Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for all possible PSMs and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for all detected proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses. PMID:21488652
Integrated optics to improve resolution on multiple configuration

NASA Astrophysics Data System (ADS)

Liu, Hua; Ding, Quanxin; Guo, Chunjie; Zhou, Liwei

2015-04-01

Inspired to in order to reveal the structure to improve imaging resolution, further technical requirement is proposed in some areas of the function and influence on the development of multiple configuration. To breakthrough diffraction limit, smart structures are recommended as the most efficient and economical method, while by used to improve the system performance, especially on signal to noise ratio and resolution. Integrated optics were considered in the selection, with which typical multiple configuration, by use the method of simulation experiment. Methodology can change traditional design concept and to develop the application space. Our calculations using multiple matrix transfer method, also the correlative algorithm and full calculations, show the expected beam shaping through system and, in particular, the experimental results will support our argument, which will be reported in the presentation.

integIRTy: a method to identify genes altered in cancer by accounting for multiple mechanisms of regulation using item response theory.

PubMed

Tong, Pan; Coombes, Kevin R

2012-11-15

Identifying genes altered in cancer plays a crucial role in both understanding the mechanism of carcinogenesis and developing novel therapeutics. It is known that there are various mechanisms of regulation that can lead to gene dysfunction, including copy number change, methylation, abnormal expression, mutation and so on. Nowadays, all these types of alterations can be simultaneously interrogated by different types of assays. Although many methods have been proposed to identify altered genes from a single assay, there is no method that can deal with multiple assays accounting for different alteration types systematically. In this article, we propose a novel method, integration using item response theory (integIRTy), to identify altered genes by using item response theory that allows integrated analysis of multiple high-throughput assays. When applied to a single assay, the proposed method is more robust and reliable than conventional methods such as Student's t-test or the Wilcoxon rank-sum test. When used to integrate multiple assays, integIRTy can identify novel-altered genes that cannot be found by looking at individual assay separately. We applied integIRTy to three public cancer datasets (ovarian carcinoma, breast cancer, glioblastoma) for cross-assay type integration which all show encouraging results. The R package integIRTy is available at the web site http://bioinformatics.mdanderson.org/main/OOMPA:Overview. kcoombes@mdanderson.org. Supplementary data are available at Bioinformatics online.
Analysis of the Multiple-Solution Response of a Flexible Rotor Supported on Non-Linear Squeeze Film Dampers

NASA Astrophysics Data System (ADS)

ZHU, C. S.; ROBB, D. A.; EWINS, D. J.

2002-05-01

The multiple-solution response of rotors supported on squeeze film dampers is a typical non-linear phenomenon. The behaviour of the multiple-solution response in a flexible rotor supported on two identical squeeze film dampers with centralizing springs is studied by three methods: synchronous circular centred-orbit motion solution, numerical integration method and slow acceleration method using the assumption of a short bearing and cavitated oil film; the differences of computational results obtained by the three different methods are compared in this paper. It is shown that there are three basic forms for the multiple-solution response in the flexible rotor system supported on the squeeze film dampers, which are the resonant, isolated bifurcation and swallowtail bifurcation multiple solutions. In the multiple-solution speed regions, the rotor motion may be subsynchronous, super-subsynchronous, almost-periodic and even chaotic, besides synchronous circular centred, even if the gravity effect is not considered. The assumption of synchronous circular centred-orbit motion for the journal and rotor around the static deflection line can be used only in some special cases; the steady state numerical integration method is very useful, but time consuming. Using the slow acceleration method, not only can the multiple-solution speed regions be detected, but also the non-synchronous response regions.
Integrated modeling and analysis of the multiple electromechanical couplings for the direct driven feed system in machine tools

NASA Astrophysics Data System (ADS)

Yang, Xiaojun; Lu, Dun; Liu, Hui; Zhao, Wanhua

2018-06-01

The complicated electromechanical coupling phenomena due to different kinds of causes have significant influences on the dynamic precision of the direct driven feed system in machine tools. In this paper, a novel integrated modeling and analysis method of the multiple electromechanical couplings for the direct driven feed system in machine tools is presented. At first, four different kinds of electromechanical coupling phenomena in the direct driven feed system are analyzed systematically. Then a novel integrated modeling and analysis method of the electromechanical coupling which is influenced by multiple factors is put forward. In addition, the effects of multiple electromechanical couplings on the dynamic precision of the feed system and their main influencing factors are compared and discussed, respectively. Finally, the results of modeling and analysis are verified by the experiments. It finds out that multiple electromechanical coupling loops, which are overlapped and influenced by each other, are the main reasons of the displacement fluctuations in the direct driven feed system.
A study of compositional verification based IMA integration method

NASA Astrophysics Data System (ADS)

Huang, Hui; Zhang, Guoquan; Xu, Wanmeng

2018-03-01

The rapid development of avionics systems is driving the application of integrated modular avionics (IMA) systems. But meanwhile it is improving avionics system integration, complexity of system test. Then we need simplify the method of IMA system test. The IMA system supports a module platform that runs multiple applications, and shares processing resources. Compared with federated avionics system, IMA system is difficult to isolate failure. Therefore, IMA system verification will face the critical problem is how to test shared resources of multiple application. For a simple avionics system, traditional test methods are easily realizing to test a whole system. But for a complex system, it is hard completed to totally test a huge and integrated avionics system. Then this paper provides using compositional-verification theory in IMA system test, so that reducing processes of test and improving efficiency, consequently economizing costs of IMA system integration.
Multisignal detecting system of pile integrity testing

NASA Astrophysics Data System (ADS)

Liu, Zuting; Luo, Ying; Yu, Shihai

2002-05-01

The low strain reflection wave method plays a principal rule in the integrating detection of base piles. However, there are some deficiencies with this method. For example, there is a blind area of detection on top of the tested pile; it is difficult to recognize the defects at deep-seated parts of the pile; there is still the planar of 3D domino effect, etc. It is very difficult to solve these problems only with the single-transducer pile integrity testing system. A new multi-signal piles integrity testing system is proposed in this paper, which is able to impulse and collect signals on multiple points on top of the pile. By using the multiple superposition data processing method, the detecting system can effectively restrain the interference and elevate the precision and SNR of pile integrity testing. The system can also be applied to the evaluation of engineering structure health.
Method and systems for collecting data from multiple fields of view

NASA Technical Reports Server (NTRS)

Schwemmer, Geary K. (Inventor)

2002-01-01

Systems and methods for processing light from multiple fields (48, 54, 55) of view without excessive machinery for scanning optical elements. In an exemplary embodiment of the invention, multiple holographic optical elements (41, 42, 43, 44, 45), integrated on a common film (4), diffract and project light from respective fields of view.
Simplifying Differential Equations for Multiscale Feynman Integrals beyond Multiple Polylogarithms.

PubMed

Adams, Luise; Chaubey, Ekta; Weinzierl, Stefan

2017-04-07

In this Letter we exploit factorization properties of Picard-Fuchs operators to decouple differential equations for multiscale Feynman integrals. The algorithm reduces the differential equations to blocks of the size of the order of the irreducible factors of the Picard-Fuchs operator. As a side product, our method can be used to easily convert the differential equations for Feynman integrals which evaluate to multiple polylogarithms to an ϵ form.
Promising Perceptions, Divergent Practices and Barriers to Integrated Malaria Prevention in Wakiso District, Uganda: A Mixed Methods Study

PubMed Central

Musoke, David; Miiro, George; Karani, George; Morris, Keith; Kasasa, Simon; Ndejjo, Rawlance; Nakiyingi-Miiro, Jessica; Guwatudde, David; Musoke, Miph Boses

2015-01-01

Background The World Health Organization recommends use of multiple approaches to control malaria. The integrated approach to malaria prevention advocates the use of several malaria prevention methods in a holistic manner. This study assessed perceptions and practices on integrated malaria prevention in Wakiso district, Uganda. Methods A clustered cross-sectional survey was conducted among 727 households from 29 villages using both quantitative and qualitative methods. Assessment was done on awareness of various malaria prevention methods, potential for use of the methods in a holistic manner, and reasons for dislike of certain methods. Households were classified as using integrated malaria prevention if they used at least two methods. Logistic regression was used to test for factors associated with the use of integrated malaria prevention while adjusting for clustering within villages. Results Participants knew of the various malaria prevention methods in the integrated approach including use of insecticide treated nets (97.5%), removing mosquito breeding sites (89.1%), clearing overgrown vegetation near houses (97.9%), and closing windows and doors early in the evenings (96.4%). If trained, most participants (68.6%) would use all the suggested malaria prevention methods of the integrated approach. Among those who would not use all methods, the main reasons given were there being too many (70.2%) and cost (32.0%). Only 33.0% households were using the integrated approach to prevent malaria. Use of integrated malaria prevention by households was associated with reading newspapers (AOR 0.34; 95% CI 0.22 –0.53) and ownership of a motorcycle/car (AOR 1.75; 95% CI 1.03 – 2.98). Conclusion Although knowledge of malaria prevention methods was high and perceptions on the integrated approach promising, practices on integrated malaria prevention was relatively low. The use of the integrated approach can be improved by promoting use of multiple malaria prevention methods through various communication channels such as mass media. PMID:25837978
Flexible Reporting of Clinical Data

PubMed Central

Andrews, Robert D.

1987-01-01

Two prototype methods have been developed to aid in the presentation of relevant clinical data: 1) an integrated report that displays results from a patient's computer-stored data and also allows manual entry of data, and 2) a graph program that plots results of multiple kinds of tests. These reports provide a flexible means of displaying data to help evaluate patient treatment. The two methods also explore ways of integrating the display of data from multiple components of the Veterans Administration's (VA) Decentralized Hospital Computer Program (DHCP) database.
Systems and methods for integrating ion mobility and ion trap mass spectrometers

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

Ibrahim, Yehia M.; Garimella, Sandilya; Prost, Spencer A.

Described herein are examples of systems and methods for integrating IMS and MS systems. In certain examples, systems and methods for decoding double multiplexed data are described. The systems and methods can also perform multiple refining procedures in order to minimize the demultiplexing artifacts. The systems and methods can be used, for example, for the analysis of proteomic and petroleum samples, where the integration of IMS and high mass resolution are used for accurate assignment of molecular formulae.
Integrative prescreening in analysis of multiple cancer genomic studies

PubMed Central

2012-01-01

Background In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost. Results An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach. Conclusions The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers. PMID:22799431
Using Images, Metaphor, and Hypnosis in Integrating Multiple Personality and Dissociative States: A Review of the Literature.

ERIC Educational Resources Information Center

Crawford, Carrie L.

1990-01-01

Reviews literature on hypnosis, imagery, and metaphor as applied to the treatment and integration of those with multiple personality disorder (MPD) and dissociative states. Considers diagnostic criteria of MPD; explores current theories of etiology and treatment; and suggests specific examples of various clinical methods of treatment using…
Registration and Fusion of Multiple Source Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline

2004-01-01

Earth and Space Science often involve the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, global coverage of an area at multiple resolutions, map updating or validation of new instruments, as well as integration of data provided by multiple instruments carried on multiple platforms, e.g. in spacecraft constellations or fleets of planetary rovers. Our focus is on developing methods to perform fast, accurate and automatic image registration and fusion. General methods for automatic image registration are being reviewed and evaluated. Various choices for feature extraction, feature matching and similarity measurements are being compared, including wavelet-based algorithms, mutual information and statistically robust techniques. Our work also involves studies related to image fusion and investigates dimension reduction and co-kriging for application-dependent fusion. All methods are being tested using several multi-sensor datasets, acquired at EOS Core Sites, and including multiple sensors such as IKONOS, Landsat-7/ETM+, EO1/ALI and Hyperion, MODIS, and SeaWIFS instruments. Issues related to the coregistration of data from the same platform (i.e., AIRS and MODIS from Aqua) or from several platforms of the A-train (i.e., MLS, HIRDLS, OMI from Aura with AIRS and MODIS from Terra and Aqua) will also be considered.
Cosmological perturbation theory using the FFTLog: formalism and connection to QFT loop integrals

NASA Astrophysics Data System (ADS)

Simonović, Marko; Baldauf, Tobias; Zaldarriaga, Matias; Carrasco, John Joseph; Kollmeier, Juna A.

2018-04-01

We present a new method for calculating loops in cosmological perturbation theory. This method is based on approximating a ΛCDM-like cosmology as a finite sum of complex power-law universes. The decomposition is naturally achieved using an FFTLog algorithm. For power-law cosmologies, all loop integrals are formally equivalent to loop integrals of massless quantum field theory. These integrals have analytic solutions in terms of generalized hypergeometric functions. We provide explicit formulae for the one-loop and the two-loop power spectrum and the one-loop bispectrum. A chief advantage of our approach is that the difficult part of the calculation is cosmology independent, need be done only once, and can be recycled for any relevant predictions. Evaluation of standard loop diagrams then boils down to a simple matrix multiplication. We demonstrate the promise of this method for applications to higher multiplicity/loop correlation functions.
Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175
New methods for the numerical integration of ordinary differential equations and their application to the equations of motion of spacecraft

NASA Technical Reports Server (NTRS)

Banyukevich, A.; Ziolkovski, K.

1975-01-01

A number of hybrid methods for solving Cauchy problems are described on the basis of an evaluation of advantages of single and multiple-point numerical integration methods. The selection criterion is the principle of minimizing computer time. The methods discussed include the Nordsieck method, the Bulirsch-Stoer extrapolation method, and the method of recursive Taylor-Steffensen power series.
Development of a modularized two-step (M2S) chromosome integration technique for integration of multiple transcription units in Saccharomyces cerevisiae.

PubMed

Li, Siwei; Ding, Wentao; Zhang, Xueli; Jiang, Huifeng; Bi, Changhao

2016-01-01

Saccharomyces cerevisiae has already been used for heterologous production of fuel chemicals and valuable natural products. The establishment of complicated heterologous biosynthetic pathways in S. cerevisiae became the research focus of Synthetic Biology and Metabolic Engineering. Thus, simple and efficient genomic integration techniques of large number of transcription units are demanded urgently. An efficient DNA assembly and chromosomal integration method was created by combining homologous recombination (HR) in S. cerevisiae and Golden Gate DNA assembly method, designated as modularized two-step (M2S) technique. Two major assembly steps are performed consecutively to integrate multiple transcription units simultaneously. In Step 1, Modularized scaffold containing a head-to-head promoter module and a pair of terminators was assembled with two genes. Thus, two transcription units were assembled with Golden Gate method into one scaffold in one reaction. In Step 2, the two transcription units were mixed with modules of selective markers and integration sites and transformed into S. cerevisiae for assembly and integration. In both steps, universal primers were designed for identification of correct clones. Establishment of a functional β-carotene biosynthetic pathway in S. cerevisiae within 5 days demonstrated high efficiency of this method, and a 10-transcriptional-unit pathway integration illustrated the capacity of this method. Modular design of transcription units and integration elements simplified assembly and integration procedure, and eliminated frequent designing and synthesis of DNA fragments in previous methods. Also, by assembling most parts in Step 1 in vitro, the number of DNA cassettes for homologous integration in Step 2 was significantly reduced. Thus, high assembly efficiency, high integration capacity, and low error rate were achieved.
Integrative Analysis of Prognosis Data on Multiple Cancer Subtypes

PubMed Central

Liu, Jin; Huang, Jian; Zhang, Yawei; Lan, Qing; Rothman, Nathaniel; Zheng, Tongzhang; Ma, Shuangge

2014-01-01

Summary In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is diverse. Examining the similarity and difference in the genetic basis of multiple subtypes of the same cancer can lead to a better understanding of their connections and distinctions. Classic meta-analysis methods analyze each subtype separately and then compare analysis results across subtypes. Integrative analysis methods, in contrast, analyze the raw data on multiple subtypes simultaneously and can outperform meta-analysis methods. In this study, prognosis data on multiple subtypes of the same cancer are analyzed. An AFT (accelerated failure time) model is adopted to describe survival. The genetic basis of multiple subtypes is described using the heterogeneity model, which allows a gene/SNP to be associated with prognosis of some subtypes but not others. A compound penalization method is developed to identify genes that contain important SNPs associated with prognosis. The proposed method has an intuitive formulation and is realized using an iterative algorithm. Asymptotic properties are rigorously established. Simulation shows that the proposed method has satisfactory performance and outperforms a penalization-based meta-analysis method and a regularized thresholding method. An NHL (non-Hodgkin lymphoma) prognosis study with SNP measurements is analyzed. Genes associated with the three major subtypes, namely DLBCL, FL, and CLL/SLL, are identified. The proposed method identifies genes that are different from alternatives and have important implications and satisfactory prediction performance. PMID:24766212
HIV integration sites in latently infected cell lines: evidence of ongoing replication.

PubMed

Symons, Jori; Chopra, Abha; Malatinkova, Eva; De Spiegelaere, Ward; Leary, Shay; Cooper, Don; Abana, Chike O; Rhodes, Ajantha; Rezaei, Simin D; Vandekerckhove, Linos; Mallal, Simon; Lewin, Sharon R; Cameron, Paul U

2017-01-13

Assessing the location and frequency of HIV integration sites in latently infected cells can potentially inform our understanding of how HIV persists during combination antiretroviral therapy. We developed a novel high throughput sequencing method to evaluate HIV integration sites in latently infected cell lines to determine whether there was virus replication or clonal expansion in these cell lines observed as multiple integration events at the same position. We modified a previously reported method using random DNA shearing and PCR to allow for high throughput robotic processing to identify the site and frequency of HIV integration in latently infected cell lines. Latently infected cell lines infected with intact virus demonstrated multiple distinct HIV integration sites (28 different sites in U1, 110 in ACH-2 and 117 in J1.1 per 150,000 cells). In contrast, cell lines infected with replication-incompetent viruses (J-Lat cells) demonstrated single integration sites. Following in vitro passaging of the ACH-2 cell line, we observed a significant increase in the frequency of unique HIV integration sites and there were multiple mutations and large deletions in the proviral DNA. When the ACH-2 cell line was cultured with the integrase inhibitor raltegravir, there was a significant decrease in the number of unique HIV integration sites and a transient increase in the frequency of 2-LTR circles consistent with virus replication in these cells. Cell lines latently infected with intact HIV demonstrated multiple unique HIV integration sites indicating that these cell lines are not clonal and in the ACH-2 cell line there was evidence of low level virus replication. These findings have implications for the use of latently infected cell lines as models of HIV latency and for the use of these cells as standards.
A case study to illustrate the utility of the Aggregate Exposure Pathway and Adverse Outcome Pathway frameworks for integrating human health and ecological data into cumulative risk assessment

EPA Science Inventory

Cumulative risk assessment (CRA) methods, which evaluate the risk of multiple adverse outcomes (AOs) from multiple chemicals, promote the use of a conceptual site model (CSM) to integrate risk from relevant stressors. The Adverse Outcome Pathway (AOP) framework can inform these r...

Integrating Opportunities: Applied Interdisciplinary Research in Undergraduate Geography and Geology Education

ERIC Educational Resources Information Center

Viertel, David C.; Burns, Diane M.

2012-01-01

Unique integrative learning approaches represent a fundamental opportunity for undergraduate students and faculty alike to combine interdisciplinary methods with applied spatial research. Geography and geoscience-related disciplines are particularly well-suited to adapt multiple methods within a holistic and reflective mentored research paradigm.…
Integrated Metrics for Improving the Life Cycle Approach to Assessing Product System Sustainability

EPA Science Inventory

Life cycle approaches are critical for identifying and managing to reduce burdens in the sustainability of product systems. While these methods can indicate potential environmental impacts of a product, current Life Cycle Assessment (LCA) methods fail to integrate the multiple im...
A non-planar two-loop three-point function beyond multiple polylogarithms

NASA Astrophysics Data System (ADS)

von Manteuffel, Andreas; Tancredi, Lorenzo

2017-06-01

We consider the analytic calculation of a two-loop non-planar three-point function which contributes to the two-loop amplitudes for t\\overline{t} production and γγ production in gluon fusion through a massive top-quark loop. All subtopology integrals can be written in terms of multiple polylogarithms over an irrational alphabet and we employ a new method for the integration of the differential equations which does not rely on the rationalization of the latter. The top topology integrals, instead, in spite of the absence of a massive three-particle cut, cannot be evaluated in terms of multiple polylogarithms and require the introduction of integrals over complete elliptic integrals and polylogarithms. We provide one-fold integral representations for the solutions and continue them analytically to all relevant regions of the phase space in terms of real functions, extracting all imaginary parts explicitly. The numerical evaluation of our expressions becomes straightforward in this way.
Smart Phase Tuning in Microwave Photonic Integrated Circuits Toward Automated Frequency Multiplication by Design

NASA Astrophysics Data System (ADS)

Nabavi, N.

2018-07-01

The author investigates the monitoring methods for fine adjustment of the previously proposed on-chip architecture for frequency multiplication and translation of harmonics by design. Digital signal processing (DSP) algorithms are utilized to create an optimized microwave photonic integrated circuit functionality toward automated frequency multiplication. The implemented DSP algorithms are formed on discrete Fourier transform and optimization-based algorithms (Greedy and gradient-based algorithms), which are analytically derived and numerically compared based on the accuracy and speed of convergence criteria.
Unsupervised multiple kernel learning for heterogeneous data integration.

PubMed

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.
Quadrature rules with multiple nodes for evaluating integrals with strong singularities

NASA Astrophysics Data System (ADS)

Milovanovic, Gradimir V.; Spalevic, Miodrag M.

2006-05-01

We present a method based on the Chakalov-Popoviciu quadrature formula of Lobatto type, a rather general case of quadrature with multiple nodes, for approximating integrals defined by Cauchy principal values or by Hadamard finite parts. As a starting point we use the results obtained by L. Gori and E. Santi (cf. On the evaluation of Hilbert transforms by means of a particular class of Turan quadrature rules, Numer. Algorithms 10 (1995), 27-39; Quadrature rules based on s-orthogonal polynomials for evaluating integrals with strong singularities, Oberwolfach Proceedings: Applications and Computation of Orthogonal Polynomials, ISNM 131, Birkhauser, Basel, 1999, pp. 109-119). We generalize their results by using some of our numerical procedures for stable calculation of the quadrature formula with multiple nodes of Gaussian type and proposed methods for estimating the remainder term in such type of quadrature formulae. Numerical examples, illustrations and comparisons are also shown.
Argumentation Based Joint Learning: A Novel Ensemble Learning Approach

PubMed Central

Xu, Junyi; Yao, Li; Li, Le

2015-01-01

Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification. PMID:25966359
Exponential integrators in time-dependent density-functional calculations

NASA Astrophysics Data System (ADS)

Kidd, Daniel; Covington, Cody; Varga, Kálmán

2017-12-01

The integrating factor and exponential time differencing methods are implemented and tested for solving the time-dependent Kohn-Sham equations. Popular time propagation methods used in physics, as well as other robust numerical approaches, are compared to these exponential integrator methods in order to judge the relative merit of the computational schemes. We determine an improvement in accuracy of multiple orders of magnitude when describing dynamics driven primarily by a nonlinear potential. For cases of dynamics driven by a time-dependent external potential, the accuracy of the exponential integrator methods are less enhanced but still match or outperform the best of the conventional methods tested.
Multiple Revolution Solutions for the Perturbed Lambert Problem using the Method of Particular Solutions and Picard Iteration

NASA Astrophysics Data System (ADS)

Woollands, Robyn M.; Read, Julie L.; Probe, Austin B.; Junkins, John L.

2017-12-01

We present a new method for solving the multiple revolution perturbed Lambert problem using the method of particular solutions and modified Chebyshev-Picard iteration. The method of particular solutions differs from the well-known Newton-shooting method in that integration of the state transition matrix (36 additional differential equations) is not required, and instead it makes use of a reference trajectory and a set of n particular solutions. Any numerical integrator can be used for solving two-point boundary problems with the method of particular solutions, however we show that using modified Chebyshev-Picard iteration affords an avenue for increased efficiency that is not available with other step-by-step integrators. We take advantage of the path approximation nature of modified Chebyshev-Picard iteration (nodes iteratively converge to fixed points in space) and utilize a variable fidelity force model for propagating the reference trajectory. Remarkably, we demonstrate that computing the particular solutions with only low fidelity function evaluations greatly increases the efficiency of the algorithm while maintaining machine precision accuracy. Our study reveals that solving the perturbed Lambert's problem using the method of particular solutions with modified Chebyshev-Picard iteration is about an order of magnitude faster compared with the classical shooting method and a tenth-twelfth order Runge-Kutta integrator. It is well known that the solution to Lambert's problem over multiple revolutions is not unique and to ensure that all possible solutions are considered we make use of a reliable preexisting Keplerian Lambert solver to warm start our perturbed algorithm.
Bayesian correlated clustering to integrate multiple datasets

PubMed Central

Kirk, Paul; Griffin, Jim E.; Savage, Richard S.; Ghahramani, Zoubin; Wild, David L.

2012-01-01

Motivation: The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct—but often complementary—information. We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration). MDI can integrate information from a wide range of different datasets and data types simultaneously (including the ability to model time series data explicitly using Gaussian processes). Each dataset is modelled using a Dirichlet-multinomial allocation (DMA) mixture model, with dependencies between these models captured through parameters that describe the agreement among the datasets. Results: Using a set of six artificially constructed time series datasets, we show that MDI is able to integrate a significant number of datasets simultaneously, and that it successfully captures the underlying structural similarity between the datasets. We also analyse a variety of real Saccharomyces cerevisiae datasets. In the two-dataset case, we show that MDI’s performance is comparable with the present state-of-the-art. We then move beyond the capabilities of current approaches and integrate gene expression, chromatin immunoprecipitation–chip and protein–protein interaction data, to identify a set of protein complexes for which genes are co-regulated during the cell cycle. Comparisons to other unsupervised data integration techniques—as well as to non-integrative approaches—demonstrate that MDI is competitive, while also providing information that would be difficult or impossible to extract using other methods. Availability: A Matlab implementation of MDI is available from http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/. Contact: D.L.Wild@warwick.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23047558
Acoustic 3D modeling by the method of integral equations

NASA Astrophysics Data System (ADS)

Malovichko, M.; Khokhlov, N.; Yavich, N.; Zhdanov, M.

2018-02-01

This paper presents a parallel algorithm for frequency-domain acoustic modeling by the method of integral equations (IE). The algorithm is applied to seismic simulation. The IE method reduces the size of the problem but leads to a dense system matrix. A tolerable memory consumption and numerical complexity were achieved by applying an iterative solver, accompanied by an effective matrix-vector multiplication operation, based on the fast Fourier transform (FFT). We demonstrate that, the IE system matrix is better conditioned than that of the finite-difference (FD) method, and discuss its relation to a specially preconditioned FD matrix. We considered several methods of matrix-vector multiplication for the free-space and layered host models. The developed algorithm and computer code were benchmarked against the FD time-domain solution. It was demonstrated that, the method could accurately calculate the seismic field for the models with sharp material boundaries and a point source and receiver located close to the free surface. We used OpenMP to speed up the matrix-vector multiplication, while MPI was used to speed up the solution of the system equations, and also for parallelizing across multiple sources. The practical examples and efficiency tests are presented as well.
A Case Study Application of the Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP) Frameworks to Facilitate the Integration of Human Health and Ecological End Points for Cumulative Risk Assessment (CRA)

EPA Science Inventory

Cumulative risk assessment (CRA) methods promote the use of a conceptual site model (CSM) to apportion exposures and integrate risk from multiple stressors. While CSMs may encompass multiple species, evaluating end points across taxa can be challenging due to data availability an...
Large space antenna communications systems: Integrated Langley Research Center/Jet Propulsion Laboratory development activities. 2: Langley Research Center activities

NASA Technical Reports Server (NTRS)

Cambell, T. G.; Bailey, M. C.; Cockrell, C. R.; Beck, F. B.

1983-01-01

The electromagnetic analysis activities at the Langley Research Center are resulting in efficient and accurate analytical methods for predicting both far- and near-field radiation characteristics of large offset multiple-beam multiple-aperture mesh reflector antennas. The utilization of aperture integration augmented with Geometrical Theory of Diffraction in analyzing the large reflector antenna system is emphasized.
Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

PubMed

Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.
Downscaling remotely sensed imagery using area-to-point cokriging and multiple-point geostatistical simulation

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong

2015-03-01

A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.
Angular width of the Cherenkov radiation with inclusion of multiple scattering

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

Zheng, Jian, E-mail: jzheng@ustc.edu.cn

2016-06-15

Visible Cherenkov radiation can offer a method of the measurement of the velocity of charged particles. The angular width of the radiation is important since it determines the resolution of the velocity measurement. In this article, the angular width of Cherenkov radiation with inclusion of multiple scattering is calculated through the path-integral method, and the analytical expressions are presented. The condition that multiple scattering processes dominate the angular distribution is obtained.
Integrating Multiple Teaching Methods into a General Chemistry Classroom

NASA Astrophysics Data System (ADS)

Francisco, Joseph S.; Nicoll, Gayle; Trautmann, Marcella

1998-02-01

In addition to the traditional lecture format, three other teaching strategies (class discussions, concept maps, and cooperative learning) were incorporated into a freshman level general chemistry course. Student perceptions of their involvement in each of the teaching methods, as well as their perceptions of the utility of each method were used to assess the effectiveness of the integration of the teaching strategies as received by the students. Results suggest that each strategy serves a unique purpose for the students and increased student involvement in the course. These results indicate that the multiple teaching strategies were well received by the students and that all teaching strategies are necessary for students to get the most out of the course.
shinyGISPA: A web application for characterizing phenotype by gene sets using multiple omics data combinations.

PubMed

Dwivedi, Bhakti; Kowalski, Jeanne

2018-01-01

While many methods exist for integrating multi-omics data or defining gene sets, there is no one single tool that defines gene sets based on merging of multiple omics data sets. We present shinyGISPA, an open-source application with a user-friendly web-based interface to define genes according to their similarity in several molecular changes that are driving a disease phenotype. This tool was developed to help facilitate the usability of a previously published method, Gene Integrated Set Profile Analysis (GISPA), among researchers with limited computer-programming skills. The GISPA method allows the identification of multiple gene sets that may play a role in the characterization, clinical application, or functional relevance of a disease phenotype. The tool provides an automated workflow that is highly scalable and adaptable to applications that go beyond genomic data merging analysis. It is available at http://shinygispa.winship.emory.edu/shinyGISPA/.
shinyGISPA: A web application for characterizing phenotype by gene sets using multiple omics data combinations

PubMed Central

Dwivedi, Bhakti

2018-01-01

While many methods exist for integrating multi-omics data or defining gene sets, there is no one single tool that defines gene sets based on merging of multiple omics data sets. We present shinyGISPA, an open-source application with a user-friendly web-based interface to define genes according to their similarity in several molecular changes that are driving a disease phenotype. This tool was developed to help facilitate the usability of a previously published method, Gene Integrated Set Profile Analysis (GISPA), among researchers with limited computer-programming skills. The GISPA method allows the identification of multiple gene sets that may play a role in the characterization, clinical application, or functional relevance of a disease phenotype. The tool provides an automated workflow that is highly scalable and adaptable to applications that go beyond genomic data merging analysis. It is available at http://shinygispa.winship.emory.edu/shinyGISPA/. PMID:29415010
Analysis of methods. [information systems evolution environment

NASA Technical Reports Server (NTRS)

Mayer, Richard J. (Editor); Ackley, Keith A.; Wells, M. Sue; Mayer, Paula S. D.; Blinn, Thomas M.; Decker, Louis P.; Toland, Joel A.; Crump, J. Wesley; Menzel, Christopher P.; Bodenmiller, Charles A.

1991-01-01

Information is one of an organization's most important assets. For this reason the development and maintenance of an integrated information system environment is one of the most important functions within a large organization. The Integrated Information Systems Evolution Environment (IISEE) project has as one of its primary goals a computerized solution to the difficulties involved in the development of integrated information systems. To develop such an environment a thorough understanding of the enterprise's information needs and requirements is of paramount importance. This document is the current release of the research performed by the Integrated Development Support Environment (IDSE) Research Team in support of the IISEE project. Research indicates that an integral part of any information system environment would be multiple modeling methods to support the management of the organization's information. Automated tool support for these methods is necessary to facilitate their use in an integrated environment. An integrated environment makes it necessary to maintain an integrated database which contains the different kinds of models developed under the various methodologies. In addition, to speed the process of development of models, a procedure or technique is needed to allow automatic translation from one methodology's representation to another while maintaining the integrity of both. The purpose for the analysis of the modeling methods included in this document is to examine these methods with the goal being to include them in an integrated development support environment. To accomplish this and to develop a method for allowing intra-methodology and inter-methodology model element reuse, a thorough understanding of multiple modeling methodologies is necessary. Currently the IDSE Research Team is investigating the family of Integrated Computer Aided Manufacturing (ICAM) DEFinition (IDEF) languages IDEF(0), IDEF(1), and IDEF(1x), as well as ENALIM, Entity Relationship, Data Flow Diagrams, and Structure Charts, for inclusion in an integrated development support environment.

Integrated device architectures for electrochromic devices

DOEpatents

Frey, Jonathan Mack; Berland, Brian Spencer

2015-04-21

This disclosure describes systems and methods for creating monolithically integrated electrochromic devices which may be a flexible electrochromic device. Monolithic integration of thin film electrochromic devices may involve the electrical interconnection of multiple individual electrochromic devices through the creation of specific structures such as conductive pathway or insulating isolation trenches.
Our Town Integrated Studies: A Resource.

ERIC Educational Resources Information Center

North Carolina State Dept. of Public Education, Raleigh.

This integrated state curriculum guide was developed by North Carolina fourth grade teachers, principals, and supervisors during a workshop which explored methods of integrating curriculum objectives from multiple instructional areas by using the community as both a resource and a subject of study and by introducing the concept of webbing, an…
Navigating Access and Maintaining Established Practice: Social Studies Teachers' Technology Integration at Three Florida Middle Schools

ERIC Educational Resources Information Center

Sheffield, Caroline

2011-01-01

This mixed methods multiple case study explored middle school social studies teachers' instructional use of digital technology at three suburban middle schools This mixed methods, multiple-case study explored middle school social studies teachers' instructional use of digital technology at three suburban middle schools in a large Florida school…
A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets.

PubMed

Carrig, Madeline M; Manrique-Vallier, Daniel; Ranby, Krista W; Reiter, Jerome P; Hoyle, Rick H

2015-01-01

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches.
A Nonparametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets

PubMed Central

Carrig, Madeline M.; Manrique-Vallier, Daniel; Ranby, Krista W.; Reiter, Jerome P.; Hoyle, Rick H.

2015-01-01

Complex research questions often cannot be addressed adequately with a single data set. One sensible alternative to the high cost and effort associated with the creation of large new data sets is to combine existing data sets containing variables related to the constructs of interest. The goal of the present research was to develop a flexible, broadly applicable approach to the integration of disparate data sets that is based on nonparametric multiple imputation and the collection of data from a convenient, de novo calibration sample. We demonstrate proof of concept for the approach by integrating three existing data sets containing items related to the extent of problematic alcohol use and associations with deviant peers. We discuss both necessary conditions for the approach to work well and potential strengths and weaknesses of the method compared to other data set integration approaches. PMID:26257437
Integrating computational methods to retrofit enzymes to synthetic pathways.

PubMed

Brunk, Elizabeth; Neri, Marilisa; Tavernelli, Ivano; Hatzimanikatis, Vassily; Rothlisberger, Ursula

2012-02-01

Microbial production of desired compounds provides an efficient framework for the development of renewable energy resources. To be competitive to traditional chemistry, one requirement is to utilize the full capacity of the microorganism to produce target compounds with high yields and turnover rates. We use integrated computational methods to generate and quantify the performance of novel biosynthetic routes that contain highly optimized catalysts. Engineering a novel reaction pathway entails addressing feasibility on multiple levels, which involves handling the complexity of large-scale biochemical networks while respecting the critical chemical phenomena at the atomistic scale. To pursue this multi-layer challenge, our strategy merges knowledge-based metabolic engineering methods with computational chemistry methods. By bridging multiple disciplines, we provide an integral computational framework that could accelerate the discovery and implementation of novel biosynthetic production routes. Using this approach, we have identified and optimized a novel biosynthetic route for the production of 3HP from pyruvate. Copyright © 2011 Wiley Periodicals, Inc.
Mixed methods in psychotherapy research: A review of method(ology) integration in psychotherapy science.

PubMed

Bartholomew, Theodore T; Lockard, Allison J

2018-06-13

Mixed methods can foster depth and breadth in psychological research. However, its use remains in development in psychotherapy research. Our purpose was to review the use of mixed methods in psychotherapy research. Thirty-one studies were identified via the PRISMA systematic review method. Using Creswell & Plano Clark's typologies to identify design characteristics, we assessed each study for rigor and how each used mixed methods. Key features of mixed methods designs and these common patterns were identified: (a) integration of clients' perceptions via mixing; (b) understanding group psychotherapy; (c) integrating methods with cases and small samples; (d) analyzing clinical data as qualitative data; and (e) exploring cultural identities in psychotherapy through mixed methods. The review is discussed with respect to the value of integrating multiple data in single studies to enhance psychotherapy research. © 2018 Wiley Periodicals, Inc.
Methods for radiation detection and characterization using a multiple detector probe

DOEpatents

Akers, Douglas William; Roybal, Lyle Gene

2014-11-04

Apparatuses, methods, and systems relating to radiological characterization of environments are disclosed. Multi-detector probes with a plurality of detectors in a common housing may be used to substantially concurrently detect a plurality of different radiation activities and types. Multiple multi-detector probes may be used in a down-hole environment to substantially concurrently detect radioactive activity and contents of a buried waste container. Software may process, analyze, and integrate the data from the different multi-detector probes and the different detector types therein to provide source location and integrated analysis as to the source types and activity in the measured environment. Further, the integrated data may be used to compensate for differential density effects and the effects of radiation shielding materials within the volume being measured.
Achieving Integration in Mixed Methods Designs—Principles and Practices

PubMed Central

Fetters, Michael D; Curry, Leslie A; Creswell, John W

2013-01-01

Mixed methods research offers powerful tools for investigating complex processes and systems in health and health care. This article describes integration principles and practices at three levels in mixed methods research and provides illustrative examples. Integration at the study design level occurs through three basic mixed method designs—exploratory sequential, explanatory sequential, and convergent—and through four advanced frameworks—multistage, intervention, case study, and participatory. Integration at the methods level occurs through four approaches. In connecting, one database links to the other through sampling. With building, one database informs the data collection approach of the other. When merging, the two databases are brought together for analysis. With embedding, data collection and analysis link at multiple points. Integration at the interpretation and reporting level occurs through narrative, data transformation, and joint display. The fit of integration describes the extent the qualitative and quantitative findings cohere. Understanding these principles and practices of integration can help health services researchers leverage the strengths of mixed methods. PMID:24279835
Achieving integration in mixed methods designs-principles and practices.

PubMed

Fetters, Michael D; Curry, Leslie A; Creswell, John W

2013-12-01

Mixed methods research offers powerful tools for investigating complex processes and systems in health and health care. This article describes integration principles and practices at three levels in mixed methods research and provides illustrative examples. Integration at the study design level occurs through three basic mixed method designs-exploratory sequential, explanatory sequential, and convergent-and through four advanced frameworks-multistage, intervention, case study, and participatory. Integration at the methods level occurs through four approaches. In connecting, one database links to the other through sampling. With building, one database informs the data collection approach of the other. When merging, the two databases are brought together for analysis. With embedding, data collection and analysis link at multiple points. Integration at the interpretation and reporting level occurs through narrative, data transformation, and joint display. The fit of integration describes the extent the qualitative and quantitative findings cohere. Understanding these principles and practices of integration can help health services researchers leverage the strengths of mixed methods. © Health Research and Educational Trust.
Module-based construction of plasmids for chromosomal integration of the fission yeast Schizosaccharomyces pombe

PubMed Central

Kakui, Yasutaka; Sunaga, Tomonari; Arai, Kunio; Dodgson, James; Ji, Liang; Csikász-Nagy, Attila; Carazo-Salas, Rafael; Sato, Masamitsu

2015-01-01

Integration of an external gene into a fission yeast chromosome is useful to investigate the effect of the gene product. An easy way to knock-in a gene construct is use of an integration plasmid, which can be targeted and inserted to a chromosome through homologous recombination. Despite the advantage of integration, construction of integration plasmids is energy- and time-consuming, because there is no systematic library of integration plasmids with various promoters, fluorescent protein tags, terminators and selection markers; therefore, researchers are often forced to make appropriate ones through multiple rounds of cloning procedures. Here, we establish materials and methods to easily construct integration plasmids. We introduce a convenient cloning system based on Golden Gate DNA shuffling, which enables the connection of multiple DNA fragments at once: any kind of promoters and terminators, the gene of interest, in combination with any fluorescent protein tag genes and any selection markers. Each of those DNA fragments, called a ‘module’, can be tandemly ligated in the order we desire in a single reaction, which yields a circular plasmid in a one-step manner. The resulting plasmids can be integrated through standard methods for transformation. Thus, these materials and methods help easy construction of knock-in strains, and this will further increase the value of fission yeast as a model organism. PMID:26108218
System and method for integrating and accessing multiple data sources within a data warehouse architecture

DOEpatents

Musick, Charles R [Castro Valley, CA; Critchlow, Terence [Livermore, CA; Ganesh, Madhaven [San Jose, CA; Slezak, Tom [Livermore, CA; Fidelis, Krzysztof [Brentwood, CA

2006-12-19

A system and method is disclosed for integrating and accessing multiple data sources within a data warehouse architecture. The metadata formed by the present method provide a way to declaratively present domain specific knowledge, obtained by analyzing data sources, in a consistent and useable way. Four types of information are represented by the metadata: abstract concepts, databases, transformations and mappings. A mediator generator automatically generates data management computer code based on the metadata. The resulting code defines a translation library and a mediator class. The translation library provides a data representation for domain specific knowledge represented in a data warehouse, including "get" and "set" methods for attributes that call transformation methods and derive a value of an attribute if it is missing. The mediator class defines methods that take "distinguished" high-level objects as input and traverse their data structures and enter information into the data warehouse.
Impact of Instructor Teaching Style and Content Course on Mathematics Anxiety of Preservice Teachers

ERIC Educational Resources Information Center

Van der Sandt, Suriza; O'Brien, Steve

2017-01-01

Integrative-STEM methodologies entail integrating multiple disciplines with active design-centric teaching and learning methods. If math anxiety is prevalent, for teachers or students, then both the level of integration and design thinking may be limited. This quantitative study of 160 preservice teachers investigated how math anxiety was impacted…
Prompted Journal Writing Supports Preservice History Teachers in Drawing on Multiple Knowledge Domains for Designing Learning Tasks

ERIC Educational Resources Information Center

Wäschle, Kristin; Lehmann, Thomas; Brauch, Nicola; Nückles, Matthias

2015-01-01

Becoming a history teacher requires the integration of pedagogical knowledge, pedagogical content knowledge, and content knowledge. Because the integration of knowledge from different disciplines is a complex task, we investigated prompted learning journals as a method to support teacher students' knowledge integration. Fifty-two preservice…
A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjects.

PubMed

Cacha, L A; Parida, S; Dehuri, S; Cho, S-B; Poznanski, R R

2016-12-01

The huge number of voxels in fMRI over time poses a major challenge to for effective analysis. Fast, accurate, and reliable classifiers are required for estimating the decoding accuracy of brain activities. Although machine-learning classifiers seem promising, individual classifiers have their own limitations. To address this limitation, the present paper proposes a method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification for application across multiple subjects. Similarly, the fuzzy integral (FI) approach has been employed as an efficient tool for combining different classifiers. The FI approach led to the development of a classifiers ensemble technique that performs better than any of the single classifier by reducing the misclassification, the bias, and the variance. The proposed method successfully classified the different cognitive states for multiple subjects with high accuracy of classification. Comparison of the performance improvement, while applying ensemble neural networks method, vs. that of the individual neural network strongly points toward the usefulness of the proposed method.
Relations between elliptic multiple zeta values and a special derivation algebra

NASA Astrophysics Data System (ADS)

Broedel, Johannes; Matthes, Nils; Schlotterer, Oliver

2016-04-01

We investigate relations between elliptic multiple zeta values (eMZVs) and describe a method to derive the number of indecomposable elements of given weight and length. Our method is based on representing eMZVs as iterated integrals over Eisenstein series and exploiting the connection with a special derivation algebra. Its commutator relations give rise to constraints on the iterated integrals over Eisenstein series relevant for eMZVs and thereby allow to count the indecomposable representatives. Conversely, the above connection suggests apparently new relations in the derivation algebra. Under https://tools.aei.mpg.de/emzv we provide relations for eMZVs over a wide range of weights and lengths.
Multispectral high-resolution hologram generation using orthographic projection images

NASA Astrophysics Data System (ADS)

Muniraj, I.; Guo, C.; Sheridan, J. T.

2016-08-01

We present a new method of synthesizing a digital hologram of three-dimensional (3D) real-world objects from multiple orthographic projection images (OPI). A high-resolution multiple perspectives of 3D objects (i.e., two dimensional elemental image array) are captured under incoherent white light using synthetic aperture integral imaging (SAII) technique and their OPIs are obtained respectively. The reference beam is then multiplied with the corresponding OPI and integrated to form a Fourier hologram. Eventually, a modified phase retrieval algorithm (GS/HIO) is applied to reconstruct the hologram. The principle is validated experimentally and the results support the feasibility of the proposed method.
A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

NASA Technical Reports Server (NTRS)

Kautzmann, Frank N., III

1988-01-01

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.
Multicultural identity integration and well-being: a qualitative exploration of variations in narrative coherence and multicultural identification

PubMed Central

Yampolsky, Maya A.; Amiot, Catherine E.; de la Sablonnière, Roxane

2013-01-01

Understanding the experiences of multicultural individuals is vital in our diverse populations. Multicultural people often need to navigate the different norms and values associated with their multiple cultural identities. Recent research on multicultural identification has focused on how individuals with multiple cultural groups manage these different identities within the self, and how this process predicts well-being. The current study built on this research by using a qualitative method to examine the process of configuring one's identities within the self. The present study employed three of the four different multiple identity configurations in Amiot et al. (2007) cognitive-developmental model of social identity integration: categorization, where people identify with one of their cultural groups over others; compartmentalization, where individuals maintain multiple, separate identities within themselves; and integration, where people link their multiple cultural identities. Life narratives were used to investigate the relationship between each of these configurations and well-being, as indicated by narrative coherence. It was expected that individuals with integrated cultural identities would report greater narrative coherence than individuals who compartmentalized and categorized their cultural identities. For all twenty-two participants, identity integration was significantly and positively related to narrative coherence, while compartmentalization was significantly and negatively related to narrative coherence. ANOVAs revealed that integrated and categorized participants reported significantly greater narrative coherence than compartmentalized participants. These findings are discussed in light of previous research on multicultural identity integration. PMID:23504407
Multiconstrained gene clustering based on generalized projections

PubMed Central

2010-01-01

Background Gene clustering for annotating gene functions is one of the fundamental issues in bioinformatics. The best clustering solution is often regularized by multiple constraints such as gene expressions, Gene Ontology (GO) annotations and gene network structures. How to integrate multiple pieces of constraints for an optimal clustering solution still remains an unsolved problem. Results We propose a novel multiconstrained gene clustering (MGC) method within the generalized projection onto convex sets (POCS) framework used widely in image reconstruction. Each constraint is formulated as a corresponding set. The generalized projector iteratively projects the clustering solution onto these sets in order to find a consistent solution included in the intersection set that satisfies all constraints. Compared with previous MGC methods, POCS can integrate multiple constraints from different nature without distorting the original constraints. To evaluate the clustering solution, we also propose a new performance measure referred to as Gene Log Likelihood (GLL) that considers genes having more than one function and hence in more than one cluster. Comparative experimental results show that our POCS-based gene clustering method outperforms current state-of-the-art MGC methods. Conclusions The POCS-based MGC method can successfully combine multiple constraints from different nature for gene clustering. Also, the proposed GLL is an effective performance measure for the soft clustering solutions. PMID:20356386

Adaptive method with intercessory feedback control for an intelligent agent

DOEpatents

Goldsmith, Steven Y.

2004-06-22

An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.
On the method of Ermakov and Zolotukhin for multiple integration

NASA Technical Reports Server (NTRS)

Cranley, R.; Patterson, T. N. L.

1971-01-01

The method of Ermakov and Zolotukhin is discussed along with its later developments. By introducing the idea of pseudo-implementation a practical assessment of the method is made. The performance of the method is found to be unimpressive in comparison with a recent regression method.
MetaMeta: integrating metagenome analysis tools to improve taxonomic profiling.

PubMed

Piro, Vitor C; Matschkowski, Marcel; Renard, Bernhard Y

2017-08-14

Many metagenome analysis tools are presently available to classify sequences and profile environmental samples. In particular, taxonomic profiling and binning methods are commonly used for such tasks. Tools available among these two categories make use of several techniques, e.g., read mapping, k-mer alignment, and composition analysis. Variations on the construction of the corresponding reference sequence databases are also common. In addition, different tools provide good results in different datasets and configurations. All this variation creates a complicated scenario to researchers to decide which methods to use. Installation, configuration and execution can also be difficult especially when dealing with multiple datasets and tools. We propose MetaMeta: a pipeline to execute and integrate results from metagenome analysis tools. MetaMeta provides an easy workflow to run multiple tools with multiple samples, producing a single enhanced output profile for each sample. MetaMeta includes a database generation, pre-processing, execution, and integration steps, allowing easy execution and parallelization. The integration relies on the co-occurrence of organisms from different methods as the main feature to improve community profiling while accounting for differences in their databases. In a controlled case with simulated and real data, we show that the integrated profiles of MetaMeta overcome the best single profile. Using the same input data, it provides more sensitive and reliable results with the presence of each organism being supported by several methods. MetaMeta uses Snakemake and has six pre-configured tools, all available at BioConda channel for easy installation (conda install -c bioconda metameta). The MetaMeta pipeline is open-source and can be downloaded at: https://gitlab.com/rki_bioinformatics .
A sampling-based method for ranking protein structural models by integrating multiple scores and features.

PubMed

Shi, Xiaohu; Zhang, Jingfen; He, Zhiquan; Shang, Yi; Xu, Dong

2011-09-01

One of the major challenges in protein tertiary structure prediction is structure quality assessment. In many cases, protein structure prediction tools generate good structural models, but fail to select the best models from a huge number of candidates as the final output. In this study, we developed a sampling-based machine-learning method to rank protein structural models by integrating multiple scores and features. First, features such as predicted secondary structure, solvent accessibility and residue-residue contact information are integrated by two Radial Basis Function (RBF) models trained from different datasets. Then, the two RBF scores and five selected scoring functions developed by others, i.e., Opus-CA, Opus-PSP, DFIRE, RAPDF, and Cheng Score are synthesized by a sampling method. At last, another integrated RBF model ranks the structural models according to the features of sampling distribution. We tested the proposed method by using two different datasets, including the CASP server prediction models of all CASP8 targets and a set of models generated by our in-house software MUFOLD. The test result shows that our method outperforms any individual scoring function on both best model selection, and overall correlation between the predicted ranking and the actual ranking of structural quality.
Parallel/Vector Integration Methods for Dynamical Astronomy

NASA Astrophysics Data System (ADS)

Fukushima, T.

Progress of parallel/vector computers has driven us to develop suitable numerical integrators utilizing their computational power to the full extent while being independent on the size of system to be integrated. Unfortunately, the parallel version of Runge-Kutta type integrators are known to be not so efficient. Recently we developed a parallel version of the extrapolation method (Ito and Fukushima 1997), which allows variable timesteps and still gives an acceleration factor of 3-4 for general problems. While the vector-mode usage of Picard-Chebyshev method (Fukushima 1997a, 1997b) will lead the acceleration factor of order of 1000 for smooth problems such as planetary/satellites orbit integration. The success of multiple-correction PECE mode of time-symmetric implicit Hermitian integrator (Kokubo 1998) seems to enlighten Milankar's so-called "pipelined predictor corrector method", which is expected to lead an acceleration factor of 3-4. We will review these directions and discuss future prospects.
Is the Evaluation of the Students' Values Possible? An Integrated Approach to Determining the Weights of Students' Personal Goals Using Multiple-Criteria Methods

ERIC Educational Resources Information Center

Dadelo, Stanislav; Turskis, Zenonas; Zavadskas, Edmundas Kazimieras; Kacerauskas, Tomas; Dadeliene, Ruta

2016-01-01

To maximize the effectiveness of a decision, it is necessary to support decision-making with integrated methods. It can be assumed that subjective evaluation (considering only absolute values) is only remotely connected with the evaluation of real processes. Therefore, relying solely on these values in process management decision-making would be a…
[Modern research progress of traditional Chinese medicine based on integrative pharmacology].

PubMed

Wang, Ping; Tang, Shi-Huan; Su, Jin; Zhang, Jia-Qi; Cui, Ru-Yi; Xu, Hai-Yu; Yang, Hong-Jun

2018-04-01

Integrative pharmacology (IP) is a discipline that studies the interaction, integration and principle of action of multiple components with the body, emphasizing the integrations of multi-level and multi-link, such as "whole and part", " in vivo and in vitro ", " in vivo process and activity evaluation". After four years of development and practice, the theory and method of IP has received extensive attention and application.In order to better promote the development of IP, this paper systematically reviews the concepts, research contents, research methods and application fields about IP. Copyright© by the Chinese Pharmaceutical Association.
Methods for biological data integration: perspectives and challenges

PubMed Central

Gligorijević, Vladimir; Pržulj, Nataša

2015-01-01

Rapid technological advances have led to the production of different types of biological data and enabled construction of complex networks with various types of interactions between diverse biological entities. Standard network data analysis methods were shown to be limited in dealing with such heterogeneous networked data and consequently, new methods for integrative data analyses have been proposed. The integrative methods can collectively mine multiple types of biological data and produce more holistic, systems-level biological insights. We survey recent methods for collective mining (integration) of various types of networked biological data. We compare different state-of-the-art methods for data integration and highlight their advantages and disadvantages in addressing important biological problems. We identify the important computational challenges of these methods and provide a general guideline for which methods are suited for specific biological problems, or specific data types. Moreover, we propose that recent non-negative matrix factorization-based approaches may become the integration methodology of choice, as they are well suited and accurate in dealing with heterogeneous data and have many opportunities for further development. PMID:26490630
Unlocking Flexibility: Integrated Optimization and Control of Multienergy Systems

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

Dall'Anese, Emiliano; Mancarella, Pierluigi; Monti, Antonello

Electricity, natural gas, water, and dis trict heating/cooling systems are predominantly planned and operated independently. However, it is increasingly recognized that integrated optimization and control of such systems at multiple spatiotemporal scales can bring significant socioeconomic, operational efficiency, and environmental benefits. Accordingly, the concept of the multi-energy system is gaining considerable attention, with the overarching objectives of 1) uncovering fundamental gains (and potential drawbacks) that emerge from the integrated operation of multiple systems and 2) developing holistic yet computationally affordable optimization and control methods that maximize operational benefits, while 3) acknowledging intrinsic interdependencies and quality-of-service requirements for each provider.
An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...
Contact-free heart rate measurement using multiple video data

NASA Astrophysics Data System (ADS)

Hung, Pang-Chan; Lee, Kual-Zheng; Tsai, Luo-Wei

2013-10-01

In this paper, we propose a contact-free heart rate measurement method by analyzing sequential images of multiple video data. In the proposed method, skin-like pixels are firstly detected from multiple video data for extracting the color features. These color features are synchronized and analyzed by independent component analysis. A representative component is finally selected among these independent component candidates to measure the HR, which achieves under 2% deviation on average compared with a pulse oximeter in the controllable environment. The advantages of the proposed method include: 1) it uses low cost and high accessibility camera device; 2) it eases users' discomfort by utilizing contact-free measurement; and 3) it achieves the low error rate and the high stability by integrating multiple video data.
Power control apparatus and methods for electric vehicles

DOEpatents

Gadh, Rajit; Chung, Ching-Yen; Chu, Chi-Cheng; Qiu, Li

2016-03-22

Electric vehicle (EV) charging apparatus and methods are described which allow the sharing of charge current between multiple vehicles connected to a single source of charging energy. In addition, this charge sharing can be performed in a grid-friendly manner by lowering current supplied to EVs when necessary in order to satisfy the needs of the grid, or building operator. The apparatus and methods can be integrated into charging stations or can be implemented with a middle-man approach in which a multiple EV charging box, which includes an EV emulator and multiple pilot signal generation circuits, is coupled to a single EV charge station.
Invited OSU class lecture: An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...
An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on multiple ecosystem services - 4/27/10

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...
Screening of groundwater remedial alternatives for brownfield sites: a comprehensive method integrated MCDA with numerical simulation.

PubMed

Li, Wei; Zhang, Min; Wang, Mingyu; Han, Zhantao; Liu, Jiankai; Chen, Zhezhou; Liu, Bo; Yan, Yan; Liu, Zhu

2018-06-01

Brownfield sites pollution and remediation is an urgent environmental issue worldwide. The screening and assessment of remedial alternatives is especially complex owing to its multiple criteria that involves technique, economy, and policy. To help the decision-makers selecting the remedial alternatives efficiently, the criteria framework conducted by the U.S. EPA is improved and a comprehensive method that integrates multiple criteria decision analysis (MCDA) with numerical simulation is conducted in this paper. The criteria framework is modified and classified into three categories: qualitative, semi-quantitative, and quantitative criteria, MCDA method, AHP-PROMETHEE (analytical hierarchy process-preference ranking organization method for enrichment evaluation) is used to determine the priority ranking of the remedial alternatives and the solute transport simulation is conducted to assess the remedial efficiency. A case study was present to demonstrate the screening method in a brownfield site in Cangzhou, northern China. The results show that the systematic method provides a reliable way to quantify the priority of the remedial alternatives.
Surface albedo from bidirectional reflectance

NASA Technical Reports Server (NTRS)

Ranson, K. J.; Irons, J. R.; Daughtry, C. S. T.

1991-01-01

The validity of integrating over discrete wavelength bands is examined to estimate total shortwave bidirectional reflectance of vegetated and bare soil surfaces. Methods for estimating albedo from multiple angle, discrete wavelength band radiometer measurements are studied. These methods include a numerical integration technique and the integration of an empirically derived equation for bidirectional reflectance. It is concluded that shortwave albedos estimated through both techniques agree favorably with the independent pyranometer measurements. Absolute rms errors are found to be 0.5 percent or less for both grass sod and bare soil surfaces.
Trust-region based return mapping algorithm for implicit integration of elastic-plastic constitutive models

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

Lester, Brian; Scherzinger, William

2017-01-19

Here, a new method for the solution of the non-linear equations forming the core of constitutive model integration is proposed. Specifically, the trust-region method that has been developed in the numerical optimization community is successfully modified for use in implicit integration of elastic-plastic models. Although attention here is restricted to these rate-independent formulations, the proposed approach holds substantial promise for adoption with models incorporating complex physics, multiple inelastic mechanisms, and/or multiphysics. As a first step, the non-quadratic Hosford yield surface is used as a representative case to investigate computationally challenging constitutive models. The theory and implementation are presented, discussed, andmore » compared to other common integration schemes. Multiple boundary value problems are studied and used to verify the proposed algorithm and demonstrate the capabilities of this approach over more common methodologies. Robustness and speed are then investigated and compared to existing algorithms. Through these efforts, it is shown that the utilization of a trust-region approach leads to superior performance versus a traditional closest-point projection Newton-Raphson method and comparable speed and robustness to a line search augmented scheme.« less
Trust-region based return mapping algorithm for implicit integration of elastic-plastic constitutive models

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

Lester, Brian T.; Scherzinger, William M.

2017-01-19

A new method for the solution of the non-linear equations forming the core of constitutive model integration is proposed. Specifically, the trust-region method that has been developed in the numerical optimization community is successfully modified for use in implicit integration of elastic-plastic models. Although attention here is restricted to these rate-independent formulations, the proposed approach holds substantial promise for adoption with models incorporating complex physics, multiple inelastic mechanisms, and/or multiphysics. As a first step, the non-quadratic Hosford yield surface is used as a representative case to investigate computationally challenging constitutive models. The theory and implementation are presented, discussed, and comparedmore » to other common integration schemes. Multiple boundary value problems are studied and used to verify the proposed algorithm and demonstrate the capabilities of this approach over more common methodologies. Robustness and speed are then investigated and compared to existing algorithms. As a result through these efforts, it is shown that the utilization of a trust-region approach leads to superior performance versus a traditional closest-point projection Newton-Raphson method and comparable speed and robustness to a line search augmented scheme.« less
Multiple Frequency Contrast Source Inversion Method for Vertical Electromagnetic Profiling: 2D Simulation Results and Analyses

NASA Astrophysics Data System (ADS)

Li, Jinghe; Song, Linping; Liu, Qing Huo

2016-02-01

A simultaneous multiple frequency contrast source inversion (CSI) method is applied to reconstructing hydrocarbon reservoir targets in a complex multilayered medium in two dimensions. It simulates the effects of a salt dome sedimentary formation in the context of reservoir monitoring. In this method, the stabilized biconjugate-gradient fast Fourier transform (BCGS-FFT) algorithm is applied as a fast solver for the 2D volume integral equation for the forward computation. The inversion technique with CSI combines the efficient FFT algorithm to speed up the matrix-vector multiplication and the stable convergence of the simultaneous multiple frequency CSI in the iteration process. As a result, this method is capable of making quantitative conductivity image reconstruction effectively for large-scale electromagnetic oil exploration problems, including the vertical electromagnetic profiling (VEP) survey investigated here. A number of numerical examples have been demonstrated to validate the effectiveness and capacity of the simultaneous multiple frequency CSI method for a limited array view in VEP.
Effective quadrature formula in solving linear integro-differential equations of order two

NASA Astrophysics Data System (ADS)

Eshkuvatov, Z. K.; Kammuji, M.; Long, N. M. A. Nik; Yunus, Arif A. M.

2017-08-01

In this note, we solve general form of Fredholm-Volterra integro-differential equations (IDEs) of order 2 with boundary condition approximately and show that proposed method is effective and reliable. Initially, IDEs is reduced into integral equation of the third kind by using standard integration techniques and identity between multiple and single integrals then truncated Legendre series are used to estimate the unknown function. For the kernel integrals, we have applied Gauss-Legendre quadrature formula and collocation points are chosen as the roots of the Legendre polynomials. Finally, reduce the integral equations of the third kind into the system of algebraic equations and Gaussian elimination method is applied to get approximate solutions. Numerical examples and comparisons with other methods reveal that the proposed method is very effective and dominated others in many cases. General theory of existence of the solution is also discussed.

Graph-Based Weakly-Supervised Methods for Information Extraction & Integration

ERIC Educational Resources Information Center

Talukdar, Partha Pratim

2010-01-01

The variety and complexity of potentially-related data resources available for querying--webpages, databases, data warehouses--has been growing ever more rapidly. There is a growing need to pose integrative queries "across" multiple such sources, exploiting foreign keys and other means of interlinking data to merge information from diverse…
Mathematical Methods for Physics and Engineering Third Edition Paperback Set

NASA Astrophysics Data System (ADS)

Riley, Ken F.; Hobson, Mike P.; Bence, Stephen J.

2006-06-01

Prefaces; 1. Preliminary algebra; 2. Preliminary calculus; 3. Complex numbers and hyperbolic functions; 4. Series and limits; 5. Partial differentiation; 6. Multiple integrals; 7. Vector algebra; 8. Matrices and vector spaces; 9. Normal modes; 10. Vector calculus; 11. Line, surface and volume integrals; 12. Fourier series; 13. Integral transforms; 14. First-order ordinary differential equations; 15. Higher-order ordinary differential equations; 16. Series solutions of ordinary differential equations; 17. Eigenfunction methods for differential equations; 18. Special functions; 19. Quantum operators; 20. Partial differential equations: general and particular; 21. Partial differential equations: separation of variables; 22. Calculus of variations; 23. Integral equations; 24. Complex variables; 25. Application of complex variables; 26. Tensors; 27. Numerical methods; 28. Group theory; 29. Representation theory; 30. Probability; 31. Statistics; Index.
Network-based drug discovery by integrating systems biology and computational technologies

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768
Measuring the degree of integration for an integrated service network

PubMed Central

Ye, Chenglin; Browne, Gina; Grdisa, Valerie S; Beyene, Joseph; Thabane, Lehana

2012-01-01

Background Integration involves the coordination of services provided by autonomous agencies and improves the organization and delivery of multiple services for target patients. Current measures generally do not distinguish between agencies’ perception and expectation. We propose a method for quantifying the agencies’ service integration. Using the data from the Children’s Treatment Network (CTN), we aimed to measure the degree of integration for the CTN agencies in York and Simcoe. Theory and methods We quantified the integration by the agreement between perceived and expected levels of involvement and calculated four scores from different perspectives for each agency. We used the average score to measure the global network integration and examined the sensitivity of the global score. Results Most agencies’ integration scores were <65%. As measured by the agreement between every other agency’s perception and expectation, the overall integration of CTN in Simcoe and York was 44% (95% CI: 39%–49%) and 52% (95% CI: 48%–56%), respectively. The sensitivity analysis showed that the global scores were robust. Conclusion Our method extends existing measures of integration and possesses a good extent of validity. We can also apply the method in monitoring improvement and linking integration with other outcomes. PMID:23593050
System and method for integrating hazard-based decision making tools and processes

DOEpatents

Hodgin, C Reed [Westminster, CO

2012-03-20

A system and method for inputting, analyzing, and disseminating information necessary for identified decision-makers to respond to emergency situations. This system and method provides consistency and integration among multiple groups, and may be used for both initial consequence-based decisions and follow-on consequence-based decisions. The system and method in a preferred embodiment also provides tools for accessing and manipulating information that are appropriate for each decision-maker, in order to achieve more reasoned and timely consequence-based decisions. The invention includes processes for designing and implementing a system or method for responding to emergency situations.
Integrability of the coupled cubic-quintic complex Ginzburg-Landau equations and multiple-soliton solutions via mathematical methods

NASA Astrophysics Data System (ADS)

Selima, Ehab S.; Seadawy, Aly R.; Yao, Xiaohua; Essa, F. A.

2018-02-01

This paper is devoted to study the (1+1)-dimensional coupled cubic-quintic complex Ginzburg-Landau equations (cc-qcGLEs) with complex coefficients. This equation can be used to describe the nonlinear evolution of slowly varying envelopes of periodic spatial-temporal patterns in a convective binary fluid. Dispersion relation and properties of cc-qcGLEs are constructed. Painlevé analysis is used to check the integrability of cc-qcGLEs and to establish the Bäcklund transformation form. New traveling wave solutions and a general form of multiple-soliton solutions of cc-qcGLEs are obtained via the Bäcklund transformation and simplest equation method with Bernoulli, Riccati and Burgers’ equations as simplest equations.
Formulation of an explicit-multiple-time-step time integration method for use in a global primitive equation grid model

NASA Technical Reports Server (NTRS)

Chao, W. C.

1982-01-01

With appropriate modifications, a recently proposed explicit-multiple-time-step scheme (EMTSS) is incorporated into the UCLA model. In this scheme, the linearized terms in the governing equations that generate the gravity waves are split into different vertical modes. Each mode is integrated with an optimal time step, and at periodic intervals these modes are recombined. The other terms are integrated with a time step dictated by the CFL condition for low-frequency waves. This large time step requires a special modification of the advective terms in the polar region to maintain stability. Test runs for 72 h show that EMTSS is a stable, efficient and accurate scheme.
Evaluating quality of patient care communication in integrated care settings: a mixed method approach.

PubMed

Gulmans, J; Vollenbroek-Hutten, M M R; Van Gemert-Pijnen, J E W C; Van Harten, W H

2007-10-01

Owing to the involvement of multiple professionals from various institutions, integrated care settings are prone to suboptimal patient care communication. To assure continuity, communication gaps should be identified for targeted improvement initiatives. However, available assessment methods are often one-sided evaluations not appropriate for integrated care settings. We developed an evaluation approach that takes into account the multiple communication links and evaluation perspectives inherent to these settings. In this study, we describe this approach, using the integrated care setting of Cerebral Palsy as illustration. The approach follows a three-step mixed design in which the results of each step are used to mark out the subsequent step's focus. The first step patient questionnaire aims to identify quality gaps experienced by patients, comparing their expectancies and experiences with respect to patient-professional and inter-professional communication. Resulting gaps form the input of in-depth interviews with a subset of patients to evaluate underlying factors of ineffective communication. Resulting factors form the input of the final step's focus group meetings with professionals to corroborate and complete the findings. By combining methods, the presented approach aims to minimize limitations inherent to the application of single methods. The comprehensiveness of the approach enables its applicability in various integrated care settings. Its sequential design allows for in-depth evaluation of relevant quality gaps. Further research is needed to evaluate the approach's feasibility in practice. In our subsequent study, we present the results of the approach in the integrated care setting of children with Cerebral Palsy in three Dutch care regions.
DEVELOPMENT OF TOOLS TO ASSESS THE EFFECTS OF INDIVIDUAL, POPULATION, AND SPATIAL LEVELS: INTEGRATED ASSESSMENT OF MULTIPLE STRESSORS ON PISCIVOROUS BIRDS

EPA Science Inventory

The goal of the US Environmental Protection Agency's National Health and Environmental Research Laboratory's Wildlife Risk Assessment program is to develop scientifically valid methods to assess risks to wildlife and aquatic organisms from multiple stressors. To this end, the Loo...
Making the Cut in Gifted Selection: Score Combination Rules and Their Impact on Program Diversity

ERIC Educational Resources Information Center

Lakin, Joni M.

2018-01-01

The recommendation of using "multiple measures" is common in policy guidelines for gifted and talented assessment systems. However, the integration of multiple test scores in a system that uses cut-scores requires choosing between different methods of combining quantitative scores. Past research has indicated that OR combination rules…
Integrating Genetic, Psychopharmacological and Neuroimaging Studies: A Converging Methods Approach to Understanding the Neurobiology of ADHD

ERIC Educational Resources Information Center

Durston, Sarah; Konrad, Kerstin

2007-01-01

This paper aims to illustrate how combining multiple approaches can inform us about the neurobiology of ADHD. Converging evidence from genetic, psychopharmacological and functional neuroimaging studies has implicated dopaminergic fronto-striatal circuitry in ADHD. However, while the observation of converging evidence from multiple vantage points…
A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.
Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

PubMed Central

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419
Integration of virtual and real scenes within an integral 3D imaging environment

NASA Astrophysics Data System (ADS)

Ren, Jinsong; Aggoun, Amar; McCormick, Malcolm

2002-11-01

The Imaging Technologies group at De Montfort University has developed an integral 3D imaging system, which is seen as the most likely vehicle for 3D television avoiding psychological effects. To create real fascinating three-dimensional television programs, a virtual studio that performs the task of generating, editing and integrating the 3D contents involving virtual and real scenes is required. The paper presents, for the first time, the procedures, factors and methods of integrating computer-generated virtual scenes with real objects captured using the 3D integral imaging camera system. The method of computer generation of 3D integral images, where the lens array is modelled instead of the physical camera is described. In the model each micro-lens that captures different elemental images of the virtual scene is treated as an extended pinhole camera. An integration process named integrated rendering is illustrated. Detailed discussion and deep investigation are focused on depth extraction from captured integral 3D images. The depth calculation method from the disparity and the multiple baseline method that is used to improve the precision of depth estimation are also presented. The concept of colour SSD and its further improvement in the precision is proposed and verified.
A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.
The SAGE Model of Social Psychological Research.

PubMed

Power, Séamus A; Velez, Gabriel; Qadafi, Ahmad; Tennant, Joseph

2018-05-01

We propose a SAGE model for social psychological research. Encapsulated in our acronym is a proposal to have a synthetic approach to social psychological research, in which qualitative methods are augmentative to quantitative ones, qualitative methods can be generative of new experimental hypotheses, and qualitative methods can capture experiences that evade experimental reductionism. We remind social psychological researchers that psychology was founded in multiple methods of investigation at multiple levels of analysis. We discuss historical examples and our own research as contemporary examples of how a SAGE model can operate in part or as an integrated whole. The implications of our model are discussed.
Monolithic integration of multiple wavelength vertical-cavity surface-emitting lasers by mask molecular beam epitaxy

NASA Astrophysics Data System (ADS)

Saito, Hideaki; Ogura, Ichiro; Sugimoto, Yoshimasa; Kasahara, Kenichi

1995-05-01

The monolithic incorporation and performance of vertical-cavity surface-emitting lasers (VCSELs) emitting at two distinct wavelengths, which were suited for application to wavelength division multiplexing (WDM) systems were reported. The monolithic integration of two-wavelength VCSEL arrays was achieved by using mask molecular beam epitaxy. This method can generate arrays that have the desired integration area size and wavelength separation.
Towards establishing a human fecal contamination index in microbial source tracking

EPA Science Inventory

There have been significant advances in development of PCR-based methods to detect source associated DNA sequences (markers), but method evaluation has focused on performance with individual challenge samples. Little attention has been given to integration of multiple samples fro...
Integrating Multiple Data Sources for Combinatorial Marker Discovery: A Study in Tumorigenesis.

PubMed

Bandyopadhyay, Sanghamitra; Mallik, Saurav

2018-01-01

Identification of combinatorial markers from multiple data sources is a challenging task in bioinformatics. Here, we propose a novel computational framework for identifying significant combinatorial markers ( s) using both gene expression and methylation data. The gene expression and methylation data are integrated into a single continuous data as well as a (post-discretized) boolean data based on their intrinsic (i.e., inverse) relationship. A novel combined score of methylation and expression data (viz., ) is introduced which is computed on the integrated continuous data for identifying initial non-redundant set of genes. Thereafter, (maximal) frequent closed homogeneous genesets are identified using a well-known biclustering algorithm applied on the integrated boolean data of the determined non-redundant set of genes. A novel sample-based weighted support ( ) is then proposed that is consecutively calculated on the integrated boolean data of the determined non-redundant set of genes in order to identify the non-redundant significant genesets. The top few resulting genesets are identified as potential s. Since our proposed method generates a smaller number of significant non-redundant genesets than those by other popular methods, the method is much faster than the others. Application of the proposed technique on an expression and a methylation data for Uterine tumor or Prostate Carcinoma produces a set of significant combination of markers. We expect that such a combination of markers will produce lower false positives than individual markers.
Student Solution Manual for Mathematical Methods for Physics and Engineering Third Edition

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2006-03-01

Preface; 1. Preliminary algebra; 2. Preliminary calculus; 3. Complex numbers and hyperbolic functions; 4. Series and limits; 5. Partial differentiation; 6. Multiple integrals; 7. Vector algebra; 8. Matrices and vector spaces; 9. Normal modes; 10. Vector calculus; 11. Line, surface and volume integrals; 12. Fourier series; 13. Integral transforms; 14. First-order ordinary differential equations; 15. Higher-order ordinary differential equations; 16. Series solutions of ordinary differential equations; 17. Eigenfunction methods for differential equations; 18. Special functions; 19. Quantum operators; 20. Partial differential equations: general and particular; 21. Partial differential equations: separation of variables; 22. Calculus of variations; 23. Integral equations; 24. Complex variables; 25. Application of complex variables; 26. Tensors; 27. Numerical methods; 28. Group theory; 29. Representation theory; 30. Probability; 31. Statistics.

methylPipe and compEpiTools: a suite of R packages for the integrative analysis of epigenomics data.

PubMed

Kishore, Kamal; de Pretis, Stefano; Lister, Ryan; Morelli, Marco J; Bianchi, Valerio; Amati, Bruno; Ecker, Joseph R; Pelizzola, Mattia

2015-09-29

Numerous methods are available to profile several epigenetic marks, providing data with different genome coverage and resolution. Large epigenomic datasets are then generated, and often combined with other high-throughput data, including RNA-seq, ChIP-seq for transcription factors (TFs) binding and DNase-seq experiments. Despite the numerous computational tools covering specific steps in the analysis of large-scale epigenomics data, comprehensive software solutions for their integrative analysis are still missing. Multiple tools must be identified and combined to jointly analyze histone marks, TFs binding and other -omics data together with DNA methylation data, complicating the analysis of these data and their integration with publicly available datasets. To overcome the burden of integrating various data types with multiple tools, we developed two companion R/Bioconductor packages. The former, methylPipe, is tailored to the analysis of high- or low-resolution DNA methylomes in several species, accommodating (hydroxy-)methyl-cytosines in both CpG and non-CpG sequence context. The analysis of multiple whole-genome bisulfite sequencing experiments is supported, while maintaining the ability of integrating targeted genomic data. The latter, compEpiTools, seamlessly incorporates the results obtained with methylPipe and supports their integration with other epigenomics data. It provides a number of methods to score these data in regions of interest, leading to the identification of enhancers, lncRNAs, and RNAPII stalling/elongation dynamics. Moreover, it allows a fast and comprehensive annotation of the resulting genomic regions, and the association of the corresponding genes with non-redundant GeneOntology terms. Finally, the package includes a flexible method based on heatmaps for the integration of various data types, combining annotation tracks with continuous or categorical data tracks. methylPipe and compEpiTools provide a comprehensive Bioconductor-compliant solution for the integrative analysis of heterogeneous epigenomics data. These packages are instrumental in providing biologists with minimal R skills a complete toolkit facilitating the analysis of their own data, or in accelerating the analyses performed by more experienced bioinformaticians.
Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

NASA Technical Reports Server (NTRS)

Lo, Ching F.

1999-01-01

The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.
Evaluating Feynman integrals by the hypergeometry

NASA Astrophysics Data System (ADS)

Feng, Tai-Fu; Chang, Chao-Hsi; Chen, Jian-Bin; Gu, Zhi-Hua; Zhang, Hai-Bin

2018-02-01

The hypergeometric function method naturally provides the analytic expressions of scalar integrals from concerned Feynman diagrams in some connected regions of independent kinematic variables, also presents the systems of homogeneous linear partial differential equations satisfied by the corresponding scalar integrals. Taking examples of the one-loop B0 and massless C0 functions, as well as the scalar integrals of two-loop vacuum and sunset diagrams, we verify our expressions coinciding with the well-known results of literatures. Based on the multiple hypergeometric functions of independent kinematic variables, the systems of homogeneous linear partial differential equations satisfied by the mentioned scalar integrals are established. Using the calculus of variations, one recognizes the system of linear partial differential equations as stationary conditions of a functional under some given restrictions, which is the cornerstone to perform the continuation of the scalar integrals to whole kinematic domains numerically with the finite element methods. In principle this method can be used to evaluate the scalar integrals of any Feynman diagrams.
Impact of Integrated Teaching Sessions for Comprehensive Learning and Rational Pharmacotherapeutics for Medical Undergraduates

PubMed Central

Ambwani, Sneha; Vegada, Bhavisha; Sidhu, Rimple; Charan, Jaykaran

2017-01-01

Background: It is postulated that integrated teaching method may enhance retention of the knowledge and clinical applicability of the basic sciences as compared to the didactic method. Aim: The present study was undertaken to compare the integrated teaching method with the didactic method for the learning ability and clinical applicability of the basic sciences. Materials and Methods: The 2nd year MBBS students were divided into two groups randomly. The study was conducted into two stages. In the first stage, conventional didactic lectures on hypertension (HT) were delivered to one group and multidisciplinary integrated teaching to another group. For the second stage, diabetes mellitus groups were swapped. Retention of the knowledge between the groups were assessed through a multiple choice questions (MCQ) test. Feedback of the students and faculty was obtained on a 5 point Likert scale. For the comparison, student's data were regrouped into four groups, i.e., integrated HT, didactic HT, integrated diabetes and didactic diabetes. Results: There was no significant difference of MCQ score between integrated HT, didactic HT, and integrated diabetes group. However, the score obtained in didactic diabetes was significantly more (P = 0.00) than other groups. Majority of the students favored integrated teaching for clinical application of basic science and learning of the skill for the future clinical practice. Faculties considered integrated method as a useful method and suggested frequent use of this method. Conclusion: There was no clear difference in knowledge acquisition; however, the students and faculties favored integrated teaching method in the feedback questionnaire. PMID:29344460
Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework.

PubMed

Zhou, Ronggang; Chan, Alan H S

2017-01-01

In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim rely heavily on human judgment about the various attributes of a product, but often fail to take into account of the inherent uncertainties in these judgments in the evaluation process. This paper presents a universal method of usability evaluation by combining the analytic hierarchical process (AHP) and the fuzzy evaluation method. By integrating multiple sources of uncertain information during product usability evaluation, the method proposed here aims to derive an index that is structured hierarchically in terms of the three usability components of effectiveness, efficiency, and user satisfaction of a product. With consideration of the theoretical basis of fuzzy evaluation, a two-layer comprehensive evaluation index was first constructed. After the membership functions were determined by an expert panel, the evaluation appraisals were computed by using the fuzzy comprehensive evaluation technique model to characterize fuzzy human judgments. Then with the use of AHP, the weights of usability components were elicited from these experts. Compared to traditional usability evaluation methods, the major strength of the fuzzy method is that it captures the fuzziness and uncertainties in human judgments and provides an integrated framework that combines the vague judgments from multiple stages of a product evaluation process.
Digital processing of array seismic recordings

USGS Publications Warehouse

Ryall, Alan; Birtill, John

1962-01-01

This technical letter contains a brief review of the operations which are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these operations (the "UK Method" and multiple correlation). Examples are presented of analyses by the several techniques on array recordings which were obtained by the U.S. Geological Survey during chemical and nuclear explosions in the western United States. Seismograms are synthesized using actual noise and Pn-signal recordings, such that the signal-to-noise ratio, onset time and velocity of the signal are predetermined for the synthetic record. These records are then analyzed by summation, cross-multiplication, multiple correlation and the UK technique, and the results are compared. For all of the examples presented, analysis by the non-linear techniques of multiple correlation and cross-multiplication of the traces on an array recording are preferred to analyses by the linear operations involved in summation and the UK Method.
Using a Multifaceted Approach to Working With Children Who Have Differences in Sensory Processing and Integration

PubMed Central

Glennon, Tara J.; Ausderau, Karla; Bendixen, Roxanna M.; Kuhaneck, Heather Miller; Pfeiffer, Beth; Watling, Renee; Wilkinson, Kimberly; Bodison, Stefanie C.

2017-01-01

Pediatric occupational therapy practitioners frequently provide interventions for children with differences in sensory processing and integration. Confusion exists regarding how best to intervene with these children and about how to describe and document methods. Some practitioners hold the misconception that Ayres Sensory Integration intervention is the only approach that can and should be used with this population. The issue is that occupational therapy practitioners must treat the whole client in varied environments; to do so effectively, multiple approaches to intervention often are required. This article presents a framework for conceptualizing interventions for children with differences in sensory processing and integration that incorporates multiple evidence-based approaches. To best meet the needs of the children and families seeking occupational therapy services, interventions must be focused on participation and should be multifaceted. PMID:28218599
Using Commercially available Tools for multi-faceted health assessment: Data Integration Lessons Learned

PubMed Central

Wilamowska, Katarzyna; Le, Thai; Demiris, George; Thompson, Hilaire

2013-01-01

Health monitoring data collected from multiple available intake devices provide a rich resource to support older adult health and wellness. Though large amounts of data can be collected, there is currently a lack of understanding on integration of these various data sources using commercially available products. This article describes an inexpensive approach to integrating data from multiple sources from a recently completed pilot project that assessed older adult wellness, and demonstrates challenges and benefits in pursuing data integration using commercially available products. The data in this project were sourced from a) electronically captured participant intake surveys, and existing commercial software output for b) vital signs and c) cognitive function. All the software used for data integration in this project was freeware and was chosen because of its ease of comprehension by novice database users. The methods and results of this approach provide a model for researchers with similar data integration needs to easily replicate this effort at a low cost. PMID:23728444
Multiple-image hiding using super resolution reconstruction in high-frequency domains

NASA Astrophysics Data System (ADS)

Li, Xiao-Wei; Zhao, Wu-Xiang; Wang, Jun; Wang, Qiong-Hua

2017-12-01

In this paper, a robust multiple-image hiding method using the computer-generated integral imaging and the modified super-resolution reconstruction algorithm is proposed. In our work, the host image is first transformed into frequency domains by cellular automata (CA), to assure the quality of the stego-image, the secret images are embedded into the CA high-frequency domains. The proposed method has the following advantages: (1) robustness to geometric attacks because of the memory-distributed property of elemental images, (2) increasing quality of the reconstructed secret images as the scheme utilizes the modified super-resolution reconstruction algorithm. The simulation results show that the proposed multiple-image hiding method outperforms other similar hiding methods and is robust to some geometric attacks, e.g., Gaussian noise and JPEG compression attacks.
Progress in the Visualization and Mining of Chemical and Target Spaces.

PubMed

Medina-Franco, José L; Aguayo-Ortiz, Rodrigo

2013-12-01

Chemogenomics is a growing field that aims to integrate the chemical and target spaces. As part of a multi-disciplinary effort to achieve this goal, computational methods initially developed to visualize the chemical space of compound collections and mine single-target structure-activity relationships, are being adapted to visualize and mine complex relationships in chemogenomics data sets. Similarly, the growing evidence that clinical effects are many times due to the interaction of single or multiple drugs with multiple targets, is encouraging the development of novel methodologies that are integrated in multi-target drug discovery endeavors. Herein we review advances in the development and application of approaches to generate visual representations of chemical space with particular emphasis on methods that aim to explore and uncover relationships between chemical and target spaces. Also, progress in the data mining of the structure-activity relationships of sets of compounds screened across multiple targets are discussed in light of the concept of activity landscape modeling. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Adhesive Defect Monitoring of Glass Fiber Epoxy Plate Using an Impedance-Based Non-Destructive Testing Method for Multiple Structures

PubMed Central

Na, Wongi S.; Baek, Jongdae

2017-01-01

The emergence of composite materials has revolutionized the approach to building engineering structures. With the number of applications for composites increasing every day, maintaining structural integrity is of utmost importance. For composites, adhesive bonding is usually the preferred choice over the mechanical fastening method, and monitoring for delamination is an essential factor in the field of composite materials. In this study, a non-destructive method known as the electromechanical impedance method is used with an approach of monitoring multiple areas by specifying certain frequency ranges to correspond to a certain test specimen. Experiments are conducted using various numbers of stacks created by attaching glass fiber epoxy composite plates onto one another, and two different debonding damage types are introduced to evaluate the performance of the multiple monitoring electromechanical impedance method. PMID:28629194
Conjugate-Gradient Algorithms For Dynamics Of Manipulators

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1993-01-01

Algorithms for serial and parallel computation of forward dynamics of multiple-link robotic manipulators by conjugate-gradient method developed. Parallel algorithms have potential for speedup of computations on multiple linked, specialized processors implemented in very-large-scale integrated circuits. Such processors used to stimulate dynamics, possibly faster than in real time, for purposes of planning and control.
Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...
A Multiple Case Study of Verbal Short-Term Memory in Velo-Cardio-Facial Syndrome

ERIC Educational Resources Information Center

Majerus, S.; Glaser, B.; Van der Linden, M.; Eliez, S.

2006-01-01

Background: Velo-cardio-facial syndrome (VCFS, 22q 11.2 deletion) is characterized by severely delayed language development. The current study explored the integrity of verbal short-term memory (STM), a cognitive function critically involved in language development, in eight children with VCFS. Methods: Using a multiple case study design, we…
Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.
Handling missing rows in multi-omics data integration: multiple imputation in multiple factor analysis framework.

PubMed

Voillet, Valentin; Besse, Philippe; Liaubet, Laurence; San Cristobal, Magali; González, Ignacio

2016-10-03

In omics data integration studies, it is common, for a variety of reasons, for some individuals to not be present in all data tables. Missing row values are challenging to deal with because most statistical methods cannot be directly applied to incomplete datasets. To overcome this issue, we propose a multiple imputation (MI) approach in a multivariate framework. In this study, we focus on multiple factor analysis (MFA) as a tool to compare and integrate multiple layers of information. MI involves filling the missing rows with plausible values, resulting in M completed datasets. MFA is then applied to each completed dataset to produce M different configurations (the matrices of coordinates of individuals). Finally, the M configurations are combined to yield a single consensus solution. We assessed the performance of our method, named MI-MFA, on two real omics datasets. Incomplete artificial datasets with different patterns of missingness were created from these data. The MI-MFA results were compared with two other approaches i.e., regularized iterative MFA (RI-MFA) and mean variable imputation (MVI-MFA). For each configuration resulting from these three strategies, the suitability of the solution was determined against the true MFA configuration obtained from the original data and a comprehensive graphical comparison showing how the MI-, RI- or MVI-MFA configurations diverge from the true configuration was produced. Two approaches i.e., confidence ellipses and convex hulls, to visualize and assess the uncertainty due to missing values were also described. We showed how the areas of ellipses and convex hulls increased with the number of missing individuals. A free and easy-to-use code was proposed to implement the MI-MFA method in the R statistical environment. We believe that MI-MFA provides a useful and attractive method for estimating the coordinates of individuals on the first MFA components despite missing rows. MI-MFA configurations were close to the true configuration even when many individuals were missing in several data tables. This method takes into account the uncertainty of MI-MFA configurations induced by the missing rows, thereby allowing the reliability of the results to be evaluated.
Wave excitation at Lindblad resonances using the method of multiple scales

NASA Astrophysics Data System (ADS)

Horák, Jiří

2017-12-01

In this note, the method of multiple scales is adopted to the problem of excitation of non–axisymmetric acoustic waves in vertically integrated disk by tidal gravitational fields. We derive a formula describing a waveform of exited wave that is uniformly valid in a whole disk as long as only a single Lindblad resonance is present. Our formalism is subsequently applied to two classical problems: trapped p–mode oscillations in relativistic accretion disks and the excitation of waves in infinite disks.
Real object-based 360-degree integral-floating display using multiple depth camera

NASA Astrophysics Data System (ADS)

Erdenebat, Munkh-Uchral; Dashdavaa, Erkhembaatar; Kwon, Ki-Chul; Wu, Hui-Ying; Yoo, Kwan-Hee; Kim, Young-Seok; Kim, Nam

2015-03-01

A novel 360-degree integral-floating display based on the real object is proposed. The general procedure of the display system is similar with conventional 360-degree integral-floating displays. Unlike previously presented 360-degree displays, the proposed system displays the 3D image generated from the real object in 360-degree viewing zone. In order to display real object in 360-degree viewing zone, multiple depth camera have been utilized to acquire the depth information around the object. Then, the 3D point cloud representations of the real object are reconstructed according to the acquired depth information. By using a special point cloud registration method, the multiple virtual 3D point cloud representations captured by each depth camera are combined as single synthetic 3D point cloud model, and the elemental image arrays are generated for the newly synthesized 3D point cloud model from the given anamorphic optic system's angular step. The theory has been verified experimentally, and it shows that the proposed 360-degree integral-floating display can be an excellent way to display real object in the 360-degree viewing zone.
Integrated analysis of miRNA and mRNA expression data identifies multiple miRNAs regulatory networks for the tumorigenesis of colorectal cancer.

PubMed

Xu, Peng; Wang, Junhua; Sun, Bo; Xiao, Zhongdang

2018-06-15

Investigating the potential biological function of differential changed genes through integrating multiple omics data including miRNA and mRNA expression profiles, is always hot topic. However, how to evaluate the repression effect on target genes integrating miRNA and mRNA expression profiles are not fully solved. In this study, we provide an analyzing method by integrating both miRNAs and mRNAs expression data simultaneously. Difference analysis was adopted based on the repression score, then significantly repressed mRNAs were screened out by DEGseq. Pathway analysis for the significantly repressed mRNAs shows that multiple pathways such as MAPK signaling pathway, TGF-beta signaling pathway and so on, may correlated to the colorectal cancer(CRC). Focusing on the MAPK signaling pathway, a miRNA-mRNA network that centering the cell fate genes was constructed. Finally, the miRNA-mRNAs that potentially important in the CRC carcinogenesis were screened out and scored by impact index. Copyright © 2018 Elsevier B.V. All rights reserved.
Simplified computational methods for elastic and elastic-plastic fracture problems

NASA Technical Reports Server (NTRS)

Atluri, Satya N.

1992-01-01

An overview is given of some of the recent (1984-1991) developments in computational/analytical methods in the mechanics of fractures. Topics covered include analytical solutions for elliptical or circular cracks embedded in isotropic or transversely isotropic solids, with crack faces being subjected to arbitrary tractions; finite element or boundary element alternating methods for two or three dimensional crack problems; a 'direct stiffness' method for stiffened panels with flexible fasteners and with multiple cracks; multiple site damage near a row of fastener holes; an analysis of cracks with bonded repair patches; methods for the generation of weight functions for two and three dimensional crack problems; and domain-integral methods for elastic-plastic or inelastic crack mechanics.

The Integration of Children with Disabilities into Regular Schools. A Naturalistic Study. Stage 2 Report.

ERIC Educational Resources Information Center

Center, Yola; And Others

The study used a multiple case study method to investigate the quality of the educational and social experiences of elementary-level and secondary-level children with disabilities currently integrated within the Australian regular school system. This second stage of the study used for its sample 23 children with intellectual disabilities, 18 with…
A multiple-feature and multiple-kernel scene segmentation algorithm for humanoid robot.

PubMed

Liu, Zhi; Xu, Shuqiong; Zhang, Yun; Chen, Chun Lung Philip

2014-11-01

This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method.
The SAGE Model of Social Psychological Research

PubMed Central

Power, Séamus A.; Velez, Gabriel; Qadafi, Ahmad; Tennant, Joseph

2018-01-01

We propose a SAGE model for social psychological research. Encapsulated in our acronym is a proposal to have a synthetic approach to social psychological research, in which qualitative methods are augmentative to quantitative ones, qualitative methods can be generative of new experimental hypotheses, and qualitative methods can capture experiences that evade experimental reductionism. We remind social psychological researchers that psychology was founded in multiple methods of investigation at multiple levels of analysis. We discuss historical examples and our own research as contemporary examples of how a SAGE model can operate in part or as an integrated whole. The implications of our model are discussed. PMID:29361241
Adapting the Quebecois method for assessing implementation to the French National Alzheimer Plan 2008–2012: lessons for gerontological services integration

PubMed Central

Somme, Dominique; Trouvé, Hélène; Perisset, Catherine; Corvol, Aline; Ankri, Joël; Saint-Jean, Olivier; de Stampa, Matthieu

2014-01-01

Introduction Many countries face ageing-related demographic and epidemiological challenges, notably neurodegenerative disorders, due to the multiple care services they require, thereby pleading for a more integrated system of care. The integrated Quebecois method issued from the Programme of Research to Integrate Services for the Maintenance of Autonomy inspired a French pilot experiment and the National Alzheimer Plan 2008–2012. Programme of Research to Integrate Services for the Maintenance of Autonomy method implementation was rated with an evaluation grid adapted to assess its successive degrees of completion. Discussion The approaching end of the president's term led to the method's institutionalization (2011–2012), before the implementation study ended. When the government changed, the study was interrupted. The results extracted from that ‘lost’ study (presented herein) have, nonetheless, ‘found’ some key lessons. Key lessons/conclusion It was possible to implement a Quebecois integrated-care method in France. We describe the lessons and pitfalls encountered in adapting this evaluation tool. This process is necessarily multidisciplinary and requires a test phase. A simple tool for quantitative assessment of integration was obtained. The first assessment of the tool was unsatisfactory but requires further studies. In the meantime, we recommend using mixed methodologies to assess the services integration level. PMID:24959112
Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework

PubMed Central

Zhou, Ronggang; Chan, Alan H. S.

2016-01-01

BACKGROUND: In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim rely heavily on human judgment about the various attributes of a product, but often fail to take into account of the inherent uncertainties in these judgments in the evaluation process. OBJECTIVE: This paper presents a universal method of usability evaluation by combining the analytic hierarchical process (AHP) and the fuzzy evaluation method. By integrating multiple sources of uncertain information during product usability evaluation, the method proposed here aims to derive an index that is structured hierarchically in terms of the three usability components of effectiveness, efficiency, and user satisfaction of a product. METHODS: With consideration of the theoretical basis of fuzzy evaluation, a two-layer comprehensive evaluation index was first constructed. After the membership functions were determined by an expert panel, the evaluation appraisals were computed by using the fuzzy comprehensive evaluation technique model to characterize fuzzy human judgments. Then with the use of AHP, the weights of usability components were elicited from these experts. RESULTS AND CONCLUSIONS: Compared to traditional usability evaluation methods, the major strength of the fuzzy method is that it captures the fuzziness and uncertainties in human judgments and provides an integrated framework that combines the vague judgments from multiple stages of a product evaluation process. PMID:28035943
Seven gene deletions in seven days: Fast generation of Escherichia coli strains tolerant to acetate and osmotic stress

PubMed Central

Jensen, Sheila I.; Lennen, Rebecca M.; Herrgård, Markus J.; Nielsen, Alex T.

2015-01-01

Generation of multiple genomic alterations is currently a time consuming process. Here, a method was established that enables highly efficient and simultaneous deletion of multiple genes in Escherichia coli. A temperature sensitive plasmid containing arabinose inducible lambda Red recombineering genes and a rhamnose inducible flippase recombinase was constructed to facilitate fast marker-free deletions. To further speed up the procedure, we integrated the arabinose inducible lambda Red recombineering genes and the rhamnose inducible FLP into the genome of E. coli K-12 MG1655. This system enables growth at 37 °C, thereby facilitating removal of integrated antibiotic cassettes and deletion of additional genes in the same day. Phosphorothioated primers were demonstrated to enable simultaneous deletions during one round of electroporation. Utilizing these methods, we constructed strains in which four to seven genes were deleted in E. coli W and E. coli K-12. The growth rate of an E. coli K-12 quintuple deletion strain was significantly improved in the presence of high concentrations of acetate and NaCl. In conclusion, we have generated a method that enables efficient and simultaneous deletion of multiple genes in several E. coli variants. The method enables deletion of up to seven genes in as little as seven days. PMID:26643270
The Use of Mixed Methods for Therapeutic Massage Research

PubMed Central

Porcino, Antony Joseph; Verhoef, Marja J.

2010-01-01

Mixed methods research is the integration of quantitative and qualitative components in a research project. Whether you are reading or designing a mixed methods research project, it is important to be familiar with both qualitative and quantitative research methods and the specific purposes for which they are brought together in a study: triangulation, complementarity, expansion, initiation, or development. In addition, decisions need to be made about the sequencing and the priority or importance of each qualitative and quantitative component relative to the other components, and the point or points at which the various qualitative and quantitative components will be integrated. Mixed methods research is increasingly being recognized for its ability to bring multiple points of view to a research project, taking advantage of the strengths of each of the quantitative and qualitative components to explain or resolve complex phenomena or results. This ability becomes critical when complex healing systems such as therapeutic massage are being studied. Complex healing systems may have multiple physiologic effects, often reflected in changes throughout the patient’s body. Additionally, the patient’s experience of the treatment may be an important outcome. PMID:21589698
Improved FFT-based numerical inversion of Laplace transforms via fast Hartley transform algorithm

NASA Technical Reports Server (NTRS)

Hwang, Chyi; Lu, Ming-Jeng; Shieh, Leang S.

1991-01-01

The disadvantages of numerical inversion of the Laplace transform via the conventional fast Fourier transform (FFT) are identified and an improved method is presented to remedy them. The improved method is based on introducing a new integration step length Delta(omega) = pi/mT for trapezoidal-rule approximation of the Bromwich integral, in which a new parameter, m, is introduced for controlling the accuracy of the numerical integration. Naturally, this method leads to multiple sets of complex FFT computations. A new inversion formula is derived such that N equally spaced samples of the inverse Laplace transform function can be obtained by (m/2) + 1 sets of N-point complex FFT computations or by m sets of real fast Hartley transform (FHT) computations.
Multilevel metallization method for fabricating a metal oxide semiconductor device

NASA Technical Reports Server (NTRS)

Hollis, B. R., Jr.; Feltner, W. R.; Bouldin, D. L.; Routh, D. E. (Inventor)

1978-01-01

An improved method is described of constructing a metal oxide semiconductor device having multiple layers of metal deposited by dc magnetron sputtering at low dc voltages and low substrate temperatures. The method provides multilevel interconnections and cross over between individual circuit elements in integrated circuits without significantly reducing the reliability or seriously affecting the yield.
Integration of multi-omics data for integrative gene regulatory network inference.

PubMed

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun; Kang, Mingon

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called 'multi-omics data', that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN's capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed.
Integration of multi-omics data for integrative gene regulatory network inference

PubMed Central

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called ‘multi-omics data’, that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN’s capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed. PMID:29354189
Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 Elsevier B.V. All rights reserved.
Software for the Integration of Multiomics Experiments in Bioconductor.

PubMed

Ramos, Marcel; Schiffer, Lucas; Re, Angela; Azhar, Rimsha; Basunia, Azfar; Rodriguez, Carmen; Chan, Tiffany; Chapman, Phil; Davis, Sean R; Gomez-Cabrero, David; Culhane, Aedin C; Haibe-Kains, Benjamin; Hansen, Kasper D; Kodali, Hanish; Louis, Marie S; Mer, Arvind S; Riester, Markus; Morgan, Martin; Carey, Vince; Waldron, Levi

2017-11-01

Multiomics experiments are increasingly commonplace in biomedical research and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multiomics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide the unrestricted multiple 'omics data for each cancer tissue in The Cancer Genome Atlas as ready-to-analyze MultiAssayExperiment objects and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable, and reproducible statistical analysis of multiomics data and enhances data science applications of multiple omics datasets. Cancer Res; 77(21); e39-42. ©2017 AACR . ©2017 American Association for Cancer Research.
Iterative integral parameter identification of a respiratory mechanics model.

PubMed

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Integral imaging with multiple image planes using a uniaxial crystal plate.

PubMed

Park, Jae-Hyeung; Jung, Sungyong; Choi, Heejin; Lee, Byoungho

2003-08-11

Integral imaging has been attracting much attention recently for its several advantages such as full parallax, continuous view-points, and real-time full-color operation. However, the thickness of the displayed three-dimensional image is limited to relatively small value due to the degradation of the image resolution. In this paper, we propose a method to provide observers with enhanced perception of the depth without severe resolution degradation by the use of the birefringence of a uniaxial crystal plate. The proposed integral imaging system can display images integrated around three central depth planes by dynamically altering the polarization and controlling both elemental images and dynamic slit array mask accordingly. We explain the principle of the proposed method and verify it experimentally.
Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition

PubMed Central

2017-01-01

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively. PMID:28817094
Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition.

PubMed

Choi, Hyo-Rim; Kim, TaeYong

2017-08-17

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user's location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively.
Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

PubMed

Li, Yan

2017-05-25

The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.
Integrating Case Topics in Medical School Curriculum to Enhance Multiple Skill Learning: Using Fetal Alcohol Spectrum Disorders as an Exemplary Case

ERIC Educational Resources Information Center

Paley, Blair; O'Connor, Mary J.; Baillie, Susan J.; Guiton, Gretchen; Stuber, Margaret L.

2009-01-01

Objectives: This article describes the use of fetal alcohol spectrum disorders (FASDs) as a theme to connect the learning of basic neurosciences with clinical applications across the age span within a systems-based, integrated curricular structure that emphasizes problem-based learning. Methods: In collaboration with the Centers for Disease…
Toward the Development of Integrative Risk-Adjusted Measures of Quality Using Large Clinical Data Bases: The Case of Anesthesia Services.

ERIC Educational Resources Information Center

Fleming, Steven T.

1992-01-01

The concept of risk-adjusted measures of quality is discussed, and a methodology is proposed for risk-adjusting and integrating multiple adverse outcomes of anesthesia services into measures for quality assurance and quality improvement programs. Although designed for a new anesthesiology database, the methods should apply to other health…

Integrating GIS Technology With Forest Management And Habitat Assessment Efforts On Our National Forests

Treesearch

Joan M. Nichols; S. Arif Husain; Christos Papadas

2000-01-01

Research was conducted on a section of the Superior National Forest to develop and examine potential methods or approaches that may be used to integrate non-timber resources in multiple-use planning. An indicator species for old-growth conifer forests, pine marten (Martes americana), was chosen to examine potential conflicts between specific forest management practices...
Evaluating ICT Integration in Turkish K-12 Schools through Teachers' Views

ERIC Educational Resources Information Center

Aydin, Mehmet Kemal; Gürol, Mehmet; Vanderlinde, Ruben

2016-01-01

The current study aims to explore ICT integration in Turkish K-12 schools purposively selected as a representation of F@tih and non-F@tih public schools together with a private school. A convergent mixed methods design was employed with a multiple case strategy as such it will enable to make casewise comparisons. The quantitative data was…
A fast and high performance multiple data integration algorithm for identifying human disease genes

PubMed Central

2015-01-01

Background Integrating multiple data sources is indispensable in improving disease gene identification. It is not only due to the fact that disease genes associated with similar genetic diseases tend to lie close with each other in various biological networks, but also due to the fact that gene-disease associations are complex. Although various algorithms have been proposed to identify disease genes, their prediction performances and the computational time still should be further improved. Results In this study, we propose a fast and high performance multiple data integration algorithm for identifying human disease genes. A posterior probability of each candidate gene associated with individual diseases is calculated by using a Bayesian analysis method and a binary logistic regression model. Two prior probability estimation strategies and two feature vector construction methods are developed to test the performance of the proposed algorithm. Conclusions The proposed algorithm is not only generated predictions with high AUC scores, but also runs very fast. When only a single PPI network is employed, the AUC score is 0.769 by using F2 as feature vectors. The average running time for each leave-one-out experiment is only around 1.5 seconds. When three biological networks are integrated, the AUC score using F3 as feature vectors increases to 0.830, and the average running time for each leave-one-out experiment takes only about 12.54 seconds. It is better than many existing algorithms. PMID:26399620
Hierarchical modeling and robust synthesis for the preliminary design of large scale complex systems

NASA Astrophysics Data System (ADS)

Koch, Patrick Nathan

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: (1) Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis, (2) Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration, and (3) Noise modeling techniques for implementing robust preliminary design when approximate models are employed. The method developed and associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system; the turbofan system-level problem is partitioned into engine cycle and configuration design and a compressor module is integrated for more detailed subsystem-level design exploration, improving system evaluation.
Perceptions and Use of Technology to Support Older Adults with Multimorbidity.

PubMed

Murphy, Emma; Doyle, Julie; Hannigan, Caoimhe; Smith, Suzanne; Kuiper, Janneke; Jacobs, An; Hoogerwerf, Evert-Jan; Desideri, Lorenzo; Fiordelmondo, Valentina; Maluccelli, Lorenza; Brady, Anne-Marie; Dinsmore, John

2017-01-01

Digital technologies hold great potential to improve and advance home based integrated care for older people living with multiple chronic health conditions. In this paper, we present the results of a user requirement study for a planned digital integrated care system, based on the experiences and needs of key stakeholders. We present rich, multi-stakeholder, qualitative data on the perceptions and use of technology among older people with multiple chronic health conditions and their key support actors. We have outlined our future work for the design of the system, which will involve continuous stakeholder engagement through a user-centred co-design method.
Method for Visually Integrating Multiple Data Acquisition Technologies for Real Time and Retrospective Analysis

NASA Technical Reports Server (NTRS)

Bogart, Edward H. (Inventor); Pope, Alan T. (Inventor)

2000-01-01

A system for display on a single video display terminal of multiple physiological measurements is provided. A subject is monitored by a plurality of instruments which feed data to a computer programmed to receive data, calculate data products such as index of engagement and heart rate, and display the data in a graphical format simultaneously on a single video display terminal. In addition live video representing the view of the subject and the experimental setup may also be integrated into the single data display. The display may be recorded on a standard video tape recorder for retrospective analysis.
Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation

NASA Technical Reports Server (NTRS)

Burken, John J.; Lu, Ping; Wu, Zheng-Lu; Bahm, Cathy

2001-01-01

Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the fight body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.
Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework

PubMed Central

Talluto, Matthew V.; Boulangeat, Isabelle; Ameztegui, Aitor; Aubin, Isabelle; Berteaux, Dominique; Butler, Alyssa; Doyon, Frédérik; Drever, C. Ronnie; Fortin, Marie-Josée; Franceschini, Tony; Liénard, Jean; McKenney, Dan; Solarik, Kevin A.; Strigul, Nikolay; Thuiller, Wilfried; Gravel, Dominique

2016-01-01

Aim Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. Location Eastern North America (as an example). Methods Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple (Acer saccharum), an abundant tree native to eastern North America. Results For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. Main conclusions We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi-source and multi-scale data into ecological decision-making. PMID:27499698
Great Basin Integrated Landscape Monitoring Pilot Summary Report

USGS Publications Warehouse

Finn, Sean P.; Kitchell, Kate; Baer, Lori Anne; Bedford, David R.; Brooks, Matthew L.; Flint, Alan L.; Flint, Lorraine E.; Matchett, J.R.; Mathie, Amy; Miller, David M.; Pilliod, David S.; Torregrosa, Alicia; Woodward, Andrea

2010-01-01

The Great Basin Integrated Landscape Monitoring Pilot project (GBILM) was one of four regional pilots to implement the U.S. Geological Survey (USGS) Science Thrust on Integrated Landscape Monitoring (ILM) whose goal was to observe, understand, and predict landscape change and its implications on natural resources at multiple spatial and temporal scales and address priority natural resource management and policy issues. The Great Basin is undergoing rapid environmental change stemming from interactions among global climate trends, increasing human populations, expanding and accelerating land and water uses, invasive species, and altered fire regimes. GBLIM tested concepts and developed tools to store and analyze monitoring data, understand change at multiple scales, and forecast landscape change. The GBILM endeavored to develop and test a landscape-level monitoring approach in the Great Basin that integrates USGS disciplines, addresses priority management questions, catalogs and uses existing monitoring data, evaluates change at multiple scales, and contributes to development of regional monitoring strategies. GBILM functioned as an integrative team from 2005 to 2010, producing more than 35 science and data management products that addressed pressing ecosystem drivers and resource management agency needs in the region. This report summarizes the approaches and methods of this interdisciplinary effort, identifies and describes the products generated, and provides lessons learned during the project.
An integrated GIS-based data model for multimodal urban public transportation analysis and management

NASA Astrophysics Data System (ADS)

Chen, Shaopei; Tan, Jianjun; Ray, C.; Claramunt, C.; Sun, Qinqin

2008-10-01

Diversity is one of the main characteristics of transportation data collected from multiple sources or formats, which can be extremely complex and disparate. Moreover, these multimodal transportation data are usually characterised by spatial and temporal properties. Multimodal transportation network data modelling involves both an engineering and research domain that has attracted the design of a number of spatio-temporal data models in the geographic information system (GIS). However, the application of these specific models to multimodal transportation network is still a challenging task. This research addresses this challenge from both integrated multimodal data organization and object-oriented modelling perspectives, that is, how a complex urban transportation network should be organized, represented and modeled appropriately when considering a multimodal point of view, and using object-oriented modelling method. We proposed an integrated GIS-based data model for multimodal urban transportation network that lays a foundation to enhance the multimodal transportation network analysis and management. This modelling method organizes and integrates multimodal transit network data, and supports multiple representations for spatio-temporal objects and relationship as both visual and graphic views. The data model is expressed by using a spatio-temporal object-oriented modelling method, i.e., the unified modelling language (UML) extended to spatial and temporal plug-in for visual languages (PVLs), which provides an essential support to the spatio-temporal data modelling for transportation GIS.
3D noise-resistant segmentation and tracking of unknown and occluded objects using integral imaging

NASA Astrophysics Data System (ADS)

Aloni, Doron; Jung, Jae-Hyun; Yitzhaky, Yitzhak

2017-10-01

Three dimensional (3D) object segmentation and tracking can be useful in various computer vision applications, such as: object surveillance for security uses, robot navigation, etc. We present a method for 3D multiple-object tracking using computational integral imaging, based on accurate 3D object segmentation. The method does not employ object detection by motion analysis in a video as conventionally performed (such as background subtraction or block matching). This means that the movement properties do not significantly affect the detection quality. The object detection is performed by analyzing static 3D image data obtained through computational integral imaging With regard to previous works that used integral imaging data in such a scenario, the proposed method performs the 3D tracking of objects without prior information about the objects in the scene, and it is found efficient under severe noise conditions.
Nonstationary EO/IR Clutter Suppression and Dim Object Tracking

DTIC Science & Technology

2010-01-01

Brown, A., and Brown, J., Enhanced Algorithms for EO /IR Electronic Stabilization, Clutter Suppression, and Track - Before - Detect for Multiple Low...estimation-suppression and nonlinear filtering-based multiple-object track - before - detect . These algorithms are suitable for integration into...In such cases, it is imperative to develop efficient real or near-real time tracking before detection methods. This paper continues the work started
Concordant integrative gene set enrichment analysis of multiple large-scale two-sample expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2014-01-01

Gene set enrichment analysis (GSEA) is an important approach to the analysis of coordinate expression changes at a pathway level. Although many statistical and computational methods have been proposed for GSEA, the issue of a concordant integrative GSEA of multiple expression data sets has not been well addressed. Among different related data sets collected for the same or similar study purposes, it is important to identify pathways or gene sets with concordant enrichment. We categorize the underlying true states of differential expression into three representative categories: no change, positive change and negative change. Due to data noise, what we observe from experiments may not indicate the underlying truth. Although these categories are not observed in practice, they can be considered in a mixture model framework. Then, we define the mathematical concept of concordant gene set enrichment and calculate its related probability based on a three-component multivariate normal mixture model. The related false discovery rate can be calculated and used to rank different gene sets. We used three published lung cancer microarray gene expression data sets to illustrate our proposed method. One analysis based on the first two data sets was conducted to compare our result with a previous published result based on a GSEA conducted separately for each individual data set. This comparison illustrates the advantage of our proposed concordant integrative gene set enrichment analysis. Then, with a relatively new and larger pathway collection, we used our method to conduct an integrative analysis of the first two data sets and also all three data sets. Both results showed that many gene sets could be identified with low false discovery rates. A consistency between both results was also observed. A further exploration based on the KEGG cancer pathway collection showed that a majority of these pathways could be identified by our proposed method. This study illustrates that we can improve detection power and discovery consistency through a concordant integrative analysis of multiple large-scale two-sample gene expression data sets.
Combination of High-density Microelectrode Array and Patch Clamp Recordings to Enable Studies of Multisynaptic Integration.

PubMed

Jäckel, David; Bakkum, Douglas J; Russell, Thomas L; Müller, Jan; Radivojevic, Milos; Frey, Urs; Franke, Felix; Hierlemann, Andreas

2017-04-20

We present a novel, all-electric approach to record and to precisely control the activity of tens of individual presynaptic neurons. The method allows for parallel mapping of the efficacy of multiple synapses and of the resulting dynamics of postsynaptic neurons in a cortical culture. For the measurements, we combine an extracellular high-density microelectrode array, featuring 11'000 electrodes for extracellular recording and stimulation, with intracellular patch-clamp recording. We are able to identify the contributions of individual presynaptic neurons - including inhibitory and excitatory synaptic inputs - to postsynaptic potentials, which enables us to study dendritic integration. Since the electrical stimuli can be controlled at microsecond resolution, our method enables to evoke action potentials at tens of presynaptic cells in precisely orchestrated sequences of high reliability and minimum jitter. We demonstrate the potential of this method by evoking short- and long-term synaptic plasticity through manipulation of multiple synaptic inputs to a specific neuron.
Integrating semantic information into multiple kernels for protein-protein interaction extraction from biomedical literatures.

PubMed

Li, Lishuang; Zhang, Panpan; Zheng, Tianfu; Zhang, Hongying; Jiang, Zhenchao; Huang, Degen

2014-01-01

Protein-Protein Interaction (PPI) extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were basically ignored. In this paper, we propose a multiple-kernel learning-based approach to extract PPIs, combining the feature-based kernel, tree kernel and semantic kernel. Particularly, we extend the shortest path-enclosed tree kernel (SPT) by a dynamic extended strategy to retrieve the richer syntactic information. Our semantic kernel calculates the protein-protein pair similarity and the context similarity based on two semantic resources: WordNet and Medical Subject Heading (MeSH). We evaluate our method with Support Vector Machine (SVM) and achieve an F-score of 69.40% and an AUC of 92.00%, which show that our method outperforms most of the state-of-the-art systems by integrating semantic information.
Integrated argument-based inquiry with multiple representation approach to promote scientific argumentation skill

NASA Astrophysics Data System (ADS)

Suminar, Iin; Muslim, Liliawati, Winny

2017-05-01

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

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278
Design of a Multi-Sensor Cooperation Travel Environment Perception System for Autonomous Vehicle

PubMed Central

Chen, Long; Li, Qingquan; Li, Ming; Zhang, Liang; Mao, Qingzhou

2012-01-01

This paper describes the environment perception system designed for intelligent vehicle SmartV-II, which won the 2010 Future Challenge. This system utilizes the cooperation of multiple lasers and cameras to realize several necessary functions of autonomous navigation: road curb detection, lane detection and traffic sign recognition. Multiple single scan lasers are integrated to detect the road curb based on Z-variance method. Vision based lane detection is realized by two scans method combining with image model. Haar-like feature based method is applied for traffic sign detection and SURF matching method is used for sign classification. The results of experiments validate the effectiveness of the proposed algorithms and the whole system.
Simulating propagation of coherent light in random media using the Fredholm type integral equation

NASA Astrophysics Data System (ADS)

Kraszewski, Maciej; Pluciński, Jerzy

2017-06-01

Studying propagation of light in random scattering materials is important for both basic and applied research. Such studies often require usage of numerical method for simulating behavior of light beams in random media. However, if such simulations require consideration of coherence properties of light, they may become a complex numerical problems. There are well established methods for simulating multiple scattering of light (e.g. Radiative Transfer Theory and Monte Carlo methods) but they do not treat coherence properties of light directly. Some variations of these methods allows to predict behavior of coherent light but only for an averaged realization of the scattering medium. This limits their application in studying many physical phenomena connected to a specific distribution of scattering particles (e.g. laser speckle). In general, numerical simulation of coherent light propagation in a specific realization of random medium is a time- and memory-consuming problem. The goal of the presented research was to develop new efficient method for solving this problem. The method, presented in our earlier works, is based on solving the Fredholm type integral equation, which describes multiple light scattering process. This equation can be discretized and solved numerically using various algorithms e.g. by direct solving the corresponding linear equations system, as well as by using iterative or Monte Carlo solvers. Here we present recent development of this method including its comparison with well-known analytical results and a finite-difference type simulations. We also present extension of the method for problems of multiple scattering of a polarized light on large spherical particles that joins presented mathematical formalism with Mie theory.
Reconfigurable Flight Control Designs With Application to the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Burken, John J.; Lu, Ping; Wu, Zhenglu

1999-01-01

Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the right body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

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

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.

2016-05-03

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. Themetabolite,protein, andlipidextraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of thismore » protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental,in vitro, and clinical). IMPORTANCEIn systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample.« less
Effects of complex internal structures on rheology of multiple emulsions particles in 2D from a boundary integral method.

PubMed

Wang, Jingtao; Liu, Jinxia; Han, Junjie; Guan, Jing

2013-02-08

A boundary integral method is developed to investigate the effects of inner droplets and asymmetry of internal structures on rheology of two-dimensional multiple emulsion particles with arbitrary numbers of layers and droplets within each layer. Under a modest extensional flow, the number increment of layers and inner droplets, and the collision among inner droplets subject the particle to stronger shears. In addition, the coalescence or release of inner droplets changes the internal structure of the multiple emulsion particles. Since the rheology of such particles is sensitive to internal structures and their change, modeling them as the core-shell particles to obtain the viscosity equation of a single particle should be modified by introducing the time-dependable volume fraction Φ(t) of the core instead of the fixed Φ. An asymmetric internal structure induces an oriented contact and merging of the outer and inner interface. The start time of the interface merging is controlled by adjusting the viscosity ratio and enhancing the asymmetry, which is promising in the controlled release of inner droplets through hydrodynamics for targeted drug delivery.
An integrated decision making approach for assessing healthcare waste treatment technologies from a multiple stakeholder.

PubMed

Shi, Hua; Liu, Hu-Chen; Li, Ping; Xu, Xue-Guo

2017-01-01

With increased worldwide awareness of environmental issues, healthcare waste (HCW) management has received much attention from both researchers and practitioners over the past decade. The task of selecting the optimum treatment technology for HCWs is a challenging decision making problem involving conflicting evaluation criteria and multiple stakeholders. In this paper, we develop an integrated decision making framework based on cloud model and MABAC method for evaluating and selecting the best HCW treatment technology from a multiple stakeholder perspective. The introduced framework deals with uncertain linguistic assessments of alternatives by using interval 2-tuple linguistic variables, determines decision makers' relative weights based on the uncertainty and divergence degrees of every decision maker, and obtains the ranking of all HCW disposal alternatives with the aid of an extended MABAC method. Finally, an empirical example from Shanghai, China, is provided to illustrate the feasibility and effectiveness of the proposed approach. Results indicate that the methodology being proposed is more suitable and effective to handle the HCW treatment technology selection problem under vague and uncertain information environment. Copyright © 2016 Elsevier Ltd. All rights reserved.
Comparative Microbial Modules Resource: Generation and Visualization of Multi-species Biclusters

PubMed Central

Bate, Ashley; Eichenberger, Patrick; Bonneau, Richard

2011-01-01

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures – results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation. PMID:22144874
Comparative microbial modules resource: generation and visualization of multi-species biclusters.

PubMed

Kacmarczyk, Thadeous; Waltman, Peter; Bate, Ashley; Eichenberger, Patrick; Bonneau, Richard

2011-12-01

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures - results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation. © 2011 Kacmarczyk et al.
Power-efficient method for IM-DD optical transmission of multiple OFDM signals.

PubMed

Effenberger, Frank; Liu, Xiang

2015-05-18

We propose a power-efficient method for transmitting multiple frequency-division multiplexed (FDM) orthogonal frequency-division multiplexing (OFDM) signals in intensity-modulation direct-detection (IM-DD) optical systems. This method is based on quadratic soft clipping in combination with odd-only channel mapping. We show, both analytically and experimentally, that the proposed approach is capable of improving the power efficiency by about 3 dB as compared to conventional FDM OFDM signals under practical bias conditions, making it a viable solution in applications such as optical fiber-wireless integrated systems where both IM-DD optical transmission and OFDM signaling are important.
NASA/BLM Applications Pilot Test (APT), phase 2. Volume 3: Technology transfer

NASA Technical Reports Server (NTRS)

1981-01-01

Techniques used and materials presented at a planning session and two workshops held to provide hands-on training in the integration of quantitatively based remote sensing data are described as well as methods used to enhance understanding of approaches to inventories that integrate multiple data sources given various resource information objectives. Significant results from each of the technology transfer sessions are examined.
Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.

PubMed

Wu, Mengmeng; Zeng, Wanwen; Liu, Wenqiang; Lv, Hairong; Chen, Ting; Jiang, Rui

2018-06-03

Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is still a challenging task to extract biological knowledge from the GWAS data, due to such issues as missing heritability and weak interpretability. Indeed, the fact that the majority of discovered loci fall into noncoding regions without clear links to genes has been preventing the characterization of their functions and appealing for a sophisticated approach to bridge genetic and genomic studies. Towards this problem, network-based prioritization of candidate genes, which performs integrated analysis of gene networks with GWAS data, has emerged as a promising direction and attracted much attention. However, most existing methods overlook the sparse and noisy properties of gene networks and thus may lead to suboptimal performance. Motivated by this understanding, we proposed a novel method called REGENT for integrating multiple gene networks with GWAS data to prioritize candidate genes for complex diseases. We leveraged a technique called the network representation learning to embed a gene network into a compact and robust feature space, and then designed a hierarchical statistical model to integrate features of multiple gene networks with GWAS data for the effective inference of genes associated with a disease of interest. We applied our method to six complex diseases and demonstrated the superior performance of REGENT over existing approaches in recovering known disease-associated genes. We further conducted a pathway analysis and showed that the ability of REGENT to discover disease-associated pathways. We expect to see applications of our method to a broad spectrum of diseases for post-GWAS analysis. REGENT is freely available at https://github.com/wmmthu/REGENT. Copyright © 2018 Elsevier Inc. All rights reserved.
Numerical Model of Multiple Scattering and Emission from Layering Snowpack for Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Jin, Y.; Liang, Z.

2002-12-01

The vector radiative transfer (VRT) equation is an integral-deferential equation to describe multiple scattering, absorption and transmission of four Stokes parameters in random scatter media. From the integral formal solution of VRT equation, the lower order solutions, such as the first-order scattering for a layer medium or the second order scattering for a half space, can be obtained. The lower order solutions are usually good at low frequency when high-order scattering is negligible. It won't be feasible to continue iteration for obtaining high order scattering solution because too many folds integration would be involved. In the space-borne microwave remote sensing, for example, the DMSP (Defense Meterological Satellite Program) SSM/I (Special Sensor Microwave/Imager) employed seven channels of 19, 22, 37 and 85GHz. Multiple scattering from the terrain surfaces such as snowpack cannot be neglected at these channels. The discrete ordinate and eigen-analysis method has been studied to take into account for multiple scattering and applied to remote sensing of atmospheric precipitation, snowpack etc. Snowpack was modeled as a layer of dense spherical particles, and the VRT for a layer of uniformly dense spherical particles has been numerically studied by the discrete ordinate method. However, due to surface melting and refrozen crusts, the snowpack undergoes stratifying to form inhomegeneous profiles of the ice grain size, fractional volume and physical temperature etc. It becomes necessary to study multiple scattering and emission from stratified snowpack of dense ice grains. But, the discrete ordinate and eigen-analysis method cannot be simply applied to multi-layers model, because numerically solving a set of multi-equations of VRT is difficult. Stratifying the inhomogeneous media into multi-slabs and employing the first order Mueller matrix of each thin slab, this paper developed an iterative method to derive high orders scattering solutions of whole scatter media. High order scattering and emission from inhomogeneous stratifying media of dense spherical particles are numerically obtained. The brightness temperature at low frequency such as 5.3 GHz without high order scattering and at SSM/I channels with high order scattering are obtained. This approach is also compared with the conventional discrete ordinate method for an uniform layer model. Numerical simulation for inhomogeneous snowpack is also compared with the measurements of microwave remote sensing.
The fabrication of integrated carbon pipes with sub-micron diameters

NASA Astrophysics Data System (ADS)

Kim, B. M.; Murray, T.; Bau, H. H.

2005-08-01

A method for fabricating integrated carbon pipes (nanopipettes) of sub-micron diameters and tens of microns in length is demonstrated. The carbon pipes are formed from a template consisting of the tip of a pulled alumino-silicate glass capillary coated with carbon deposited from a vapour phase. This method renders carbon nanopipettes without the need for ex situ assembly and facilitates parallel production of multiple carbon-pipe devices. An electric-field-driven transfer of ions in a KCl solution through the integrated carbon pipes exhibits nonlinear current-voltage (I-V) curves, markedly different from the Ohmic I-V curves observed in glass pipettes under similar conditions. The filling of the nanopipette with fluorescent suspension is also demonstrated.
An Integrated Method for Airfoil Optimization

NASA Astrophysics Data System (ADS)

Okrent, Joshua B.

Design exploration and optimization is a large part of the initial engineering and design process. To evaluate the aerodynamic performance of a design, viscous Navier-Stokes solvers can be used. However this method can prove to be overwhelmingly time consuming when performing an initial design sweep. Therefore, another evaluation method is needed to provide accurate results at a faster pace. To accomplish this goal, a coupled viscous-inviscid method is used. This thesis proposes an integrated method for analyzing, evaluating, and optimizing an airfoil using a coupled viscous-inviscid solver along with a genetic algorithm to find the optimal candidate. The method proposed is different from prior optimization efforts in that it greatly broadens the design space, while allowing the optimization to search for the best candidate that will meet multiple objectives over a characteristic mission profile rather than over a single condition and single optimization parameter. The increased design space is due to the use of multiple parametric airfoil families, namely the NACA 4 series, CST family, and the PARSEC family. Almost all possible airfoil shapes can be created with these three families allowing for all possible configurations to be included. This inclusion of multiple airfoil families addresses a possible criticism of prior optimization attempts since by only focusing on one airfoil family, they were inherently limiting the number of possible airfoil configurations. By using multiple parametric airfoils, it can be assumed that all reasonable airfoil configurations are included in the analysis and optimization and that a global and not local maximum is found. Additionally, the method used is amenable to customization to suit any specific needs as well as including the effects of other physical phenomena or design criteria and/or constraints. This thesis found that an airfoil configuration that met multiple objectives could be found for a given set of nominal operational conditions from a broad design space with the use of minimal computational resources on both an absolute and relative scale to traditional analysis techniques. Aerodynamicists, program managers, aircraft configuration specialist, and anyone else in charge of aircraft configuration, design studies, and program level decisions might find the evaluation and optimization method proposed of interest.
Algorithms for the computation of solutions of the Ornstein-Zernike equation.

PubMed

Peplow, A T; Beardmore, R E; Bresme, F

2006-10-01

We introduce a robust and efficient methodology to solve the Ornstein-Zernike integral equation using the pseudoarc length (PAL) continuation method that reformulates the integral equation in an equivalent but nonstandard form. This enables the computation of solutions in regions where the compressibility experiences large changes or where the existence of multiple solutions and so-called branch points prevents Newton's method from converging. We illustrate the use of the algorithm with a difficult problem that arises in the numerical solution of integral equations, namely the evaluation of the so-called no-solution line of the Ornstein-Zernike hypernetted chain (HNC) integral equation for the Lennard-Jones potential. We are able to use the PAL algorithm to solve the integral equation along this line and to connect physical and nonphysical solution branches (both isotherms and isochores) where appropriate. We also show that PAL continuation can compute solutions within the no-solution region that cannot be computed when Newton and Picard methods are applied directly to the integral equation. While many solutions that we find are new, some correspond to states with negative compressibility and consequently are not physical.
Monte Carlo methods for multidimensional integration for European option pricing

NASA Astrophysics Data System (ADS)

Todorov, V.; Dimov, I. T.

2016-10-01

In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.
Free Energy Reconstruction from Logarithmic Mean-Force Dynamics Using Multiple Nonequilibrium Trajectories.

PubMed

Morishita, Tetsuya; Yonezawa, Yasushige; Ito, Atsushi M

2017-07-11

Efficient and reliable estimation of the mean force (MF), the derivatives of the free energy with respect to a set of collective variables (CVs), has been a challenging problem because free energy differences are often computed by integrating the MF. Among various methods for computing free energy differences, logarithmic mean-force dynamics (LogMFD) [ Morishita et al., Phys. Rev. E 2012 , 85 , 066702 ] invokes the conservation law in classical mechanics to integrate the MF, which allows us to estimate the free energy profile along the CVs on-the-fly. Here, we present a method called parallel dynamics, which improves the estimation of the MF by employing multiple replicas of the system and is straightforwardly incorporated in LogMFD or a related method. In the parallel dynamics, the MF is evaluated by a nonequilibrium path-ensemble using the multiple replicas based on the Crooks-Jarzynski nonequilibrium work relation. Thanks to the Crooks relation, realizing full-equilibrium states is no longer mandatory for estimating the MF. Additionally, sampling in the hidden subspace orthogonal to the CV space is highly improved with appropriate weights for each metastable state (if any), which is hardly achievable by typical free energy computational methods. We illustrate how to implement parallel dynamics by combining it with LogMFD, which we call logarithmic parallel dynamics (LogPD). Biosystems of alanine dipeptide and adenylate kinase in explicit water are employed as benchmark systems to which LogPD is applied to demonstrate the effect of multiple replicas on the accuracy and efficiency in estimating the free energy profiles using parallel dynamics.
A Cost Effective Block Framing Scheme for Underwater Communication

PubMed Central

Shin, Soo-Young; Park, Soo-Hyun

2011-01-01

In this paper, the Selective Multiple Acknowledgement (SMA) method, based on Multiple Acknowledgement (MA), is proposed to efficiently reduce the amount of data transmission by redesigning the transmission frame structure and taking into consideration underwater transmission characteristics. The method is suited to integrated underwater system models, as the proposed method can handle the same amount of data in a much more compact frame structure without any appreciable loss of reliability. Herein, the performance of the proposed SMA method was analyzed and compared to those of the conventional Automatic Repeat-reQuest (ARQ), Block Acknowledgement (BA), block response, and MA methods. The efficiency of the underwater sensor network, which forms a large cluster and mostly contains uplink data, is expected to be improved by the proposed method. PMID:22247689
Integrating multiple fitting regression and Bayes decision for cancer diagnosis with transcriptomic data from tumor-educated blood platelets.

PubMed

Huang, Guangzao; Yuan, Mingshun; Chen, Moliang; Li, Lei; You, Wenjie; Li, Hanjie; Cai, James J; Ji, Guoli

2017-10-07

The application of machine learning in cancer diagnostics has shown great promise and is of importance in clinic settings. Here we consider applying machine learning methods to transcriptomic data derived from tumor-educated platelets (TEPs) from individuals with different types of cancer. We aim to define a reliability measure for diagnostic purposes to increase the potential for facilitating personalized treatments. To this end, we present a novel classification method called MFRB (for Multiple Fitting Regression and Bayes decision), which integrates the process of multiple fitting regression (MFR) with Bayes decision theory. MFR is first used to map multidimensional features of the transcriptomic data into a one-dimensional feature. The probability density function of each class in the mapped space is then adjusted using the Gaussian probability density function. Finally, the Bayes decision theory is used to build a probabilistic classifier with the estimated probability density functions. The output of MFRB can be used to determine which class a sample belongs to, as well as to assign a reliability measure for a given class. The classical support vector machine (SVM) and probabilistic SVM (PSVM) are used to evaluate the performance of the proposed method with simulated and real TEP datasets. Our results indicate that the proposed MFRB method achieves the best performance compared to SVM and PSVM, mainly due to its strong generalization ability for limited, imbalanced, and noisy data.
iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets

PubMed Central

2012-01-01

Background ChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB). However, detecting allelic imbalance from a single ChIP-seq dataset often has low statistical power since only sequence reads mapped to heterozygote SNPs are informative for discriminating two alleles. Results We develop a new method iASeq to address this issue by jointly analyzing multiple ChIP-seq datasets. iASeq uses a Bayesian hierarchical mixture model to learn correlation patterns of allele-specificity among multiple proteins. Using the discovered correlation patterns, the model allows one to borrow information across datasets to improve detection of allelic imbalance. Application of iASeq to 77 ChIP-seq samples from 40 ENCODE datasets and 1 genomic DNA sample in GM12878 cells reveals that allele-specificity of multiple proteins are highly correlated, and demonstrates the ability of iASeq to improve allelic inference compared to analyzing each individual dataset separately. Conclusions iASeq illustrates the value of integrating multiple datasets in the allele-specificity inference and offers a new tool to better analyze ASB. PMID:23194258
Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.
Integrated Droplet-Based Microextraction with ESI-MS for Removal of Matrix Interference in Single-Cell Analysis.

PubMed

Zhang, Xiao-Chao; Wei, Zhen-Wei; Gong, Xiao-Yun; Si, Xing-Yu; Zhao, Yao-Yao; Yang, Cheng-Dui; Zhang, Si-Chun; Zhang, Xin-Rong

2016-04-29

Integrating droplet-based microfluidics with mass spectrometry is essential to high-throughput and multiple analysis of single cells. Nevertheless, matrix effects such as the interference of culture medium and intracellular components influence the sensitivity and the accuracy of results in single-cell analysis. To resolve this problem, we developed a method that integrated droplet-based microextraction with single-cell mass spectrometry. Specific extraction solvent was used to selectively obtain intracellular components of interest and remove interference of other components. Using this method, UDP-Glc-NAc, GSH, GSSG, AMP, ADP and ATP were successfully detected in single MCF-7 cells. We also applied the method to study the change of unicellular metabolites in the biological process of dysfunctional oxidative phosphorylation. The method could not only realize matrix-free, selective and sensitive detection of metabolites in single cells, but also have the capability for reliable and high-throughput single-cell analysis.
Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana.

PubMed

Hansen, Bjoern Oest; Meyer, Etienne H; Ferrari, Camilla; Vaid, Neha; Movahedi, Sara; Vandepoele, Klaas; Nikoloski, Zoran; Mutwil, Marek

2018-03-01

Recent advances in gene function prediction rely on ensemble approaches that integrate results from multiple inference methods to produce superior predictions. Yet, these developments remain largely unexplored in plants. We have explored and compared two methods to integrate 10 gene co-function networks for Arabidopsis thaliana and demonstrate how the integration of these networks produces more accurate gene function predictions for a larger fraction of genes with unknown function. These predictions were used to identify genes involved in mitochondrial complex I formation, and for five of them, we confirmed the predictions experimentally. The ensemble predictions are provided as a user-friendly online database, EnsembleNet. The methods presented here demonstrate that ensemble gene function prediction is a powerful method to boost prediction performance, whereas the EnsembleNet database provides a cutting-edge community tool to guide experimentalists. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Integrating heterogeneous databases in clustered medic care environments using object-oriented technology

NASA Astrophysics Data System (ADS)

Thakore, Arun K.; Sauer, Frank

1994-05-01

The organization of modern medical care environments into disease-related clusters, such as a cancer center, a diabetes clinic, etc., has the side-effect of introducing multiple heterogeneous databases, often containing similar information, within the same organization. This heterogeneity fosters incompatibility and prevents the effective sharing of data amongst applications at different sites. Although integration of heterogeneous databases is now feasible, in the medical arena this is often an ad hoc process, not founded on proven database technology or formal methods. In this paper we illustrate the use of a high-level object- oriented semantic association method to model information found in different databases into an integrated conceptual global model that integrates the databases. We provide examples from the medical domain to illustrate an integration approach resulting in a consistent global view, without attacking the autonomy of the underlying databases.
Future Directions in Vulnerability to Depression among Youth: Integrating Risk Factors and Processes across Multiple Levels of Analysis

PubMed Central

Hankin, Benjamin L.

2014-01-01

Depression is a developmental phenomenon. Considerable progress has been made in describing the syndrome, establishing its prevalence and features, providing clues as to its etiology, and developing evidence-based treatment and prevention options. Despite considerable headway in distinct lines of vulnerability research, there is an explanatory gap in the field ability to more comprehensively explain and predict who is likely to become depressed, when, and why. Still, despite clear success in predicting moderate variance for future depression, especially with empirically rigorous methods and designs, the heterogeneous and multi-determined nature of depression suggests that additional etiologies need to be included to advance knowledge on developmental pathways to depression. This paper advocates for a multiple levels of analysis approach to investigating vulnerability to depression across the lifespan and providing a more comprehensive understanding of its etiology. One example of a multiple levels of analysis model of vulnerabilities to depression is provided that integrates the most accessible, observable factors (e.g., cognitive and temperament risks), intermediate processes and endophenotypes (e.g., information processing biases, biological stress physiology, and neural activation and connectivity), and genetic influences (e.g., candidate genes and epigenetics). Evidence for each of these factors as well as their cross-level integration is provided. Methodological and conceptual considerations important for conducting integrative, multiple levels of depression vulnerability research are discussed. Finally, translational implications for how a multiple levels of analysis perspective may confer additional leverage to reduce the global burden of depression and improve care are considered. PMID:22900513
An information diffusion technique to assess integrated hazard risks.

PubMed

Huang, Chongfu; Huang, Yundong

2018-02-01

An integrated risk is a scene in the future associated with some adverse incident caused by multiple hazards. An integrated probability risk is the expected value of disaster. Due to the difficulty of assessing an integrated probability risk with a small sample, weighting methods and copulas are employed to avoid this obstacle. To resolve the problem, in this paper, we develop the information diffusion technique to construct a joint probability distribution and a vulnerability surface. Then, an integrated risk can be directly assessed by using a small sample. A case of an integrated risk caused by flood and earthquake is given to show how the suggested technique is used to assess the integrated risk of annual property loss. Copyright © 2017 Elsevier Inc. All rights reserved.
System For Research On Multiple-Arm Robots

NASA Technical Reports Server (NTRS)

Backes, Paul G.; Hayati, Samad; Tso, Kam S.; Hayward, Vincent

1991-01-01

Kali system of computer programs and equipment provides environment for research on distributed programming and distributed control of coordinated-multiple-arm robots. Suitable for telerobotics research involving sensing and execution of low level tasks. Software and configuration of hardware designed flexible so system modified easily to test various concepts in control and programming of robots, including multiple-arm control, redundant-arm control, shared control, traded control, force control, force/position hybrid control, design and integration of sensors, teleoperation, task-space description and control, methods of adaptive control, control of flexible arms, and human factors.
Systems Epidemiology: What’s in a Name?

PubMed Central

Dammann, O.; Gray, P.; Gressens, P.; Wolkenhauer, O.; Leviton, A.

2014-01-01

Systems biology is an interdisciplinary effort to integrate molecular, cellular, tissue, organ, and organism levels of function into computational models that facilitate the identification of general principles. Systems medicine adds a disease focus. Systems epidemiology adds yet another level consisting of antecedents that might contribute to the disease process in populations. In etiologic and prevention research, systems-type thinking about multiple levels of causation will allow epidemiologists to identify contributors to disease at multiple levels as well as their interactions. In public health, systems epidemiology will contribute to the improvement of syndromic surveillance methods. We encourage the creation of computational simulation models that integrate information about disease etiology, pathogenetic data, and the expertise of investigators from different disciplines. PMID:25598870
DynaMIT: the dynamic motif integration toolkit

PubMed Central

Dassi, Erik; Quattrone, Alessandro

2016-01-01

De-novo motif search is a frequently applied bioinformatics procedure to identify and prioritize recurrent elements in sequences sets for biological investigation, such as the ones derived from high-throughput differential expression experiments. Several algorithms have been developed to perform motif search, employing widely different approaches and often giving divergent results. In order to maximize the power of these investigations and ultimately be able to draft solid biological hypotheses, there is the need for applying multiple tools on the same sequences and merge the obtained results. However, motif reporting formats and statistical evaluation methods currently make such an integration task difficult to perform and mostly restricted to specific scenarios. We thus introduce here the Dynamic Motif Integration Toolkit (DynaMIT), an extremely flexible platform allowing to identify motifs employing multiple algorithms, integrate them by means of a user-selected strategy and visualize results in several ways; furthermore, the platform is user-extendible in all its aspects. DynaMIT is freely available at http://cibioltg.bitbucket.org. PMID:26253738
Methods and materials for the production of L-lactic acid in yeast

DOEpatents

Hause, Ben [Jordan, MN; Rajgarhia, Vineet [Minnetonka, MN; Suominen, Pirkko [Maple Grove, MN

2009-05-19

Recombinant yeast are provided having, in one aspect, multiple exogenous LDH genes integrated into the genome, while leaving native PDC genes intact. In a second aspect, recombinant yeast are provided having an exogenous LDH gene integrated into its genome at the locus of a native PDC gene, with deletion of the native PDC gene. The recombinant yeast are useful in fermentation process for producing lactic acid.
A demonstration of mixed-methods research in the health sciences.

PubMed

Katz, Janet; Vandermause, Roxanne; McPherson, Sterling; Barbosa-Leiker, Celestina

2016-11-18

Background The growth of patient, community and population-centred nursing research is a rationale for the use of research methods that can examine complex healthcare issues, not only from a biophysical perspective, but also from cultural, psychosocial and political viewpoints. This need for multiple perspectives requires mixed-methods research. Philosophy and practicality are needed to plan, conduct, and make mixed-methods research more broadly accessible to the health sciences research community. The traditions and dichotomy between qualitative and quantitative research makes the application of mixed methods a challenge. Aim To propose an integrated model for a research project containing steps from start to finish, and to use the unique strengths brought by each approach to meet the health needs of patients and communities. Discussion Mixed-methods research is a practical approach to inquiry, that focuses on asking questions and how best to answer them to improve the health of individuals, communities and populations. An integrated model of research begins with the research question(s) and moves in a continuum. The lines dividing methods do not dissolve, but become permeable boundaries where two or more methods can be used to answer research questions more completely. Rigorous and expert methodologists work together to solve common problems. Conclusion Mixed-methods research enables discussion among researchers from varied traditions. There is a plethora of methodological approaches available. Combining expertise by communicating across disciplines and professions is one way to tackle large and complex healthcare issues. Implications for practice The model presented in this paper exemplifies the integration of multiple approaches in a unified focus on identified phenomena. The dynamic nature of the model signals a need to be open to the data generated and the methodological directions implied by findings.
Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

NASA Technical Reports Server (NTRS)

Czaja, Wojciech; Le Moigne-Stewart, Jacqueline

2014-01-01

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.
Mixed methods research in music therapy research.

PubMed

Bradt, Joke; Burns, Debra S; Creswell, John W

2013-01-01

Music therapists have an ethical and professional responsibility to provide the highest quality care possible to their patients. Much of the time, high quality care is guided by evidence-based practice standards that integrate the most current, available research in making decisions. Accordingly, music therapists need research that integrates multiple ways of knowing and forms of evidence. Mixed methods research holds great promise for facilitating such integration. At this time, there have not been any methodological articles published on mixed methods research in music therapy. The purpose of this article is to introduce mixed methods research as an approach to address research questions relevant to music therapy practice. This article describes the core characteristics of mixed methods research, considers paradigmatic issues related to this research approach, articulates major challenges in conducting mixed methods research, illustrates four basic designs, and provides criteria for evaluating the quality of mixed methods articles using examples of mixed methods research from the music therapy literature. Mixed methods research offers unique opportunities for strengthening the evidence base in music therapy. Recommendations are provided to ensure rigorous implementation of this research approach.
Facilitating the transition from physiology to hospital wards through an interdisciplinary case study of septic shock

PubMed Central

2014-01-01

Background In order to develop clinical reasoning, medical students must be able to integrate knowledge across traditional subject boundaries and multiple disciplines. At least two dimensions of integration have been identified: horizontal integration, bringing together different disciplines in considering a topic; and vertical integration, bridging basic science and clinical practice. Much attention has been focused on curriculum overhauls, but our approach is to facilitate horizontal and vertical integration on a smaller scale through an interdisciplinary case study discussion and then to assess its utility. Methods An interdisciplinary case study discussion about a critically ill patient was implemented at the end of an organ system-based, basic sciences module at New York University School of Medicine. Three clinical specialists—a cardiologist, a pulmonologist, and a nephrologist—jointly led a discussion about a complex patient in the intensive care unit with multiple medical problems secondary to septic shock. The discussion emphasized the physiologic underpinnings behind the patient’s presentation and the physiologic considerations across the various systems in determining proper treatment. The discussion also highlighted the interdependence between the cardiovascular, respiratory, and renal systems, which were initially presented in separate units. After the session students were given a brief, anonymous three-question free-response questionnaire in which they were asked to evaluate and freely comment on the exercise. Results Students not only took away physiological principles but also gained an appreciation for various thematic lessons for bringing basic science to the bedside, especially horizontal and vertical integration. The response of the participants was overwhelmingly positive with many indicating that the exercise integrated the material across organ systems, and strengthened their appreciation of the role of physiology in understanding disease presentations and guiding appropriate therapy. Conclusions Horizontal and vertical integration can be presented effectively through a single-session case study, with complex patient cases involving multiple organ systems providing students opportunities to integrate their knowledge across organ systems while emphasizing the importance of physiology in clinical reasoning. Furthermore, having several clinicians from different specialties discuss the case together can reinforce the matter of integration across multiple organ systems and disciplines in students’ minds. PMID:24725336
Path optimization method for the sign problem

NASA Astrophysics Data System (ADS)

Ohnishi, Akira; Mori, Yuto; Kashiwa, Kouji

2018-03-01

We propose a path optimization method (POM) to evade the sign problem in the Monte-Carlo calculations for complex actions. Among many approaches to the sign problem, the Lefschetz-thimble path-integral method and the complex Langevin method are promising and extensively discussed. In these methods, real field variables are complexified and the integration manifold is determined by the flow equations or stochastically sampled. When we have singular points of the action or multiple critical points near the original integral surface, however, we have a risk to encounter the residual and global sign problems or the singular drift term problem. One of the ways to avoid the singular points is to optimize the integration path which is designed not to hit the singular points of the Boltzmann weight. By specifying the one-dimensional integration-path as z = t +if(t)(f ɛ R) and by optimizing f(t) to enhance the average phase factor, we demonstrate that we can avoid the sign problem in a one-variable toy model for which the complex Langevin method is found to fail. In this proceedings, we propose POM and discuss how we can avoid the sign problem in a toy model. We also discuss the possibility to utilize the neural network to optimize the path.
Feature point based 3D tracking of multiple fish from multi-view images

PubMed Central

Qian, Zhi-Ming

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly. PMID:28665966
Feature point based 3D tracking of multiple fish from multi-view images.

PubMed

Qian, Zhi-Ming; Chen, Yan Qiu

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.
Parallel/Vector Integration Methods for Dynamical Astronomy

NASA Astrophysics Data System (ADS)

Fukushima, Toshio

1999-01-01

This paper reviews three recent works on the numerical methods to integrate ordinary differential equations (ODE), which are specially designed for parallel, vector, and/or multi-processor-unit(PU) computers. The first is the Picard-Chebyshev method (Fukushima, 1997a). It obtains a global solution of ODE in the form of Chebyshev polynomial of large (> 1000) degree by applying the Picard iteration repeatedly. The iteration converges for smooth problems and/or perturbed dynamics. The method runs around 100-1000 times faster in the vector mode than in the scalar mode of a certain computer with vector processors (Fukushima, 1997b). The second is a parallelization of a symplectic integrator (Saha et al., 1997). It regards the implicit midpoint rules covering thousands of timesteps as large-scale nonlinear equations and solves them by the fixed-point iteration. The method is applicable to Hamiltonian systems and is expected to lead an acceleration factor of around 50 in parallel computers with more than 1000 PUs. The last is a parallelization of the extrapolation method (Ito and Fukushima, 1997). It performs trial integrations in parallel. Also the trial integrations are further accelerated by balancing computational load among PUs by the technique of folding. The method is all-purpose and achieves an acceleration factor of around 3.5 by using several PUs. Finally, we give a perspective on the parallelization of some implicit integrators which require multiple corrections in solving implicit formulas like the implicit Hermitian integrators (Makino and Aarseth, 1992), (Hut et al., 1995) or the implicit symmetric multistep methods (Fukushima, 1998), (Fukushima, 1999).
Two-dimensional imaging via a narrowband MIMO radar system with two perpendicular linear arrays.

PubMed

Wang, Dang-wei; Ma, Xiao-yan; Su, Yi

2010-05-01

This paper presents a system model and method for the 2-D imaging application via a narrowband multiple-input multiple-output (MIMO) radar system with two perpendicular linear arrays. Furthermore, the imaging formulation for our method is developed through a Fourier integral processing, and the parameters of antenna array including the cross-range resolution, required size, and sampling interval are also examined. Different from the spatial sequential procedure sampling the scattered echoes during multiple snapshot illuminations in inverse synthetic aperture radar (ISAR) imaging, the proposed method utilizes a spatial parallel procedure to sample the scattered echoes during a single snapshot illumination. Consequently, the complex motion compensation in ISAR imaging can be avoided. Moreover, in our array configuration, multiple narrowband spectrum-shared waveforms coded with orthogonal polyphase sequences are employed. The mainlobes of the compressed echoes from the different filter band could be located in the same range bin, and thus, the range alignment in classical ISAR imaging is not necessary. Numerical simulations based on synthetic data are provided for testing our proposed method.
Integrated multiplexed capillary electrophoresis system

DOEpatents

Yeung, Edward S.; Tan, Hongdong

2002-05-14

The present invention provides an integrated multiplexed capillary electrophoresis system for the analysis of sample analytes. The system integrates and automates multiple components, such as chromatographic columns and separation capillaries, and further provides a detector for the detection of analytes eluting from the separation capillaries. The system employs multiplexed freeze/thaw valves to manage fluid flow and sample movement. The system is computer controlled and is capable of processing samples through reaction, purification, denaturation, pre-concentration, injection, separation and detection in parallel fashion. Methods employing the system of the invention are also provided.
Optimal information networks: Application for data-driven integrated health in populations

PubMed Central

Servadio, Joseph L.; Convertino, Matteo

2018-01-01

Development of composite indicators for integrated health in populations typically relies on a priori assumptions rather than model-free, data-driven evidence. Traditional variable selection processes tend not to consider relatedness and redundancy among variables, instead considering only individual correlations. In addition, a unified method for assessing integrated health statuses of populations is lacking, making systematic comparison among populations impossible. We propose the use of maximum entropy networks (MENets) that use transfer entropy to assess interrelatedness among selected variables considered for inclusion in a composite indicator. We also define optimal information networks (OINs) that are scale-invariant MENets, which use the information in constructed networks for optimal decision-making. Health outcome data from multiple cities in the United States are applied to this method to create a systemic health indicator, representing integrated health in a city. PMID:29423440
Integrating the human element into the systems engineering process and MBSE methodology

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

Tadros, Michael Samir

In response to the challenges related to the increasing size and complexity of systems, organizations have recognized the need to integrate human considerations in the beginning stages of systems development. Human Systems Integration (HSI) seeks to accomplish this objective by incorporating human factors within systems engineering (SE) processes and methodologies, which is the focus of this paper. A representative set of HSI methods from multiple sources are organized, analyzed, and mapped to the systems engineering Vee-model. These methods are then consolidated and evaluated against the SE process and Models-Based Systems Engineering (MBSE) methodology to determine where and how they couldmore » integrate within systems development activities in the form of specific enhancements. Overall conclusions based on these evaluations are presented and future research areas are proposed.« less
Drift-Free Position Estimation of Periodic or Quasi-Periodic Motion Using Inertial Sensors

PubMed Central

Latt, Win Tun; Veluvolu, Kalyana Chakravarthy; Ang, Wei Tech

2011-01-01

Position sensing with inertial sensors such as accelerometers and gyroscopes usually requires other aided sensors or prior knowledge of motion characteristics to remove position drift resulting from integration of acceleration or velocity so as to obtain accurate position estimation. A method based on analytical integration has previously been developed to obtain accurate position estimate of periodic or quasi-periodic motion from inertial sensors using prior knowledge of the motion but without using aided sensors. In this paper, a new method is proposed which employs linear filtering stage coupled with adaptive filtering stage to remove drift and attenuation. The prior knowledge of the motion the proposed method requires is only approximate band of frequencies of the motion. Existing adaptive filtering methods based on Fourier series such as weighted-frequency Fourier linear combiner (WFLC), and band-limited multiple Fourier linear combiner (BMFLC) are modified to combine with the proposed method. To validate and compare the performance of the proposed method with the method based on analytical integration, simulation study is performed using periodic signals as well as real physiological tremor data, and real-time experiments are conducted using an ADXL-203 accelerometer. Results demonstrate that the performance of the proposed method outperforms the existing analytical integration method. PMID:22163935

Framework and Method for Controlling a Robotic System Using a Distributed Computer Network

NASA Technical Reports Server (NTRS)

Sanders, Adam M. (Inventor); Strawser, Philip A. (Inventor); Barajas, Leandro G. (Inventor); Permenter, Frank Noble (Inventor)

2015-01-01

A robotic system for performing an autonomous task includes a humanoid robot having a plurality of compliant robotic joints, actuators, and other integrated system devices that are controllable in response to control data from various control points, and having sensors for measuring feedback data at the control points. The system includes a multi-level distributed control framework (DCF) for controlling the integrated system components over multiple high-speed communication networks. The DCF has a plurality of first controllers each embedded in a respective one of the integrated system components, e.g., the robotic joints, a second controller coordinating the components via the first controllers, and a third controller for transmitting a signal commanding performance of the autonomous task to the second controller. The DCF virtually centralizes all of the control data and the feedback data in a single location to facilitate control of the robot across the multiple communication networks.
An evaluation of a reagentless method for the determination of total mercury in aquatic life

USGS Publications Warehouse

Haynes, Sekeenia; Gragg, Richard D.; Johnson, Elijah; Robinson, Larry; Orazio, Carl E.

2006-01-01

Multiple treatment (i.e., drying, chemical digestion, and oxidation) steps are often required during preparation of biological matrices for quantitative analysis of mercury; these multiple steps could potentially lead to systematic errors and poor recovery of the analyte. In this study, the Direct Mercury Analyzer (Milestone Inc., Monroe, CT) was utilized to measure total mercury in fish tissue by integrating steps of drying, sample combustion and gold sequestration with successive identification using atomic absorption spectrometry. We also evaluated the differences between the mercury concentrations found in samples that were homogenized and samples with no preparation. These results were confirmed with cold vapor atomic absorbance and fluorescence spectrometric methods of analysis. Finally, total mercury in wild captured largemouth bass (n = 20) were assessed using the Direct Mercury Analyzer to examine internal variability between mercury concentrations in muscle, liver and brain organs. Direct analysis of total mercury measured in muscle tissue was strongly correlated with muscle tissue that was homogenized before analysis (r = 0.81, p < 0.0001). Additionally, results using this integrated method compared favorably (p < 0.05) with conventional cold vapor spectrometry with atomic absorbance and fluorescence detection methods. Mercury concentrations in brain were significantly lower than concentrations in muscle (p < 0.001) and liver (p < 0.05) tissues. This integrated method can measure a wide range of mercury concentrations (0-500 ??g) using small sample sizes. Total mercury measurements in this study are comparative to the methods (cold vapor) commonly used for total mercury analysis and are devoid of laborious sample preparation and expensive hazardous waste. ?? Springer 2006.
Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.

PubMed

Zhu, Xiaofeng; Feng, Tao; Tayo, Bamidele O; Liang, Jingjing; Young, J Hunter; Franceschini, Nora; Smith, Jennifer A; Yanek, Lisa R; Sun, Yan V; Edwards, Todd L; Chen, Wei; Nalls, Mike; Fox, Ervin; Sale, Michele; Bottinger, Erwin; Rotimi, Charles; Liu, Yongmei; McKnight, Barbara; Liu, Kiang; Arnett, Donna K; Chakravati, Aravinda; Cooper, Richard S; Redline, Susan

2015-01-08

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
A Novel System for Simultaneous or Sequential Integration of Multiple Gene-Loading Vectors into a Defined Site of a Human Artificial Chromosome

PubMed Central

Suzuki, Teruhiko; Kazuki, Yasuhiro; Oshimura, Mitsuo; Hara, Takahiko

2014-01-01

Human artificial chromosomes (HACs) are gene-delivery vectors suitable for introducing large DNA fragments into mammalian cells. Although a HAC theoretically incorporates multiple gene expression cassettes of unlimited DNA size, its application has been limited because the conventional gene-loading system accepts only one gene-loading vector (GLV) into a HAC. We report a novel method for the simultaneous or sequential integration of multiple GLVs into a HAC vector (designated as the SIM system) via combined usage of Cre, FLP, Bxb1, and φC31 recombinase/integrase. As a proof of principle, we first attempted simultaneous integration of three GLVs encoding EGFP, Venus, and TdTomato into a gene-loading site of a HAC in CHO cells. These cells successfully expressed all three fluorescent proteins. Furthermore, microcell-mediated transfer of HACs enabled the expression of those fluorescent proteins in recipient cells. We next demonstrated that GLVs could be introduced into a HAC one-by-one via reciprocal usage of recombinase/integrase. Lastly, we introduced a fourth GLV into a HAC after simultaneous integration of three GLVs by FLP-mediated DNA recombination. The SIM system expands the applicability of HAC vectors and is useful for various biomedical studies, including cell reprogramming. PMID:25303219
A novel system for simultaneous or sequential integration of multiple gene-loading vectors into a defined site of a human artificial chromosome.

PubMed

Suzuki, Teruhiko; Kazuki, Yasuhiro; Oshimura, Mitsuo; Hara, Takahiko

2014-01-01

Human artificial chromosomes (HACs) are gene-delivery vectors suitable for introducing large DNA fragments into mammalian cells. Although a HAC theoretically incorporates multiple gene expression cassettes of unlimited DNA size, its application has been limited because the conventional gene-loading system accepts only one gene-loading vector (GLV) into a HAC. We report a novel method for the simultaneous or sequential integration of multiple GLVs into a HAC vector (designated as the SIM system) via combined usage of Cre, FLP, Bxb1, and φC31 recombinase/integrase. As a proof of principle, we first attempted simultaneous integration of three GLVs encoding EGFP, Venus, and TdTomato into a gene-loading site of a HAC in CHO cells. These cells successfully expressed all three fluorescent proteins. Furthermore, microcell-mediated transfer of HACs enabled the expression of those fluorescent proteins in recipient cells. We next demonstrated that GLVs could be introduced into a HAC one-by-one via reciprocal usage of recombinase/integrase. Lastly, we introduced a fourth GLV into a HAC after simultaneous integration of three GLVs by FLP-mediated DNA recombination. The SIM system expands the applicability of HAC vectors and is useful for various biomedical studies, including cell reprogramming.
Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework.

PubMed

Talluto, Matthew V; Boulangeat, Isabelle; Ameztegui, Aitor; Aubin, Isabelle; Berteaux, Dominique; Butler, Alyssa; Doyon, Frédérik; Drever, C Ronnie; Fortin, Marie-Josée; Franceschini, Tony; Liénard, Jean; McKenney, Dan; Solarik, Kevin A; Strigul, Nikolay; Thuiller, Wilfried; Gravel, Dominique

2016-02-01

Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. Eastern North America (as an example). Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple ( Acer saccharum ), an abundant tree native to eastern North America. For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi-source and multi-scale data into ecological decision-making.
Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

PubMed

Li, Miao; Li, Jun; Zhou, Yiyu

2015-12-08

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.
Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array

PubMed Central

Li, Miao; Li, Jun; Zhou, Yiyu

2015-01-01

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts—MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing. PMID:26670234
Very high frame rate volumetric integration of depth images on mobile devices.

PubMed

Kähler, Olaf; Adrian Prisacariu, Victor; Yuheng Ren, Carl; Sun, Xin; Torr, Philip; Murray, David

2015-11-01

Volumetric methods provide efficient, flexible and simple ways of integrating multiple depth images into a full 3D model. They provide dense and photorealistic 3D reconstructions, and parallelised implementations on GPUs achieve real-time performance on modern graphics hardware. To run such methods on mobile devices, providing users with freedom of movement and instantaneous reconstruction feedback, remains challenging however. In this paper we present a range of modifications to existing volumetric integration methods based on voxel block hashing, considerably improving their performance and making them applicable to tablet computer applications. We present (i) optimisations for the basic data structure, and its allocation and integration; (ii) a highly optimised raycasting pipeline; and (iii) extensions to the camera tracker to incorporate IMU data. In total, our system thus achieves frame rates up 47 Hz on a Nvidia Shield Tablet and 910 Hz on a Nvidia GTX Titan XGPU, or even beyond 1.1 kHz without visualisation.
The fast multipole method and point dipole moment polarizable force fields.

PubMed

Coles, Jonathan P; Masella, Michel

2015-01-14

We present an implementation of the fast multipole method for computing Coulombic electrostatic and polarization forces from polarizable force-fields based on induced point dipole moments. We demonstrate the expected O(N) scaling of that approach by performing single energy point calculations on hexamer protein subunits of the mature HIV-1 capsid. We also show the long time energy conservation in molecular dynamics at the nanosecond scale by performing simulations of a protein complex embedded in a coarse-grained solvent using a standard integrator and a multiple time step integrator. Our tests show the applicability of fast multipole method combined with state-of-the-art chemical models in molecular dynamical systems.
Allopatric integrations selectively change host transcriptomes, leading to varied expression efficiencies of exotic genes in Myxococcus xanthus.

PubMed

Zhu, Li-Ping; Yue, Xin-Jing; Han, Kui; Li, Zhi-Feng; Zheng, Lian-Shuai; Yi, Xiu-Nan; Wang, Hai-Long; Zhang, You-Ming; Li, Yue-Zhong

2015-07-22

Exotic genes, especially clustered multiple-genes for a complex pathway, are normally integrated into chromosome for heterologous expression. The influences of insertion sites on heterologous expression and allotropic expressions of exotic genes on host remain mostly unclear. We compared the integration and expression efficiencies of single and multiple exotic genes that were inserted into Myxococcus xanthus genome by transposition and attB-site-directed recombination. While the site-directed integration had a rather stable chloramphenicol acetyl transferase (CAT) activity, the transposition produced varied CAT enzyme activities. We attempted to integrate the 56-kb gene cluster for the biosynthesis of antitumor polyketides epothilones into M. xanthus genome by site-direction but failed, which was determined to be due to the insertion size limitation at the attB site. The transposition technique produced many recombinants with varied production capabilities of epothilones, which, however, were not paralleled to the transcriptional characteristics of the local sites where the genes were integrated. Comparative transcriptomics analysis demonstrated that the allopatric integrations caused selective changes of host transcriptomes, leading to varied expressions of epothilone genes in different mutants. With the increase of insertion fragment size, transposition is a more practicable integration method for the expression of exotic genes. Allopatric integrations selectively change host transcriptomes, which lead to varied expression efficiencies of exotic genes.
The Practice Integration Profile: Rationale, development, method, and research.

PubMed

Macchi, C R; Kessler, Rodger; Auxier, Andrea; Hitt, Juvena R; Mullin, Daniel; van Eeghen, Constance; Littenberg, Benjamin

2016-12-01

Insufficient knowledge exists regarding how to measure the presence and degree of integrated care. Prior estimates of integration levels are neither grounded in theory nor psychometrically validated. They provide scant guidance to inform improvement activities, compare integration efforts, discriminate among practices by degree of integration, measure the effect of integration on quadruple aim outcomes, or address the needs of clinicians, regulators, and policymakers seeking new models of health care delivery and funding. We describe the development of the Practice Integration Profile (PIP), a novel instrument designed to measure levels of integrated behavioral health care within a primary care clinic. The PIP draws upon the Agency for Health care Research & Quality's (AHRQ) Lexicon of Collaborative Care which provides theoretic justification for a paradigm case of collaborative care. We used the key clauses of the Lexicon to derive domains of integration and generate measures corresponding to those key clauses. After reviewing currently used methods for identifying collaborative care, or integration, and identifying the need to improve on them, we describe a national collaboration to describe and evaluate the PIP. We also describe its potential use in practice improvement, research, responsiveness to multiple stakeholder needs, and other future directions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Longitudinal comparative evaluation of the equivalence of an integrated peer-support and clinical staffing model for residential mental health rehabilitation: a mixed methods protocol incorporating multiple stakeholder perspectives.

PubMed

Parker, Stephen; Dark, Frances; Newman, Ellie; Korman, Nicole; Meurk, Carla; Siskind, Dan; Harris, Meredith

2016-06-02

A novel staffing model integrating peer support workers and clinical staff within a unified team is being trialled at community based residential rehabilitation units in Australia. A mixed-methods protocol for the longitudinal evaluation of the outcomes, expectations and experiences of care by consumers and staff under this staffing model in two units will be compared to one unit operating a traditional clinical staffing. The study is unique with regards to the context, the longitudinal approach and consideration of multiple stakeholder perspectives. The longitudinal mixed methods design integrates a quantitative evaluation of the outcomes of care for consumers at three residential rehabilitation units with an applied qualitative research methodology. The quantitative component utilizes a prospective cohort design to explore whether equivalent outcomes are achieved through engagement at residential rehabilitation units operating integrated and clinical staffing models. Comparative data will be available from the time of admission, discharge and 12-month period post-discharge from the units. Additionally, retrospective data for the 12-month period prior to admission will be utilized to consider changes in functioning pre and post engagement with residential rehabilitation care. The primary outcome will be change in psychosocial functioning, assessed using the total score on the Health of the Nation Outcome Scales (HoNOS). Planned secondary outcomes will include changes in symptomatology, disability, recovery orientation, carer quality of life, emergency department presentations, psychiatric inpatient bed days, and psychological distress and wellbeing. Planned analyses will include: cohort description; hierarchical linear regression modelling of the predictors of change in HoNOS following CCU care; and descriptive comparisons of the costs associated with the two staffing models. The qualitative component utilizes a pragmatic approach to grounded theory, with collection of data from consumers and staff at multiple time points exploring their expectations, experiences and reflections on the care provided by these services. It is expected that the new knowledge gained through this study will guide the adaptation of these and similar services. For example, if differential outcomes are achieved for consumers under the integrated and clinical staffing models this may inform staffing guidelines.
Unmanned aircraft system sense and avoid integrity and continuity

NASA Astrophysics Data System (ADS)

Jamoom, Michael B.

This thesis describes new methods to guarantee safety of sense and avoid (SAA) functions for Unmanned Aircraft Systems (UAS) by evaluating integrity and continuity risks. Previous SAA efforts focused on relative safety metrics, such as risk ratios, comparing the risk of using an SAA system versus not using it. The methods in this thesis evaluate integrity and continuity risks as absolute measures of safety, as is the established practice in commercial aircraft terminal area navigation applications. The main contribution of this thesis is a derivation of a new method, based on a standard intruder relative constant velocity assumption, that uses hazard state estimates and estimate error covariances to establish (1) the integrity risk of the SAA system not detecting imminent loss of '"well clear," which is the time and distance required to maintain safe separation from intruder aircraft, and (2) the probability of false alert, the continuity risk. Another contribution is applying these integrity and continuity risk evaluation methods to set quantifiable and certifiable safety requirements on sensors. A sensitivity analysis uses this methodology to evaluate the impact of sensor errors on integrity and continuity risks. The penultimate contribution is an integrity and continuity risk evaluation where the estimation model is refined to address realistic intruder relative linear accelerations, which goes beyond the current constant velocity standard. The final contribution is an integrity and continuity risk evaluation addressing multiple intruders. This evaluation is a new innovation-based method to determine the risk of mis-associating intruder measurements. A mis-association occurs when the SAA system incorrectly associates a measurement to the wrong intruder, causing large errors in the estimated intruder trajectories. The new methods described in this thesis can help ensure safe encounters between aircraft and enable SAA sensor certification for UAS integration into the National Airspace System.
Integrability: mathematical methods for studying solitary waves theory

NASA Astrophysics Data System (ADS)

Wazwaz, Abdul-Majid

2014-03-01

In recent decades, substantial experimental research efforts have been devoted to linear and nonlinear physical phenomena. In particular, studies of integrable nonlinear equations in solitary waves theory have attracted intensive interest from mathematicians, with the principal goal of fostering the development of new methods, and physicists, who are seeking solutions that represent physical phenomena and to form a bridge between mathematical results and scientific structures. The aim for both groups is to build up our current understanding and facilitate future developments, develop more creative results and create new trends in the rapidly developing field of solitary waves. The notion of the integrability of certain partial differential equations occupies an important role in current and future trends, but a unified rigorous definition of the integrability of differential equations still does not exist. For example, an integrable model in the Painlevé sense may not be integrable in the Lax sense. The Painlevé sense indicates that the solution can be represented as a Laurent series in powers of some function that vanishes on an arbitrary surface with the possibility of truncating the Laurent series at finite powers of this function. The concept of Lax pairs introduces another meaning of the notion of integrability. The Lax pair formulates the integrability of nonlinear equation as the compatibility condition of two linear equations. However, it was shown by many researchers that the necessary integrability conditions are the existence of an infinite series of generalized symmetries or conservation laws for the given equation. The existence of multiple soliton solutions often indicates the integrability of the equation but other tests, such as the Painlevé test or the Lax pair, are necessary to confirm the integrability for any equation. In the context of completely integrable equations, studies are flourishing because these equations are able to describe the real features in a variety of vital areas in science, technology and engineering. In recognition of the importance of solitary waves theory and the underlying concept of integrable equations, a variety of powerful methods have been developed to carry out the required analysis. Examples of such methods which have been advanced are the inverse scattering method, the Hirota bilinear method, the simplified Hirota method, the Bäcklund transformation method, the Darboux transformation, the Pfaffian technique, the Painlevé analysis, the generalized symmetry method, the subsidiary ordinary differential equation method, the coupled amplitude-phase formulation, the sine-cosine method, the sech-tanh method, the mapping and deformation approach and many new other methods. The inverse scattering method, viewed as a nonlinear analogue of the Fourier transform method, is a powerful approach that demonstrates the existence of soliton solutions through intensive computations. At the center of the theory of integrable equations lies the bilinear forms and Hirota's direct method, which can be used to obtain soliton solutions by using exponentials. The Bäcklund transformation method is a useful invariant transformation that transforms one solution into another of a differential equation. The Darboux transformation method is a well known tool in the theory of integrable systems. It is believed that there is a connection between the Bäcklund transformation and the Darboux transformation, but it is as yet not known. Archetypes of integrable equations are the Korteweg-de Vries (KdV) equation, the modified KdV equation, the sine-Gordon equation, the Schrödinger equation, the Vakhnenko equation, the KdV6 equation, the Burgers equation, the fifth-order Lax equation and many others. These equations yield soliton solutions, multiple soliton solutions, breather solutions, quasi-periodic solutions, kink solutions, homo-clinic solutions and other solutions as well. The couplings of linear and nonlinear equations were recently discovered and subsequently received considerable attention. The concept of couplings forms a new direction for developing innovative construction methods. The recently obtained results in solitary waves theory highlight new approaches for additional creative ideas, promising further achievements and increased progress in this field. We are grateful to all of the authors who accepted our invitation to contribute to this comment section.
Method and apparatus for simultaneous detection and measurement of charged particles at one or more levels of particle flux for analysis of same

DOEpatents

Denton, M Bonner [Tucson, AZ; Sperline, Roger , Koppenaal, David W. , Barinaga, Charles J. , Hieftje, Gary , Barnes, IV, James H.; Atlas, Eugene [Irvine, CA

2009-03-03

A charged particle detector and method are disclosed providing for simultaneous detection and measurement of charged particles at one or more levels of particle flux in a measurement cycle. The detector provides multiple and independently selectable levels of integration and/or gain in a fully addressable readout manner.
METAL COATED ARTICLES AND METHOD OF MAKING

DOEpatents

Eubank, L.D.

1958-08-26

A method for manufacturing a solid metallic uranium body having an integral multiple layer protective coating, comprising an inner uranium-aluminum alloy firmly bonded to the metallic uranium is presented. A third layer of silver-zinc alloy is bonded to the zinc-aluiminum layer and finally a fourth layer of lead-silver alloy is firmly bonded to the silver-zinc layer.
Integrating Multiple Criteria in Selection Procedures for Improving Student Quality and Reducing Cost Per Graduate. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Jones, Gerald L.; Westen, Risdon J.

The multivariate approach of canonical correlation was used to assess selection procedures of the Air Force Academy. It was felt that improved student selection methods might reduce the number of dropouts while maintaining or improving the quality of graduates. The method of canonical correlation was designed to maximize prediction of academic…
Fuzzy comprehensive evaluation of multiple environmental factors for swine building assessment and control.

PubMed

Xie, Qiuju; Ni, Ji-Qin; Su, Zhongbin

2017-10-15

In confined swine buildings, temperature, humidity, and air quality are all important for animal health and productivity. However, the current swine building environmental control is only based on temperature; and evaluation and control methods based on multiple environmental factors are needed. In this paper, fuzzy comprehensive evaluation (FCE) theory was adopted for multi-factor assessment of environmental quality in two commercial swine buildings using real measurement data. An assessment index system and membership functions were established; and predetermined weights were given using analytic hierarchy process (AHP) combined with knowledge of experts. The results show that multi-factors such as temperature, humidity, and concentrations of ammonia (NH 3 ), carbon dioxide (CO 2 ), and hydrogen sulfide (H 2 S) can be successfully integrated in FCE for swine building environment assessment. The FCE method has a high correlation coefficient of 0.737 compared with the method of single-factor evaluation (SFE). The FCE method can significantly increase the sensitivity and perform an effective and integrative assessment. It can be used as part of environmental controlling and warning systems for swine building environment management to improve swine production and welfare. Copyright © 2017 Elsevier B.V. All rights reserved.
Flexible Method for Inter-object Communication in C++

NASA Technical Reports Server (NTRS)

Curlett, Brian P.; Gould, Jack J.

1994-01-01

A method has been developed for organizing and sharing large amounts of information between objects in C++ code. This method uses a set of object classes to define variables and group them into tables. The variable tables presented here provide a convenient way of defining and cataloging data, as well as a user-friendly input/output system, a standardized set of access functions, mechanisms for ensuring data integrity, methods for interprocessor data transfer, and an interpretive language for programming relationships between parameters. The object-oriented nature of these variable tables enables the use of multiple data types, each with unique attributes and behavior. Because each variable provides its own access methods, redundant table lookup functions can be bypassed, thus decreasing access times while maintaining data integrity. In addition, a method for automatic reference counting was developed to manage memory safely.

Systematic genomic identification of colorectal cancer genes delineating advanced from early clinical stage and metastasis

PubMed Central

2013-01-01

Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539
Finite element area and line integral transforms for generalization of aperture function and geometry in Kirchhoff scalar diffraction theory

NASA Astrophysics Data System (ADS)

Kraus, Hal G.

1993-02-01

Two finite element-based methods for calculating Fresnel region and near-field region intensities resulting from diffraction of light by two-dimensional apertures are presented. The first is derived using the Kirchhoff area diffraction integral and the second is derived using a displaced vector potential to achieve a line integral transformation. The specific form of each of these formulations is presented for incident spherical waves and for Gaussian laser beams. The geometry of the two-dimensional diffracting aperture(s) is based on biquadratic isoparametric elements, which are used to define apertures of complex geometry. These elements are also used to build complex amplitude and phase functions across the aperture(s), which may be of continuous or discontinuous form. The finite element transform integrals are accurately and efficiently integrated numerically using Gaussian quadrature. The power of these methods is illustrated in several examples which include secondary obstructions, secondary spider supports, multiple mirror arrays, synthetic aperture arrays, apertures covered by screens, apodization, phase plates, and off-axis apertures. Typically, the finite element line integral transform results in significant gains in computational efficiency over the finite element Kirchhoff transform method, but is also subject to some loss in generality.
The FLIGHT Drosophila RNAi database

PubMed Central

Bursteinas, Borisas; Jain, Ekta; Gao, Qiong; Baum, Buzz; Zvelebil, Marketa

2010-01-01

FLIGHT (http://flight.icr.ac.uk/) is an online resource compiling data from high-throughput Drosophila in vivo and in vitro RNAi screens. FLIGHT includes details of RNAi reagents and their predicted off-target effects, alongside RNAi screen hits, scores and phenotypes, including images from high-content screens. The latest release of FLIGHT is designed to enable users to upload, analyze, integrate and share their own RNAi screens. Users can perform multiple normalizations, view quality control plots, detect and assign screen hits and compare hits from multiple screens using a variety of methods including hierarchical clustering. FLIGHT integrates RNAi screen data with microarray gene expression as well as genomic annotations and genetic/physical interaction datasets to provide a single interface for RNAi screen analysis and datamining in Drosophila. PMID:20855970
ProbFold: a probabilistic method for integration of probing data in RNA secondary structure prediction.

PubMed

Sahoo, Sudhakar; Świtnicki, Michał P; Pedersen, Jakob Skou

2016-09-01

Recently, new RNA secondary structure probing techniques have been developed, including Next Generation Sequencing based methods capable of probing transcriptome-wide. These techniques hold great promise for improving structure prediction accuracy. However, each new data type comes with its own signal properties and biases, which may even be experiment specific. There is therefore a growing need for RNA structure prediction methods that can be automatically trained on new data types and readily extended to integrate and fully exploit multiple types of data. Here, we develop and explore a modular probabilistic approach for integrating probing data in RNA structure prediction. It can be automatically trained given a set of known structures with probing data. The approach is demonstrated on SHAPE datasets, where we evaluate and selectively model specific correlations. The approach often makes superior use of the probing data signal compared to other methods. We illustrate the use of ProbFold on multiple data types using both simulations and a small set of structures with both SHAPE, DMS and CMCT data. Technically, the approach combines stochastic context-free grammars (SCFGs) with probabilistic graphical models. This approach allows rapid adaptation and integration of new probing data types. ProbFold is implemented in C ++. Models are specified using simple textual formats. Data reformatting is done using separate C ++ programs. Source code, statically compiled binaries for x86 Linux machines, C ++ programs, example datasets and a tutorial is available from http://moma.ki.au.dk/prj/probfold/ : jakob.skou@clin.au.dk Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Hunting down the chimera of multiple disciplinarity in conservation science.

PubMed

Pooley, Simon P; Mendelsohn, J Andrew; Milner-Gulland, E J

2014-02-01

The consensus is that both ecological and social factors are essential dimensions of conservation research and practice. However, much of the literature on multiple disciplinary collaboration focuses on the difficulties of undertaking it. This review of the challenges of conducting multiple disciplinary collaboration offers a framework for thinking about the diversity and complexity of this endeavor. We focused on conceptual challenges, of which 5 main categories emerged: methodological challenges, value judgments, theories of knowledge, disciplinary prejudices, and interdisciplinary communication. The major problems identified in these areas have proved remarkably persistent in the literature surveyed (c.1960-2012). Reasons for these failures to learn from past experience include the pressure to produce positive outcomes and gloss over disagreements, the ephemeral nature of many such projects and resulting lack of institutional memory, and the apparent complexity and incoherence of the endeavor. We suggest that multiple disciplinary collaboration requires conceptual integration among carefully selected multiple disciplinary team members united in investigating a shared problem or question. We outline a 9-point sequence of steps for setting up a successful multiple disciplinary project. This encompasses points on recruitment, involving stakeholders, developing research questions, negotiating power dynamics and hidden values and conceptual differences, explaining and choosing appropriate methods, developing a shared language, facilitating on-going communications, and discussing data integration and project outcomes. Although numerous solutions to the challenges of multiple disciplinary research have been proposed, lessons learned are often lost when projects end or experienced individuals move on. We urge multiple disciplinary teams to capture the challenges recognized, and solutions proposed, by their researchers while projects are in process. A database of well-documented case studies would showcase theories and methods from a variety of disciplines and their interactions, enable better comparative study and evaluation, and provide a useful resource for developing future projects and training multiple disciplinary researchers. © 2013 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.
Hunting Down the Chimera of Multiple Disciplinarity in Conservation Science

PubMed Central

POOLEY, SIMON P; MENDELSOHN, J ANDREW; MILNER-GULLAND, E J

2014-01-01

The consensus is that both ecological and social factors are essential dimensions of conservation research and practice. However, much of the literature on multiple disciplinary collaboration focuses on the difficulties of undertaking it. This review of the challenges of conducting multiple disciplinary collaboration offers a framework for thinking about the diversity and complexity of this endeavor. We focused on conceptual challenges, of which 5 main categories emerged: methodological challenges, value judgments, theories of knowledge, disciplinary prejudices, and interdisciplinary communication. The major problems identified in these areas have proved remarkably persistent in the literature surveyed (c.1960–2012). Reasons for these failures to learn from past experience include the pressure to produce positive outcomes and gloss over disagreements, the ephemeral nature of many such projects and resulting lack of institutional memory, and the apparent complexity and incoherence of the endeavor. We suggest that multiple disciplinary collaboration requires conceptual integration among carefully selected multiple disciplinary team members united in investigating a shared problem or question. We outline a 9-point sequence of steps for setting up a successful multiple disciplinary project. This encompasses points on recruitment, involving stakeholders, developing research questions, negotiating power dynamics and hidden values and conceptual differences, explaining and choosing appropriate methods, developing a shared language, facilitating on-going communications, and discussing data integration and project outcomes. Although numerous solutions to the challenges of multiple disciplinary research have been proposed, lessons learned are often lost when projects end or experienced individuals move on. We urge multiple disciplinary teams to capture the challenges recognized, and solutions proposed, by their researchers while projects are in process. A database of well-documented case studies would showcase theories and methods from a variety of disciplines and their interactions, enable better comparative study and evaluation, and provide a useful resource for developing future projects and training multiple disciplinary researchers. PMID:24299167
Pedagogical alternatives for triple integrals: moving towards more inclusive and personalized learning

NASA Astrophysics Data System (ADS)

Tisdell, Christopher C.

2018-07-01

This paper is based on the presumption that teaching multiple ways to solve the same problem has academic and social value. In particular, we argue that such a multifaceted approach to pedagogy moves towards an environment of more inclusive and personalized learning. From a mathematics education perspective, our discussion is framed around pedagogical approaches to triple integrals seen in a standard multivariable calculus curriculum. We present some critical perspectives regarding the dominant and long-standing approach to the teaching of triple integrals currently seen in hegemonic calculus textbooks; and we illustrate the need for more diverse pedagogical methods. Finally, we take a constructive position by introducing a new and alternate pedagogical approach to solve some of the classical problems involving triple integrals from the literature through a simple application of integration by parts. This pedagogical alternative for triple integrals is designed to question the dominant one-size-fits-all approach of rearranging the order of integration and the privileging of graphical methods; and to enable a shift towards a more inclusive, enhanced and personalized learning experience.
Rapid determination of moisture content in paper materials by multiple headspace extraction gas chromatography.

PubMed

Xie, Wei-Qi; Chai, Xin-Sheng

2016-04-22

This paper describes a new method for the rapid determination of the moisture content in paper materials. The method is based on multiple headspace extraction gas chromatography (MHE-GC) at a temperature above the boiling point of water, from which an integrated water loss from the tested sample due to evaporation can be measured and from which the moisture content in the sample can be determined. The results show that the new method has a good precision (with the relative standard deviation <0.96%), high sensitivity (the limit of quantitation=0.005%) and good accuracy (the relative differences <1.4%). Therefore, the method is quite suitable for many uses in research and industrial applications. Copyright © 2016 Elsevier B.V. All rights reserved.
Screen Space Ambient Occlusion Based Multiple Importance Sampling for Real-Time Rendering

NASA Astrophysics Data System (ADS)

Zerari, Abd El Mouméne; Babahenini, Mohamed Chaouki

2018-03-01

We propose a new approximation technique for accelerating the Global Illumination algorithm for real-time rendering. The proposed approach is based on the Screen-Space Ambient Occlusion (SSAO) method, which approximates the global illumination for large, fully dynamic scenes at interactive frame rates. Current algorithms that are based on the SSAO method suffer from difficulties due to the large number of samples that are required. In this paper, we propose an improvement to the SSAO technique by integrating it with a Multiple Importance Sampling technique that combines a stratified sampling method with an importance sampling method, with the objective of reducing the number of samples. Experimental evaluation demonstrates that our technique can produce high-quality images in real time and is significantly faster than traditional techniques.
Performance evaluation for volumetric segmentation of multiple sclerosis lesions using MATLAB and computing engine in the graphical processing unit (GPU)

NASA Astrophysics Data System (ADS)

Le, Anh H.; Park, Young W.; Ma, Kevin; Jacobs, Colin; Liu, Brent J.

2010-03-01

Multiple Sclerosis (MS) is a progressive neurological disease affecting myelin pathways in the brain. Multiple lesions in the white matter can cause paralysis and severe motor disabilities of the affected patient. To solve the issue of inconsistency and user-dependency in manual lesion measurement of MRI, we have proposed a 3-D automated lesion quantification algorithm to enable objective and efficient lesion volume tracking. The computer-aided detection (CAD) of MS, written in MATLAB, utilizes K-Nearest Neighbors (KNN) method to compute the probability of lesions on a per-voxel basis. Despite the highly optimized algorithm of imaging processing that is used in CAD development, MS CAD integration and evaluation in clinical workflow is technically challenging due to the requirement of high computation rates and memory bandwidth in the recursive nature of the algorithm. In this paper, we present the development and evaluation of using a computing engine in the graphical processing unit (GPU) with MATLAB for segmentation of MS lesions. The paper investigates the utilization of a high-end GPU for parallel computing of KNN in the MATLAB environment to improve algorithm performance. The integration is accomplished using NVIDIA's CUDA developmental toolkit for MATLAB. The results of this study will validate the practicality and effectiveness of the prototype MS CAD in a clinical setting. The GPU method may allow MS CAD to rapidly integrate in an electronic patient record or any disease-centric health care system.
Simultaneous reconstruction of multiple depth images without off-focus points in integral imaging using a graphics processing unit.

PubMed

Yi, Faliu; Lee, Jieun; Moon, Inkyu

2014-05-01

The reconstruction of multiple depth images with a ray back-propagation algorithm in three-dimensional (3D) computational integral imaging is computationally burdensome. Further, a reconstructed depth image consists of a focus and an off-focus area. Focus areas are 3D points on the surface of an object that are located at the reconstructed depth, while off-focus areas include 3D points in free-space that do not belong to any object surface in 3D space. Generally, without being removed, the presence of an off-focus area would adversely affect the high-level analysis of a 3D object, including its classification, recognition, and tracking. Here, we use a graphics processing unit (GPU) that supports parallel processing with multiple processors to simultaneously reconstruct multiple depth images using a lookup table containing the shifted values along the x and y directions for each elemental image in a given depth range. Moreover, each 3D point on a depth image can be measured by analyzing its statistical variance with its corresponding samples, which are captured by the two-dimensional (2D) elemental images. These statistical variances can be used to classify depth image pixels as either focus or off-focus points. At this stage, the measurement of focus and off-focus points in multiple depth images is also implemented in parallel on a GPU. Our proposed method is conducted based on the assumption that there is no occlusion of the 3D object during the capture stage of the integral imaging process. Experimental results have demonstrated that this method is capable of removing off-focus points in the reconstructed depth image. The results also showed that using a GPU to remove the off-focus points could greatly improve the overall computational speed compared with using a CPU.
A novel navigation method used in a ballistic missile

NASA Astrophysics Data System (ADS)

Qian, Hua-ming; Sun, Long; Cai, Jia-nan; Peng, Yu

2013-10-01

The traditional strapdown inertial/celestial integrated navigation method used in a ballistic missile cannot accurately estimate the accelerometer bias. It might cause a divergence of navigation errors. To solve this problem, a new navigation method named strapdown inertial/starlight refractive celestial integrated navigation is proposed. To verify the feasibility of the proposed method, a simulated program of a ballistic missile is presented. The simulation results indicated that, when multiple refraction stars are used, the proposed method can accurately estimate the accelerometer bias, and suppress the divergence of navigation errors completely. Specifically, in order to apply this method to a ballistic missile, a novel measurement equation based on stellar refraction was developed. Furthermore a method to calculate the number of refraction stars observed by the stellar sensor was given. Finally, the relationship between the number of refraction stars used and the navigation accuracy is analysed.
Integrative set enrichment testing for multiple omics platforms

PubMed Central

2011-01-01

Background Enrichment testing assesses the overall evidence of differential expression behavior of the elements within a defined set. When we have measured many molecular aspects, e.g. gene expression, metabolites, proteins, it is desirable to assess their differential tendencies jointly across platforms using an integrated set enrichment test. In this work we explore the properties of several methods for performing a combined enrichment test using gene expression and metabolomics as the motivating platforms. Results Using two simulation models we explored the properties of several enrichment methods including two novel methods: the logistic regression 2-degree of freedom Wald test and the 2-dimensional permutation p-value for the sum-of-squared statistics test. In relation to their univariate counterparts we find that the joint tests can improve our ability to detect results that are marginal univariately. We also find that joint tests improve the ranking of associated pathways compared to their univariate counterparts. However, there is a risk of Type I error inflation with some methods and self-contained methods lose specificity when the sets are not representative of underlying association. Conclusions In this work we show that consideration of data from multiple platforms, in conjunction with summarization via a priori pathway information, leads to increased power in detection of genomic associations with phenotypes. PMID:22118224
Fast two-stream method for computing diurnal-mean actinic flux in vertically inhomogeneous atmospheres

NASA Technical Reports Server (NTRS)

Filyushkin, V. V.; Madronich, S.; Brasseur, G. P.; Petropavlovskikh, I. V.

1994-01-01

Based on a derivation of the two-stream daytime-mean equations of radiative flux transfer, a method for computing the daytime-mean actinic fluxes in the absorbing and scattering vertically inhomogeneous atmosphere is suggested. The method applies direct daytime integration of the particular solutions of the two-stream approximations or the source functions. It is valid for any duration of period of averaging. The merit of the method is that the multiple scattering computation is carried out only once for the whole averaging period. It can be implemented with a number of widely used two-stream approximations. The method agrees with the results obtained with 200-point multiple scattering calculations. The method was also tested in runs with a 1-km cloud layer with optical depth of 10, as well as with aerosol background. Comparison of the results obtained for a cloud subdivided into 20 layers with those obtained for a one-layer cloud with the same optical parameters showed that direct integration of particular solutions possesses an 'analytical' accuracy. In the case of the source function interpolation, the actinic fluxes calculated above the one-layer and 20-layer clouds agreed within 1%-1.5%, while below the cloud they may differ up to 5% (in the worst case). The ways of enhancing the accuracy (in a 'two-stream sense') and computational efficiency of the method are discussed.
Methods for forecasting freight in uncertainty : time series analysis of multiple factors.

DOT National Transportation Integrated Search

2011-01-31

The main goal of this research was to analyze and more accurately model freight movement in : Alabama. Ultimately, the goal of this project was to provide an overall approach to the : integration of accurate freight models into transportation plans a...
Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

NASA Technical Reports Server (NTRS)

Solarna, David; Moser, Gabriele; Le Moigne-Stewart, Jacqueline; Serpico, Sebastiano B.

2017-01-01

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.
Passing messages between biological networks to refine predicted interactions.

PubMed

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net.
MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

PubMed Central

Nakayasu, Ernesto S.; Nicora, Carrie D.; Sims, Amy C.; Burnum-Johnson, Kristin E.; Kim, Young-Mo; Kyle, Jennifer E.; Matzke, Melissa M.; Shukla, Anil K.; Chu, Rosalie K.; Schepmoes, Athena A.; Jacobs, Jon M.; Baric, Ralph S.; Webb-Robertson, Bobbie-Jo; Smith, Richard D.

2016-01-01

ABSTRACT Integrative multi-omics analyses can empower more effective investigation and complete understanding of complex biological systems. Despite recent advances in a range of omics analyses, multi-omic measurements of the same sample are still challenging and current methods have not been well evaluated in terms of reproducibility and broad applicability. Here we adapted a solvent-based method, widely applied for extracting lipids and metabolites, to add proteomics to mass spectrometry-based multi-omics measurements. The metabolite, protein, and lipid extraction (MPLEx) protocol proved to be robust and applicable to a diverse set of sample types, including cell cultures, microbial communities, and tissues. To illustrate the utility of this protocol, an integrative multi-omics analysis was performed using a lung epithelial cell line infected with Middle East respiratory syndrome coronavirus, which showed the impact of this virus on the host glycolytic pathway and also suggested a role for lipids during infection. The MPLEx method is a simple, fast, and robust protocol that can be applied for integrative multi-omic measurements from diverse sample types (e.g., environmental, in vitro, and clinical). IMPORTANCE In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample. Author Video: An author video summary of this article is available. PMID:27822525
Integrated Main Propulsion System Performance Reconstruction Process/Models

NASA Technical Reports Server (NTRS)

Lopez, Eduardo; Elliott, Katie; Snell, Steven; Evans, Michael

2013-01-01

The Integrated Main Propulsion System (MPS) Performance Reconstruction process provides the MPS post-flight data files needed for postflight reporting to the project integration management and key customers to verify flight performance. This process/model was used as the baseline for the currently ongoing Space Launch System (SLS) work. The process utilizes several methodologies, including multiple software programs, to model integrated propulsion system performance through space shuttle ascent. It is used to evaluate integrated propulsion systems, including propellant tanks, feed systems, rocket engine, and pressurization systems performance throughout ascent based on flight pressure and temperature data. The latest revision incorporates new methods based on main engine power balance model updates to model higher mixture ratio operation at lower engine power levels.
Feature generation and representations for protein-protein interaction classification.

PubMed

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

Detecting and removing multiplicative spatial bias in high-throughput screening technologies.

PubMed

Caraus, Iurie; Mazoure, Bogdan; Nadon, Robert; Makarenkov, Vladimir

2017-10-15

Considerable attention has been paid recently to improve data quality in high-throughput screening (HTS) and high-content screening (HCS) technologies widely used in drug development and chemical toxicity research. However, several environmentally- and procedurally-induced spatial biases in experimental HTS and HCS screens decrease measurement accuracy, leading to increased numbers of false positives and false negatives in hit selection. Although effective bias correction methods and software have been developed over the past decades, almost all of these tools have been designed to reduce the effect of additive bias only. Here, we address the case of multiplicative spatial bias. We introduce three new statistical methods meant to reduce multiplicative spatial bias in screening technologies. We assess the performance of the methods with synthetic and real data affected by multiplicative spatial bias, including comparisons with current bias correction methods. We also describe a wider data correction protocol that integrates methods for removing both assay and plate-specific spatial biases, which can be either additive or multiplicative. The methods for removing multiplicative spatial bias and the data correction protocol are effective in detecting and cleaning experimental data generated by screening technologies. As our protocol is of a general nature, it can be used by researchers analyzing current or next-generation high-throughput screens. The AssayCorrector program, implemented in R, is available on CRAN. makarenkov.vladimir@uqam.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Neurocardiology: Therapeutic Implications for Cardiovascular Disease

PubMed Central

Goldstein, David S.

2016-01-01

SUMMARY The term “neurocardiology” refers to physiologic and pathophysiological interplays of the nervous and cardiovascular systems. This selective review provides an update about cardiovascular therapeutic implications of neurocardiology, with emphasis on disorders involving primary or secondary abnormalities of catecholamine systems. Concepts of scientific integrative medicine help understand these disorders. Scientific integrative medicine is not a treatment method or discipline but a way of thinking that applies systems concepts to acute and chronic disorders of regulation. Some of these concepts include stability by negative feedback regulation, multiple effectors, effector sharing, instability by positive feedback loops, allostasis, and allostatic load. Scientific integrative medicine builds on systems biology but is also distinct in several ways. A large variety of drugs and non-drug treatments are now available or under study for neurocardiologic disorders in which catecholamine systems are hyperfunctional or hypofunctional. The future of therapeutics in neurocardiology is not so much in new curative drugs as in applying scientific integrative medical ideas that take into account concurrent chronic degenerative disorders and interactions of multiple drug and non-drug treatments with each other and with those disorders. PMID:21108771
Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

PubMed Central

Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

2011-01-01

Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673
Privacy protection in surveillance systems based on JPEG DCT baseline compression and spectral domain watermarking

NASA Astrophysics Data System (ADS)

Sablik, Thomas; Velten, Jörg; Kummert, Anton

2015-03-01

An novel system for automatic privacy protection in digital media based on spectral domain watermarking and JPEG compression is described in the present paper. In a first step private areas are detected. Therefore a detection method is presented. The implemented method uses Haar cascades to detects faces. Integral images are used to speed up calculations and the detection. Multiple detections of one face are combined. Succeeding steps comprise embedding the data into the image as part of JPEG compression using spectral domain methods and protecting the area of privacy. The embedding process is integrated into and adapted to JPEG compression. A Spread Spectrum Watermarking method is used to embed the size and position of the private areas into the cover image. Different methods for embedding regarding their robustness are compared. Moreover the performance of the method concerning tampered images is presented.
Rationale, design and methods of the HEALTHY study behavior intervention component

USDA-ARS?s Scientific Manuscript database

HEALTHY was a multi-center primary prevention trial designed to reduce risk factors for type 2 diabetes in adolescents. Seven centers each recruited six middle schools that were randomized to either intervention or control. The HEALTHY intervention integrated multiple components in nutrition, physic...
An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on forest ecosystem services

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...
Multiple Metaphors: Teaching Tense and Aspect to English-Speakers.

ERIC Educational Resources Information Center

Cody, Karen

2000-01-01

This paper proposes a synthesis of instructional methods from both traditional/explicit grammar and learner-centered/constructivist camps that also incorporates many types of metaphors (abstract, visual, and kinesthetic) in order to lead learners from declarative to proceduralized to automatized knowledge. This integrative, synthetic approach…
Querying and Computing with BioCyc Databases

PubMed Central

Krummenacker, Markus; Paley, Suzanne; Mueller, Lukas; Yan, Thomas; Karp, Peter D.

2006-01-01

Summary We describe multiple methods for accessing and querying the complex and integrated cellular data in the BioCyc family of databases: access through multiple file formats, access through Application Program Interfaces (APIs) for LISP, Perl and Java, and SQL access through the BioWarehouse relational database. Availability The Pathway Tools software and 20 BioCyc DBs in Tiers 1 and 2 are freely available to academic users; fees apply to some types of commercial use. For download instructions see http://BioCyc.org/download.shtml PMID:15961440
Building Bridges to Integrate Care (BRIDGES): Incubating Health Service Innovation across the Continuum of Care for Patients with Multiple Chronic Conditions.

PubMed

Bhattacharyya, Onil; Schull, Michael; Shojania, Kaveh; Stergiopoulos, Vicky; Naglie, Gary; Webster, Fiona; Brandao, Ricardo; Mohammed, Tamara; Christian, Jennifer; Hawker, Gillian; Wilson, Lynn; Levinson, Wendy

2016-01-01

Integrating care for people with complex needs is challenging. Indeed, evidence of solutions is mixed, and therefore, well-designed, shared evaluation approaches are needed to create cumulative learning. The Toronto-based Building Bridges to Integrate Care (BRIDGES) collaborative provided resources to refine and test nine new models linking primary, hospital and community care. It used mixed methods, a cross-project meta-evaluation and shared outcome measures. Given the range of skills required to develop effective interventions, a novel incubator was used to test and spread opportunities for system integration that included operational expertise and support for evaluation and process improvement.
An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

PubMed

Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

2017-08-17

It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.
Integrating Multiple Intelligences in EFL/ESL Classrooms

ERIC Educational Resources Information Center

Bas, Gokhan

2008-01-01

This article deals with the integration of the theory of Multiple Intelligences in EFL/ESL classrooms. In this study, after the theory of multiple intelligences was presented shortly, the integration of this theory into English classrooms. Intelligence types in MI Theory were discussed and some possible application ways of these intelligence types…
Fully-relativistic full-potential multiple scattering theory: A pathology-free scheme

NASA Astrophysics Data System (ADS)

Liu, Xianglin; Wang, Yang; Eisenbach, Markus; Stocks, G. Malcolm

2018-03-01

The Green function plays an essential role in the Korringa-Kohn-Rostoker(KKR) multiple scattering method. In practice, it is constructed from the regular and irregular solutions of the local Kohn-Sham equation and robust methods exist for spherical potentials. However, when applied to a non-spherical potential, numerical errors from the irregular solutions give rise to pathological behaviors of the charge density at small radius. Here we present a full-potential implementation of the fully-relativistic KKR method to perform ab initio self-consistent calculation by directly solving the Dirac differential equations using the generalized variable phase (sine and cosine matrices) formalism Liu et al. (2016). The pathology around the origin is completely eliminated by carrying out the energy integration of the single-site Green function along the real axis. By using an efficient pole-searching technique to identify the zeros of the well-behaved Jost matrices, we demonstrated that this scheme is numerically stable and computationally efficient, with speed comparable to the conventional contour energy integration method, while free of the pathology problem of the charge density. As an application, this method is utilized to investigate the crystal structures of polonium and their bulk properties, which is challenging for a conventional real-energy scheme. The noble metals are also calculated, both as a test of our method and to study the relativistic effects.
A GPU-accelerated semi-implicit fractional step method for numerical solutions of incompressible Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Ha, Sanghyun; Park, Junshin; You, Donghyun

2017-11-01

Utility of the computational power of modern Graphics Processing Units (GPUs) is elaborated for solutions of incompressible Navier-Stokes equations which are integrated using a semi-implicit fractional-step method. Due to its serial and bandwidth-bound nature, the present choice of numerical methods is considered to be a good candidate for evaluating the potential of GPUs for solving Navier-Stokes equations using non-explicit time integration. An efficient algorithm is presented for GPU acceleration of the Alternating Direction Implicit (ADI) and the Fourier-transform-based direct solution method used in the semi-implicit fractional-step method. OpenMP is employed for concurrent collection of turbulence statistics on a CPU while Navier-Stokes equations are computed on a GPU. Extension to multiple NVIDIA GPUs is implemented using NVLink supported by the Pascal architecture. Performance of the present method is experimented on multiple Tesla P100 GPUs compared with a single-core Xeon E5-2650 v4 CPU in simulations of boundary-layer flow over a flat plate. Supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (Ministry of Science, ICT and Future Planning NRF-2016R1E1A2A01939553, NRF-2014R1A2A1A11049599, and Ministry of Trade, Industry and Energy 201611101000230).
Fully-relativistic full-potential multiple scattering theory: A pathology-free scheme

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

Liu, Xianglin; Wang, Yang; Eisenbach, Markus

The Green function plays an essential role in the Korringa–Kohn–Rostoker(KKR) multiple scattering method. In practice, it is constructed from the regular and irregular solutions of the local Kohn–Sham equation and robust methods exist for spherical potentials. However, when applied to a non-spherical potential, numerical errors from the irregular solutions give rise to pathological behaviors of the charge density at small radius. Here we present a full-potential implementation of the fully-relativistic KKR method to perform ab initio self-consistent calculation by directly solving the Dirac differential equations using the generalized variable phase (sine and cosine matrices) formalism Liu et al. (2016). Themore » pathology around the origin is completely eliminated by carrying out the energy integration of the single-site Green function along the real axis. Here, by using an efficient pole-searching technique to identify the zeros of the well-behaved Jost matrices, we demonstrated that this scheme is numerically stable and computationally efficient, with speed comparable to the conventional contour energy integration method, while free of the pathology problem of the charge density. As an application, this method is utilized to investigate the crystal structures of polonium and their bulk properties, which is challenging for a conventional real-energy scheme. The noble metals are also calculated, both as a test of our method and to study the relativistic effects.« less
Fully-relativistic full-potential multiple scattering theory: A pathology-free scheme

DOE PAGES

Liu, Xianglin; Wang, Yang; Eisenbach, Markus; ...

2017-10-28

The Green function plays an essential role in the Korringa–Kohn–Rostoker(KKR) multiple scattering method. In practice, it is constructed from the regular and irregular solutions of the local Kohn–Sham equation and robust methods exist for spherical potentials. However, when applied to a non-spherical potential, numerical errors from the irregular solutions give rise to pathological behaviors of the charge density at small radius. Here we present a full-potential implementation of the fully-relativistic KKR method to perform ab initio self-consistent calculation by directly solving the Dirac differential equations using the generalized variable phase (sine and cosine matrices) formalism Liu et al. (2016). Themore » pathology around the origin is completely eliminated by carrying out the energy integration of the single-site Green function along the real axis. Here, by using an efficient pole-searching technique to identify the zeros of the well-behaved Jost matrices, we demonstrated that this scheme is numerically stable and computationally efficient, with speed comparable to the conventional contour energy integration method, while free of the pathology problem of the charge density. As an application, this method is utilized to investigate the crystal structures of polonium and their bulk properties, which is challenging for a conventional real-energy scheme. The noble metals are also calculated, both as a test of our method and to study the relativistic effects.« less
From classical to quantum and back: Hamiltonian adaptive resolution path integral, ring polymer, and centroid molecular dynamics

NASA Astrophysics Data System (ADS)

Kreis, Karsten; Kremer, Kurt; Potestio, Raffaello; Tuckerman, Mark E.

2017-12-01

Path integral-based methodologies play a crucial role for the investigation of nuclear quantum effects by means of computer simulations. However, these techniques are significantly more demanding than corresponding classical simulations. To reduce this numerical effort, we recently proposed a method, based on a rigorous Hamiltonian formulation, which restricts the quantum modeling to a small but relevant spatial region within a larger reservoir where particles are treated classically. In this work, we extend this idea and show how it can be implemented along with state-of-the-art path integral simulation techniques, including path-integral molecular dynamics, which allows for the calculation of quantum statistical properties, and ring-polymer and centroid molecular dynamics, which allow the calculation of approximate quantum dynamical properties. To this end, we derive a new integration algorithm that also makes use of multiple time-stepping. The scheme is validated via adaptive classical-path-integral simulations of liquid water. Potential applications of the proposed multiresolution method are diverse and include efficient quantum simulations of interfaces as well as complex biomolecular systems such as membranes and proteins.
Using Systems Thinking to Frame the Evaluation of a Complex Educational Intervention

NASA Astrophysics Data System (ADS)

Kastens, K. A.; Baldassari, C.; DeLisi, J.; Manduca, C. A.

2014-12-01

InTeGrate (serc.carleton.edu/integrate/) is the geoscience component of NSF's STEM Talent Expansion Center program. As such, it is a $10M, 5 year effort, with dual goals of improving undergraduate STEM education and addressing an important national challenge, which in InTeGrate's case is environmental sustainability. InTeGrate is very complicated, involving five PI's, dozens of curriculum developers, scores of workshops and webinars, hundreds of faculty, and thousands of students. To get a handle on this complexity, the leadership team and evaluators are viewing project activities and outcomes through a system thinking lens, analogous to how geoscientists view the Earth system. For each major component of the project, we have a flowchart logic model that traces the flows of information, materials, influence, and people that are thought to result from project activities. As is to be expected in a complex system, individual activities are often influenced by multiple inputs and contribute to multiple outputs. The systems approach allows us to spot critical points in the system where evaluative probes are needed; for example, are workshops actually resulting in a flux of new people into roles of increased responsibility within InTeGrate as intended? InTeGrate is permeated with opportunities for participants to engage in assessment, reflection and peer-review. From a systems perspective, this evaluative culture can be seen as an effort to create reinforcing feedback loops for processes that advance InTeGrate's values. For example, assessment team members review draft instructional materials against a materials development rubric and coach developers through an iterative development cycle towards materials that embody InTeGrate's priorities. Of particular interest are flows of information or influence that may carry InTeGrate's impact outward in space and time beyond activities that are directly funded by the project. For example, positive experiences during materials development may influence developers' teaching practice such that they embed InTeGrate's methods into their teaching of non-InTeGrate materials and advocate for InTeGrate methods on their campuses. Only if such influence pathways exist will InTeGrate be able to achieve national and enduring impact.
The Born approximation, multiple scattering, and the butterfly algorithm

NASA Astrophysics Data System (ADS)

Martinez, Alejandro F.

Radar works by focusing a beam of light and seeing how long it takes to reflect. To see a large region the beam is pointed in different directions. The focus of the beam depends on the size of the antenna (called an aperture). Synthetic aperture radar (SAR) works by moving the antenna through some region of space. A fundamental assumption in SAR is that waves only bounce once. Several imaging algorithms have been designed using that assumption. The scattering process can be described by iterations of a badly behaving integral. Recently a method for efficiently evaluating these types of integrals has been developed. We will give a detailed implementation of this algorithm and apply it to study the multiple scattering effects in SAR using target estimates from single scattering algorithms.
Soft Somatosensitive Actuators via Embedded 3D Printing.

PubMed

Truby, Ryan L; Wehner, Michael; Grosskopf, Abigail K; Vogt, Daniel M; Uzel, Sebastien G M; Wood, Robert J; Lewis, Jennifer A

2018-04-01

Humans possess manual dexterity, motor skills, and other physical abilities that rely on feedback provided by the somatosensory system. Herein, a method is reported for creating soft somatosensitive actuators (SSAs) via embedded 3D printing, which are innervated with multiple conductive features that simultaneously enable haptic, proprioceptive, and thermoceptive sensing. This novel manufacturing approach enables the seamless integration of multiple ionically conductive and fluidic features within elastomeric matrices to produce SSAs with the desired bioinspired sensing and actuation capabilities. Each printed sensor is composed of an ionically conductive gel that exhibits both long-term stability and hysteresis-free performance. As an exemplar, multiple SSAs are combined into a soft robotic gripper that provides proprioceptive and haptic feedback via embedded curvature, inflation, and contact sensors, including deep and fine touch contact sensors. The multimaterial manufacturing platform enables complex sensing motifs to be easily integrated into soft actuating systems, which is a necessary step toward closed-loop feedback control of soft robots, machines, and haptic devices. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Anharmonic Rovibrational Partition Functions for Fluxional Species at High Temperatures via Monte Carlo Phase Space Integrals

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

Jasper, Ahren W.; Gruey, Zackery B.; Harding, Lawrence B.

Monte Carlo phase space integration (MCPSI) is used to compute full dimensional and fully anharmonic, but classical, rovibrational partition functions for 22 small- and medium-sized molecules and radicals. Several of the species considered here feature multiple minima and low-frequency nonlocal motions, and efficiently sampling these systems is facilitated using curvilinear (stretch, bend, and torsion) coordinates. The curvilinear coordinate MCPSI method is demonstrated to be applicable to the treatment of fluxional species with complex rovibrational structures and as many as 21 fully coupled rovibrational degrees of freedom. Trends in the computed anharmonicity corrections are discussed. For many systems, rovibrational anharmonicities atmore » elevated temperatures are shown to vary consistently with the number of degrees of freedom and with temperature once rovibrational coupling and torsional anharmonicity are accounted for. Larger corrections are found for systems with complex vibrational structures, such as systems with multiple large-amplitude modes and/or multiple minima.« less

Pooling Data from Multiple Longitudinal Studies: The Role of Item Response Theory in Integrative Data Analysis

PubMed Central

Curran, Patrick J.; Hussong, Andrea M.; Cai, Li; Huang, Wenjing; Chassin, Laurie; Sher, Kenneth J.; Zucker, Robert A.

2010-01-01

There are a number of significant challenges encountered when studying development over an extended period of time including subject attrition, changing measurement structures across group and developmental period, and the need to invest substantial time and money. Integrative data analysis is an emerging set of methodologies that overcomes many of the challenges of single sample designs through the pooling of data drawn from multiple existing developmental studies. This approach is characterized by a host of advantages, but this also introduces several new complexities that must be addressed prior to broad adoption by developmental researchers. In this paper we focus on methods for fitting measurement models and creating scale scores using data drawn from multiple longitudinal studies. We present findings from the analysis of repeated measures of internalizing symptomatology that were pooled from three existing developmental studies. We describe and demonstrate each step in the analysis and we conclude with a discussion of potential limitations and directions for future research. PMID:18331129
The impact of relative intensity noise on the signal in multiple reference optical coherence tomography

NASA Astrophysics Data System (ADS)

Neuhaus, Kai; Subhash, Hrebesh; Alexandrov, Sergey; Dsouza, Roshan; Hogan, Josh; Wilson, Carol; Leahy, Martin; Slepneva, Svetlana; Huyet, Guillaume

2016-03-01

Multiple reference optical coherence tomography (MR-OCT) applies a unique low-cost solution to enhance the scanning depth of standard time domain OCT by inserting an partial mirror into the reference arm of the interferometric system. This novel approach achieves multiple reflections for different layers and depths of an sample with minimal effort of engineering and provides an excellent platform for low-cost OCT systems based on well understood production methods for micro-mechanical systems such as CD/DVD pick-up systems. The direct integration of a superluminescent light-emitting diode (SLED) is a preferable solution to reduce the form- factor of an MR-OCT system. Such direct integration exposes the light source to environmental conditions that can increase fluctuations in heat dissipation and vibrations and affect the noise characteristics of the output spectrum. This work describes the impact of relative intensity noise (RIN) on the quality of the interference signal of MR-OCT related to a variety of environmental conditions, such as temperature.
Bayesian Estimation of Pneumonia Etiology: Epidemiologic Considerations and Applications to the Pneumonia Etiology Research for Child Health Study

PubMed Central

Fu, Wei; Shi, Qiyuan; Prosperi, Christine; Wu, Zhenke; Hammitt, Laura L.; Feikin, Daniel R.; Baggett, Henry C.; Howie, Stephen R.C.; Scott, J. Anthony G.; Murdoch, David R.; Madhi, Shabir A.; Thea, Donald M.; Brooks, W. Abdullah; Kotloff, Karen L.; Li, Mengying; Park, Daniel E.; Lin, Wenyi; Levine, Orin S.; O’Brien, Katherine L.; Zeger, Scott L.

2017-01-01

Abstract In pneumonia, specimens are rarely obtained directly from the infection site, the lung, so the pathogen causing infection is determined indirectly from multiple tests on peripheral clinical specimens, which may have imperfect and uncertain sensitivity and specificity, so inference about the cause is complex. Analytic approaches have included expert review of case-only results, case–control logistic regression, latent class analysis, and attributable fraction, but each has serious limitations and none naturally integrate multiple test results. The Pneumonia Etiology Research for Child Health (PERCH) study required an analytic solution appropriate for a case–control design that could incorporate evidence from multiple specimens from cases and controls and that accounted for measurement error. We describe a Bayesian integrated approach we developed that combined and extended elements of attributable fraction and latent class analyses to meet some of these challenges and illustrate the advantage it confers regarding the challenges identified for other methods. PMID:28575370
[Integral quantitative evaluation of working conditions in the construction industry].

PubMed

Guseĭnov, A A

1993-01-01

Present method evaluating the quality of environment (using MAC and MAL) does not enable to assess completely and objectively the work conditions of building industry due to multiple confounding elements. A solution to this complicated problem including the analysis of various correlating elements of the system "human--work conditions--environment" may be encouraged by social norm of morbidity, which is independent on industrial and natural environment. The complete integral assessment enables to see the whole situation and reveal the points at risk.
Quantitation of valve regurgitation severity by three-dimensional vena contracta area is superior to flow convergence method of quantitation on transesophageal echocardiography.

PubMed

Abudiab, Muaz M; Chao, Chieh-Ju; Liu, Shuang; Naqvi, Tasneem Z

2017-07-01

Quantitation of regurgitation severity using the proximal isovelocity acceleration (PISA) method to calculate effective regurgitant orifice (ERO) area has limitations. Measurement of three-dimensional (3D) vena contracta area (VCA) accurately grades mitral regurgitation (MR) severity on transthoracic echocardiography (TTE). We evaluated 3D VCA quantitation of regurgitant jet severity using 3D transesophageal echocardiography (TEE) in 110 native mitral, aortic, and tricuspid valves and six prosthetic valves in patients with at least mild valvular regurgitation. The ASE-recommended integrative method comprising semiquantitative and quantitative assessment of valvular regurgitation was used as a reference method, including ERO area by 2D PISA for assigning severity of regurgitation grade. Mean age was 62.2±14.4 years; 3D VCA quantitation was feasible in 91% regurgitant valves compared to 78% by the PISA method. When both methods were feasible and in the presence of a single regurgitant jet, 3D VCA and 2D PISA were similar in differentiating assigned severity (ANOVAP<.001). In valves with multiple jets, however, 3D VCA had a better correlation to assigned severity (ANOVAP<.0001). The agreement of 2D PISA and 3D VCA with the integrative method was 47% and 58% for moderate and 65% and 88% for severe regurgitation, respectively. Measurement of 3D VCA by TEE is superior to the 2D PISA method in determination of regurgitation severity in multiple native and prosthetic valves. © 2017, Wiley Periodicals, Inc.
Integrated mixed methods policy analysis for sustainable food systems: trends, challenges and future research.

PubMed

Cuevas, Soledad

Agriculture is a major contributor to greenhouse gas emissions, an important part of which is associated to deforestation and indirect land use change. Appropriate and coherent food policies can play an important role in aligning health, economic and environmental goals. From the point of view of policy analysis, however, this requires multi-sectoral, interdisciplinary approaches which can be highly complex. Important methodological advances in the area are not exempted from limitations and criticism. We argue that there is scope for further developments in integrated quantitative and qualitative policy analysis combining existing methods, including mathematical modelling and stakeholder analysis. We outline methodological trends in the field, briefly characterise integrated mixed methods policy analysis and identify contributions, challenges and opportunities for future research. In particular, this type of approach can help address issues of uncertainty and context-specific validity, incorporate multiple perspectives and help advance meaningful interdisciplinary collaboration in the field. Substantial challenges remain, however, such as the integration of key issues related to non-communicable disease, or the incorporation of a broader range of qualitative approaches that can address important cultural and ethical dimensions of food.
Integration of heterogeneous features for remote sensing scene classification

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.
Integrating multiple lines of evidence to assess biological hazards of complex mixtures: A case study in the Maumee River

EPA Science Inventory

Product Description:Due to technological improvements, increasing numbers of chemical contaminants are being detected in surface waters nation-wide, including the Great Lakes. Methods are needed to understand what impact these complex mixtures of contaminants can have on aquatic ...
Invited seminar, University of North Texas: An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...
An integrated eco-hydrologic modeling framework for assessing the effects of interacting stressors on forest ecosystem services - ESRP mtg

EPA Science Inventory

The U.S. Environmental Protection Agency recently established the Ecosystem Services Research Program to help formulate methods and models for conducting comprehensive risk assessments that quantify how multiple ecosystem services interact and respond in concert to environmental ...
Interdisciplinary Research Funding: Reaching Outside the Boundaries of Kinesiology

ERIC Educational Resources Information Center

Freedson, Patty

2009-01-01

Interdisciplinary research requires that experts from multiple disciplines work together to combine methods and ideas in an integrative fashion to generate new knowledge. In many respects, the field of kinesiology is ideally positioned to take advantage of its inherent multidisciplinary design. Because of the multidisciplinary structure of…
Fostering Inclusive Schools & Communities: A Public Relations Guide.

ERIC Educational Resources Information Center

Hammond, Marilyn; And Others

This guide provides instructions on implementing a low-budget public relations (PR) program to improve acceptance and integration of students with disabilities. Sixteen steps for a PR program and the use of multiple methods of publicity are outlined. Topics covered include: using appropriate terminology when writing or talking about disability…
Transmedia Teaching Framework: From Group Projects to Curriculum Development

ERIC Educational Resources Information Center

Reid, James; Gilardi, Filippo

2016-01-01

This paper describes an innovative project-based learning framework theoretically based on the ideas of Transmedia Storytelling, Participatory Cultures and Multiple intelligences that can be integrated into the f?lipped classroom method, and practically addressed using Content- Based Instruction (CBI) and Project-Based Learning (PBL) approaches.…
Finding Diego: A Bilingual Student Integrates School, Language, and Identity

ERIC Educational Resources Information Center

Danzak, Robin L.; Wilkinson, Louise C.

2017-01-01

This article presents a mixed-methods case study of Diego, a bilingual teen who completed public school in Florida. During adolescence, Diego negotiated multiple identities: successful student, Mexican American, bilingual, and typical U.S. teenager. Diego provided interviews and bilingual (English/Spanish) writing (narrative/expository) in 2008…
Integrating Computational Science Tools into a Thermodynamics Course

ERIC Educational Resources Information Center

Vieira, Camilo; Magana, Alejandra J.; García, R. Edwin; Jana, Aniruddha; Krafcik, Matthew

2018-01-01

Computational tools and methods have permeated multiple science and engineering disciplines, because they enable scientists and engineers to process large amounts of data, represent abstract phenomena, and to model and simulate complex concepts. In order to prepare future engineers with the ability to use computational tools in the context of…
Equality in Sport for Women.

ERIC Educational Resources Information Center

Geadelmann, Patricia L.; And Others

Essays concerning multiple aspects of integrating the concept of professional equality between the sexes into the field of sport are presented. The abstract idea of sexual equality is examined, and methods for determining the degree of equality present in given working situations are set forth. A discussion of the laws, enforcing agencies, and…
Personalised Care Plan Management Utilizing Guideline-Driven Clinical Decision Support Systems.

PubMed

Laleci Erturkmen, Gokce Banu; Yuksel, Mustafa; Sarigul, Bunyamin; Lilja, Mikael; Chen, Rong; Arvanitis, Theodoros N

2018-01-01

Older age is associated with an increased accumulation of multiple chronic conditions. The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. Integrated care is a means to address the growing demand for improved patient experience and health outcomes of multimorbid and long-term care patients. Care planning is a prevalent approach of integrated care, where the aim is to deliver more personalized and targeted care creating shared care plans by clearly articulating the role of each provider and patient in the care process. In this paper, we present a method and corresponding implementation of a semi-automatic care plan management tool, integrated with clinical decision support services which can seamlessly access and assess the electronic health records (EHRs) of the patient in comparison with evidence based clinical guidelines to suggest personalized recommendations for goals and interventions to be added to the individualized care plans.
Validating Measurement of Knowledge Integration in Science Using Multiple-Choice and Explanation Items

ERIC Educational Resources Information Center

Lee, Hee-Sun; Liu, Ou Lydia; Linn, Marcia C.

2011-01-01

This study explores measurement of a construct called knowledge integration in science using multiple-choice and explanation items. We use construct and instructional validity evidence to examine the role multiple-choice and explanation items plays in measuring students' knowledge integration ability. For construct validity, we analyze item…
Information Integration in Multiple Cue Judgment: A Division of Labor Hypothesis

ERIC Educational Resources Information Center

Juslin, Peter; Karlsson, Linnea; Olsson, Henrik

2008-01-01

There is considerable evidence that judgment is constrained to additive integration of information. The authors propose an explanation of why serial and additive cognitive integration can produce accurate multiple cue judgment both in additive and non-additive environments in terms of an adaptive division of labor between multiple representations.…
Integrated Forecast-Decision Systems For River Basin Planning and Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.

2005-12-01

A central application of climatology, meteorology, and hydrology is the generation of reliable forecasts for water resources management. In principle, effective use of forecasts could improve water resources management by providing extra protection against floods, mitigating the adverse effects of droughts, generating more hydropower, facilitating recreational activities, and minimizing the impacts of extreme events on the environment and the ecosystems. In practice, however, realization of these benefits depends on three requisite elements. First is the skill and reliability of forecasts. Second is the existence of decision support methods/systems with the ability to properly utilize forecast information. And third is the capacity of the institutional infrastructure to incorporate the information provided by the decision support systems into the decision making processes. This presentation discusses several decision support systems (DSS) using ensemble forecasting that have been developed by the Georgia Water Resources Institute for river basin management. These DSS are currently operational in Africa, Europe, and the US and address integrated water resources and energy planning and management in river basins with multiple water uses, multiple relevant temporal and spatial scales, and multiple decision makers. The article discusses the methods used and advocates that the design, development, and implementation of effective forecast-decision support systems must bring together disciplines, people, and institutions necessary to address today's complex water resources challenges.

Multiple point statistical simulation using uncertain (soft) conditional data

NASA Astrophysics Data System (ADS)

Hansen, Thomas Mejer; Vu, Le Thanh; Mosegaard, Klaus; Cordua, Knud Skou

2018-05-01

Geostatistical simulation methods have been used to quantify spatial variability of reservoir models since the 80s. In the last two decades, state of the art simulation methods have changed from being based on covariance-based 2-point statistics to multiple-point statistics (MPS), that allow simulation of more realistic Earth-structures. In addition, increasing amounts of geo-information (geophysical, geological, etc.) from multiple sources are being collected. This pose the problem of integration of these different sources of information, such that decisions related to reservoir models can be taken on an as informed base as possible. In principle, though difficult in practice, this can be achieved using computationally expensive Monte Carlo methods. Here we investigate the use of sequential simulation based MPS simulation methods conditional to uncertain (soft) data, as a computational efficient alternative. First, it is demonstrated that current implementations of sequential simulation based on MPS (e.g. SNESIM, ENESIM and Direct Sampling) do not account properly for uncertain conditional information, due to a combination of using only co-located information, and a random simulation path. Then, we suggest two approaches that better account for the available uncertain information. The first make use of a preferential simulation path, where more informed model parameters are visited preferentially to less informed ones. The second approach involves using non co-located uncertain information. For different types of available data, these approaches are demonstrated to produce simulation results similar to those obtained by the general Monte Carlo based approach. These methods allow MPS simulation to condition properly to uncertain (soft) data, and hence provides a computationally attractive approach for integration of information about a reservoir model.
Protein fold recognition using geometric kernel data fusion.

PubMed

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.
Disposable world-to-chip interface for digital microfluidics

DOEpatents

Van Dam, R. Michael; Shah, Gaurav; Keng, Pei-Yuin

2017-05-16

The present disclosure sets forth incorporating microfluidic chips interfaces for use with digital microfluidic processes. Methods and devices according to the present disclosure utilize compact, integrated platforms that interface with a chip upstream and downstream of the reaction, as well as between intermediate reaction steps if needed. In some embodiments these interfaces are automated, including automation of a multiple reagent process. Various reagent delivery systems and methods are also disclosed.
Validation of Digital Systems in Avionics and Flight Control Applications Handbook. Volume 1.

DTIC Science & Technology

1983-07-01

will also be available to Airways Facilities, Systems Research and Development Service, Air Traffic Control Service, and Flight Standards elements...2114, March 12-14, 1979. 3. Validation Methods Research for Fault-Tolerant Avionics and Control Systems-- *r Working Group Meeting II, NASA...command generation with the multiple methods becoming avail- able for closure of the outer control loop necessitates research on alternative integration
A semi-analytical method for near-trapped mode and fictitious frequencies of multiple scattering by an array of elliptical cylinders in water waves

NASA Astrophysics Data System (ADS)

Chen, Jeng-Tzong; Lee, Jia-Wei

2013-09-01

In this paper, we focus on the water wave scattering by an array of four elliptical cylinders. The null-field boundary integral equation method (BIEM) is used in conjunction with degenerate kernels and eigenfunctions expansion. The closed-form fundamental solution is expressed in terms of the degenerate kernel containing the Mathieu and the modified Mathieu functions in the elliptical coordinates. Boundary densities are represented by using the eigenfunction expansion. To avoid using the addition theorem to translate the Mathieu functions, the present approach can solve the water wave problem containing multiple elliptical cylinders in a semi-analytical manner by introducing the adaptive observer system. Regarding water wave problems, the phenomena of numerical instability of fictitious frequencies may appear when the BIEM/boundary element method (BEM) is used. Besides, the near-trapped mode for an array of four identical elliptical cylinders is observed in a special layout. Both physical (near-trapped mode) and mathematical (fictitious frequency) resonances simultaneously appear in the present paper for a water wave problem by an array of four identical elliptical cylinders. Two regularization techniques, the combined Helmholtz interior integral equation formulation (CHIEF) method and the Burton and Miller approach, are adopted to alleviate the numerical resonance due to fictitious frequency.
Integrative Analysis of High-throughput Cancer Studies with Contrasted Penalization

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Shia, BenChang; Ma, Shuangge

2015-01-01

In cancer studies with high-throughput genetic and genomic measurements, integrative analysis provides a way to effectively pool and analyze heterogeneous raw data from multiple independent studies and outperforms “classic” meta-analysis and single-dataset analysis. When marker selection is of interest, the genetic basis of multiple datasets can be described using the homogeneity model or the heterogeneity model. In this study, we consider marker selection under the heterogeneity model, which includes the homogeneity model as a special case and can be more flexible. Penalization methods have been developed in the literature for marker selection. This study advances from the published ones by introducing the contrast penalties, which can accommodate the within- and across-dataset structures of covariates/regression coefficients and, by doing so, further improve marker selection performance. Specifically, we develop a penalization method that accommodates the across-dataset structures by smoothing over regression coefficients. An effective iterative algorithm, which calls an inner coordinate descent iteration, is developed. Simulation shows that the proposed method outperforms the benchmark with more accurate marker identification. The analysis of breast cancer and lung cancer prognosis studies with gene expression measurements shows that the proposed method identifies genes different from those using the benchmark and has better prediction performance. PMID:24395534
Cholesky-decomposed density MP2 with density fitting: Accurate MP2 and double-hybrid DFT energies for large systems

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

Maurer, Simon A.; Clin, Lucien; Ochsenfeld, Christian, E-mail: christian.ochsenfeld@uni-muenchen.de

2014-06-14

Our recently developed QQR-type integral screening is introduced in our Cholesky-decomposed pseudo-densities Møller-Plesset perturbation theory of second order (CDD-MP2) method. We use the resolution-of-the-identity (RI) approximation in combination with efficient integral transformations employing sparse matrix multiplications. The RI-CDD-MP2 method shows an asymptotic cubic scaling behavior with system size and a small prefactor that results in an early crossover to conventional methods for both small and large basis sets. We also explore the use of local fitting approximations which allow to further reduce the scaling behavior for very large systems. The reliability of our method is demonstrated on test sets formore » interaction and reaction energies of medium sized systems and on a diverse selection from our own benchmark set for total energies of larger systems. Timings on DNA systems show that fast calculations for systems with more than 500 atoms are feasible using a single processor core. Parallelization extends the range of accessible system sizes on one computing node with multiple cores to more than 1000 atoms in a double-zeta basis and more than 500 atoms in a triple-zeta basis.« less
Multi-objective Decision Based Available Transfer Capability in Deregulated Power System Using Heuristic Approaches

NASA Astrophysics Data System (ADS)

Pasam, Gopi Krishna; Manohar, T. Gowri

2016-09-01

Determination of available transfer capability (ATC) requires the use of experience, intuition and exact judgment in order to meet several significant aspects in the deregulated environment. Based on these points, this paper proposes two heuristic approaches to compute ATC. The first proposed heuristic algorithm integrates the five methods known as continuation repeated power flow, repeated optimal power flow, radial basis function neural network, back propagation neural network and adaptive neuro fuzzy inference system to obtain ATC. The second proposed heuristic model is used to obtain multiple ATC values. Out of these, a specific ATC value will be selected based on a number of social, economic, deregulated environmental constraints and related to specific applications like optimization, on-line monitoring, and ATC forecasting known as multi-objective decision based optimal ATC. The validity of results obtained through these proposed methods are scrupulously verified on various buses of the IEEE 24-bus reliable test system. The results presented and derived conclusions in this paper are very useful for planning, operation, maintaining of reliable power in any power system and its monitoring in an on-line environment of deregulated power system. In this way, the proposed heuristic methods would contribute the best possible approach to assess multiple objective ATC using integrated methods.
An Automated Parallel Image Registration Technique Based on the Correlation of Wavelet Features

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Campbell, William J.; Cromp, Robert F.; Zukor, Dorothy (Technical Monitor)

2001-01-01

With the increasing importance of multiple platform/multiple remote sensing missions, fast and automatic integration of digital data from disparate sources has become critical to the success of these endeavors. Our work utilizes maxima of wavelet coefficients to form the basic features of a correlation-based automatic registration algorithm. Our wavelet-based registration algorithm is tested successfully with data from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) and the Landsat/Thematic Mapper(TM), which differ by translation and/or rotation. By the choice of high-frequency wavelet features, this method is similar to an edge-based correlation method, but by exploiting the multi-resolution nature of a wavelet decomposition, our method achieves higher computational speeds for comparable accuracies. This algorithm has been implemented on a Single Instruction Multiple Data (SIMD) massively parallel computer, the MasPar MP-2, as well as on the CrayT3D, the Cray T3E and a Beowulf cluster of Pentium workstations.
Testing for Divergent Transmission Histories among Cultural Characters: A Study Using Bayesian Phylogenetic Methods and Iranian Tribal Textile Data

PubMed Central

Matthews, Luke J.; Tehrani, Jamie J.; Jordan, Fiona M.; Collard, Mark; Nunn, Charles L.

2011-01-01

Background Archaeologists and anthropologists have long recognized that different cultural complexes may have distinct descent histories, but they have lacked analytical techniques capable of easily identifying such incongruence. Here, we show how Bayesian phylogenetic analysis can be used to identify incongruent cultural histories. We employ the approach to investigate Iranian tribal textile traditions. Methods We used Bayes factor comparisons in a phylogenetic framework to test two models of cultural evolution: the hierarchically integrated system hypothesis and the multiple coherent units hypothesis. In the hierarchically integrated system hypothesis, a core tradition of characters evolves through descent with modification and characters peripheral to the core are exchanged among contemporaneous populations. In the multiple coherent units hypothesis, a core tradition does not exist. Rather, there are several cultural units consisting of sets of characters that have different histories of descent. Results For the Iranian textiles, the Bayesian phylogenetic analyses supported the multiple coherent units hypothesis over the hierarchically integrated system hypothesis. Our analyses suggest that pile-weave designs represent a distinct cultural unit that has a different phylogenetic history compared to other textile characters. Conclusions The results from the Iranian textiles are consistent with the available ethnographic evidence, which suggests that the commercial rug market has influenced pile-rug designs but not the techniques or designs incorporated in the other textiles produced by the tribes. We anticipate that Bayesian phylogenetic tests for inferring cultural units will be of great value for researchers interested in studying the evolution of cultural traits including language, behavior, and material culture. PMID:21559083
Inquiry-based Instruction with Archived, Online Data: An Intervention Study with Preservice Teachers

NASA Astrophysics Data System (ADS)

Ucar, Sedat; Trundle, Kathy Cabe; Krissek, Lawrence

2011-03-01

This mixed methods study described preservice teachers' conceptions of tides and explored the efficacy of integrating online data into inquiry-based instruction. Data sources included a multiple-choice assessment and in-depth interviews. A total of 79 participants in secondary, middle, and early childhood teacher education programs completed the multiple-choice assessment of their baseline knowledge of tides-related concepts. A sub-group of 29 participants also was interviewed to explore their understanding of tides in more detail before instruction. Eighteen of those 29 teachers participated in the instruction, were interviewed again after the instruction, and completed the multiple-choice assessment as a posttest. The interview data sets were analyzed via a constant comparative method in order to produce profiles of each participant's pre- and post-instruction conceptual understandings of tides. Additional quantitative analysis consisted of a paired-sample t-test, which investigated the changes in scores before and after the instructional intervention. Before instruction, all participants held alternative or alternative fragments as their conceptual understandings of tides. After completing the inquiry-based instruction that integrated online tidal data, participants were more likely to hold a scientific conceptual understanding. After instruction, some preservice teachers continued to hold on to the conception that the rotation of the moon around the Earth during one 24-hour period causes the tides to move with the moon. The quantitative results, however, indicated that pre- to post-instruction gains were significant. The findings of this study provide evidence that integrating Web-based archived data into inquiry-based instruction can be used to effectively promote conceptual change among preservice teachers.
Decision making for best cogeneration power integration into a grid

NASA Astrophysics Data System (ADS)

Al Asmar, Joseph; Zakhia, Nadim; Kouta, Raed; Wack, Maxime

2016-07-01

Cogeneration systems are known to be efficient power systems for their ability to reduce pollution. Their integration into a grid requires simultaneous consideration of the economic and environmental challenges. Thus, an optimal cogeneration power are adopted to face such challenges. This work presents a novelty in selectinga suitable solution using heuristic optimization method. Its aim is to optimize the cogeneration capacity to be installed according to the economic and environmental concerns. This novelty is based on the sensitivity and data analysis method, namely, Multiple Linear Regression (MLR). This later establishes a compromise between power, economy, and pollution, which leads to find asuitable cogeneration power, and further, to be integrated into a grid. The data exploited were the results of the Genetic Algorithm (GA) multi-objective optimization. Moreover, the impact of the utility's subsidy on the selected power is shown.
Scale-adaptive compressive tracking with feature integration

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Jicheng; Chen, Xiao; Li, Shuxin

2016-05-01

Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.
Integrated structural control design of large space structures

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

Allen, J.J.; Lauffer, J.P.

1995-01-01

Active control of structures has been under intensive development for the last ten years. Reference 2 reviews much of the identification and control technology for structural control developed during this time. The technology was initially focused on space structure and weapon applications; however, recently the technology is also being directed toward applications in manufacturing and transportation. Much of this technology focused on multiple-input/multiple-output (MIMO) identification and control methodology because many of the applications require a coordinated control involving multiple disturbances and control objectives where multiple actuators and sensors are necessary for high performance. There have been many optimal robust controlmore » methods developed for the design of MIMO robust control laws; however, there appears to be a significant gap between the theoretical development and experimental evaluation of control and identification methods to address structural control applications. Many methods have been developed for MIMO identification and control of structures, such as the Eigensystem Realization Algorithm (ERA), Q-Markov Covariance Equivalent Realization (Q-Markov COVER) for identification; and, Linear Quadratic Gaussian (LQG), Frequency Weighted LQG and H-/ii-synthesis methods for control. Upon implementation, many of the identification and control methods have shown limitations such as the excitation of unmodelled dynamics and sensitivity to system parameter variations. As a result, research on methods which address these problems have been conducted.« less
Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios

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

Jarman, Kenneth D.; Brothers, Alan J.; Whitney, Paul D.

2010-06-06

The practice of choosing a single modeling paradigm for predictive analysis can limit the scope and relevance of predictions and their utility to decision-making processes. Considering multiple modeling methods simultaneously may improve this situation, but a better solution provides a framework for directly integrating different, potentially complementary modeling paradigms to enable more comprehensive modeling and predictions, and thus better-informed decisions. The primary challenges of this kind of model integration are to bridge language and conceptual gaps between modeling paradigms, and to determine whether natural and useful linkages can be made in a formal mathematical manner. To address these challenges inmore » the context of two specific modeling paradigms, we explore mathematical and computational options for linking System Dynamics (SD) and Bayesian network (BN) models and incorporating data into the integrated models. We demonstrate that integrated SD/BN models can naturally be described as either state space equations or Dynamic Bayes Nets, which enables the use of many existing computational methods for simulation and data integration. To demonstrate, we apply our model integration approach to techno-social models of insurgent-led attacks and security force counter-measures centered on improvised explosive devices.« less
Functional Module Analysis for Gene Coexpression Networks with Network Integration.

PubMed

Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

2015-01-01

Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.
Phenotypic integration and the evolution of signal repertoires: A case study of treefrog acoustic communication.

PubMed

Reichert, Michael S; Höbel, Gerlinde

2018-03-01

Animal signals are inherently complex phenotypes with many interacting parts combining to elicit responses from receivers. The pattern of interrelationships between signal components reflects the extent to which each component is expressed, and responds to selection, either in concert with or independently of others. Furthermore, many species have complex repertoires consisting of multiple signal types used in different contexts, and common morphological and physiological constraints may result in interrelationships extending across the multiple signals in species' repertoires. The evolutionary significance of interrelationships between signal traits can be explored within the framework of phenotypic integration, which offers a suite of quantitative techniques to characterize complex phenotypes. In particular, these techniques allow for the assessment of modularity and integration, which describe, respectively, the extent to which sets of traits covary either independently or jointly. Although signal and repertoire complexity are thought to be major drivers of diversification and social evolution, few studies have explicitly measured the phenotypic integration of signals to investigate the evolution of diverse communication systems. We applied methods from phenotypic integration studies to quantify integration in the two primary vocalization types (advertisement and aggressive calls) in the treefrogs Hyla versicolor , Hyla cinerea, and Dendropsophus ebraccatus . We recorded male calls and calculated standardized phenotypic variance-covariance ( P ) matrices for characteristics within and across call types. We found significant integration across call types, but the strength of integration varied by species and corresponded with the acoustic similarity of the call types within each species. H. versicolor had the most modular advertisement and aggressive calls and the least acoustically similar call types. Additionally, P was robust to changing social competition levels in H. versicolor . Our findings suggest new directions in animal communication research in which the complex relationships among the traits of multiple signals are a key consideration for understanding signal evolution.
An integrate-over-temperature approach for enhanced sampling.

PubMed

Gao, Yi Qin

2008-02-14

A simple method is introduced to achieve efficient random walking in the energy space in molecular dynamics simulations which thus enhances the sampling over a large energy range. The approach is closely related to multicanonical and replica exchange simulation methods in that it allows configurations of the system to be sampled in a wide energy range by making use of Boltzmann distribution functions at multiple temperatures. A biased potential is quickly generated using this method and is then used in accelerated molecular dynamics simulations.
Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.

PubMed

Brosch, Tom; Tang, Lisa Y W; Youngjin Yoo; Li, David K B; Traboulsee, Anthony; Tam, Roger

2016-05-01

We propose a novel segmentation approach based on deep 3D convolutional encoder networks with shortcut connections and apply it to the segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. Our model is a neural network that consists of two interconnected pathways, a convolutional pathway, which learns increasingly more abstract and higher-level image features, and a deconvolutional pathway, which predicts the final segmentation at the voxel level. The joint training of the feature extraction and prediction pathways allows for the automatic learning of features at different scales that are optimized for accuracy for any given combination of image types and segmentation task. In addition, shortcut connections between the two pathways allow high- and low-level features to be integrated, which enables the segmentation of lesions across a wide range of sizes. We have evaluated our method on two publicly available data sets (MICCAI 2008 and ISBI 2015 challenges) with the results showing that our method performs comparably to the top-ranked state-of-the-art methods, even when only relatively small data sets are available for training. In addition, we have compared our method with five freely available and widely used MS lesion segmentation methods (EMS, LST-LPA, LST-LGA, Lesion-TOADS, and SLS) on a large data set from an MS clinical trial. The results show that our method consistently outperforms these other methods across a wide range of lesion sizes.
An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

PubMed

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both local and global learning strategies, able to exploit the overall topology of the network. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

New methods for indexing multi-lattice diffraction data

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

Gildea, Richard J.; Waterman, David G.; CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA

2014-10-01

A new indexing method is presented which is capable of indexing multiple crystal lattices from narrow wedges of data. The efficacy of this method is demonstrated with both semi-synthetic multi-lattice data and real multi-lattice data recorded from microcrystals of ∼1 µm in size. A new indexing method is presented which is capable of indexing multiple crystal lattices from narrow wedges of diffraction data. The method takes advantage of a simplification of Fourier transform-based methods that is applicable when the unit-cell dimensions are known a priori. The efficacy of this method is demonstrated with both semi-synthetic multi-lattice data and real multi-latticemore » data recorded from crystals of ∼1 µm in size, where it is shown that up to six lattices can be successfully indexed and subsequently integrated from a 1° wedge of data. Analysis is presented which shows that improvements in data-quality indicators can be obtained through accurate identification and rejection of overlapping reflections prior to scaling.« less
Free-energy landscapes from adaptively biased methods: Application to quantum systems

NASA Astrophysics Data System (ADS)

Calvo, F.

2010-10-01

Several parallel adaptive biasing methods are applied to the calculation of free-energy pathways along reaction coordinates, choosing as a difficult example the double-funnel landscape of the 38-atom Lennard-Jones cluster. In the case of classical statistics, the Wang-Landau and adaptively biased molecular-dynamics (ABMD) methods are both found efficient if multiple walkers and replication and deletion schemes are used. An extension of the ABMD technique to quantum systems, implemented through the path-integral MD framework, is presented and tested on Ne38 against the quantum superposition method.
A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data.

PubMed

Vanegas, Fernando; Bratanov, Dmitry; Powell, Kevin; Weiss, John; Gonzalez, Felipe

2018-01-17

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used-the sensors, the UAV, and the flight operations-the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analising and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications.
Using "Omics" and Integrated Multi-Omics Approaches to Guide Probiotic Selection to Mitigate Chytridiomycosis and Other Emerging Infectious Diseases.

PubMed

Rebollar, Eria A; Antwis, Rachael E; Becker, Matthew H; Belden, Lisa K; Bletz, Molly C; Brucker, Robert M; Harrison, Xavier A; Hughey, Myra C; Kueneman, Jordan G; Loudon, Andrew H; McKenzie, Valerie; Medina, Daniel; Minbiole, Kevin P C; Rollins-Smith, Louise A; Walke, Jenifer B; Weiss, Sophie; Woodhams, Douglas C; Harris, Reid N

2016-01-01

Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called "omics," are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov-Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species.
Multiple and mixed methods in formative evaluation: Is more better? Reflections from a South African study.

PubMed

Odendaal, Willem; Atkins, Salla; Lewin, Simon

2016-12-15

Formative programme evaluations assess intervention implementation processes, and are seen widely as a way of unlocking the 'black box' of any programme in order to explore and understand why a programme functions as it does. However, few critical assessments of the methods used in such evaluations are available, and there are especially few that reflect on how well the evaluation achieved its objectives. This paper describes a formative evaluation of a community-based lay health worker programme for TB and HIV/AIDS clients across three low-income communities in South Africa. It assesses each of the methods used in relation to the evaluation objectives, and offers suggestions on ways of optimising the use of multiple, mixed-methods within formative evaluations of complex health system interventions. The evaluation's qualitative methods comprised interviews, focus groups, observations and diary keeping. Quantitative methods included a time-and-motion study of the lay health workers' scope of practice and a client survey. The authors conceptualised and conducted the evaluation, and through iterative discussions, assessed the methods used and their results. Overall, the evaluation highlighted programme issues and insights beyond the reach of traditional single methods evaluations. The strengths of the multiple, mixed-methods in this evaluation included a detailed description and nuanced understanding of the programme and its implementation, and triangulation of the perspectives and experiences of clients, lay health workers, and programme managers. However, the use of multiple methods needs to be carefully planned and implemented as this approach can overstretch the logistic and analytic resources of an evaluation. For complex interventions, formative evaluation designs including multiple qualitative and quantitative methods hold distinct advantages over single method evaluations. However, their value is not in the number of methods used, but in how each method matches the evaluation questions and the scientific integrity with which the methods are selected and implemented.
Integrative Analysis of Cancer Diagnosis Studies with Composite Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2013-01-01

Summary In cancer diagnosis studies, high-throughput gene profiling has been extensively conducted, searching for genes whose expressions may serve as markers. Data generated from such studies have the “large d, small n” feature, with the number of genes profiled much larger than the sample size. Penalization has been extensively adopted for simultaneous estimation and marker selection. Because of small sample sizes, markers identified from the analysis of single datasets can be unsatisfactory. A cost-effective remedy is to conduct integrative analysis of multiple heterogeneous datasets. In this article, we investigate composite penalization methods for estimation and marker selection in integrative analysis. The proposed methods use the minimax concave penalty (MCP) as the outer penalty. Under the homogeneity model, the ridge penalty is adopted as the inner penalty. Under the heterogeneity model, the Lasso penalty and MCP are adopted as the inner penalty. Effective computational algorithms based on coordinate descent are developed. Numerical studies, including simulation and analysis of practical cancer datasets, show satisfactory performance of the proposed methods. PMID:24578589
Optimization of fixture layouts of glass laser optics using multiple kernel regression.

PubMed

Su, Jianhua; Cao, Enhua; Qiao, Hong

2014-05-10

We aim to build an integrated fixturing model to describe the structural properties and thermal properties of the support frame of glass laser optics. Therefore, (a) a near global optimal set of clamps can be computed to minimize the surface shape error of the glass laser optic based on the proposed model, and (b) a desired surface shape error can be obtained by adjusting the clamping forces under various environmental temperatures based on the model. To construct the model, we develop a new multiple kernel learning method and call it multiple kernel support vector functional regression. The proposed method uses two layer regressions to group and order the data sources by the weights of the kernels and the factors of the layers. Because of that, the influences of the clamps and the temperature can be evaluated by grouping them into different layers.
Solving the problem of comparing whole bacterial genomes across different sequencing platforms.

PubMed

Kaas, Rolf S; Leekitcharoenphon, Pimlapas; Aarestrup, Frank M; Lund, Ole

2014-01-01

Whole genome sequencing (WGS) shows great potential for real-time monitoring and identification of infectious disease outbreaks. However, rapid and reliable comparison of data generated in multiple laboratories and using multiple technologies is essential. So far studies have focused on using one technology because each technology has a systematic bias making integration of data generated from different platforms difficult. We developed two different procedures for identifying variable sites and inferring phylogenies in WGS data across multiple platforms. The methods were evaluated on three bacterial data sets and sequenced on three different platforms (Illumina, 454, Ion Torrent). We show that the methods are able to overcome the systematic biases caused by the sequencers and infer the expected phylogenies. It is concluded that the cause of the success of these new procedures is due to a validation of all informative sites that are included in the analysis. The procedures are available as web tools.
Time-Series Analysis: Assessing the Effects of Multiple Educational Interventions in a Small-Enrollment Course

NASA Astrophysics Data System (ADS)

Warren, Aaron R.

2009-11-01

Time-series designs are an alternative to pretest-posttest methods that are able to identify and measure the impacts of multiple educational interventions, even for small student populations. Here, we use an instrument employing standard multiple-choice conceptual questions to collect data from students at regular intervals. The questions are modified by asking students to distribute 100 Confidence Points among the options in order to indicate the perceived likelihood of each answer option being the correct one. Tracking the class-averaged ratings for each option produces a set of time-series. ARIMA (autoregressive integrated moving average) analysis is then used to test for, and measure, changes in each series. In particular, it is possible to discern which educational interventions produce significant changes in class performance. Cluster analysis can also identify groups of students whose ratings evolve in similar ways. A brief overview of our methods and an example are presented.
Isolation with Migration Models for More Than Two Populations

PubMed Central

Hey, Jody

2010-01-01

A method for studying the divergence of multiple closely related populations is described and assessed. The approach of Hey and Nielsen (2007, Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proc Natl Acad Sci USA. 104:2785–2790) for fitting an isolation-with-migration model was extended to the case of multiple populations with a known phylogeny. Analysis of simulated data sets reveals the kinds of history that are accessible with a multipopulation analysis. Necessarily, processes associated with older time periods in a phylogeny are more difficult to estimate; and histories with high levels of gene flow are particularly difficult with more than two populations. However, for histories with modest levels of gene flow, or for very large data sets, it is possible to study large complex divergence problems that involve multiple closely related populations or species. PMID:19955477
Isolation with migration models for more than two populations.

PubMed

Hey, Jody

2010-04-01

A method for studying the divergence of multiple closely related populations is described and assessed. The approach of Hey and Nielsen (2007, Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proc Natl Acad Sci USA. 104:2785-2790) for fitting an isolation-with-migration model was extended to the case of multiple populations with a known phylogeny. Analysis of simulated data sets reveals the kinds of history that are accessible with a multipopulation analysis. Necessarily, processes associated with older time periods in a phylogeny are more difficult to estimate; and histories with high levels of gene flow are particularly difficult with more than two populations. However, for histories with modest levels of gene flow, or for very large data sets, it is possible to study large complex divergence problems that involve multiple closely related populations or species.
Embedded diagnostic, prognostic, and health management system and method for a humanoid robot

NASA Technical Reports Server (NTRS)

Barajas, Leandro G. (Inventor); Strawser, Philip A (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)

2013-01-01

A robotic system includes a humanoid robot with multiple compliant joints, each moveable using one or more of the actuators, and having sensors for measuring control and feedback data. A distributed controller controls the joints and other integrated system components over multiple high-speed communication networks. Diagnostic, prognostic, and health management (DPHM) modules are embedded within the robot at the various control levels. Each DPHM module measures, controls, and records DPHM data for the respective control level/connected device in a location that is accessible over the networks or via an external device. A method of controlling the robot includes embedding a plurality of the DPHM modules within multiple control levels of the distributed controller, using the DPHM modules to measure DPHM data within each of the control levels, and recording the DPHM data in a location that is accessible over at least one of the high-speed communication networks.
Entropy-Based Analysis and Bioinformatics-Inspired Integration of Global Economic Information Transfer

PubMed Central

An, Sungbae; Kwon, Young-Kyun; Yoon, Sungroh

2013-01-01

The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs) between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis. PMID:23300959
Electromagnetic pulsed thermography for natural cracks inspection

NASA Astrophysics Data System (ADS)

Gao, Yunlai; Tian, Gui Yun; Wang, Ping; Wang, Haitao; Gao, Bin; Woo, Wai Lok; Li, Kongjing

2017-02-01

Emerging integrated sensing and monitoring of material degradation and cracks are increasingly required for characterizing the structural integrity and safety of infrastructure. However, most conventional nondestructive evaluation (NDE) methods are based on single modality sensing which is not adequate to evaluate structural integrity and natural cracks. This paper proposed electromagnetic pulsed thermography for fast and comprehensive defect characterization. It hybrids multiple physical phenomena i.e. magnetic flux leakage, induced eddy current and induction heating linking to physics as well as signal processing algorithms to provide abundant information of material properties and defects. New features are proposed using 1st derivation that reflects multiphysics spatial and temporal behaviors to enhance the detection of cracks with different orientations. Promising results that robust to lift-off changes and invariant features for artificial and natural cracks detection have been demonstrated that the proposed method significantly improves defect detectability. It opens up multiphysics sensing and integrated NDE with potential impact for natural understanding and better quantitative evaluation of natural cracks including stress corrosion crack (SCC) and rolling contact fatigue (RCF).
Entropy-based analysis and bioinformatics-inspired integration of global economic information transfer.

PubMed

Kim, Jinkyu; Kim, Gunn; An, Sungbae; Kwon, Young-Kyun; Yoon, Sungroh

2013-01-01

The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs) between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis.
Unified framework for information integration based on information geometry

PubMed Central

Oizumi, Masafumi; Amari, Shun-ichi

2016-01-01

Assessment of causal influences is a ubiquitous and important subject across diverse research fields. Drawn from consciousness studies, integrated information is a measure that defines integration as the degree of causal influences among elements. Whereas pairwise causal influences between elements can be quantified with existing methods, quantifying multiple influences among many elements poses two major mathematical difficulties. First, overestimation occurs due to interdependence among influences if each influence is separately quantified in a part-based manner and then simply summed over. Second, it is difficult to isolate causal influences while avoiding noncausal confounding influences. To resolve these difficulties, we propose a theoretical framework based on information geometry for the quantification of multiple causal influences with a holistic approach. We derive a measure of integrated information, which is geometrically interpreted as the divergence between the actual probability distribution of a system and an approximated probability distribution where causal influences among elements are statistically disconnected. This framework provides intuitive geometric interpretations harmonizing various information theoretic measures in a unified manner, including mutual information, transfer entropy, stochastic interaction, and integrated information, each of which is characterized by how causal influences are disconnected. In addition to the mathematical assessment of consciousness, our framework should help to analyze causal relationships in complex systems in a complete and hierarchical manner. PMID:27930289
Improving membrane protein expression by optimizing integration efficiency

PubMed Central

2017-01-01

The heterologous overexpression of integral membrane proteins in Escherichia coli often yields insufficient quantities of purifiable protein for applications of interest. The current study leverages a recently demonstrated link between co-translational membrane integration efficiency and protein expression levels to predict protein sequence modifications that improve expression. Membrane integration efficiencies, obtained using a coarse-grained simulation approach, robustly predicted effects on expression of the integral membrane protein TatC for a set of 140 sequence modifications, including loop-swap chimeras and single-residue mutations distributed throughout the protein sequence. Mutations that improve simulated integration efficiency were 4-fold enriched with respect to improved experimentally observed expression levels. Furthermore, the effects of double mutations on both simulated integration efficiency and experimentally observed expression levels were cumulative and largely independent, suggesting that multiple mutations can be introduced to yield higher levels of purifiable protein. This work provides a foundation for a general method for the rational overexpression of integral membrane proteins based on computationally simulated membrane integration efficiencies. PMID:28918393
In vivo optical modulation of neural signals using monolithically integrated two-dimensional neural probe arrays

PubMed Central

Son, Yoojin; Jenny Lee, Hyunjoo; Kim, Jeongyeon; Shin, Hyogeun; Choi, Nakwon; Justin Lee, C.; Yoon, Eui-Sung; Yoon, Euisik; Wise, Kensall D.; Geun Kim, Tae; Cho, Il-Joo

2015-01-01

Integration of stimulation modalities (e.g. electrical, optical, and chemical) on a large array of neural probes can enable an investigation of important underlying mechanisms of brain disorders that is not possible through neural recordings alone. Furthermore, it is important to achieve this integration of multiple functionalities in a compact structure to utilize a large number of the mouse models. Here we present a successful optical modulation of in vivo neural signals of a transgenic mouse through our compact 2D MEMS neural array (optrodes). Using a novel fabrication method that embeds a lower cladding layer in a silicon substrate, we achieved a thin silicon 2D optrode array that is capable of delivering light to multiple sites using SU-8 as a waveguide core. Without additional modification to the microelectrodes, the measured impedance of the multiple microelectrodes was below 1 MΩ at 1 kHz. In addition, with a low background noise level (±25 μV), neural spikes from different individual neurons were recorded on each microelectrode. Lastly, we successfully used our optrodes to modulate the neural activity of a transgenic mouse through optical stimulation. These results demonstrate the functionality of the 2D optrode array and its potential as a next-generation tool for optogenetic applications. PMID:26494437
The need and approach for characterization - U.S. air force perspectives on materials state awareness

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Lindgren, Eric A.

2018-04-01

This paper expands on the objective and motivation for NDE-based characterization and includes a discussion of the current approach using model-assisted inversion being pursued within the Air Force Research Laboratory (AFRL). This includes a discussion of the multiple model-based methods that can be used, including physics-based models, deep machine learning, and heuristic approaches. The benefits and drawbacks of each method is reviewed and the potential to integrate multiple methods is discussed. Initial successes are included to highlight the ability to obtain quantitative values of damage. Additional steps remaining to realize this capability with statistical metrics of accuracy are discussed, and how these results can be used to enable probabilistic life management are addressed. The outcome of this initiative will realize the long-term desired capability of NDE methods to provide quantitative characterization to accelerate certification of new materials and enhance life management of engineered systems.
Improving Predictions of Multiple Binary Models in ILP

PubMed Central

2014-01-01

Despite the success of ILP systems in learning first-order rules from small number of examples and complexly structured data in various domains, they struggle in dealing with multiclass problems. In most cases they boil down a multiclass problem into multiple black-box binary problems following the one-versus-one or one-versus-rest binarisation techniques and learn a theory for each one. When evaluating the learned theories of multiple class problems in one-versus-rest paradigm particularly, there is a bias caused by the default rule toward the negative classes leading to an unrealistic high performance beside the lack of prediction integrity between the theories. Here we discuss the problem of using one-versus-rest binarisation technique when it comes to evaluating multiclass data and propose several methods to remedy this problem. We also illustrate the methods and highlight their link to binary tree and Formal Concept Analysis (FCA). Our methods allow learning of a simple, consistent, and reliable multiclass theory by combining the rules of the multiple one-versus-rest theories into one rule list or rule set theory. Empirical evaluation over a number of data sets shows that our proposed methods produce coherent and accurate rule models from the rules learned by the ILP system of Aleph. PMID:24696657

Integrated data analysis for genome-wide research.

PubMed

Steinfath, Matthias; Repsilber, Dirk; Scholz, Matthias; Walther, Dirk; Selbig, Joachim

2007-01-01

Integrated data analysis is introduced as the intermediate level of a systems biology approach to analyse different 'omics' datasets, i.e., genome-wide measurements of transcripts, protein levels or protein-protein interactions, and metabolite levels aiming at generating a coherent understanding of biological function. In this chapter we focus on different methods of correlation analyses ranging from simple pairwise correlation to kernel canonical correlation which were recently applied in molecular biology. Several examples are presented to illustrate their application. The input data for this analysis frequently originate from different experimental platforms. Therefore, preprocessing steps such as data normalisation and missing value estimation are inherent to this approach. The corresponding procedures, potential pitfalls and biases, and available software solutions are reviewed. The multiplicity of observations obtained in omics-profiling experiments necessitates the application of multiple testing correction techniques.
Jointly characterizing epigenetic dynamics across multiple human cell types

PubMed Central

An, Lin; Yue, Feng; Hardison, Ross C

2016-01-01

Advanced sequencing technologies have generated a plethora of data for many chromatin marks in multiple tissues and cell types, yet there is lack of a generalized tool for optimal utility of those data. A major challenge is to quantitatively model the epigenetic dynamics across both the genome and many cell types for understanding their impacts on differential gene regulation and disease. We introduce IDEAS, an integrative and discriminative epigenome annotation system, for jointly characterizing epigenetic landscapes in many cell types and detecting differential regulatory regions. A key distinction between our method and existing state-of-the-art algorithms is that IDEAS integrates epigenomes of many cell types simultaneously in a way that preserves the position-dependent and cell type-specific information at fine scales, thereby greatly improving segmentation accuracy and producing comparable annotations across cell types. PMID:27095202
Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

PubMed

Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

2016-01-01

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.
Multi-domain boundary element method for axi-symmetric layered linear acoustic systems

NASA Astrophysics Data System (ADS)

Reiter, Paul; Ziegelwanger, Harald

2017-12-01

Homogeneous porous materials like rock wool or synthetic foam are the main tool for acoustic absorption. The conventional absorbing structure for sound-proofing consists of one or multiple absorbers placed in front of a rigid wall, with or without air-gaps in between. Various models exist to describe these so called multi-layered acoustic systems mathematically for incoming plane waves. However, there is no efficient method to calculate the sound field in a half space above a multi layered acoustic system for an incoming spherical wave. In this work, an axi-symmetric multi-domain boundary element method (BEM) for absorbing multi layered acoustic systems and incoming spherical waves is introduced. In the proposed BEM formulation, a complex wave number is used to model absorbing materials as a fluid and a coordinate transformation is introduced which simplifies singular integrals of the conventional BEM to non-singular radial and angular integrals. The radial and angular part are integrated analytically and numerically, respectively. The output of the method can be interpreted as a numerical half space Green's function for grounds consisting of layered materials.
A high-order relaxation method with projective integration for solving nonlinear systems of hyperbolic conservation laws

NASA Astrophysics Data System (ADS)

Lafitte, Pauline; Melis, Ward; Samaey, Giovanni

2017-07-01

We present a general, high-order, fully explicit relaxation scheme which can be applied to any system of nonlinear hyperbolic conservation laws in multiple dimensions. The scheme consists of two steps. In a first (relaxation) step, the nonlinear hyperbolic conservation law is approximated by a kinetic equation with stiff BGK source term. Then, this kinetic equation is integrated in time using a projective integration method. After taking a few small (inner) steps with a simple, explicit method (such as direct forward Euler) to damp out the stiff components of the solution, the time derivative is estimated and used in an (outer) Runge-Kutta method of arbitrary order. We show that, with an appropriate choice of inner step size, the time step restriction on the outer time step is similar to the CFL condition for the hyperbolic conservation law. Moreover, the number of inner time steps is also independent of the stiffness of the BGK source term. We discuss stability and consistency, and illustrate with numerical results (linear advection, Burgers' equation and the shallow water and Euler equations) in one and two spatial dimensions.
THE NASOLABIAL FLAP: THE MOST VERSATILE METHOD IN FACIAL RECONSTRUCTION.

PubMed

Bayer, J; Schwarzmannová, K; Dušková, M; Novotná, K; Kníže, J; Sukop, A

2018-01-01

The nasolabial flap was described 170 years ago and still remains one of the most frequently used methods in facial reconstruction. This technically easy and maximally effective procedure has become a real workhorse and an integral instrument for every plastic surgeon. Over time multiple modifications of this technique have been described. In this article, authors present an overview of nasolabial flap modalities and discuss advantages and disadvantages of these techniques.
Video Analytics Evaluation: Survey of Datasets, Performance Metrics and Approaches

DTIC Science & Technology

2014-09-01

training phase and a fusion of the detector outputs. 6.3.1 Training Techniques 1. Bagging: The basic idea of Bagging is to train multiple classifiers...can reduce more noise interesting points. Person detection and background subtraction methods were used to create hot regions. The hot regions were...detection algorithms are incorporated with MHT to construct one integrated detector /tracker. 6.8 IRDS-CASIA team IRDS-CASIA proposed a method to solve a
A Preliminary Investigation on Improving Functional Communication Training by Mitigating Resurgence of Destructive Behavior

ERIC Educational Resources Information Center

Fuhrman, Ashley M.; Fisher, Wayne W.; Greer, Brian D.

2016-01-01

Despite the effectiveness and widespread use of functional communication training (FCT), resurgence of destructive behavior can occur if the functional communication response (FCR) contacts a challenge, such as lapses in treatment integrity. We evaluated a method to mitigate resurgence by conducting FCT using a multiple schedule of reinforcement…
Integrating Human Health and Environmental Health into the DPSIR Framework: A Tool to Identify Research Opportunities for Sustainable and Healthy Communities

EPA Science Inventory

The U.S. Environmental Protection Agency has recently realigned its research enterprise around the concept of sustainability. Scientists from across multiple disciplines have a role to play in contributing the information, methods, and tools to more fully understand the long-term...
20180311 - Development of a Tool for Systematic Integration of Traditional and New Approach Methods for Prioritizing Chemical Lists (SOT)

EPA Science Inventory

Multiple chemical regulatory bodies (US EPA, ECHA, OECD, Health Canada) are currently tasked with prioritizing chemicals for in-depth risk assessments. These prioritization efforts are driven by the fact that there are many chemicals in commerce, or in the environment for which d...
Research-Based Worksheets on Using Multiple Representations in Science Classrooms

ERIC Educational Resources Information Center

Hill, Matthew; Sharma, Manjula

2015-01-01

The ability to represent the world like a scientist is difficult to teach; it is more than simply knowing the representations (e.g., graphs, words, equations and diagrams). For meaningful science learning to take place, consideration needs to be given to explicitly integrating representations into instructional methods, linked to the content, and…
Development of a Tool for Systematic Integration of Traditional and New Approach Methods for Prioritizing Chemical Lists

EPA Science Inventory

Multiple chemical regulatory bodies (US EPA, ECHA, OECD, Health Canada) are currently tasked with prioritizing chemicals for in-depth risk assessments. These prioritization efforts are driven by the fact that there are many chemicals in commerce, or in the environment for which d...
Cyber Portfolio: The Innovative Menu for 21st Century Technology

ERIC Educational Resources Information Center

Robles, Ava Clare Marie O.

2012-01-01

Cyber portfolio is a valuable innovative menu for teachers who seek out strategies or methods to integrate technology into their lessons. This paper presents a straightforward preparation on how to innovate a menu that addresses the 21st century skills blended with higher order thinking skills, multiple intelligence, technology and multimedia.…
Understanding Genetic Toxicity Through Data Mining: The Process of Building Knowledge by Integrating Multiple Genetic Toxicity Databases

EPA Science Inventory

This paper demonstrates the usefulness of representing a chemical by its structural features and the use of these features to profile a battery of tests rather than relying on a single toxicity test of a given chemical. This paper presents data mining/profiling methods applied in...
Testing the TIDE: Examining the Nature of Students' Epistemic Beliefs Using a Multiple Methods Approach

ERIC Educational Resources Information Center

Muis, Krista R.; Trevors, Gregory; Duffy, Melissa; Ranellucci, John; Foy, Michael J.

2016-01-01

The purpose of this study was to empirically scrutinize Muis, Bendixen, and Haerle's (2006) Theory of Integrated Domains in Epistemology framework. Secondary, college, undergraduate, and graduate students completed self-reports designed to measure their domain-specific and domain-general epistemic beliefs for mathematics, psychology, and general…
JOINT AND INDIVIDUAL VARIATION EXPLAINED (JIVE) FOR INTEGRATED ANALYSIS OF MULTIPLE DATA TYPES.

PubMed

Lock, Eric F; Hoadley, Katherine A; Marron, J S; Nobel, Andrew B

2013-03-01

Research in several fields now requires the analysis of datasets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Cancer Genome Atlas (TCGA) includes data from several diverse genomic technologies on the same cancerous tumor samples. In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such datasets. The decomposition consists of three terms: a low-rank approximation capturing joint variation across data types, low-rank approximations for structured variation individual to each data type, and residual noise. JIVE quantifies the amount of joint variation between data types, reduces the dimensionality of the data, and provides new directions for the visual exploration of joint and individual structure. The proposed method represents an extension of Principal Component Analysis and has clear advantages over popular two-block methods such as Canonical Correlation Analysis and Partial Least Squares. A JIVE analysis of gene expression and miRNA data on Glioblastoma Multiforme tumor samples reveals gene-miRNA associations and provides better characterization of tumor types.
Magnetic steering control of multi-cellular bio-hybrid microswimmers.

PubMed

Carlsen, Rika Wright; Edwards, Matthew R; Zhuang, Jiang; Pacoret, Cecile; Sitti, Metin

2014-10-07

Bio-hybrid devices, which integrate biological cells with synthetic components, have opened a new path in miniaturized systems with the potential to provide actuation and control for systems down to a few microns in size. Here, we address the challenge of remotely controlling bio-hybrid microswimmers propelled by multiple bacterial cells. These devices have been proposed as a viable method for targeted drug delivery but have also been shown to exhibit stochastic motion. We demonstrate a method of remote magnetic control that significantly reduces the stochasticity of the motion, enabling steering control. The demonstrated microswimmers consist of multiple Serratia marcescens (S. marcescens) bacteria attached to a 6 μm-diameter superparamagnetic bead. We characterize their motion and define the parameters governing their controllability. We show that the microswimmers can be controlled along two-dimensional (2-D) trajectories using weak magnetic fields (≤10 mT) and can achieve 2-D swimming speeds up to 7.3 μm s(-1). This magnetic steering approach can be integrated with sensory-based steering in future work, enabling new control strategies for bio-hybrid microsystems.
Dynamic equilibrium strategy for drought emergency temporary water transfer and allocation management

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Ma, Ning; Lv, Chengwei

2016-08-01

Efficient water transfer and allocation are critical for disaster mitigation in drought emergencies. This is especially important when the different interests of the multiple decision makers and the fluctuating water resource supply and demand simultaneously cause space and time conflicts. To achieve more effective and efficient water transfers and allocations, this paper proposes a novel optimization method with an integrated bi-level structure and a dynamic strategy, in which the bi-level structure works to deal with space dimension conflicts in drought emergencies, and the dynamic strategy is used to deal with time dimension conflicts. Combining these two optimization methods, however, makes calculation complex, so an integrated interactive fuzzy program and a PSO-POA are combined to develop a hybrid-heuristic algorithm. The successful application of the proposed model in a real world case region demonstrates its practicality and efficiency. Dynamic cooperation between multiple reservoirs under the coordination of a global regulator reflects the model's efficiency and effectiveness in drought emergency water transfer and allocation, especially in a fluctuating environment. On this basis, some corresponding management recommendations are proposed to improve practical operations.
Passing Messages between Biological Networks to Refine Predicted Interactions

PubMed Central

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net. PMID:23741402
A multiplex microplatform for the detection of multiple DNA methylation events using gold-DNA affinity.

PubMed

Sina, Abu Ali Ibn; Foster, Matthew Thomas; Korbie, Darren; Carrascosa, Laura G; Shiddiky, Muhammad J A; Gao, Jing; Dey, Shuvashis; Trau, Matt

2017-10-07

We report a new multiplexed strategy for the electrochemical detection of regional DNA methylation across multiple regions. Using the sequence dependent affinity of bisulfite treated DNA towards gold surfaces, the method integrates the high sensitivity of a micro-fabricated multiplex device comprising a microarray of gold electrodes, with the powerful multiplexing capability of multiplex-PCR. The synergy of this combination enables the monitoring of the methylation changes across several genomic regions simultaneously from as low as 500 pg μl -1 of DNA with no sequencing requirement.

Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content

PubMed Central

Kling, Teresia; Johansson, Patrik; Sanchez, José; Marinescu, Voichita D.; Jörnsten, Rebecka; Nelander, Sven

2015-01-01

Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool (cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets. PMID:25953855
Learning to rank atlases for multiple-atlas segmentation.

PubMed

Sanroma, Gerard; Wu, Guorong; Gao, Yaozong; Shen, Dinggang

2014-10-01

Recently, multiple-atlas segmentation (MAS) has achieved a great success in the medical imaging area. The key assumption is that multiple atlases have greater chances of correctly labeling a target image than a single atlas. However, the problem of atlas selection still remains unexplored. Traditionally, image similarity is used to select a set of atlases. Unfortunately, this heuristic criterion is not necessarily related to the final segmentation performance. To solve this seemingly simple but critical problem, we propose a learning-based atlas selection method to pick up the best atlases that would lead to a more accurate segmentation. Our main idea is to learn the relationship between the pairwise appearance of observed instances (i.e., a pair of atlas and target images) and their final labeling performance (e.g., using the Dice ratio). In this way, we select the best atlases based on their expected labeling accuracy. Our atlas selection method is general enough to be integrated with any existing MAS method. We show the advantages of our atlas selection method in an extensive experimental evaluation in the ADNI, SATA, IXI, and LONI LPBA40 datasets. As shown in the experiments, our method can boost the performance of three widely used MAS methods, outperforming other learning-based and image-similarity-based atlas selection methods.
An integrated framework for detecting suspicious behaviors in video surveillance

NASA Astrophysics Data System (ADS)

Zin, Thi Thi; Tin, Pyke; Hama, Hiromitsu; Toriu, Takashi

2014-03-01

In this paper, we propose an integrated framework for detecting suspicious behaviors in video surveillance systems which are established in public places such as railway stations, airports, shopping malls and etc. Especially, people loitering in suspicion, unattended objects left behind and exchanging suspicious objects between persons are common security concerns in airports and other transit scenarios. These involve understanding scene/event, analyzing human movements, recognizing controllable objects, and observing the effect of the human movement on those objects. In the proposed framework, multiple background modeling technique, high level motion feature extraction method and embedded Markov chain models are integrated for detecting suspicious behaviors in real time video surveillance systems. Specifically, the proposed framework employs probability based multiple backgrounds modeling technique to detect moving objects. Then the velocity and distance measures are computed as the high level motion features of the interests. By using an integration of the computed features and the first passage time probabilities of the embedded Markov chain, the suspicious behaviors in video surveillance are analyzed for detecting loitering persons, objects left behind and human interactions such as fighting. The proposed framework has been tested by using standard public datasets and our own video surveillance scenarios.
Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11

PubMed Central

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-01-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. PMID:26369671
“I see it now”: Using photo elicitation to understand chronic illness self-management

PubMed Central

Fritz, Heather; Lysack, Cathy

2018-01-01

Background How people integrate self-management into daily life remains underexamined, and such processes are difficult to elicit through traditional approaches used to understand human occupation. Purpose This paper will provide a brief overview of one visual research method, photo elicitation, that holds promise for studying self-management of health behaviours and will present findings from an analysis of how the use of photo elicitation interviews contributed additional insights into self-management beyond those generated from the data collected through the other methods used in the study. Method A qualitative, multiple-methods, multiple-case study was conducted with a purposive sample of 10 low-income women ages 40 to 64 with type 2 diabetes. Findings The photo elicitation interviews contributed insights beyond those generated from other study methods about how individuals viewed their self-management behaviours and how occupations changed across time. Implications Photo elicitation is a valuable research method for better understanding clients' chronic illness self-management practices. PMID:29898501
Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions.

PubMed

Salis, Howard; Kaznessis, Yiannis

2005-02-01

The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.
A microfluidic device integrating dual CMOS polysilicon nanowire sensors for on-chip whole blood processing and simultaneous detection of multiple analytes.

PubMed

Kuan, Da-Han; Wang, I-Shun; Lin, Jiun-Rue; Yang, Chao-Han; Huang, Chi-Hsien; Lin, Yen-Hung; Lin, Chih-Ting; Huang, Nien-Tsu

2016-08-02

The hemoglobin-A1c test, measuring the ratio of glycated hemoglobin (HbA1c) to hemoglobin (Hb) levels, has been a standard assay in diabetes diagnosis that removes the day-to-day glucose level variation. Currently, the HbA1c test is restricted to hospitals and central laboratories due to the laborious, time-consuming whole blood processing and bulky instruments. In this paper, we have developed a microfluidic device integrating dual CMOS polysilicon nanowire sensors (MINS) for on-chip whole blood processing and simultaneous detection of multiple analytes. The micromachined polymethylmethacrylate (PMMA) microfluidic device consisted of a serpentine microchannel with multiple dam structures designed for non-lysed cells or debris trapping, uniform plasma/buffer mixing and dilution. The CMOS-fabricated polysilicon nanowire sensors integrated with the microfluidic device were designed for the simultaneous, label-free electrical detection of multiple analytes. Our study first measured the Hb and HbA1c levels in 11 clinical samples via these nanowire sensors. The results were compared with those of standard Hb and HbA1c measurement methods (Hb: the sodium lauryl sulfate hemoglobin detection method; HbA1c: cation-exchange high-performance liquid chromatography) and showed comparable outcomes. Finally, we successfully demonstrated the efficacy of the MINS device's on-chip whole blood processing followed by simultaneous Hb and HbA1c measurement in a clinical sample. Compared to current Hb and HbA1c sensing instruments, the MINS platform is compact and can simultaneously detect two analytes with only 5 μL of whole blood, which corresponds to a 300-fold blood volume reduction. The total assay time, including the in situ sample processing and analyte detection, was just 30 minutes. Based on its on-chip whole blood processing and simultaneous multiple analyte detection functionalities with a lower sample volume requirement and shorter process time, the MINS device can be effectively applied to real-time diabetes diagnostics and monitoring in point-of-care settings.
Heterogeneous Monolithic Integration of Single-Crystal Organic Materials.

PubMed

Park, Kyung Sun; Baek, Jangmi; Park, Yoonkyung; Lee, Lynn; Hyon, Jinho; Koo Lee, Yong-Eun; Shrestha, Nabeen K; Kang, Youngjong; Sung, Myung Mo

2017-02-01

Manufacturing high-performance organic electronic circuits requires the effective heterogeneous integration of different nanoscale organic materials with uniform morphology and high crystallinity in a desired arrangement. In particular, the development of high-performance organic electronic and optoelectronic devices relies on high-quality single crystals that show optimal intrinsic charge-transport properties and electrical performance. Moreover, the heterogeneous integration of organic materials on a single substrate in a monolithic way is highly demanded for the production of fundamental organic electronic components as well as complex integrated circuits. Many of the various methods that have been designed to pattern multiple heterogeneous organic materials on a substrate and the heterogeneous integration of organic single crystals with their crystal growth are described here. Critical issues that have been encountered in the development of high-performance organic integrated electronics are also addressed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A New Combinatorial Optimization Approach for Integrated Feature Selection Using Different Datasets: A Prostate Cancer Transcriptomic Study

PubMed Central

Puthiyedth, Nisha; Riveros, Carlos; Berretta, Regina; Moscato, Pablo

2015-01-01

Background The joint study of multiple datasets has become a common technique for increasing statistical power in detecting biomarkers obtained from smaller studies. The approach generally followed is based on the fact that as the total number of samples increases, we expect to have greater power to detect associations of interest. This methodology has been applied to genome-wide association and transcriptomic studies due to the availability of datasets in the public domain. While this approach is well established in biostatistics, the introduction of new combinatorial optimization models to address this issue has not been explored in depth. In this study, we introduce a new model for the integration of multiple datasets and we show its application in transcriptomics. Methods We propose a new combinatorial optimization problem that addresses the core issue of biomarker detection in integrated datasets. Optimal solutions for this model deliver a feature selection from a panel of prospective biomarkers. The model we propose is a generalised version of the (α,β)-k-Feature Set problem. We illustrate the performance of this new methodology via a challenging meta-analysis task involving six prostate cancer microarray datasets. The results are then compared to the popular RankProd meta-analysis tool and to what can be obtained by analysing the individual datasets by statistical and combinatorial methods alone. Results Application of the integrated method resulted in a more informative signature than the rank-based meta-analysis or individual dataset results, and overcomes problems arising from real world datasets. The set of genes identified is highly significant in the context of prostate cancer. The method used does not rely on homogenisation or transformation of values to a common scale, and at the same time is able to capture markers associated with subgroups of the disease. PMID:26106884
Identification of quality markers of Yuanhu Zhitong tablets based on integrative pharmacology and data mining.

PubMed

Li, Ke; Li, Junfang; Su, Jin; Xiao, Xuefeng; Peng, Xiujuan; Liu, Feng; Li, Defeng; Zhang, Yi; Chong, Tao; Xu, Haiyu; Liu, Changxiao; Yang, Hongjun

2018-03-07

The quality evaluation of traditional Chinese medicine (TCM) formulations is needed to guarantee the safety and efficacy. In our laboratory, we established interaction rules between chemical quality control and biological activity evaluations to study Yuanhu Zhitong tablets (YZTs). Moreover, a quality marker (Q-marker) has recently been proposed as a new concept in the quality control of TCM. However, no appropriate methods are available for the identification of Q-markers from the complex TCM systems. We aimed to use an integrative pharmacological (IP) approach to further identify Q-markers from YZTs through the integration of multidisciplinary knowledge. In addition, data mining was used to determine the correlation between multiple constituents of this TCM and its bioactivity to improve quality control. The IP approach was used to identify the active constituents of YZTs and elucidate the molecular mechanisms by integrating chemical and biosynthetic analyses, drug metabolism, and network pharmacology. Data mining methods including grey relational analysis (GRA) and least squares support vector machine (LS-SVM) regression techniques, were used to establish the correlations among the constituents and efficacy, and dose efficacy in multiple dimensions. Seven constituents (tetrahydropalmatine, α-allocryptopine, protopine, corydaline, imperatorin, isoimperatorin, and byakangelicin) were identified as Q-markers of YZT using IP based on their high abundance, specific presence in the individual herbal constituents and the product, appropriate drug-like properties, and critical contribution to the bioactivity of the mixture of YZT constituents. Moreover, three Q-markers (protopine, α-allocryptopine, and corydaline) were highly correlated with the multiple bioactivities of the YZTs, as found using data mining. Finally, three constituents (tetrahydropalmatine, corydaline, and imperatorin) were chosen as minimum combinations that both distinguished the authentic components from false products and indicated the intensity of bioactivity to improve the quality control of YZTs. Tetrahydropalmatine, imperatorin, and corydaline could be used as minimum combinations to effectively control the quality of YZTs. Copyright © 2018. Published by Elsevier GmbH.
An integrative framework to reevaluate the Neotropical catfish genus Guyanancistrus (Siluriformes: Loricariidae) with particular emphasis on the Guyanancistrus brevispinis complex.

PubMed

Fisch-Muller, Sonia; Mol, Jan H A; Covain, Raphaël

2018-01-01

Characterizing and naming species becomes more and more challenging due to the increasing difficulty of accurately delineating specific bounderies. In this context, integrative taxonomy aims to delimit taxonomic units by leveraging the complementarity of multiple data sources (geography, morphology, genetics, etc.). However, while the theoretical framework of integrative taxonomy has been explicitly stated, methods for the simultaneous analysis of multiple data sets are poorly developed and in many cases different information sources are still explored successively. Multi-table methods developed in the field of community ecology provide such an intregrative framework. In particular, multiple co-inertia analysis is flexible enough to allow the integration of morphological, distributional, and genetic data in the same analysis. We have applied this powerfull approach to delimit species boundaries in a group of poorly differentiated catfishes belonging to the genus Guyanancistrus from the Guianas region of northeastern South America. Because the species G. brevispinis has been claimed to be a species complex consisting of five species, particular attention was paid to taxon. Separate analyses indicated the presence of eight distinct species of Guyanancistrus, including five new species and one new genus. However, none of the preliminary analyses revealed different lineages within G. brevispinis, and the multi-table analysis revealed three intraspecific lineages. After taxonomic clarifications and description of the new genus, species and subspecies, a reappraisal of the biogeography of Guyanancistrus members was performed. This analysis revealed three distinct dispersals from the Upper reaches of Amazonian tributaries toward coastal rivers of the Eastern Guianas Ecoregion. The central role played by the Maroni River, as gateway from the Amazon basin, was confirmed. The Maroni River was also found to be a center of speciation for Guyanancistrus (with three species and two subspecies), as well as a source of dispersal of G. brevispinis toward the other main basins of the Eastern Guianas.
An integrative framework to reevaluate the Neotropical catfish genus Guyanancistrus (Siluriformes: Loricariidae) with particular emphasis on the Guyanancistrus brevispinis complex

PubMed Central

Fisch-Muller, Sonia; Mol, Jan H. A.

2018-01-01

Characterizing and naming species becomes more and more challenging due to the increasing difficulty of accurately delineating specific bounderies. In this context, integrative taxonomy aims to delimit taxonomic units by leveraging the complementarity of multiple data sources (geography, morphology, genetics, etc.). However, while the theoretical framework of integrative taxonomy has been explicitly stated, methods for the simultaneous analysis of multiple data sets are poorly developed and in many cases different information sources are still explored successively. Multi-table methods developed in the field of community ecology provide such an intregrative framework. In particular, multiple co-inertia analysis is flexible enough to allow the integration of morphological, distributional, and genetic data in the same analysis. We have applied this powerfull approach to delimit species boundaries in a group of poorly differentiated catfishes belonging to the genus Guyanancistrus from the Guianas region of northeastern South America. Because the species G. brevispinis has been claimed to be a species complex consisting of five species, particular attention was paid to taxon. Separate analyses indicated the presence of eight distinct species of Guyanancistrus, including five new species and one new genus. However, none of the preliminary analyses revealed different lineages within G. brevispinis, and the multi-table analysis revealed three intraspecific lineages. After taxonomic clarifications and description of the new genus, species and subspecies, a reappraisal of the biogeography of Guyanancistrus members was performed. This analysis revealed three distinct dispersals from the Upper reaches of Amazonian tributaries toward coastal rivers of the Eastern Guianas Ecoregion. The central role played by the Maroni River, as gateway from the Amazon basin, was confirmed. The Maroni River was also found to be a center of speciation for Guyanancistrus (with three species and two subspecies), as well as a source of dispersal of G. brevispinis toward the other main basins of the Eastern Guianas. PMID:29298344
Integration of Attributes from Non-Linear Characterization of Cardiovascular Time-Series for Prediction of Defibrillation Outcomes

PubMed Central

Shandilya, Sharad; Kurz, Michael C.; Ward, Kevin R.; Najarian, Kayvan

2016-01-01

Objective The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR), rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA) patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals. Materials and Methods Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF) was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI) model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA) technique. Results 358 defibrillations were evaluated (218 unsuccessful and 140 successful). Non-linear properties (Lyapunov exponent > 0) of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity) outperformed AMSA (53.6% sensitivity). At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity. Conclusion At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations. Addition of partial end-tidal carbon dioxide (PetCO2) signal improves accuracy and sensitivity of the MDI prediction model. PMID:26741805
Ultrasonography of the biliary tract - up to date. The importance of correlation between imaging methods and patients' signs and symptoms.

PubMed

Badea, Radu; Zaro, Răzvan; Tanțău, Marcel; Chiorean, Liliana

2015-09-01

Ultrasonography is generally accepted and performed as a first choice imaging technique in patients with jaundice. The method allows the discrimination between cholestatic and mechanical jaundice. The existing procedures are multiple: gray scale, Doppler, i.v. contrast enhancement, elastography, tridimensional ultrasonography, each of these with different contribution to the positive and differential diagnosis regarding the nature of the jaundice. The final diagnosis is a multimodal one and the efficiency is dependent on the level of the available technology, the examiner's experience, the degree and modality of integration of the data within the clinical context, as well as on the portfolio of available imaging procedures. This review shows the main ultrasonographic methods consecrated in the evaluation of the biliary tree. It also underlines the integrated character of the procedures, as well as the necessity to correlate with other imaging methods and the clinical situation.
Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume

2013-01-01

Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.
NASA Integrated Network COOP

NASA Technical Reports Server (NTRS)

Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

2012-01-01

Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.
Stochastic sampling of quadrature grids for the evaluation of vibrational expectation values

NASA Astrophysics Data System (ADS)

López Ríos, Pablo; Monserrat, Bartomeu; Needs, Richard J.

2018-02-01

The thermal lines method for the evaluation of vibrational expectation values of electronic observables [B. Monserrat, Phys. Rev. B 93, 014302 (2016), 10.1103/PhysRevB.93.014302] was recently proposed as a physically motivated approximation offering balance between the accuracy of direct Monte Carlo integration and the low computational cost of using local quadratic approximations. In this paper we reformulate thermal lines as a stochastic implementation of quadrature-grid integration, analyze the analytical form of its bias, and extend the method to multiple-point quadrature grids applicable to any factorizable harmonic or anharmonic nuclear wave function. The bias incurred by thermal lines is found to depend on the local form of the expectation value, and we demonstrate that the use of finer quadrature grids along selected modes can eliminate this bias, while still offering an ˜30 % lower computational cost than direct Monte Carlo integration in our tests.
A nano grating tunable MEMS optical filter for high-speed on-chip multispectral fluorescent detection.

PubMed

Truxal, Steven C; Huang, Nien-Tsu; Kurabayashi, Katsuo

2009-01-01

We report a microelectromechanical (MEMS) tunable optical filter and its integration in a fluorescence microscope for high speed on-chip spectral measurements. This integration allows for measurements of any fluorescence sample placed onto the microscope stage. We demonstrate the system capabilities by taking spectral measurements of multicolor fluorescent beads and fluorescently labeled cells passing through a microfluidic cytometer. The system has applications in biological studies where the measurement of multiple fluorescent peaks is restricted by the detection method's speed and sensitivity.
Integrable generalizations of non-linear multiple three-wave interaction models

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

1989-07-01

Integrable generalizations of multiple three-wave interaction models in terms of r-matrix formulation are investigated. The Lax representations, complete sets of first integrals in involution are constructed, the quantization leading to Gaudin's models is discussed.
Non-parametric combination and related permutation tests for neuroimaging.

PubMed

Winkler, Anderson M; Webster, Matthew A; Brooks, Jonathan C; Tracey, Irene; Smith, Stephen M; Nichols, Thomas E

2016-04-01

In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well-known definition of union-intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume-based representations of the brain, including non-imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non-parametric combination (NPC) methodology, such that instead of a two-phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one-way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

NASA Astrophysics Data System (ADS)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.
A Location Method Using Sensor Arrays for Continuous Gas Leakage in Integrally Stiffened Plates Based on the Acoustic Characteristics of the Stiffener

PubMed Central

Bian, Xu; Li, Yibo; Feng, Hao; Wang, Jiaqiang; Qi, Lei; Jin, Shijiu

2015-01-01

This paper proposes a continuous leakage location method based on the ultrasonic array sensor, which is specific to continuous gas leakage in a pressure container with an integral stiffener. This method collects the ultrasonic signals generated from the leakage hole through the piezoelectric ultrasonic sensor array, and analyzes the space-time correlation of every collected signal in the array. Meanwhile, it combines with the method of frequency compensation and superposition in time domain (SITD), based on the acoustic characteristics of the stiffener, to obtain a high-accuracy location result on the stiffener wall. According to the experimental results, the method successfully solves the orientation problem concerning continuous ultrasonic signals generated from leakage sources, and acquires high accuracy location information on the leakage source using a combination of multiple sets of orienting results. The mean value of location absolute error is 13.51 mm on the one-square-meter plate with an integral stiffener (4 mm width; 20 mm height; 197 mm spacing), and the maximum location absolute error is generally within a ±25 mm interval. PMID:26404316
Approaches to Mixed Methods Dissemination and Implementation Research: Methods, Strengths, Caveats, and Opportunities.

PubMed

Green, Carla A; Duan, Naihua; Gibbons, Robert D; Hoagwood, Kimberly E; Palinkas, Lawrence A; Wisdom, Jennifer P

2015-09-01

Limited translation of research into practice has prompted study of diffusion and implementation, and development of effective methods of encouraging adoption, dissemination and implementation. Mixed methods techniques offer approaches for assessing and addressing processes affecting implementation of evidence-based interventions. We describe common mixed methods approaches used in dissemination and implementation research, discuss strengths and limitations of mixed methods approaches to data collection, and suggest promising methods not yet widely used in implementation research. We review qualitative, quantitative, and hybrid approaches to mixed methods dissemination and implementation studies, and describe methods for integrating multiple methods to increase depth of understanding while improving reliability and validity of findings.
Approaches to Mixed Methods Dissemination and Implementation Research: Methods, Strengths, Caveats, and Opportunities

PubMed Central

Green, Carla A.; Duan, Naihua; Gibbons, Robert D.; Hoagwood, Kimberly E.; Palinkas, Lawrence A.; Wisdom, Jennifer P.

2015-01-01

Limited translation of research into practice has prompted study of diffusion and implementation, and development of effective methods of encouraging adoption, dissemination and implementation. Mixed methods techniques offer approaches for assessing and addressing processes affecting implementation of evidence-based interventions. We describe common mixed methods approaches used in dissemination and implementation research, discuss strengths and limitations of mixed methods approaches to data collection, and suggest promising methods not yet widely used in implementation research. We review qualitative, quantitative, and hybrid approaches to mixed methods dissemination and implementation studies, and describe methods for integrating multiple methods to increase depth of understanding while improving reliability and validity of findings. PMID:24722814
A Serviced-based Approach to Connect Seismological Infrastructures: Current Efforts at the IRIS DMC

NASA Astrophysics Data System (ADS)

Ahern, Tim; Trabant, Chad

2014-05-01

As part of the COOPEUS initiative to build infrastructure that connects European and US research infrastructures, IRIS has advocated for the development of Federated services based upon internationally recognized standards using web services. By deploying International Federation of Digital Seismograph Networks (FDSN) endorsed web services at multiple data centers in the US and Europe, we have shown that integration within seismological domain can be realized. By deploying identical methods to invoke the web services at multiple centers this approach can significantly ease the methods through which a scientist can access seismic data (time series, metadata, and earthquake catalogs) from distributed federated centers. IRIS has developed an IRIS federator that helps a user identify where seismic data from global seismic networks can be accessed. The web services based federator can build the appropriate URLs and return them to client software running on the scientists own computer. These URLs are then used to directly pull data from the distributed center in a very peer-based fashion. IRIS is also involved in deploying web services across horizontal domains. As part of the US National Science Foundation's (NSF) EarthCube effort, an IRIS led EarthCube Building Block's project is underway. When completed this project will aid in the discovery, access, and usability of data across multiple geoscienece domains. This presentation will summarize current IRIS efforts in building vertical integration infrastructure within seismology working closely with 5 centers in Europe and 2 centers in the US, as well as how we are taking first steps toward horizontal integration of data from 14 different domains in the US, in Europe, and around the world.
Distributed Generators Allocation in Radial Distribution Systems with Load Growth using Loss Sensitivity Approach

NASA Astrophysics Data System (ADS)

Kumar, Ashwani; Vijay Babu, P.; Murty, V. V. S. N.

2017-06-01

Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of distributed generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. The objective of the paper is to reduce the power losses and improve the voltage profile of the radial distribution system with optimal allocation of the multiple DG in the system. The main contribution in this paper is (i) combined power loss sensitivity (CPLS) based method for multiple DG locations, (ii) determination of optimal sizes for multiple DG units at unity and lagging power factor, (iii) impact of DG installed at optimal, that is, combined load power factor on the system performance, (iv) impact of load growth on optimal DG planning, (v) Impact of DG integration in distribution systems on voltage stability index, (vi) Economic and technical Impact of DG integration in the distribution systems. The load growth factor has been considered in the study which is essential for planning and expansion of the existing systems. The technical and economic aspects are investigated in terms of improvement in voltage profile, reduction in total power losses, cost of energy loss, cost of power obtained from DG, cost of power intake from the substation, and savings in cost of energy loss. The results are obtained on IEEE 69-bus radial distribution systems and also compared with other existing methods.
77 FR 54862 - Integrated Hedging Transactions of Qualifying Debt

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-06

... Integrated Hedging Transactions of Qualifying Debt AGENCY: Internal Revenue Service (IRS), Treasury. ACTION... certain integrated transactions that involve a foreign currency denominated debt instrument and multiple... foreign currency denominated debt instrument and multiple associated hedging transactions. The text of...
An integrative perspective of the anaerobic threshold.

PubMed

Sales, Marcelo Magalhães; Sousa, Caio Victor; da Silva Aguiar, Samuel; Knechtle, Beat; Nikolaidis, Pantelis Theodoros; Alves, Polissandro Mortoza; Simões, Herbert Gustavo

2017-12-14

The concept of anaerobic threshold (AT) was introduced during the nineteen sixties. Since then, several methods to identify the anaerobic threshold (AT) have been studied and suggested as novel 'thresholds' based upon the variable used for its detection (i.e. lactate threshold, ventilatory threshold, glucose threshold). These different techniques have brought some confusion about how we should name this parameter, for instance, anaerobic threshold or the physiological measure used (i.e. lactate, ventilation). On the other hand, the modernization of scientific methods and apparatus to detect AT, as well as the body of literature formed in the past decades, could provide a more cohesive understanding over the AT and the multiple physiological systems involved. Thus, the purpose of this review was to provide an integrative perspective of the methods to determine AT. Copyright © 2017 Elsevier Inc. All rights reserved.
GeneSilico protein structure prediction meta-server.

PubMed

Kurowski, Michal A; Bujnicki, Janusz M

2003-07-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.
GeneSilico protein structure prediction meta-server

PubMed Central

Kurowski, Michal A.; Bujnicki, Janusz M.

2003-01-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313
Ensemble modelling and structured decision-making to support Emergency Disease Management.

PubMed

Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

2017-03-01

Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.
Bayesian Estimation of Pneumonia Etiology: Epidemiologic Considerations and Applications to the Pneumonia Etiology Research for Child Health Study.

PubMed

Deloria Knoll, Maria; Fu, Wei; Shi, Qiyuan; Prosperi, Christine; Wu, Zhenke; Hammitt, Laura L; Feikin, Daniel R; Baggett, Henry C; Howie, Stephen R C; Scott, J Anthony G; Murdoch, David R; Madhi, Shabir A; Thea, Donald M; Brooks, W Abdullah; Kotloff, Karen L; Li, Mengying; Park, Daniel E; Lin, Wenyi; Levine, Orin S; O'Brien, Katherine L; Zeger, Scott L

2017-06-15

In pneumonia, specimens are rarely obtained directly from the infection site, the lung, so the pathogen causing infection is determined indirectly from multiple tests on peripheral clinical specimens, which may have imperfect and uncertain sensitivity and specificity, so inference about the cause is complex. Analytic approaches have included expert review of case-only results, case-control logistic regression, latent class analysis, and attributable fraction, but each has serious limitations and none naturally integrate multiple test results. The Pneumonia Etiology Research for Child Health (PERCH) study required an analytic solution appropriate for a case-control design that could incorporate evidence from multiple specimens from cases and controls and that accounted for measurement error. We describe a Bayesian integrated approach we developed that combined and extended elements of attributable fraction and latent class analyses to meet some of these challenges and illustrate the advantage it confers regarding the challenges identified for other methods. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America.
Integrating Multiple Criteria Evaluation and GIS in Ecotourism: a Review

NASA Astrophysics Data System (ADS)

Mohd, Z. H.; Ujang, U.

2016-09-01

The concept of 'Eco-tourism' is increasingly heard in recent decades. Ecotourism is one adventure that environmentally responsible intended to appreciate the nature experiences and cultures. Ecotourism should have low impact on environment and must contribute to the prosperity of local residents. This article reviews the use of Multiple Criteria Evaluation (MCE) and Geographic Information System (GIS) in ecotourism. Multiple criteria evaluation mostly used to land suitability analysis or fulfill specific objectives based on various attributes that exist in the selected area. To support the process of environmental decision making, the application of GIS is used to display and analysis the data through Analytic Hierarchy Process (AHP). Integration between MCE and GIS tool is important to determine the relative weight for the criteria used objectively. With the MCE method, it can resolve the conflict between recreation and conservation which is to minimize the environmental and human impact. Most studies evidences that the GIS-based AHP as a multi criteria evaluation is a strong and effective in tourism planning which can aid in the development of ecotourism industry effectively.
Addressing the Analytic Challenges of Cross-Sectional Pediatric Pneumonia Etiology Data.

PubMed

Hammitt, Laura L; Feikin, Daniel R; Scott, J Anthony G; Zeger, Scott L; Murdoch, David R; O'Brien, Katherine L; Deloria Knoll, Maria

2017-06-15

Despite tremendous advances in diagnostic laboratory technology, identifying the pathogen(s) causing pneumonia remains challenging because the infected lung tissue cannot usually be sampled for testing. Consequently, to obtain information about pneumonia etiology, clinicians and researchers test specimens distant to the site of infection. These tests may lack sensitivity (eg, blood culture, which is only positive in a small proportion of children with pneumonia) and/or specificity (eg, detection of pathogens in upper respiratory tract specimens, which may indicate asymptomatic carriage or a less severe syndrome, such as upper respiratory infection). While highly sensitive nucleic acid detection methods and testing of multiple specimens improve sensitivity, multiple pathogens are often detected and this adds complexity to the interpretation as the etiologic significance of results may be unclear (ie, the pneumonia may be caused by none, one, some, or all of the pathogens detected). Some of these challenges can be addressed by adjusting positivity rates to account for poor sensitivity or incorporating test results from controls without pneumonia to account for poor specificity. However, no classical analytic methods can account for measurement error (ie, sensitivity and specificity) for multiple specimen types and integrate the results of measurements for multiple pathogens to produce an accurate understanding of etiology. We describe the major analytic challenges in determining pneumonia etiology and review how the common analytical approaches (eg, descriptive, case-control, attributable fraction, latent class analysis) address some but not all challenges. We demonstrate how these limitations necessitate a new, integrated analytical approach to pneumonia etiology data. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America.
Addressing the Analytic Challenges of Cross-Sectional Pediatric Pneumonia Etiology Data

PubMed Central

Feikin, Daniel R.; Scott, J. Anthony G.; Zeger, Scott L.; Murdoch, David R.; O’Brien, Katherine L.; Deloria Knoll, Maria

2017-01-01

Abstract Despite tremendous advances in diagnostic laboratory technology, identifying the pathogen(s) causing pneumonia remains challenging because the infected lung tissue cannot usually be sampled for testing. Consequently, to obtain information about pneumonia etiology, clinicians and researchers test specimens distant to the site of infection. These tests may lack sensitivity (eg, blood culture, which is only positive in a small proportion of children with pneumonia) and/or specificity (eg, detection of pathogens in upper respiratory tract specimens, which may indicate asymptomatic carriage or a less severe syndrome, such as upper respiratory infection). While highly sensitive nucleic acid detection methods and testing of multiple specimens improve sensitivity, multiple pathogens are often detected and this adds complexity to the interpretation as the etiologic significance of results may be unclear (ie, the pneumonia may be caused by none, one, some, or all of the pathogens detected). Some of these challenges can be addressed by adjusting positivity rates to account for poor sensitivity or incorporating test results from controls without pneumonia to account for poor specificity. However, no classical analytic methods can account for measurement error (ie, sensitivity and specificity) for multiple specimen types and integrate the results of measurements for multiple pathogens to produce an accurate understanding of etiology. We describe the major analytic challenges in determining pneumonia etiology and review how the common analytical approaches (eg, descriptive, case-control, attributable fraction, latent class analysis) address some but not all challenges. We demonstrate how these limitations necessitate a new, integrated analytical approach to pneumonia etiology data. PMID:28575372
Early Design Choices: Capture, Model, Integrate, Analyze, Simulate

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2004-01-01

I. Designs are constructed incrementally to meet requirements and solve problems: a) Requirements types: objectives, scenarios, constraints, ilities. etc. b) Problem/issue types: risk/safety, cost/difficulty, interaction, conflict, etc. II. Capture requirements, problems and solutions: a) Collect design and analysis products and make them accessible for integration and analysis; b) Link changes in design requirements, problems and solutions; and c) Harvest design data for design models and choice structures. III. System designs are constructed by multiple groups designing interacting subsystems a) Diverse problems, choice criteria, analysis methods and point solutions. IV. Support integration and global analysis of repercussions: a) System implications of point solutions; b) Broad analysis of interactions beyond totals of mass, cost, etc.
THE ENGINE AND THE REAPER: INDUSTRIALIZATION AND MORTALITY IN LATE NINETEENTH CENTURY JAPAN.

PubMed

Tang, John P

2017-12-01

Economic development improves long-run health outcomes through access to medical treatment, sanitation, and higher income. Short run impacts, however, may be ambiguous given disease exposure from market integration. Using a panel dataset of Japanese vital statistics and multiple estimation methods, I find that railroad network expansion is associated with a six percent increase in gross mortality rates among newly integrated regions. Communicable diseases accounted for most of the rail-associated mortality, which indicate railways behaved as transmission vectors. At the same time, market integration facilitated by railways corresponded with an eighteen percent increase in total capital investment nationwide over ten years. Copyright © 2017 Elsevier B.V. All rights reserved.
A location-based multiple point statistics method: modelling the reservoir with non-stationary characteristics

NASA Astrophysics Data System (ADS)

Yin, Yanshu; Feng, Wenjie

2017-12-01

In this paper, a location-based multiple point statistics method is developed to model a non-stationary reservoir. The proposed method characterizes the relationship between the sedimentary pattern and the deposit location using the relative central position distance function, which alleviates the requirement that the training image and the simulated grids have the same dimension. The weights in every direction of the distance function can be changed to characterize the reservoir heterogeneity in various directions. The local integral replacements of data events, structured random path, distance tolerance and multi-grid strategy are applied to reproduce the sedimentary patterns and obtain a more realistic result. This method is compared with the traditional Snesim method using a synthesized 3-D training image of Poyang Lake and a reservoir model of Shengli Oilfield in China. The results indicate that the new method can reproduce the non-stationary characteristics better than the traditional method and is more suitable for simulation of delta-front deposits. These results show that the new method is a powerful tool for modelling a reservoir with non-stationary characteristics.
Secular dynamics of hierarchical multiple systems composed of nested binaries, with an arbitrary number of bodies and arbitrary hierarchical structure - II. External perturbations: flybys and supernovae

NASA Astrophysics Data System (ADS)

Hamers, Adrian S.

2018-05-01

We extend the formalism of a previous paper to include the effects of flybys and instantaneous perturbations such as supernovae on the long-term secular evolution of hierarchical multiple systems with an arbitrary number of bodies and hierarchy, provided that the system is composed of nested binary orbits. To model secular encounters, we expand the Hamiltonian in terms of the ratio of the separation of the perturber with respect to the barycentre of the multiple system, to the separation of the widest orbit. Subsequently, we integrate over the perturber orbit numerically or analytically. We verify our method for secular encounters and illustrate it with an example. Furthermore, we describe a method to compute instantaneous orbital changes to multiple systems, such as asymmetric supernovae and impulsive encounters. The secular code, with implementation of the extensions described in this paper, is publicly available within AMUSE, and we provide a number of simple example scripts to illustrate its usage for secular and impulsive encounters and asymmetric supernovae. The extensions presented in this paper are a next step towards efficiently modelling the evolution of complex multiple systems embedded in star clusters.
Tutorial examples for uncertainty quantification methods.

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

De Bord, Sarah

2015-08-01

This report details the work accomplished during my 2015 SULI summer internship at Sandia National Laboratories in Livermore, CA. During this internship, I worked on multiple tasks with the common goal of making uncertainty quantification (UQ) methods more accessible to the general scientific community. As part of my work, I created a comprehensive numerical integration example to incorporate into the user manual of a UQ software package. Further, I developed examples involving heat transfer through a window to incorporate into tutorial lectures that serve as an introduction to UQ methods.

Nested Sampling for Bayesian Model Comparison in the Context of Salmonella Disease Dynamics

PubMed Central

Dybowski, Richard; McKinley, Trevelyan J.; Mastroeni, Pietro; Restif, Olivier

2013-01-01

Understanding the mechanisms underlying the observed dynamics of complex biological systems requires the statistical assessment and comparison of multiple alternative models. Although this has traditionally been done using maximum likelihood-based methods such as Akaike's Information Criterion (AIC), Bayesian methods have gained in popularity because they provide more informative output in the form of posterior probability distributions. However, comparison between multiple models in a Bayesian framework is made difficult by the computational cost of numerical integration over large parameter spaces. A new, efficient method for the computation of posterior probabilities has recently been proposed and applied to complex problems from the physical sciences. Here we demonstrate how nested sampling can be used for inference and model comparison in biological sciences. We present a reanalysis of data from experimental infection of mice with Salmonella enterica showing the distribution of bacteria in liver cells. In addition to confirming the main finding of the original analysis, which relied on AIC, our approach provides: (a) integration across the parameter space, (b) estimation of the posterior parameter distributions (with visualisations of parameter correlations), and (c) estimation of the posterior predictive distributions for goodness-of-fit assessments of the models. The goodness-of-fit results suggest that alternative mechanistic models and a relaxation of the quasi-stationary assumption should be considered. PMID:24376528
Histoimmunogenetics Markup Language 1.0: Reporting next generation sequencing-based HLA and KIR genotyping.

PubMed

Milius, Robert P; Heuer, Michael; Valiga, Daniel; Doroschak, Kathryn J; Kennedy, Caleb J; Bolon, Yung-Tsi; Schneider, Joel; Pollack, Jane; Kim, Hwa Ran; Cereb, Nezih; Hollenbach, Jill A; Mack, Steven J; Maiers, Martin

2015-12-01

We present an electronic format for exchanging data for HLA and KIR genotyping with extensions for next-generation sequencing (NGS). This format addresses NGS data exchange by refining the Histoimmunogenetics Markup Language (HML) to conform to the proposed Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) reporting guidelines (miring.immunogenomics.org). Our refinements of HML include two major additions. First, NGS is supported by new XML structures to capture additional NGS data and metadata required to produce a genotyping result, including analysis-dependent (dynamic) and method-dependent (static) components. A full genotype, consensus sequence, and the surrounding metadata are included directly, while the raw sequence reads and platform documentation are externally referenced. Second, genotype ambiguity is fully represented by integrating Genotype List Strings, which use a hierarchical set of delimiters to represent allele and genotype ambiguity in a complete and accurate fashion. HML also continues to enable the transmission of legacy methods (e.g. site-specific oligonucleotide, sequence-specific priming, and Sequence Based Typing (SBT)), adding features such as allowing multiple group-specific sequencing primers, and fully leveraging techniques that combine multiple methods to obtain a single result, such as SBT integrated with NGS. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Multilevel functional genomics data integration as a tool for understanding physiology: a network biology perspective.

PubMed

Davidsen, Peter K; Turan, Nil; Egginton, Stuart; Falciani, Francesco

2016-02-01

The overall aim of physiological research is to understand how living systems function in an integrative manner. Consequently, the discipline of physiology has since its infancy attempted to link multiple levels of biological organization. Increasingly this has involved mathematical and computational approaches, typically to model a small number of components spanning several levels of biological organization. With the advent of "omics" technologies, which can characterize the molecular state of a cell or tissue (intended as the level of expression and/or activity of its molecular components), the number of molecular components we can quantify has increased exponentially. Paradoxically, the unprecedented amount of experimental data has made it more difficult to derive conceptual models underlying essential mechanisms regulating mammalian physiology. We present an overview of state-of-the-art methods currently used to identifying biological networks underlying genomewide responses. These are based on a data-driven approach that relies on advanced computational methods designed to "learn" biology from observational data. In this review, we illustrate an application of these computational methodologies using a case study integrating an in vivo model representing the transcriptional state of hypoxic skeletal muscle with a clinical study representing muscle wasting in chronic obstructive pulmonary disease patients. The broader application of these approaches to modeling multiple levels of biological data in the context of modern physiology is discussed. Copyright © 2016 the American Physiological Society.
Analytical transition-matrix treatment of electric multipole polarizabilities of hydrogen-like atoms

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

Kharchenko, V.F., E-mail: vkharchenko@bitp.kiev.ua

2015-04-15

The direct transition-matrix approach to the description of the electric polarization of the quantum bound system of particles is used to determine the electric multipole polarizabilities of the hydrogen-like atoms. It is shown that in the case of the bound system formed by the Coulomb interaction the corresponding inhomogeneous integral equation determining an off-shell scattering function, which consistently describes virtual multiple scattering, can be solved exactly analytically for all electric multipole polarizabilities. Our method allows to reproduce the known Dalgarno–Lewis formula for electric multipole polarizabilities of the hydrogen atom in the ground state and can also be applied to determinemore » the polarizability of the atom in excited bound states. - Highlights: • A new description for electric polarization of hydrogen-like atoms. • Expression for multipole polarizabilities in terms of off-shell scattering functions. • Derivation of integral equation determining the off-shell scattering function. • Rigorous analytic solving the integral equations both for ground and excited states. • Study of contributions of virtual multiple scattering to electric polarizabilities.« less
Cloud-Assisted UAV Data Collection for Multiple Emerging Events in Distributed WSNs

PubMed Central

Cao, Huiru; Liu, Yongxin; Yue, Xuejun; Zhu, Wenjian

2017-01-01

In recent years, UAVs (Unmanned Aerial Vehicles) have been widely applied for data collection and image capture. Specifically, UAVs have been integrated with wireless sensor networks (WSNs) to create data collection platforms with high flexibility. However, most studies in this domain focus on system architecture and UAVs’ flight trajectory planning while event-related factors and other important issues are neglected. To address these challenges, we propose a cloud-assisted data gathering strategy for UAV-based WSN in the light of emerging events. We also provide a cloud-assisted approach for deriving UAV’s optimal flying and data acquisition sequence of a WSN cluster. We validate our approach through simulations and experiments. It has been proved that our methodology outperforms conventional approaches in terms of flying time, energy consumption, and integrity of data acquisition. We also conducted a real-world experiment using a UAV to collect data wirelessly from multiple clusters of sensor nodes for monitoring an emerging event, which are deployed in a farm. Compared against the traditional method, this proposed approach requires less than half the flying time and achieves almost perfect data integrity. PMID:28783100
Cloud-Assisted UAV Data Collection for Multiple Emerging Events in Distributed WSNs.

PubMed

Cao, Huiru; Liu, Yongxin; Yue, Xuejun; Zhu, Wenjian

2017-08-07

In recent years, UAVs (Unmanned Aerial Vehicles) have been widely applied for data collection and image capture. Specifically, UAVs have been integrated with wireless sensor networks (WSNs) to create data collection platforms with high flexibility. However, most studies in this domain focus on system architecture and UAVs' flight trajectory planning while event-related factors and other important issues are neglected. To address these challenges, we propose a cloud-assisted data gathering strategy for UAV-based WSN in the light of emerging events. We also provide a cloud-assisted approach for deriving UAV's optimal flying and data acquisition sequence of a WSN cluster. We validate our approach through simulations and experiments. It has been proved that our methodology outperforms conventional approaches in terms of flying time, energy consumption, and integrity of data acquisition. We also conducted a real-world experiment using a UAV to collect data wirelessly from multiple clusters of sensor nodes for monitoring an emerging event, which are deployed in a farm. Compared against the traditional method, this proposed approach requires less than half the flying time and achieves almost perfect data integrity.
Interpersonal Consulting Skills among Instructional Technology Consultants at an Institution of Higher Education in the Midwest--A Multiple Case Study

ERIC Educational Resources Information Center

van Leusen, Peter

2013-01-01

As new developments in digital technologies rapidly influence our society, higher education organizations are under increasing pressure to utilize new instructional methods and technologies to educate students (Educause, 2005; Phipps & Wellman, 2001; U.S. Department of Education, 2010). The task to integrate these tools into teaching and…
D-Move: A Mobile Communication Based Delphi for Digital Natives to Support Embedded Research

ERIC Educational Resources Information Center

Petrovic, Otto

2017-01-01

Digital Natives are raised with computers and the Internet, which are a familiar part of their daily life. To gain insights into their attitude and behavior, methods and media for empirical research face new challenges like gamification, context oriented embedded research, integration of multiple data sources, and the increased importance of…
Approaching Parental Guilt, Shame, and Blame in a Helping Relationship: Multiple Methods for Teaching and Learning

ERIC Educational Resources Information Center

Bentley, Kia J.; Cohen-Filipic, Katherine; Cummings, Cory R.

2016-01-01

Social workers often feel ill-prepared to effectively engage parents in conversations about guilt, shame, and blame related to their children's mental health or substance use challenges. To address that problem, we suggest that specific content should be integrated into social work courses to teach students how to acknowledge and sensitively…
TPACK Development in a Three-Year Online Masters Program: How Do Teacher Perceptions Align with Classroom Practice?

ERIC Educational Resources Information Center

Staus, Nancy; Gillow-Wiles, Henry; Niess, Margaret

2014-01-01

A new primarily distance education Master's degree program was focused on the development of technological pedagogical content knowledge (TPACK) for integrating appropriate digital technologies in mathematics and science classes. In this mixed-method multiple case study, we documented in-service K-8 teachers' perceptions of their TPACK…
Curriculum Integration in Arts Education: Connecting Multiple Art Forms through the Idea of "Space"

ERIC Educational Resources Information Center

Bautista, Alfredo; Tan, Liang See; Ponnusamy, Letchmi Devi; Yau, Xenia

2016-01-01

Arts integration research has focused on documenting how the teaching of specific art forms can be integrated with "core" academic subject matters (e.g. science, mathematics and literacy). However, the question of how the teaching of multiple art forms themselves can be integrated in schools remains to be explored by educational…
Multiple plasmonically induced transparency for chip-scale bandpass filters in metallic nanowaveguides

NASA Astrophysics Data System (ADS)

Lu, Hua; Yue, Zengqi; Zhao, Jianlin

2018-05-01

We propose and investigate a new kind of bandpass filters based on the plasmonically induced transparency (PIT) effect in a special metal-insulator-metal (MIM) waveguide system. The finite element method (FEM) simulations illustrate that the obvious PIT response can be generated in the metallic nanostructure with the stub and coupled cavities. The lineshape and position of the PIT peak are particularly dependent on the lengths of the stub and coupled cavities, the waveguide width, as well as the coupling distance between the stub and coupled cavities. The numerical simulations are in accordance with the results obtained by the temporal coupled-mode theory. The multi-peak PIT effect can be achieved by integrating multiple coupled cavities into the plasmonic waveguide. This PIT response contributes to the flexible realization of chip-scale multi-channel bandpass filters, which could find crucial applications in highly integrated optical circuits for signal processing.
Patients, practices, and relationships: challenges and lessons learned from the Kentucky Ambulatory Network (KAN) CaRESS clinical trial.

PubMed

Love, Margaret M; Pearce, Kevin A; Williamson, M Ann; Barron, Mary A; Shelton, Brent J

2006-01-01

The Cardiovascular Risk Education and Social Support (CaRESS) study is a randomized controlled trial that evaluates a social support intervention toward reducing cardiovascular risk in type 2 diabetic patients. It involves multiple community-based practice sites from the Kentucky Ambulatory Network (KAN), which is a regional primary care practice-based research network (PBRN). CaRESS also implements multiple modes of data collection. The purpose of this methods article is to share lessons learned that might be useful to others developing or implementing complex studies that consent patients in PBRNs. Key points include building long-term relationships with the clinicians, adaptability when integrating into practice sites, adequate funding to support consistent data management and statistical support during all phases of the study, and creativity and perseverance for recruiting patients and practices while maintaining the integrity of the protocol.
Combining qualitative and quantitative operational research methods to inform quality improvement in pathways that span multiple settings

PubMed Central

Crowe, Sonya; Brown, Katherine; Tregay, Jenifer; Wray, Jo; Knowles, Rachel; Ridout, Deborah A; Bull, Catherine; Utley, Martin

2017-01-01

Background Improving integration and continuity of care across sectors within resource constraints is a priority in many health systems. Qualitative operational research methods of problem structuring have been used to address quality improvement in services involving multiple sectors but not in combination with quantitative operational research methods that enable targeting of interventions according to patient risk. We aimed to combine these methods to augment and inform an improvement initiative concerning infants with congenital heart disease (CHD) whose complex care pathway spans multiple sectors. Methods Soft systems methodology was used to consider systematically changes to services from the perspectives of community, primary, secondary and tertiary care professionals and a patient group, incorporating relevant evidence. Classification and regression tree (CART) analysis of national audit datasets was conducted along with data visualisation designed to inform service improvement within the context of limited resources. Results A ‘Rich Picture’ was developed capturing the main features of services for infants with CHD pertinent to service improvement. This was used, along with a graphical summary of the CART analysis, to guide discussions about targeting interventions at specific patient risk groups. Agreement was reached across representatives of relevant health professions and patients on a coherent set of targeted recommendations for quality improvement. These fed into national decisions about service provision and commissioning. Conclusions When tackling complex problems in service provision across multiple settings, it is important to acknowledge and work with multiple perspectives systematically and to consider targeting service improvements in response to confined resources. Our research demonstrates that applying a combination of qualitative and quantitative operational research methods is one approach to doing so that warrants further consideration. PMID:28062603
Damage detection of an in-service condensation pipeline joint

NASA Astrophysics Data System (ADS)

Briand, Julie; Rezaei, Davood; Taheri, Farid

2010-04-01

The early detection of damage in structural or mechanical systems is of vital importance. With early detection, the damage may be repaired before the integrity of the system is jeopardized, resulting in monetary losses, loss of life or limb, and environmental impacts. Among the various types of structural health monitoring techniques, vibration-based methods are of significant interest since the damage location does not need to be known beforehand, making it a more versatile approach. The non-destructive damage detection method used for the experiments herein is a novel vibration-based method which uses an index called the EMD Energy Damage Index, developed with the aim of providing improved qualitative results compared to those methods currently available. As part of an effort to establish the integrity and limitation of this novel damage detection method, field testing was completed on a mechanical pipe joint on a condensation line, located in the physical plant of Dalhousie University. Piezoceramic sensors, placed at various locations around the joint were used to monitor the free vibration of the pipe imposed through the use of an impulse hammer. Multiple damage progression scenarios were completed, each having a healthy state and multiple damage cases. Subsequently, the recorded signals from the healthy and damaged joint were processed through the EMD Energy Damage Index developed in-house in an effort to detect the inflicted damage. The proposed methodology successfully detected the inflicted damages. In this paper, the effects of impact location, sensor location, frequency bandwidth, intrinsic mode functions, and boundary conditions are discussed.
A VGI data integration framework based on linked data model

NASA Astrophysics Data System (ADS)

Wan, Lin; Ren, Rongrong

2015-12-01

This paper aims at the geographic data integration and sharing method for multiple online VGI data sets. We propose a semantic-enabled framework for online VGI sources cooperative application environment to solve a target class of geospatial problems. Based on linked data technologies - which is one of core components of semantic web, we can construct the relationship link among geographic features distributed in diverse VGI platform by using linked data modeling methods, then deploy these semantic-enabled entities on the web, and eventually form an interconnected geographic data network to support geospatial information cooperative application across multiple VGI data sources. The mapping and transformation from VGI sources to RDF linked data model is presented to guarantee the unique data represent model among different online social geographic data sources. We propose a mixed strategy which combined spatial distance similarity and feature name attribute similarity as the measure standard to compare and match different geographic features in various VGI data sets. And our work focuses on how to apply Markov logic networks to achieve interlinks of the same linked data in different VGI-based linked data sets. In our method, the automatic generating method of co-reference object identification model according to geographic linked data is discussed in more detail. It finally built a huge geographic linked data network across loosely-coupled VGI web sites. The results of the experiment built on our framework and the evaluation of our method shows the framework is reasonable and practicable.
A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data

PubMed Central

Vanegas, Fernando; Weiss, John; Gonzalez, Felipe

2018-01-01

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used—the sensors, the UAV, and the flight operations—the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analysing and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications. PMID:29342101
Tactical resource allocation and elective patient admission planning in care processes.

PubMed

Hulshof, Peter J H; Boucherie, Richard J; Hans, Erwin W; Hurink, Johann L

2013-06-01

Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to meet production targets/to serve the strategically agreed number of patients, and to use resources efficiently. This paper proposes a method to develop a tactical resource allocation and elective patient admission plan. These tactical plans allocate available resources to various care processes and determine the selection of patients to be served that are at a particular stage of their care process. Our method is developed in a Mixed Integer Linear Programming (MILP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital, thereby integrating decision making for a chain of hospital resources. Computational results indicate that our method leads to a more equitable distribution of resources and provides control of patient access times, the number of patients served and the fraction of allocated resource capacity. Our approach is generic, as the base MILP and the solution approach allow for including various extensions to both the objective criteria and the constraints. Consequently, the proposed method is applicable in various settings of tactical hospital management.
SD-MSAEs: Promoter recognition in human genome based on deep feature extraction.

PubMed

Xu, Wenxuan; Zhang, Li; Lu, Yaping

2016-06-01

The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different regions of DNA sequences. In this paper, we choose context feature and use a set of methods of SD to select the most effective n-mers distinguishing promoter regions from other DNA regions in human genome. Extracted from the total possible combinations of n-mers, we can get four sparse distributions based on promoter and non-promoters training samples. The informative n-mers are selected by optimizing the differentiating extents of these distributions. Specially, we combine the advantage of statistical divergence and multiple sparse auto-encoders (MSAEs) in deep learning to extract deep feature for promoter recognition. And then we apply multiple SVMs and a decision model to construct a human promoter recognition method called SD-MSAEs. Framework is flexible that it can integrate new feature extraction or new classification models freely. Experimental results show that our method has high sensitivity and specificity. Copyright © 2016 Elsevier Inc. All rights reserved.
Integration and the performance of healthcare networks:do integration strategies enhance efficiency, profitability, and image?

PubMed Central

Wan, Thomas T.H.; Ma, Allen; Y.J.Lin, Blossom

2001-01-01

Abstract Purpose This study examines the integration effects on efficiency and financial viability of the top 100 integrated healthcare networks (IHNs) in the United States. Theory A contingency- strategic theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. Methods The lists of the top 100 IHNs ranked in two years, 1998 and 1999, by the SMG Marketing Group were merged to create a database for the study. Multiple indicators were used to examine the relationship between IHNs' characteristics and their performance in efficiency and financial viability. A path analytical model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' images, represented by attaining ranking among the top 100 in two consecutive years, were analysed. Results and conclusion No positive associations were found between integration and network performance in efficiency or profits. Longitudinal data are needed to investigate the effect of integration on healthcare networks' financial performance. PMID:16896405

Reliable Viscosity Calculation from Equilibrium Molecular Dynamics Simulations: A Time Decomposition Method.

PubMed

Zhang, Yong; Otani, Akihito; Maginn, Edward J

2015-08-11

Equilibrium molecular dynamics is often used in conjunction with a Green-Kubo integral of the pressure tensor autocorrelation function to compute the shear viscosity of fluids. This approach is computationally expensive and is subject to a large amount of variability because the plateau region of the Green-Kubo integral is difficult to identify unambiguously. Here, we propose a time decomposition approach for computing the shear viscosity using the Green-Kubo formalism. Instead of one long trajectory, multiple independent trajectories are run and the Green-Kubo relation is applied to each trajectory. The averaged running integral as a function of time is fit to a double-exponential function with a weighting function derived from the standard deviation of the running integrals. Such a weighting function minimizes the uncertainty of the estimated shear viscosity and provides an objective means of estimating the viscosity. While the formal Green-Kubo integral requires an integration to infinite time, we suggest an integration cutoff time tcut, which can be determined by the relative values of the running integral and the corresponding standard deviation. This approach for computing the shear viscosity can be easily automated and used in computational screening studies where human judgment and intervention in the data analysis are impractical. The method has been applied to the calculation of the shear viscosity of a relatively low-viscosity liquid, ethanol, and relatively high-viscosity ionic liquid, 1-n-butyl-3-methylimidazolium bis(trifluoromethane-sulfonyl)imide ([BMIM][Tf2N]), over a range of temperatures. These test cases show that the method is robust and yields reproducible and reliable shear viscosity values.
A new multi-sensor integrated index for drought monitoring

NASA Astrophysics Data System (ADS)

Jiao, W.; Wang, L.; Tian, C.

2017-12-01

Drought is perceived as one of the most expensive and least understood natural disasters. The remote-sensing-based integrated drought indices, which integrate multiple variables, could reflect the drought conditions more comprehensively than single drought indices. However, most of current remote-sensing-based integrated drought indices focus on agricultural drought (i.e., deficit in soil moisture), their application in monitoring meteorological drought (i.e., deficit in precipitation) was limited. More importantly, most of the remote-sensing-based integrated drought indices did not take into consideration of the spatially non-stationary nature of the related variables, so such indices may lose essential local details when integrating multiple variables. In this regard, we proposed a new mathematical framework for generating integrated drought index for meteorological drought monitoring. The geographically weighted regression (GWR) model and principal component analysis were used to composite Moderate-resolution Imaging Spectroradiometer (MODIS) based temperature condition index (TCI), the Vegetation Index based on the Universal Pattern Decomposition method (VIUPD) based vegetation condition index (VCI), tropical rainfall measuring mission (TRMM) based Precipitation Condition Index (PCI) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) based soil moisture condition index (SMCI). We called the new remote-sensing-based integrated drought index geographical-location-based integrated drought index (GLIDI). We examined the utility of the GLIDI for drought monitoring in various climate divisions across the continental United States (CONUS). GLIDI showed high correlations with in-situ drought indices and outperformed most other existing drought indices. The results also indicate that the performance of GLIDI is not affected by environmental factors such as land cover, precipitation, temperature and soil conditions. As such, the GLIDI has considerable potential for drought monitoring across various environmental conditions.
The AB Initio Mia Method: Theoretical Development and Practical Applications

NASA Astrophysics Data System (ADS)

Peeters, Anik

The bottleneck in conventional ab initio Hartree -Fock calculations is the storage of the electron repulsion integrals because their number increases with the fourth power of the number of basis functions. This problem can be solved by a combination of the multiplicative integral approximation (MIA) and the direct SCF method. The MIA approach was successfully applied in the geometry optimisation of some biologically interesting compounds like the neurolepticum Haloperidol and two TIBO derivatives, inactivators of HIV1. In this thesis the potency of the MIA-method is shown by the application of this method in the calculation of the forces on the nuclei. In addition, the MIA method enabled the development of a new model for performing crystal field studies: the supermolecule model. The results for this model are in better agreement with experimental data than the results for the point charge model. This is illustrated by the study of some small molecules in the solid state: 2,3-diketopiperazine, formamide oxime and two polymorphic forms of glycine, alpha-glycine and beta-glycine.
An integrated condition-monitoring method for a milling process using reduced decomposition features

NASA Astrophysics Data System (ADS)

Liu, Jie; Wu, Bo; Wang, Yan; Hu, Youmin

2017-08-01

Complex and non-stationary cutting chatter affects productivity and quality in the milling process. Developing an effective condition-monitoring approach is critical to accurately identify cutting chatter. In this paper, an integrated condition-monitoring method is proposed, where reduced features are used to efficiently recognize and classify machine states in the milling process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition, and Shannon power spectral entropy is calculated to extract features from the decomposed signals. Principal component analysis is adopted to reduce feature size and computational cost. With the extracted feature information, the probabilistic neural network model is used to recognize and classify the machine states, including stable, transition, and chatter states. Experimental studies are conducted, and results show that the proposed method can effectively detect cutting chatter during different milling operation conditions. This monitoring method is also efficient enough to satisfy fast machine state recognition and classification.
Aquatic ecosystem protection and restoration: Advances in methods for assessment and evaluation

USGS Publications Warehouse

Bain, M.B.; Harig, A.L.; Loucks, D.P.; Goforth, R.R.; Mills, K.E.

2000-01-01

Many methods and criteria are available to assess aquatic ecosystems, and this review focuses on a set that demonstrates advancements from community analyses to methods spanning large spatial and temporal scales. Basic methods have been extended by incorporating taxa sensitivity to different forms of stress, adding measures linked to system function, synthesizing multiple faunal groups, integrating biological and physical attributes, spanning large spatial scales, and enabling simulations through time. These tools can be customized to meet the needs of a particular assessment and ecosystem. Two case studies are presented to show how new methods were applied at the ecosystem scale for achieving practical management goals. One case used an assessment of biotic structure to demonstrate how enhanced river flows can improve habitat conditions and restore a diverse fish fauna reflective of a healthy riverine ecosystem. In the second case, multitaxonomic integrity indicators were successful in distinguishing lake ecosystems that were disturbed, healthy, and in the process of restoration. Most methods strive to address the concept of biological integrity and assessment effectiveness often can be impeded by the lack of more specific ecosystem management objectives. Scientific and policy explorations are needed to define new ways for designating a healthy system so as to allow specification of precise quality criteria that will promote further development of ecosystem analysis tools.
Relativistic corrections to the multiple scattering effect on the Sunyaev-Zel'dovich effect in the isotropic approximation

NASA Astrophysics Data System (ADS)

Itoh, Naoki; Kawana, Youhei; Nozawa, Satoshi; Kohyama, Yasuharu

2001-10-01

We extend the formalism for the calculation of the relativistic corrections to the Sunyaev-Zel'dovich effect for clusters of galaxies and include the multiple scattering effects in the isotropic approximation. We present the results of the calculations by the Fokker-Planck expansion method as well as by the direct numerical integration of the collision term of the Boltzmann equation. The multiple scattering contribution is found to be very small compared with the single scattering contribution. For high-temperature galaxy clusters of kBTe~15keV, the ratio of both the contributions is -0.2 per cent in the Wien region. In the Rayleigh-Jeans region the ratio is -0.03 per cent. Therefore the multiple scattering contribution is safely neglected for the observed galaxy clusters.
Multi-viewer tracking integral imaging system and its viewing zone analysis.

PubMed

Park, Gilbae; Jung, Jae-Hyun; Hong, Keehoon; Kim, Yunhee; Kim, Young-Hoon; Min, Sung-Wook; Lee, Byoungho

2009-09-28

We propose a multi-viewer tracking integral imaging system for viewing angle and viewing zone improvement. In the tracking integral imaging system, the pickup angles in each elemental lens in the lens array are decided by the positions of viewers, which means the elemental image can be made for each viewer to provide wider viewing angle and larger viewing zone. Our tracking integral imaging system is implemented with an infrared camera and infrared light emitting diodes which can track the viewers' exact positions robustly. For multiple viewers to watch integrated three-dimensional images in the tracking integral imaging system, it is needed to formulate the relationship between the multiple viewers' positions and the elemental images. We analyzed the relationship and the conditions for the multiple viewers, and verified them by the implementation of two-viewer tracking integral imaging system.
COMPREHENSIVE ASSESSMENT OF COMPLEX TECHNOLOGIES: INTEGRATING VARIOUS ASPECTS IN HEALTH TECHNOLOGY ASSESSMENT.

PubMed

Lysdahl, Kristin Bakke; Mozygemba, Kati; Burns, Jacob; Brönneke, Jan Benedikt; Chilcott, James B; Ward, Sue; Hofmann, Bjørn

2017-01-01

Despite recent development of health technology assessment (HTA) methods, there are still methodological gaps for the assessment of complex health technologies. The INTEGRATE-HTA guidance for effectiveness, economic, ethical, socio-cultural, and legal aspects, deals with challenges when assessing complex technologies, such as heterogeneous study designs, multiple stakeholder perspectives, and unpredictable outcomes. The objective of this article is to outline this guidance and describe the added value of integrating these assessment aspects. Different methods were used to develop the various parts of the guidance, but all draw on existing, published knowledge and were supported by stakeholder involvement. The guidance was modified after application in a case study and in response to feedback from internal and external reviewers. The guidance consists of five parts, addressing five core aspects of HTA, all presenting stepwise approaches based on the assessment of complexity, context, and stakeholder involvement. The guidance on effectiveness, health economics and ethics aspects focus on helping users choose appropriate, or further develop, existing methods. The recommendations are based on existing methods' applicability for dealing with problems arising with complex interventions. The guidance offers new frameworks to identify socio-cultural and legal issues, along with overviews of relevant methods and sources. The INTEGRATE-HTA guidance outlines a wide range of methods and facilitates appropriate choices among them. The guidance enables understanding of how complexity matters for HTA and brings together assessments from disciplines, such as epidemiology, economics, ethics, law, and social theory. This indicates relevance for a broad range of technologies.
Sparse models for correlative and integrative analysis of imaging and genetic data

PubMed Central

Lin, Dongdong; Cao, Hongbao; Calhoun, Vince D.

2014-01-01

The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our ability to understand their interplay as well as their relationship with human behavior by integrating these two types of datasets. However, the high dimensionality and heterogeneity of these datasets presents a challenge to conventional statistical methods; there is a high demand for the development of both correlative and integrative analysis approaches. Here, we review our recent work on developing sparse representation based approaches to address this challenge. We show how sparse models are applied to the correlation and integration of imaging and genetic data for biomarker identification. We present examples on how these approaches are used for the detection of risk genes and classification of complex diseases such as schizophrenia. Finally, we discuss future directions on the integration of multiple imaging and genomic datasets including their interactions such as epistasis. PMID:25218561
Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2016-09-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. Proteins 2016; 84(Suppl 1):247-259. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
A multiscale Bayesian data integration approach for mapping air dose rates around the Fukushima Daiichi Nuclear Power Plant.

PubMed

Wainwright, Haruko M; Seki, Akiyuki; Chen, Jinsong; Saito, Kimiaki

2017-02-01

This paper presents a multiscale data integration method to estimate the spatial distribution of air dose rates in the regional scale around the Fukushima Daiichi Nuclear Power Plant. We integrate various types of datasets, such as ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. The Bayesian method allows us to quantify the uncertainty in the estimates, and to provide the confidence intervals that are critical for robust decision-making. Although this approach is primarily data-driven, it has great flexibility to include mechanistic models for representing radiation transport or other complex correlations. We demonstrate our approach using three types of datasets collected at the same time over Fukushima City in Japan: (1) coarse-resolution airborne surveys covering the entire area, (2) car surveys along major roads, and (3) walk surveys in multiple neighborhoods. Results show that the method can successfully integrate three types of datasets and create an integrated map (including the confidence intervals) of air dose rates over the domain in high resolution. Moreover, this study provides us with various insights into the characteristics of each dataset, as well as radiocaesium distribution. In particular, the urban areas show high heterogeneity in the contaminant distribution due to human activities as well as large discrepancy among different surveys due to such heterogeneity. Copyright © 2016 Elsevier Ltd. All rights reserved.
Putting people on the map through an approach that integrates social data in conservation planning.

PubMed

Stephanson, Sheri L; Mascia, Michael B

2014-10-01

Conservation planning is integral to strategic and effective operations of conservation organizations. Drawing upon biological sciences, conservation planning has historically made limited use of social data. We offer an approach for integrating data on social well-being into conservation planning that captures and places into context the spatial patterns and trends in human needs and capacities. This hierarchical approach provides a nested framework for characterizing and mapping data on social well-being in 5 domains: economic well-being, health, political empowerment, education, and culture. These 5 domains each have multiple attributes; each attribute may be characterized by one or more indicators. Through existing or novel data that display spatial and temporal heterogeneity in social well-being, conservation scientists, planners, and decision makers may measure, benchmark, map, and integrate these data within conservation planning processes. Selecting indicators and integrating these data into conservation planning is an iterative, participatory process tailored to the local context and planning goals. Social well-being data complement biophysical and threat-oriented social data within conservation planning processes to inform decisions regarding where and how to conserve biodiversity, provide a structure for exploring socioecological relationships, and to foster adaptive management. Building upon existing conservation planning methods and insights from multiple disciplines, this approach to putting people on the map can readily merge with current planning practices to facilitate more rigorous decision making. © 2014 Society for Conservation Biology.
Reflections on a vision for integrated research and monitoring after 15 years

USGS Publications Warehouse

Murdoch, Peter S.; McHale, Michael; Baron, Jill S.

2014-01-01

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.
Therapeutics for multiple sclerosis symptoms.

PubMed

Ben-Zacharia, Aliza Bitton

2011-01-01

Symptoms management in multiple sclerosis is an integral part of its care. Accurate assessment and addressing the different symptoms provides increased quality of life among patients with multiple sclerosis. Multiple sclerosis symptoms may be identified as primary, secondary, or tertiary symptoms. Primary symptoms, such as weakness, sensory loss, and ataxia, are directly related to demyelination and axonal loss. Secondary symptoms, such as urinary tract infections as a result of urinary retention, are a result of the primary symptoms. Tertiary symptoms, such as reactive depression or social isolation, are a result of the social and psychological consequences of the disease. Common multiple sclerosis symptoms include fatigue and weakness; decreased balance, spasticity and gait problems; depression and cognitive issues; bladder, bowel, and sexual deficits; visual and sensory loss; and neuropathic pain. Less-common symptoms include dysarthria and dysphagia, vertigo, and tremors. Rare symptoms in multiple sclerosis include seizures, hearing loss, and paralysis. Symptom management includes nonpharmacological methods, such as rehabilitation and psychosocial support, and pharmacological methods, ie, medications and surgical procedures. The keys to symptom management are awareness, knowledge, and coordination of care. Symptoms have to be recognized and management needs to be individualized. Multiple sclerosis therapeutics include nonpharmacological strategies that consist of lifestyle modifications, rehabilitation, social support, counseling, and pharmacological agents or surgical procedures. The goal is vigilant management to improve quality of life and promote realistic expectations and hope. © 2011 Mount Sinai School of Medicine.
A Bayesian approach to tracking patients having changing pharmacokinetic parameters

NASA Technical Reports Server (NTRS)

Bayard, David S.; Jelliffe, Roger W.

2004-01-01

This paper considers the updating of Bayesian posterior densities for pharmacokinetic models associated with patients having changing parameter values. For estimation purposes it is proposed to use the Interacting Multiple Model (IMM) estimation algorithm, which is currently a popular algorithm in the aerospace community for tracking maneuvering targets. The IMM algorithm is described, and compared to the multiple model (MM) and Maximum A-Posteriori (MAP) Bayesian estimation methods, which are presently used for posterior updating when pharmacokinetic parameters do not change. Both the MM and MAP Bayesian estimation methods are used in their sequential forms, to facilitate tracking of changing parameters. Results indicate that the IMM algorithm is well suited for tracking time-varying pharmacokinetic parameters in acutely ill and unstable patients, incurring only about half of the integrated error compared to the sequential MM and MAP methods on the same example.
Formation of multiple levels of porous silicon for buried insulators and conductors in silicon device technologies

DOEpatents

Blewer, Robert S.; Gullinger, Terry R.; Kelly, Michael J.; Tsao, Sylvia S.

1991-01-01

A method of forming a multiple level porous silicon substrate for semiconductor integrated circuits including anodizing non-porous silicon layers of a multi-layer silicon substrate to form multiple levels of porous silicon. At least one porous silicon layer is then oxidized to form an insulating layer and at least one other layer of porous silicon beneath the insulating layer is metallized to form a buried conductive layer. Preferably the insulating layer and conductive layer are separated by an anodization barrier formed of non-porous silicon. By etching through the anodization barrier and subsequently forming a metallized conductive layer, a fully or partially insulated buried conductor may be fabricated under single crystal silicon.
Research on polarization imaging information parsing method

NASA Astrophysics Data System (ADS)

Yuan, Hongwu; Zhou, Pucheng; Wang, Xiaolong

2016-11-01

Polarization information parsing plays an important role in polarization imaging detection. This paper focus on the polarization information parsing method: Firstly, the general process of polarization information parsing is given, mainly including polarization image preprocessing, multiple polarization parameters calculation, polarization image fusion and polarization image tracking, etc.; And then the research achievements of the polarization information parsing method are presented, in terms of polarization image preprocessing, the polarization image registration method based on the maximum mutual information is designed. The experiment shows that this method can improve the precision of registration and be satisfied the need of polarization information parsing; In terms of multiple polarization parameters calculation, based on the omnidirectional polarization inversion model is built, a variety of polarization parameter images are obtained and the precision of inversion is to be improve obviously; In terms of polarization image fusion , using fuzzy integral and sparse representation, the multiple polarization parameters adaptive optimal fusion method is given, and the targets detection in complex scene is completed by using the clustering image segmentation algorithm based on fractal characters; In polarization image tracking, the average displacement polarization image characteristics of auxiliary particle filtering fusion tracking algorithm is put forward to achieve the smooth tracking of moving targets. Finally, the polarization information parsing method is applied to the polarization imaging detection of typical targets such as the camouflage target, the fog and latent fingerprints.
Real-time inextensible surgical thread simulation.

PubMed

Xu, Lang; Liu, Qian

2018-03-27

This paper discusses a real-time simulation method of inextensible surgical thread based on the Cosserat rod theory using position-based dynamics (PBD). The method realizes stable twining and knotting of surgical thread while including inextensibility, bending, twisting and coupling effects. The Cosserat rod theory is used to model the nonlinear elastic behavior of surgical thread. The surgical thread model is solved with PBD to achieve a real-time, extremely stable simulation. Due to the one-dimensional linear structure of surgical thread, the direct solution of the distance constraint based on tridiagonal matrix algorithm is used to enhance stretching resistance in every constraint projection iteration. In addition, continuous collision detection and collision response guarantee a large time step and high performance. Furthermore, friction is integrated into the constraint projection process to stabilize the twining of multiple threads and complex contact situations. Through comparisons with existing methods, the surgical thread maintains constant length under large deformation after applying the direct distance constraint in our method. The twining and knotting of multiple threads correspond to stable solutions to contact and friction forces. A surgical suture scene is also modeled to demonstrate the practicality and simplicity of our method. Our method achieves stable and fast simulation of inextensible surgical thread. Benefiting from the unified particle framework, the rigid body, elastic rod, and soft body can be simultaneously simulated. The method is appropriate for applications in virtual surgery that require multiple dynamic bodies.
High resolution projection micro stereolithography system and method

DOEpatents

Spadaccini, Christopher M.; Farquar, George; Weisgraber, Todd; Gemberling, Steven; Fang, Nicholas; Xu, Jun; Alonso, Matthew; Lee, Howon

2016-11-15

A high-resolution P.mu.SL system and method incorporating one or more of the following features with a standard P.mu.SL system using a SLM projected digital image to form components in a stereolithographic bath: a far-field superlens for producing sub-diffraction-limited features, multiple spatial light modulators (SLM) to generate spatially-controlled three-dimensional interference holograms with nanoscale features, and the integration of microfluidic components into the resin bath of a P.mu.SL system to fabricate microstructures of different materials.
Distributed structural control using multilayered piezoelectric actuators

NASA Technical Reports Server (NTRS)

Cudney, Harley H.; Inman, Daniel J.; Oshman, Yaakov

1990-01-01

A method of segmenting piezoelectric sensors and actuators is proposed which can preclude the currently experienced cancelation of sensor signals, or the reduction of actuator effectiveness, due to the integration of the property undergoing measurement or control. The segmentation method is demonstrated by a model developed for beam structures, to which multiple layers of piezoelectric materials are attached. A numerical study is undertaken of increasing active and passive damping of a beam using the segmented sensors and actuators over unsegmented sensors and actuators.

Large space antenna communications systems: Integrated Langley Research Center/Jet Propulsion Laboratory technology development activities. 1: Introduction

NASA Technical Reports Server (NTRS)

Campbell, T. G.

1983-01-01

The Jet Propulsion Laboratory and the Langley Research Center have been developing technology related to large space antennas (LSA) during the past several years. The need for a communication system research program became apparent during the recent studies for the Land Mobile Satellite System. This study indicated the need for additional research in (1) electromagnetic analysis methods, (2) design and development of multiple beam feed systems, and (3) the measurement methods for LSA reflectors.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalugin, A. V., E-mail: Kalugin-AV@nrcki.ru; Tebin, V. V.

The specific features of calculation of the effective multiplication factor using the Monte Carlo method for weakly coupled and non-asymptotic multiplying systems are discussed. Particular examples are considered and practical recommendations on detection and Monte Carlo calculation of systems typical in numerical substantiation of nuclear safety for VVER fuel management problems are given. In particular, the problems of the choice of parameters for the batch mode and the method for normalization of the neutron batch, as well as finding and interpretation of the eigenvalue spectrum for the integral fission matrix, are discussed.
77 FR 74027 - Certain Integrated Circuit Packages Provided with Multiple Heat-Conducting Paths and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-12

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-851] Certain Integrated Circuit Packages Provided with Multiple Heat- Conducting Paths and Products Containing Same; Commission Determination Not To... provided with multiple heat-conducting paths and products containing same by reason of infringement of...
Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance

USGS Publications Warehouse

Clare, John; McKinney, Shawn T.; DePue, John E.; Loftin, Cynthia S.

2017-01-01

It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture–recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based on American marten (Martes americana) surveys using paired remote cameras, hair catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote cameras and snow tracking had comparable probability of detecting present martens, but that snow tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters.
A fast and well-conditioned spectral method for singular integral equations

NASA Astrophysics Data System (ADS)

Slevinsky, Richard Mikael; Olver, Sheehan

2017-03-01

We develop a spectral method for solving univariate singular integral equations over unions of intervals by utilizing Chebyshev and ultraspherical polynomials to reformulate the equations as almost-banded infinite-dimensional systems. This is accomplished by utilizing low rank approximations for sparse representations of the bivariate kernels. The resulting system can be solved in O (m2 n) operations using an adaptive QR factorization, where m is the bandwidth and n is the optimal number of unknowns needed to resolve the true solution. The complexity is reduced to O (mn) operations by pre-caching the QR factorization when the same operator is used for multiple right-hand sides. Stability is proved by showing that the resulting linear operator can be diagonally preconditioned to be a compact perturbation of the identity. Applications considered include the Faraday cage, and acoustic scattering for the Helmholtz and gravity Helmholtz equations, including spectrally accurate numerical evaluation of the far- and near-field solution. The JULIA software package SingularIntegralEquations.jl implements our method with a convenient, user-friendly interface.
Kinetic energy definition in velocity Verlet integration for accurate pressure evaluation

NASA Astrophysics Data System (ADS)

Jung, Jaewoon; Kobayashi, Chigusa; Sugita, Yuji

2018-04-01

In molecular dynamics (MD) simulations, a proper definition of kinetic energy is essential for controlling pressure as well as temperature in the isothermal-isobaric condition. The virial theorem provides an equation that connects the average kinetic energy with the product of particle coordinate and force. In this paper, we show that the theorem is satisfied in MD simulations with a larger time step and holonomic constraints of bonds, only when a proper definition of kinetic energy is used. We provide a novel definition of kinetic energy, which is calculated from velocities at the half-time steps (t - Δt/2 and t + Δt/2) in the velocity Verlet integration method. MD simulations of a 1,2-dispalmitoyl-sn-phosphatidylcholine (DPPC) lipid bilayer and a water box using the kinetic energy definition could reproduce the physical properties in the isothermal-isobaric condition properly. We also develop a multiple time step (MTS) integration scheme with the kinetic energy definition. MD simulations with the MTS integration for the DPPC and water box systems provided the same quantities as the velocity Verlet integration method, even when the thermostat and barostat are updated less frequently.
Kinetic energy definition in velocity Verlet integration for accurate pressure evaluation.

PubMed

Jung, Jaewoon; Kobayashi, Chigusa; Sugita, Yuji

2018-04-28

In molecular dynamics (MD) simulations, a proper definition of kinetic energy is essential for controlling pressure as well as temperature in the isothermal-isobaric condition. The virial theorem provides an equation that connects the average kinetic energy with the product of particle coordinate and force. In this paper, we show that the theorem is satisfied in MD simulations with a larger time step and holonomic constraints of bonds, only when a proper definition of kinetic energy is used. We provide a novel definition of kinetic energy, which is calculated from velocities at the half-time steps (t - Δt/2 and t + Δt/2) in the velocity Verlet integration method. MD simulations of a 1,2-dispalmitoyl-sn-phosphatidylcholine (DPPC) lipid bilayer and a water box using the kinetic energy definition could reproduce the physical properties in the isothermal-isobaric condition properly. We also develop a multiple time step (MTS) integration scheme with the kinetic energy definition. MD simulations with the MTS integration for the DPPC and water box systems provided the same quantities as the velocity Verlet integration method, even when the thermostat and barostat are updated less frequently.
Developing molecular tools for Chlamydomonas reinhardtii

NASA Astrophysics Data System (ADS)

Noor-Mohammadi, Samaneh

Microalgae have garnered increasing interest over the years for their ability to produce compounds ranging from biofuels to neutraceuticals. A main focus of researchers has been to use microalgae as a natural bioreactor for the production of valuable and complex compounds. Recombinant protein expression in the chloroplasts of green algae has recently become more routine; however, the heterologous expression of multiple proteins or complete biosynthetic pathways remains a significant challenge. To take full advantage of these organisms' natural abilities, sophisticated molecular tools are needed to be able to introduce and functionally express multiple gene biosynthetic pathways in its genome. To achieve the above objective, we have sought to establish a method to construct, integrate and express multigene operons in the chloroplast and nuclear genome of the model microalgae Chlamydomonas reinhardtii. Here we show that a modified DNA Assembler approach can be used to rapidly assemble multiple-gene biosynthetic pathways in yeast and then integrate these assembled pathways at a site-specific location in the chloroplast, or by random integration in the nuclear genome of C. reinhardtii. As a proof of concept, this method was used to successfully integrate and functionally express up to three reporter proteins (AphA6, AadA, and GFP) in the chloroplast of C. reinhardtii and up to three reporter proteins (Ble, AphVIII, and GFP) in its nuclear genome. An analysis of the relative gene expression of the engineered strains showed significant differences in the mRNA expression levels of the reporter genes and thus highlights the importance of proper promoter/untranslated-region selection when constructing a target pathway. In addition, this work focuses on expressing the cofactor regeneration enzyme phosphite dehydrogenase (PTDH) in the chloroplast and nuclear genomes of C. reinhardtii. The PTDH enzyme converts phosphite into phosphate and NAD(P)+ into NAD(P)H. The reduced nicotinamide cofactor NAD(P)H plays a pivotal role in many biochemical oxidation and reduction reactions, thus this enzyme would allow regeneration of NAD(P)H in a microalgae strain over-expressing a NAD(P)H-dependent oxidoreductase. A phosphite dehydrogenase gene was introduced into the chloroplast genome (codon optimized) and nuclear genome of C. reinhardtii by biolistic transformation and electroporation in separate events, respectively. Successful expression of the heterologous protein was confirmed by transcript analysis and protein analysis. In conclusion, this new method represents a useful genetic tool in the construction and integration of complex biochemical pathways into the chloroplast or nuclear genome of microalgae, and this should aid current efforts to engineer algae for recombinant protein expression, biofuels production and production of other desirable natural products.
Detection of Road Surface States from Tire Noise Using Neural Network Analysis

NASA Astrophysics Data System (ADS)

Kongrattanaprasert, Wuttiwat; Nomura, Hideyuki; Kamakura, Tomoo; Ueda, Koji

This report proposes a new processing method for automatically detecting the states of road surfaces from tire noises of passing vehicles. In addition to multiple indicators of the signal features in the frequency domain, we propose a few feature indicators in the time domain to successfully classify the road states into four categories: snowy, slushy, wet, and dry states. The method is based on artificial neural networks. The proposed classification is carried out in multiple neural networks using learning vector quantization. The outcomes of the networks are then integrated by the voting decision-making scheme. Experimental results obtained from recorded signals for ten days in the snowy season demonstrated that an accuracy of approximately 90% can be attained for predicting road surface states using only tire noise data.
Medical Literature Evaluation Education at US Schools of Pharmacy

PubMed Central

Phillips, Jennifer; Demaris, Kendra

2016-01-01

Objective. To determine how medical literature evaluation (MLE) is being taught across the United States and to summarize methods for teaching and assessing MLE. Methods. An 18-question survey was administered to faculty members whose primary responsibility was teaching MLE at schools and colleges of pharmacy. Results. Responses were received from 90 (71%) US schools of pharmacy. The most common method of integrating MLE into the curriculum was as a stand-alone course (49%). The most common placement was during the second professional year (43%) or integrated throughout the curriculum (25%). The majority (77%) of schools used a team-based approach. The use of active-learning strategies was common as was the use of multiple methods of evaluation. Responses varied regarding what role the course director played in incorporating MLE into advanced pharmacy practice experiences (APPEs). Conclusion. There is a trend toward incorporating MLE education components throughout the pre-APPE curriculum and placement of literature review/evaluation exercises into therapeutics practice skills laboratories to help students see how this skill integrates into other patient care skills. Several pre-APPE educational standards for MLE education exist, including journal club activities, a team-based approach to teaching and evaluation, and use of active-learning techniques. PMID:26941431
A Kirchhoff approach to seismic modeling and prestack depth migration

NASA Astrophysics Data System (ADS)

Liu, Zhen-Yue

1993-05-01

The Kirchhoff integral provides a robust method for implementing seismic modeling and prestack depth migration, which can handle lateral velocity variation and turning waves. With a little extra computation cost, the Kirchoff-type migration can obtain multiple outputs that have the same phase but different amplitudes, compared with that of other migration methods. The ratio of these amplitudes is helpful in computing some quantities such as reflection angle. I develop a seismic modeling and prestack depth migration method based on the Kirchhoff integral, that handles both laterally variant velocity and a dip beyond 90 degrees. The method uses a finite-difference algorithm to calculate travel times and WKBJ amplitudes for the Kirchhoff integral. Compared to ray-tracing algorithms, the finite-difference algorithm gives an efficient implementation and single-valued quantities (first arrivals) on output. In my finite difference algorithm, the upwind scheme is used to calculate travel times, and the Crank-Nicolson scheme is used to calculate amplitudes. Moreover, interpolation is applied to save computation cost. The modeling and migration algorithms require a smooth velocity function. I develop a velocity-smoothing technique based on damped least-squares to aid in obtaining a successful migration.
Hybrid Pixel-Based Method for Cardiac Ultrasound Fusion Based on Integration of PCA and DWT.

PubMed

Mazaheri, Samaneh; Sulaiman, Puteri Suhaiza; Wirza, Rahmita; Dimon, Mohd Zamrin; Khalid, Fatimah; Moosavi Tayebi, Rohollah

2015-01-01

Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics.
An integrated network of Arabidopsis growth regulators and its use for gene prioritization.

PubMed

Sabaghian, Ehsan; Drebert, Zuzanna; Inzé, Dirk; Saeys, Yvan

2015-12-01

Elucidating the molecular mechanisms that govern plant growth has been an important topic in plant research, and current advances in large-scale data generation call for computational tools that efficiently combine these different data sources to generate novel hypotheses. In this work, we present a novel, integrated network that combines multiple large-scale data sources to characterize growth regulatory genes in Arabidopsis, one of the main plant model organisms. The contributions of this work are twofold: first, we characterized a set of carefully selected growth regulators with respect to their connectivity patterns in the integrated network, and, subsequently, we explored to which extent these connectivity patterns can be used to suggest new growth regulators. Using a large-scale comparative study, we designed new supervised machine learning methods to prioritize growth regulators. Our results show that these methods significantly improve current state-of-the-art prioritization techniques, and are able to suggest meaningful new growth regulators. In addition, the integrated network is made available to the scientific community, providing a rich data source that will be useful for many biological processes, not necessarily restricted to plant growth.
Electromagnetic pulsed thermography for natural cracks inspection

PubMed Central

Gao, Yunlai; Tian, Gui Yun; Wang, Ping; Wang, Haitao; Gao, Bin; Woo, Wai Lok; Li, Kongjing

2017-01-01

Emerging integrated sensing and monitoring of material degradation and cracks are increasingly required for characterizing the structural integrity and safety of infrastructure. However, most conventional nondestructive evaluation (NDE) methods are based on single modality sensing which is not adequate to evaluate structural integrity and natural cracks. This paper proposed electromagnetic pulsed thermography for fast and comprehensive defect characterization. It hybrids multiple physical phenomena i.e. magnetic flux leakage, induced eddy current and induction heating linking to physics as well as signal processing algorithms to provide abundant information of material properties and defects. New features are proposed using 1st derivation that reflects multiphysics spatial and temporal behaviors to enhance the detection of cracks with different orientations. Promising results that robust to lift-off changes and invariant features for artificial and natural cracks detection have been demonstrated that the proposed method significantly improves defect detectability. It opens up multiphysics sensing and integrated NDE with potential impact for natural understanding and better quantitative evaluation of natural cracks including stress corrosion crack (SCC) and rolling contact fatigue (RCF). PMID:28169361
Space-time domain solutions of the wave equation by a non-singular boundary integral method and Fourier transform.

PubMed

Klaseboer, Evert; Sepehrirahnama, Shahrokh; Chan, Derek Y C

2017-08-01

The general space-time evolution of the scattering of an incident acoustic plane wave pulse by an arbitrary configuration of targets is treated by employing a recently developed non-singular boundary integral method to solve the Helmholtz equation in the frequency domain from which the space-time solution of the wave equation is obtained using the fast Fourier transform. The non-singular boundary integral solution can enforce the radiation boundary condition at infinity exactly and can account for multiple scattering effects at all spacings between scatterers without adverse effects on the numerical precision. More generally, the absence of singular kernels in the non-singular integral equation confers high numerical stability and precision for smaller numbers of degrees of freedom. The use of fast Fourier transform to obtain the time dependence is not constrained to discrete time steps and is particularly efficient for studying the response to different incident pulses by the same configuration of scatterers. The precision that can be attained using a smaller number of Fourier components is also quantified.
77 FR 33486 - Certain Integrated Circuit Packages Provided With Multiple Heat-Conducting Paths and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-06

... INTERNATIONAL TRADE COMMISSION [Docket No. 2899] Certain Integrated Circuit Packages Provided With... complaint entitled Certain Integrated Circuit Packages Provided With Multiple Heat-Conducting Paths and..., telephone (202) 205-2000. The public version of the complaint can be accessed on the Commission's electronic...
Reconciling incongruous qualitative and quantitative findings in mixed methods research: exemplars from research with drug using populations.

PubMed

Wagner, Karla D; Davidson, Peter J; Pollini, Robin A; Strathdee, Steffanie A; Washburn, Rachel; Palinkas, Lawrence A

2012-01-01

Mixed methods research is increasingly being promoted in the health sciences as a way to gain more comprehensive understandings of how social processes and individual behaviours shape human health. Mixed methods research most commonly combines qualitative and quantitative data collection and analysis strategies. Often, integrating findings from multiple methods is assumed to confirm or validate the findings from one method with the findings from another, seeking convergence or agreement between methods. Cases in which findings from different methods are congruous are generally thought of as ideal, whilst conflicting findings may, at first glance, appear problematic. However, the latter situation provides the opportunity for a process through which apparently discordant results are reconciled, potentially leading to new emergent understandings of complex social phenomena. This paper presents three case studies drawn from the authors' research on HIV risk amongst injection drug users in which mixed methods studies yielded apparently discrepant results. We use these case studies (involving injection drug users [IDUs] using a Needle/Syringe Exchange Program in Los Angeles, CA, USA; IDUs seeking to purchase needle/syringes at pharmacies in Tijuana, Mexico; and young street-based IDUs in San Francisco, CA, USA) to identify challenges associated with integrating findings from mixed methods projects, summarize lessons learned, and make recommendations for how to more successfully anticipate and manage the integration of findings. Despite the challenges inherent in reconciling apparently conflicting findings from qualitative and quantitative approaches, in keeping with others who have argued in favour of integrating mixed methods findings, we contend that such an undertaking has the potential to yield benefits that emerge only through the struggle to reconcile discrepant results and may provide a sum that is greater than the individual qualitative and quantitative parts. Copyright © 2011 Elsevier B.V. All rights reserved.
Reconciling incongruous qualitative and quantitative findings in mixed methods research: exemplars from research with drug using populations

PubMed Central

Wagner, Karla D.; Davidson, Peter J.; Pollini, Robin A.; Strathdee, Steffanie A.; Washburn, Rachel; Palinkas, Lawrence A.

2011-01-01

Mixed methods research is increasingly being promoted in the health sciences as a way to gain more comprehensive understandings of how social processes and individual behaviours shape human health. Mixed methods research most commonly combines qualitative and quantitative data collection and analysis strategies. Often, integrating findings from multiple methods is assumed to confirm or validate the findings from one method with the findings from another, seeking convergence or agreement between methods. Cases in which findings from different methods are congruous are generally thought of as ideal, while conflicting findings may, at first glance, appear problematic. However, the latter situation provides the opportunity for a process through which apparently discordant results are reconciled, potentially leading to new emergent understandings of complex social phenomena. This paper presents three case studies drawn from the authors’ research on HIV risk among injection drug users in which mixed methods studies yielded apparently discrepant results. We use these case studies (involving injection drug users [IDUs] using a needle/syringe exchange program in Los Angeles, California, USA; IDUs seeking to purchase needle/syringes at pharmacies in Tijuana, Mexico; and young street-based IDUs in San Francisco, CA, USA) to identify challenges associated with integrating findings from mixed methods projects, summarize lessons learned, and make recommendations for how to more successfully anticipate and manage the integration of findings. Despite the challenges inherent in reconciling apparently conflicting findings from qualitative and quantitative approaches, in keeping with others who have argued in favour of integrating mixed methods findings, we contend that such an undertaking has the potential to yield benefits that emerge only through the struggle to reconcile discrepant results and may provide a sum that is greater than the individual qualitative and quantitative parts. PMID:21680168
BIOZON: a system for unification, management and analysis of heterogeneous biological data.

PubMed

Birkland, Aaron; Yona, Golan

2006-02-15

Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability. Here we present a system (Biozon) that addresses these problems, and offers biologists a new knowledge resource to navigate through and explore. Biozon unifies multiple biological databases consisting of a variety of data types (such as DNA sequences, proteins, interactions and cellular pathways). It is fundamentally different from previous efforts as it uses a single extensive and tightly connected graph schema wrapped with hierarchical ontology of documents and relations. Beyond warehousing existing data, Biozon computes and stores novel derived data, such as similarity relationships and functional predictions. The integration of similarity data allows propagation of knowledge through inference and fuzzy searches. Sophisticated methods of query that span multiple data types were implemented and first-of-a-kind biological ranking systems were explored and integrated. The Biozon system is an extensive knowledge resource of heterogeneous biological data. Currently, it holds more than 100 million biological documents and 6.5 billion relations between them. The database is accessible through an advanced web interface that supports complex queries, "fuzzy" searches, data materialization and more, online at http://biozon.org.
Non‐parametric combination and related permutation tests for neuroimaging

PubMed Central

Webster, Matthew A.; Brooks, Jonathan C.; Tracey, Irene; Smith, Stephen M.; Nichols, Thomas E.

2016-01-01

Abstract In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well‐known definition of union‐intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume‐based representations of the brain, including non‐imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non‐parametric combination (NPC) methodology, such that instead of a two‐phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one‐way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Hum Brain Mapp 37:1486‐1511, 2016. © 2016 Wiley Periodicals, Inc. PMID:26848101

Parallel computation of three-dimensional aeroelastic fluid-structure interaction

NASA Astrophysics Data System (ADS)

Sadeghi, Mani

This dissertation presents a numerical method for the parallel computation of aeroelasticity (ParCAE). A flow solver is coupled to a structural solver by use of a fluid-structure interface method. The integration of the three-dimensional unsteady Navier-Stokes equations is performed in the time domain, simultaneously to the integration of a modal three-dimensional structural model. The flow solution is accelerated by using a multigrid method and a parallel multiblock approach. Fluid-structure coupling is achieved by subiteration. A grid-deformation algorithm is developed to interpolate the deformation of the structural boundaries onto the flow grid. The code is formulated to allow application to general, three-dimensional, complex configurations with multiple independent structures. Computational results are presented for various configurations, such as turbomachinery blade rows and aircraft wings. Investigations are performed on vortex-induced vibrations, effects of cascade mistuning on flutter, and cases of nonlinear cascade and wing flutter.
Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.
Elliptic polylogarithms and iterated integrals on elliptic curves. Part I: general formalism

NASA Astrophysics Data System (ADS)

Broedel, Johannes; Duhr, Claude; Dulat, Falko; Tancredi, Lorenzo

2018-05-01

We introduce a class of iterated integrals, defined through a set of linearly independent integration kernels on elliptic curves. As a direct generalisation of multiple polylogarithms, we construct our set of integration kernels ensuring that they have at most simple poles, implying that the iterated integrals have at most logarithmic singularities. We study the properties of our iterated integrals and their relationship to the multiple elliptic polylogarithms from the mathematics literature. On the one hand, we find that our iterated integrals span essentially the same space of functions as the multiple elliptic polylogarithms. On the other, our formulation allows for a more direct use to solve a large variety of problems in high-energy physics. We demonstrate the use of our functions in the evaluation of the Laurent expansion of some hypergeometric functions for values of the indices close to half integers.
Extensive complementarity between gene function prediction methods.

PubMed

Vidulin, Vedrana; Šmuc, Tomislav; Supek, Fran

2016-12-01

The number of sequenced genomes rises steadily but we still lack the knowledge about the biological roles of many genes. Automated function prediction (AFP) is thus a necessity. We hypothesized that AFP approaches that draw on distinct genome features may be useful for predicting different types of gene functions, motivating a systematic analysis of the benefits gained by obtaining and integrating such predictions. Our pipeline amalgamates 5 133 543 genes from 2071 genomes in a single massive analysis that evaluates five established genomic AFP methodologies. While 1227 Gene Ontology (GO) terms yielded reliable predictions, the majority of these functions were accessible to only one or two of the methods. Moreover, different methods tend to assign a GO term to non-overlapping sets of genes. Thus, inferences made by diverse genomic AFP methods display a striking complementary, both gene-wise and function-wise. Because of this, a viable integration strategy is to rely on a single most-confident prediction per gene/function, rather than enforcing agreement across multiple AFP methods. Using an information-theoretic approach, we estimate that current databases contain 29.2 bits/gene of known Escherichia coli gene functions. This can be increased by up to 5.5 bits/gene using individual AFP methods or by 11 additional bits/gene upon integration, thereby providing a highly-ranking predictor on the Critical Assessment of Function Annotation 2 community benchmark. Availability of more sequenced genomes boosts the predictive accuracy of AFP approaches and also the benefit from integrating them. The individual and integrated GO predictions for the complete set of genes are available from http://gorbi.irb.hr/ CONTACT: fran.supek@irb.hrSupplementary information: Supplementary materials are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR.

PubMed

Jakočiūnas, Tadas; Jensen, Emil D; Jensen, Michael K; Keasling, Jay D

2018-01-01

Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. CasEMBLR capitalizes on the CRISPR/Cas9 technology to generate double-strand breaks in genomic loci, thus prompting native homologous recombination (HR) machinery to integrate exogenously derived homology templates. As proof-of-principle for microbial cell factory development, CasEMBLR was used for one-step assembly and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking out two genes. This new method complements and improves the field of genome engineering in S. cerevisiae by providing a more flexible platform for rapid and precise strain building.
Variable Weight Fractional Collisions for Multiple Species Mixtures

DTIC Science & Technology

2017-08-28

DISTRIBUTION A: APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED; PA #17517 6 / 21 VARIABLE WEIGHTS FOR DYNAMIC RANGE Continuum to Discrete ...Representation: Many Particles →̃ Continuous Distribution Discretized VDF Yields Vlasov But Collision Integral Still a Problem Particle Methods VDF to Delta...Function Set Collisions between Discrete Velocities But Poorly Resolved Tail (Tail Critical to Inelastic Collisions) Variable Weights Permit Extra DOF in
On the Use of the Immediate Recall Task as a Measure of Second Language Reading Comprehension

ERIC Educational Resources Information Center

Chang, Yuh-Fang

2006-01-01

The immediate written recall task, a widely used measure of both first language (L1) and second language (L2) reading comprehension, has been advocated over traditional test methods such as multiple choice, cloze tests and open-ended questions because it is a direct and integrative assessment task. It has been, however, criticized as requiring…
A Comparison of Methods to Screen Middle School Students for Reading and Math Difficulties

ERIC Educational Resources Information Center

Nelson, Peter M.; Van Norman, Ethan R.; Lackner, Stacey K.

2016-01-01

The current study explored multiple ways in which middle schools can use and integrate data sources to predict proficiency on future high-stakes state achievement tests. The diagnostic accuracy of (a) prior achievement data, (b) teacher rating scale scores, (c) a composite score combining state test scores and rating scale responses, and (d) two…
A model-based approach to wildland fire reconstruction using sediment charcoal records

USGS Publications Warehouse

Itter, Malcolm S.; Finley, Andrew O.; Hooten, Mevin B.; Higuera, Philip E.; Marlon, Jennifer R.; Kelly, Ryan; McLachlan, Jason S.

2017-01-01

Lake sediment charcoal records are used in paleoecological analyses to reconstruct fire history, including the identification of past wildland fires. One challenge of applying sediment charcoal records to infer fire history is the separation of charcoal associated with local fire occurrence and charcoal originating from regional fire activity. Despite a variety of methods to identify local fires from sediment charcoal records, an integrated statistical framework for fire reconstruction is lacking. We develop a Bayesian point process model to estimate the probability of fire associated with charcoal counts from individual-lake sediments and estimate mean fire return intervals. A multivariate extension of the model combines records from multiple lakes to reduce uncertainty in local fire identification and estimate a regional mean fire return interval. The univariate and multivariate models are applied to 13 lakes in the Yukon Flats region of Alaska. Both models resulted in similar mean fire return intervals (100–350 years) with reduced uncertainty under the multivariate model due to improved estimation of regional charcoal deposition. The point process model offers an integrated statistical framework for paleofire reconstruction and extends existing methods to infer regional fire history from multiple lake records with uncertainty following directly from posterior distributions.
Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.
Improved genome recovery and integrated cell-size analyses of individual uncultured microbial cells and viral particles.

PubMed

Stepanauskas, Ramunas; Fergusson, Elizabeth A; Brown, Joseph; Poulton, Nicole J; Tupper, Ben; Labonté, Jessica M; Becraft, Eric D; Brown, Julia M; Pachiadaki, Maria G; Povilaitis, Tadas; Thompson, Brian P; Mascena, Corianna J; Bellows, Wendy K; Lubys, Arvydas

2017-07-20

Microbial single-cell genomics can be used to provide insights into the metabolic potential, interactions, and evolution of uncultured microorganisms. Here we present WGA-X, a method based on multiple displacement amplification of DNA that utilizes a thermostable mutant of the phi29 polymerase. WGA-X enhances genome recovery from individual microbial cells and viral particles while maintaining ease of use and scalability. The greatest improvements are observed when amplifying high G+C content templates, such as those belonging to the predominant bacteria in agricultural soils. By integrating WGA-X with calibrated index-cell sorting and high-throughput genomic sequencing, we are able to analyze genomic sequences and cell sizes of hundreds of individual, uncultured bacteria, archaea, protists, and viral particles, obtained directly from marine and soil samples, in a single experiment. This approach may find diverse applications in microbiology and in biomedical and forensic studies of humans and other multicellular organisms.Single-cell genomics can be used to study uncultured microorganisms. Here, Stepanauskas et al. present a method combining improved multiple displacement amplification and FACS, to obtain genomic sequences and cell size information from uncultivated microbial cells and viral particles in environmental samples.
Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954
A Multimodal Deep Log-Based User Experience (UX) Platform for UX Evaluation

PubMed Central

Ali Khan, Wajahat; Hur, Taeho; Muhammad Bilal, Hafiz Syed; Ul Hassan, Anees; Lee, Sungyoung

2018-01-01

The user experience (UX) is an emerging field in user research and design, and the development of UX evaluation methods presents a challenge for both researchers and practitioners. Different UX evaluation methods have been developed to extract accurate UX data. Among UX evaluation methods, the mixed-method approach of triangulation has gained importance. It provides more accurate and precise information about the user while interacting with the product. However, this approach requires skilled UX researchers and developers to integrate multiple devices, synchronize them, analyze the data, and ultimately produce an informed decision. In this paper, a method and system for measuring the overall UX over time using a triangulation method are proposed. The proposed platform incorporates observational and physiological measurements in addition to traditional ones. The platform reduces the subjective bias and validates the user’s perceptions, which are measured by different sensors through objectification of the subjective nature of the user in the UX assessment. The platform additionally offers plug-and-play support for different devices and powerful analytics for obtaining insight on the UX in terms of multiple participants. PMID:29783712
Comparing and combining biomarkers as principle surrogates for time-to-event clinical endpoints.

PubMed

Gabriel, Erin E; Sachs, Michael C; Gilbert, Peter B

2015-02-10

Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. Copyright © 2014 John Wiley & Sons, Ltd.
A Multimodal Deep Log-Based User Experience (UX) Platform for UX Evaluation.

PubMed

Hussain, Jamil; Khan, Wajahat Ali; Hur, Taeho; Bilal, Hafiz Syed Muhammad; Bang, Jaehun; Hassan, Anees Ul; Afzal, Muhammad; Lee, Sungyoung

2018-05-18

The user experience (UX) is an emerging field in user research and design, and the development of UX evaluation methods presents a challenge for both researchers and practitioners. Different UX evaluation methods have been developed to extract accurate UX data. Among UX evaluation methods, the mixed-method approach of triangulation has gained importance. It provides more accurate and precise information about the user while interacting with the product. However, this approach requires skilled UX researchers and developers to integrate multiple devices, synchronize them, analyze the data, and ultimately produce an informed decision. In this paper, a method and system for measuring the overall UX over time using a triangulation method are proposed. The proposed platform incorporates observational and physiological measurements in addition to traditional ones. The platform reduces the subjective bias and validates the user's perceptions, which are measured by different sensors through objectification of the subjective nature of the user in the UX assessment. The platform additionally offers plug-and-play support for different devices and powerful analytics for obtaining insight on the UX in terms of multiple participants.
The SUSTAIN Project: A European Study on Improving Integrated Care for Older People Living at Home

PubMed Central

Stoop, Annerieke; Billings, Jenny; Leichsenring, Kai; Ruppe, Georg; Tram, Nhu; Barbaglia, María Gabriela; Ambugo, Eliva A.; Zonneveld, Nick; Paat-Ahi, Gerli; Hoffmann, Henrik; Khan, Usman; Stein, Viktoria; Wistow, Gerald; Lette, Manon; Jansen, Aaltje P.D.; Nijpels, Giel; Baan, Caroline A.

2018-01-01

Introduction: Integrated care programmes are increasingly being put in place to provide care to older people who live at home. Knowledge of how to further develop integrated care and how to transfer successful initiatives to other contexts is still limited. Therefore, a cross-European research project, called Sustainable Tailored Integrated Care for Older People in Europe (SUSTAIN), has been initiated with a twofold objective: 1. to collaborate with local stakeholders to support and monitor improvements to established integrated care initiatives for older people with multiple health and social care needs. Improvements focus on person-centredness, prevention orientation, safety and efficiency; 2. to make these improvements applicable and adaptable to other health and social care systems, and regions in Europe. This paper presents the overall structure and approach of the SUSTAIN project. Methods: SUSTAIN uses a multiple embedded case study design. In three phases, SUSTAIN partners: (i) conduct interviews and workshops with stakeholders from fourteen established integrated care initiatives to understand where they would prefer improvements to existing ways of working; (ii) collaborate with local stakeholders to support the design and implementation of improvement plans, evaluate implementation progress and outcomes per initiative, and carry out overarching analyses to compare the different initiatives, and; (iii) translate knowledge and experience to an online roadmap. Discussion: SUSTAIN aims to generate evidence on how to improve integrated care, and apply and transfer the knowledge gained to other health and social care systems, and regions. Lessons learned will be brought together in practical tools to inform and support policy-makers and decision-makers, as well as other stakeholders involved in integrated care, to manage and improve care for older people living at home. PMID:29632456
Generation of multiphoton entangled quantum states by means of integrated frequency combs.

PubMed

Reimer, Christian; Kues, Michael; Roztocki, Piotr; Wetzel, Benjamin; Grazioso, Fabio; Little, Brent E; Chu, Sai T; Johnston, Tudor; Bromberg, Yaron; Caspani, Lucia; Moss, David J; Morandotti, Roberto

2016-03-11

Complex optical photon states with entanglement shared among several modes are critical to improving our fundamental understanding of quantum mechanics and have applications for quantum information processing, imaging, and microscopy. We demonstrate that optical integrated Kerr frequency combs can be used to generate several bi- and multiphoton entangled qubits, with direct applications for quantum communication and computation. Our method is compatible with contemporary fiber and quantum memory infrastructures and with chip-scale semiconductor technology, enabling compact, low-cost, and scalable implementations. The exploitation of integrated Kerr frequency combs, with their ability to generate multiple, customizable, and complex quantum states, can provide a scalable, practical, and compact platform for quantum technologies. Copyright © 2016, American Association for the Advancement of Science.
Single-Cell RT-PCR in Microfluidic Droplets with Integrated Chemical Lysis.

PubMed

Kim, Samuel C; Clark, Iain C; Shahi, Payam; Abate, Adam R

2018-01-16

Droplet microfluidics can identify and sort cells using digital reverse transcription polymerase chain reaction (RT-PCR) signals from individual cells. However, current methods require multiple microfabricated devices for enzymatic cell lysis and PCR reagent addition, making the process complex and prone to failure. Here, we describe a new approach that integrates all components into a single device. The method enables controlled exposure of isolated single cells to a high pH buffer, which lyses cells and inactivates reaction inhibitors but can be instantly neutralized with RT-PCR buffer. Using our chemical lysis approach, we distinguish individual cells' gene expression with data quality equivalent to more complex two-step workflows. Our system accepts cells and produces droplets ready for amplification, making single-cell droplet RT-PCR faster and more reliable.
Packaged die heater

DOEpatents

Spielberger, Richard; Ohme, Bruce Walker; Jensen, Ronald J.

2011-06-21

A heater for heating packaged die for burn-in and heat testing is described. The heater may be a ceramic-type heater with a metal filament. The heater may be incorporated into the integrated circuit package as an additional ceramic layer of the package, or may be an external heater placed in contact with the package to heat the die. Many different types of integrated circuit packages may be accommodated. The method provides increased energy efficiency for heating the die while reducing temperature stresses on testing equipment. The method allows the use of multiple heaters to heat die to different temperatures. Faulty die may be heated to weaken die attach material to facilitate removal of the die. The heater filament or a separate temperature thermistor located in the package may be used to accurately measure die temperature.
Constructing a Geology Ontology Using a Relational Database

NASA Astrophysics Data System (ADS)

Hou, W.; Yang, L.; Yin, S.; Ye, J.; Clarke, K.

2013-12-01

In geology community, the creation of a common geology ontology has become a useful means to solve problems of data integration, knowledge transformation and the interoperation of multi-source, heterogeneous and multiple scale geological data. Currently, human-computer interaction methods and relational database-based methods are the primary ontology construction methods. Some human-computer interaction methods such as the Geo-rule based method, the ontology life cycle method and the module design method have been proposed for applied geological ontologies. Essentially, the relational database-based method is a reverse engineering of abstracted semantic information from an existing database. The key is to construct rules for the transformation of database entities into the ontology. Relative to the human-computer interaction method, relational database-based methods can use existing resources and the stated semantic relationships among geological entities. However, two problems challenge the development and application. One is the transformation of multiple inheritances and nested relationships and their representation in an ontology. The other is that most of these methods do not measure the semantic retention of the transformation process. In this study, we focused on constructing a rule set to convert the semantics in a geological database into a geological ontology. According to the relational schema of a geological database, a conversion approach is presented to convert a geological spatial database to an OWL-based geological ontology, which is based on identifying semantics such as entities, relationships, inheritance relationships, nested relationships and cluster relationships. The semantic integrity of the transformation was verified using an inverse mapping process. In a geological ontology, an inheritance and union operations between superclass and subclass were used to present the nested relationship in a geochronology and the multiple inheritances relationship. Based on a Quaternary database of downtown of Foshan city, Guangdong Province, in Southern China, a geological ontology was constructed using the proposed method. To measure the maintenance of semantics in the conversation process and the results, an inverse mapping from the ontology to a relational database was tested based on a proposed conversation rule. The comparison of schema and entities and the reduction of tables between the inverse database and the original database illustrated that the proposed method retains the semantic information well during the conversation process. An application for abstracting sandstone information showed that semantic relationships among concepts in the geological database were successfully reorganized in the constructed ontology. Key words: geological ontology; geological spatial database; multiple inheritance; OWL Acknowledgement: This research is jointly funded by the Specialized Research Fund for the Doctoral Program of Higher Education of China (RFDP) (20100171120001), NSFC (41102207) and the Fundamental Research Funds for the Central Universities (12lgpy19).

Integral Methodological Pluralism in Science Education Research: Valuing Multiple Perspectives

ERIC Educational Resources Information Center

Davis, Nancy T.; Callihan, Laurie P.

2013-01-01

This article examines the multiple methodologies used in educational research and proposes a model that includes all of them as contributing to understanding educational contexts and research from multiple perspectives. The model, based on integral theory (Wilber in a theory of everything. Shambhala, Boston, 2000) values all forms of research as…
Empathetic, Critical Integrations of Multiple Perspectives: A Core Practice for Language Teacher Education?

ERIC Educational Resources Information Center

Daniel, Shannon M.

2015-01-01

In this self-study, the author reflects on her implementation of empathetic, critical integrations of multiple perspectives (ECI), which she designed to afford preservice teachers the opportunity to discuss and collectively reflect upon the oft-diverging multiple perspectives, values, and practices they experience during their practicum (Daniel,…
Impact-acoustics inspection of tile-wall bonding integrity via wavelet transform and hidden Markov models

NASA Astrophysics Data System (ADS)

Luk, B. L.; Liu, K. P.; Tong, F.; Man, K. F.

2010-05-01

The impact-acoustics method utilizes different information contained in the acoustic signals generated by tapping a structure with a small metal object. It offers a convenient and cost-efficient way to inspect the tile-wall bonding integrity. However, the existence of the surface irregularities will cause abnormal multiple bounces in the practical inspection implementations. The spectral characteristics from those bounces can easily be confused with the signals obtained from different bonding qualities. As a result, it will deteriorate the classic feature-based classification methods based on frequency domain. Another crucial difficulty posed by the implementation is the additive noise existing in the practical environments that may also cause feature mismatch and false judgment. In order to solve this problem, the work described in this paper aims to develop a robust inspection method that applies model-based strategy, and utilizes the wavelet domain features with hidden Markov modeling. It derives a bonding integrity recognition approach with enhanced immunity to surface roughness as well as the environmental noise. With the help of the specially designed artificial sample slabs, experiments have been carried out with impact acoustic signals contaminated by real environmental noises acquired under practical inspection background. The results are compared with those using classic method to demonstrate the effectiveness of the proposed method.
Merits and limitations of optimality criteria method for structural optimization

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Guptill, James D.; Berke, Laszlo

1993-01-01

The merits and limitations of the optimality criteria (OC) method for the minimum weight design of structures subjected to multiple load conditions under stress, displacement, and frequency constraints were investigated by examining several numerical examples. The examples were solved utilizing the Optimality Criteria Design Code that was developed for this purpose at NASA Lewis Research Center. This OC code incorporates OC methods available in the literature with generalizations for stress constraints, fully utilized design concepts, and hybrid methods that combine both techniques. Salient features of the code include multiple choices for Lagrange multiplier and design variable update methods, design strategies for several constraint types, variable linking, displacement and integrated force method analyzers, and analytical and numerical sensitivities. The performance of the OC method, on the basis of the examples solved, was found to be satisfactory for problems with few active constraints or with small numbers of design variables. For problems with large numbers of behavior constraints and design variables, the OC method appears to follow a subset of active constraints that can result in a heavier design. The computational efficiency of OC methods appears to be similar to some mathematical programming techniques.
Analysis of Gene Expression Profiles of Soft Tissue Sarcoma Using a Combination of Knowledge-Based Filtering with Integration of Multiple Statistics

PubMed Central

Doi, Ayano; Ichinohe, Risa; Ikuyo, Yoriko; Takahashi, Teruyoshi; Marui, Shigetaka; Yasuhara, Koji; Nakamura, Tetsuro; Sugita, Shintaro; Sakamoto, Hiromi; Yoshida, Teruhiko; Hasegawa, Tadashi

2014-01-01

The diagnosis and treatment of soft tissue sarcomas (STS) have been difficult. Of the diverse histological subtypes, undifferentiated pleomorphic sarcoma (UPS) is particularly difficult to diagnose accurately, and its classification per se is still controversial. Recent advances in genomic technologies provide an excellent way to address such problems. However, it is often difficult, if not impossible, to identify definitive disease-associated genes using genome-wide analysis alone, primarily because of multiple testing problems. In the present study, we analyzed microarray data from 88 STS patients using a combination method that used knowledge-based filtering and a simulation based on the integration of multiple statistics to reduce multiple testing problems. We identified 25 genes, including hypoxia-related genes (e.g., MIF, SCD1, P4HA1, ENO1, and STAT1) and cell cycle- and DNA repair-related genes (e.g., TACC3, PRDX1, PRKDC, and H2AFY). These genes showed significant differential expression among histological subtypes, including UPS, and showed associations with overall survival. STAT1 showed a strong association with overall survival in UPS patients (logrank p = 1.84×10−6 and adjusted p value 2.99×10−3 after the permutation test). According to the literature, the 25 genes selected are useful not only as markers of differential diagnosis but also as prognostic/predictive markers and/or therapeutic targets for STS. Our combination method can identify genes that are potential prognostic/predictive factors and/or therapeutic targets in STS and possibly in other cancers. These disease-associated genes deserve further preclinical and clinical validation. PMID:25188299
Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis.

PubMed

van Dam, Jesse C J; Schaap, Peter J; Martins dos Santos, Vitor A P; Suárez-Diez, María

2014-09-26

Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different networks. By simultaneously exploring these networks and metadata, we gained insights into regulatory mechanisms in M. tuberculosis that could not be obtained through the separate analysis of each data type.
An Integrative Framework for the Analysis of Multiple and Multimodal Representations for Meaning-Making in Science Education

ERIC Educational Resources Information Center

Tang, Kok-Sing; Delgado, Cesar; Moje, Elizabeth Birr

2014-01-01

This paper presents an integrative framework for analyzing science meaning-making with representations. It integrates the research on multiple representations and multimodal representations by identifying and leveraging the differences in their units of analysis in two dimensions: timescale and compositional grain size. Timescale considers the…
The interactions of multisensory integration with endogenous and exogenous attention

PubMed Central

Tang, Xiaoyu; Wu, Jinglong; Shen, Yong

2016-01-01

Stimuli from multiple sensory organs can be integrated into a coherent representation through multiple phases of multisensory processing; this phenomenon is called multisensory integration. Multisensory integration can interact with attention. Here, we propose a framework in which attention modulates multisensory processing in both endogenous (goal-driven) and exogenous (stimulus-driven) ways. Moreover, multisensory integration exerts not only bottom-up but also top-down control over attention. Specifically, we propose the following: (1) endogenous attentional selectivity acts on multiple levels of multisensory processing to determine the extent to which simultaneous stimuli from different modalities can be integrated; (2) integrated multisensory events exert top-down control on attentional capture via multisensory search templates that are stored in the brain; (3) integrated multisensory events can capture attention efficiently, even in quite complex circumstances, due to their increased salience compared to unimodal events and can thus improve search accuracy; and (4) within a multisensory object, endogenous attention can spread from one modality to another in an exogenous manner. PMID:26546734
The interactions of multisensory integration with endogenous and exogenous attention.

PubMed

Tang, Xiaoyu; Wu, Jinglong; Shen, Yong

2016-02-01

Stimuli from multiple sensory organs can be integrated into a coherent representation through multiple phases of multisensory processing; this phenomenon is called multisensory integration. Multisensory integration can interact with attention. Here, we propose a framework in which attention modulates multisensory processing in both endogenous (goal-driven) and exogenous (stimulus-driven) ways. Moreover, multisensory integration exerts not only bottom-up but also top-down control over attention. Specifically, we propose the following: (1) endogenous attentional selectivity acts on multiple levels of multisensory processing to determine the extent to which simultaneous stimuli from different modalities can be integrated; (2) integrated multisensory events exert top-down control on attentional capture via multisensory search templates that are stored in the brain; (3) integrated multisensory events can capture attention efficiently, even in quite complex circumstances, due to their increased salience compared to unimodal events and can thus improve search accuracy; and (4) within a multisensory object, endogenous attention can spread from one modality to another in an exogenous manner. Copyright © 2015 Elsevier Ltd. All rights reserved.
Realizing drug repositioning by adapting a recommendation system to handle the process.

PubMed

Ozsoy, Makbule Guclin; Özyer, Tansel; Polat, Faruk; Alhajj, Reda

2018-04-12

Drug repositioning is the process of identifying new targets for known drugs. It can be used to overcome problems associated with traditional drug discovery by adapting existing drugs to treat new discovered diseases. Thus, it may reduce associated risk, cost and time required to identify and verify new drugs. Nowadays, drug repositioning has received more attention from industry and academia. To tackle this problem, researchers have applied many different computational methods and have used various features of drugs and diseases. In this study, we contribute to the ongoing research efforts by combining multiple features, namely chemical structures, protein interactions and side-effects to predict new indications of target drugs. To achieve our target, we realize drug repositioning as a recommendation process and this leads to a new perspective in tackling the problem. The utilized recommendation method is based on Pareto dominance and collaborative filtering. It can also integrate multiple data-sources and multiple features. For the computation part, we applied several settings and we compared their performance. Evaluation results show that the proposed method can achieve more concentrated predictions with high precision, where nearly half of the predictions are true. Compared to other state of the art methods described in the literature, the proposed method is better at making right predictions by having higher precision. The reported results demonstrate the applicability and effectiveness of recommendation methods for drug repositioning.
A new method to identify the foot of continental slope based on an integrated profile analysis

NASA Astrophysics Data System (ADS)

Wu, Ziyin; Li, Jiabiao; Li, Shoujun; Shang, Jihong; Jin, Xiaobin

2017-06-01

A new method is proposed to identify automatically the foot of the continental slope (FOS) based on the integrated analysis of topographic profiles. Based on the extremum points of the second derivative and the Douglas-Peucker algorithm, it simplifies the topographic profiles, then calculates the second derivative of the original profiles and the D-P profiles. Seven steps are proposed to simplify the original profiles. Meanwhile, multiple identification methods are proposed to determine the FOS points, including gradient, water depth and second derivative values of data points, as well as the concave and convex, continuity and segmentation of the topographic profiles. This method can comprehensively and intelligently analyze the topographic profiles and their derived slopes, second derivatives and D-P profiles, based on which, it is capable to analyze the essential properties of every single data point in the profile. Furthermore, it is proposed to remove the concave points of the curve and in addition, to implement six FOS judgment criteria.
A New Approach for Checking and Complementing CALIPSO Lidar Calibration

NASA Technical Reports Server (NTRS)

Josset, Damien B.; Vaughan, Mark A.; Hu, Yongxiang; Avery, Melody A.; Powell, Kathleen A.; Hunt, William H.; Winker, David M.; Pelon, Jacques; Trepte, Charles R.; Lucker, Patricia L.;

2010-01-01

We have been studying the backscatter ratio of the two CALIPSO wavelengths for 3 different targets. We are showing the ratio of integrate attenuated backscatter coefficient for cirrus clouds, ocean surface and liquid. Water clouds for one month of nightime data (left:July,right:December), Only opaque cirrus classified as randomly oriented ice[1] are used. For ocean and water clouds, only the clearest shots, determined by a threshold on integrated attenuated backscatter are used. Two things can be immediately observed: 1. A similar trend (black dotted line) is visible using all targets, the color ratio shows a tendency to be higher north and lower south for those two months. 2. The water clouds average value is around 15% lower than ocean surface and cirrus clouds. This is due to the different multiple scattering at 532 nm and 1064 nm [2] which strongly impact the water cloud retrieval. Conclusion: Different targets can be used to improve CALIPSO 1064 nm calibration accuracy. All of them show the signature of an instrumental calibration shift. Multiple scattering introduce a bias in liquid water cloud signal but it still compares very well with all other methods and should not be overlooked. The effect of multiple scattering in liquid and ice clouds will be the subject of future research. If there really is a sampling issue. Combining all methods to increase the sampling, mapping the calibration coefficient or trying to reach an orbit per orbit calibration seems an appropriate way.

Oscillatory supersonic kernel function method for interfering surfaces

NASA Technical Reports Server (NTRS)

Cunningham, A. M., Jr.

1974-01-01

In the method presented in this paper, a collocation technique is used with the nonplanar supersonic kernel function to solve multiple lifting surface problems with interference in steady or oscillatory flow. The pressure functions used are based on conical flow theory solutions and provide faster solution convergence than is possible with conventional functions. In the application of the nonplanar supersonic kernel function, an improper integral of a 3/2 power singularity along the Mach hyperbola is described and treated. The method is compared with other theories and experiment for two wing-tail configurations in steady and oscillatory flow.
Unified framework to evaluate panmixia and migration direction among multiple sampling locations.

PubMed

Beerli, Peter; Palczewski, Michal

2010-05-01

For many biological investigations, groups of individuals are genetically sampled from several geographic locations. These sampling locations often do not reflect the genetic population structure. We describe a framework using marginal likelihoods to compare and order structured population models, such as testing whether the sampling locations belong to the same randomly mating population or comparing unidirectional and multidirectional gene flow models. In the context of inferences employing Markov chain Monte Carlo methods, the accuracy of the marginal likelihoods depends heavily on the approximation method used to calculate the marginal likelihood. Two methods, modified thermodynamic integration and a stabilized harmonic mean estimator, are compared. With finite Markov chain Monte Carlo run lengths, the harmonic mean estimator may not be consistent. Thermodynamic integration, in contrast, delivers considerably better estimates of the marginal likelihood. The choice of prior distributions does not influence the order and choice of the better models when the marginal likelihood is estimated using thermodynamic integration, whereas with the harmonic mean estimator the influence of the prior is pronounced and the order of the models changes. The approximation of marginal likelihood using thermodynamic integration in MIGRATE allows the evaluation of complex population genetic models, not only of whether sampling locations belong to a single panmictic population, but also of competing complex structured population models.
A review on machine learning principles for multi-view biological data integration.

PubMed

Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune

2018-03-01

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.
A simple and efficient method to enhance audiovisual binding tendencies

PubMed Central

Wozny, David R.; Shams, Ladan

2017-01-01

Individuals vary in their tendency to bind signals from multiple senses. For the same set of sights and sounds, one individual may frequently integrate multisensory signals and experience a unified percept, whereas another individual may rarely bind them and often experience two distinct sensations. Thus, while this binding/integration tendency is specific to each individual, it is not clear how plastic this tendency is in adulthood, and how sensory experiences may cause it to change. Here, we conducted an exploratory investigation which provides evidence that (1) the brain’s tendency to bind in spatial perception is plastic, (2) that it can change following brief exposure to simple audiovisual stimuli, and (3) that exposure to temporally synchronous, spatially discrepant stimuli provides the most effective method to modify it. These results can inform current theories about how the brain updates its internal model of the surrounding sensory world, as well as future investigations seeking to increase integration tendencies. PMID:28462016
The integrated quality assessment of Chinese commercial dry red wine based on a method of online HPLC-DAD-CL combined with HPLC-ESI-MS.

PubMed

Yu, Hai-Xiang; Sun, Li-Qiong; Qi, Jin

2014-07-01

To apply an integrated quality assessment strategy to investigate the quality of multiple Chinese commercial dry red wine samples. A comprehensive method was developed by combining a high performance liquid chromatography-diode array detector-chemiluminescence (HPLC-DAD-CL) online hyphenated system with an HPLC-ESI-MS technique. Chromatographic and H2O2-scavenging active fingerprints of thirteen batches of different, commercially available Chinese dry red wine samples were obtained and analyzed. Twenty-five compounds, including eighteen antioxidants were identified and evaluated. The dominant and characteristic antioxidants in the samples were identified. The relationships between antioxidant potency and the cultivated variety of grape, producing area, cellaring period, and trade mark are also discussed. The results provide the feasibility for an integrated quality assessment strategy to be efficiently and objectively used in quality (especially antioxidant activity) assessment and identification of dry red wine. Copyright © 2014 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.
Combined mining: discovering informative knowledge in complex data.

PubMed

Cao, Longbing; Zhang, Huaifeng; Zhao, Yanchang; Luo, Dan; Zhang, Chengqi

2011-06-01

Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, user preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. It would also be very time and space consuming, if not impossible, to join relevant large data sources for mining patterns consisting of multiple aspects of information. It is crucial to develop effective approaches for mining patterns combining necessary information from multiple relevant business lines, catering for real business settings and decision-making actions rather than just providing a single line of patterns. The recent years have seen increasing efforts on mining more informative patterns, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. Rather than presenting a specific algorithm, this paper builds on our existing works and proposes combined mining as a general approach to mining for informative patterns combining components from either multiple data sets or multiple features or by multiple methods on demand. We summarize general frameworks, paradigms, and basic processes for multifeature combined mining, multisource combined mining, and multimethod combined mining. Novel types of combined patterns, such as incremental cluster patterns, can result from such frameworks, which cannot be directly produced by the existing methods. A set of real-world case studies has been conducted to test the frameworks, with some of them briefed in this paper. They identify combined patterns for informing government debt prevention and improving government service objectives, which show the flexibility and instantiation capability of combined mining in discovering informative knowledge in complex data.
Integrated QSAR study for inhibitors of hedgehog signal pathway against multiple cell lines:a collaborative filtering method

PubMed Central

2012-01-01

Background The Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway. Results In this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have proposed several possible chemical modifications to improve the inhibitor affinity towards multiple targets in the Hedgehog Signaling Pathway. Conclusions Our model with the feature selection strategy presented here is efficient, robust, and flexible, and can be easily extended to model large-scale multiple cell line/QSAR data. The data and scripts for collaborative QSAR modeling are available in the Additional file 1. PMID:22849868
Integrated QSAR study for inhibitors of Hedgehog Signal Pathway against multiple cell lines:a collaborative filtering method.

PubMed

Gao, Jun; Che, Dongsheng; Zheng, Vincent W; Zhu, Ruixin; Liu, Qi

2012-07-31

The Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway. In this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have proposed several possible chemical modifications to improve the inhibitor affinity towards multiple targets in the Hedgehog Signaling Pathway. Our model with the feature selection strategy presented here is efficient, robust, and flexible, and can be easily extended to model large-scale multiple cell line/QSAR data. The data and scripts for collaborative QSAR modeling are available in the Additional file 1.

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