NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel
2017-08-01
Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.
Collaborative Filtering Based on Sequential Extraction of User-Item Clusters
NASA Astrophysics Data System (ADS)
Honda, Katsuhiro; Notsu, Akira; Ichihashi, Hidetomo
Collaborative filtering is a computational realization of “word-of-mouth” in network community, in which the items prefered by “neighbors” are recommended. This paper proposes a new item-selection model for extracting user-item clusters from rectangular relation matrices, in which mutual relations between users and items are denoted in an alternative process of “liking or not”. A technique for sequential co-cluster extraction from rectangular relational data is given by combining the structural balancing-based user-item clustering method with sequential fuzzy cluster extraction appraoch. Then, the tecunique is applied to the collaborative filtering problem, in which some items may be shared by several user clusters.
The composite sequential clustering technique for analysis of multispectral scanner data
NASA Technical Reports Server (NTRS)
Su, M. Y.
1972-01-01
The clustering technique consists of two parts: (1) a sequential statistical clustering which is essentially a sequential variance analysis, and (2) a generalized K-means clustering. In this composite clustering technique, the output of (1) is a set of initial clusters which are input to (2) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by traditional supervised maximum likelihood classification techniques. The mathematical algorithms for the composite sequential clustering program and a detailed computer program description with job setup are given.
Scalable Parallel Density-based Clustering and Applications
NASA Astrophysics Data System (ADS)
Patwary, Mostofa Ali
2014-04-01
Recently, density-based clustering algorithms (DBSCAN and OPTICS) have gotten significant attention of the scientific community due to their unique capability of discovering arbitrary shaped clusters and eliminating noise data. These algorithms have several applications, which require high performance computing, including finding halos and subhalos (clusters) from massive cosmology data in astrophysics, analyzing satellite images, X-ray crystallography, and anomaly detection. However, parallelization of these algorithms are extremely challenging as they exhibit inherent sequential data access order, unbalanced workload resulting in low parallel efficiency. To break the data access sequentiality and to achieve high parallelism, we develop new parallel algorithms, both for DBSCAN and OPTICS, designed using graph algorithmic techniques. For example, our parallel DBSCAN algorithm exploits the similarities between DBSCAN and computing connected components. Using datasets containing up to a billion floating point numbers, we show that our parallel density-based clustering algorithms significantly outperform the existing algorithms, achieving speedups up to 27.5 on 40 cores on shared memory architecture and speedups up to 5,765 using 8,192 cores on distributed memory architecture. In our experiments, we found that while achieving the scalability, our algorithms produce clustering results with comparable quality to the classical algorithms.
Robust sequential working memory recall in heterogeneous cognitive networks
Rabinovich, Mikhail I.; Sokolov, Yury; Kozma, Robert
2014-01-01
Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a result, competitive network dynamics is qualitatively altered. This dynamics defines the robust recall of the sequential information from memory and, thus, the SWM capacity. To understand pathological and non-pathological bifurcations of the sequential memory dynamics, here we investigate the model of recurrent inhibitory-excitatory networks with heterogeneous inhibition. We consider the ensemble of units with all-to-all inhibitory connections, in which the connection strengths are monotonically distributed at some interval. Based on computer experiments and studying the Lyapunov exponents, we observed and analyzed the new phenomenon—clustered sequential dynamics. The results are interpreted in the context of the winnerless competition principle. Accordingly, clustered sequential dynamics is represented in the phase space of the model by two weakly interacting quasi-attractors. One of them is similar to the sequential heteroclinic chain—the regular image of SWM, while the other is a quasi-chaotic attractor. Coexistence of these quasi-attractors means that the recall of the normal information sequence is intermittently interrupted by episodes with chaotic dynamics. We indicate potential dynamic ways for augmenting damaged working memory and other cognitive functions. PMID:25452717
Bahlmann, Claus; Burkhardt, Hans
2004-03-01
In this paper, we give a comprehensive description of our writer-independent online handwriting recognition system frog on hand. The focus of this work concerns the presentation of the classification/training approach, which we call cluster generative statistical dynamic time warping (CSDTW). CSDTW is a general, scalable, HMM-based method for variable-sized, sequential data that holistically combines cluster analysis and statistical sequence modeling. It can handle general classification problems that rely on this sequential type of data, e.g., speech recognition, genome processing, robotics, etc. Contrary to previous attempts, clustering and statistical sequence modeling are embedded in a single feature space and use a closely related distance measure. We show character recognition experiments of frog on hand using CSDTW on the UNIPEN online handwriting database. The recognition accuracy is significantly higher than reported results of other handwriting recognition systems. Finally, we describe the real-time implementation of frog on hand on a Linux Compaq iPAQ embedded device.
An unsupervised classification technique for multispectral remote sensing data.
NASA Technical Reports Server (NTRS)
Su, M. Y.; Cummings, R. E.
1973-01-01
Description of a two-part clustering technique consisting of (a) a sequential statistical clustering, which is essentially a sequential variance analysis, and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by traditional supervised maximum-likelihood classification techniques.
Unsupervised classification of earth resources data.
NASA Technical Reports Server (NTRS)
Su, M. Y.; Jayroe, R. R., Jr.; Cummings, R. E.
1972-01-01
A new clustering technique is presented. It consists of two parts: (a) a sequential statistical clustering which is essentially a sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. This unsupervised composite technique was employed for automatic classification of two sets of remote multispectral earth resource observations. The classification accuracy by the unsupervised technique is found to be comparable to that by existing supervised maximum liklihood classification technique.
Plane-Based Sampling for Ray Casting Algorithm in Sequential Medical Images
Lin, Lili; Chen, Shengyong; Shao, Yan; Gu, Zichun
2013-01-01
This paper proposes a plane-based sampling method to improve the traditional Ray Casting Algorithm (RCA) for the fast reconstruction of a three-dimensional biomedical model from sequential images. In the novel method, the optical properties of all sampling points depend on the intersection points when a ray travels through an equidistant parallel plan cluster of the volume dataset. The results show that the method improves the rendering speed at over three times compared with the conventional algorithm and the image quality is well guaranteed. PMID:23424608
Reuse of imputed data in microarray analysis increases imputation efficiency
Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su
2004-01-01
Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240
Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold
2014-12-01
In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.
Sequential desorption energy of hydrogen from nickel clusters
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deepika,; Kumar, Rakesh, E-mail: rakesh@iitrpr.ac.in; R, Kamal Raj.
2015-06-24
We report reversible Hydrogen adsorption on Nickel clusters, which act as a catalyst for solid state storage of Hydrogen on a substrate. First-principles technique is employed to investigate the maximum number of chemically adsorbed Hydrogen molecules on Nickel cluster. We observe a maximum of four Hydrogen molecules adsorbed per Nickel atom, but the average Hydrogen molecules adsorbed per Nickel atom decrease with cluster size. The dissociative chemisorption energy per Hydrogen molecule and sequential desorption energy per Hydrogen atom on Nickel cluster is found to decrease with number of adsorbed Hydrogen molecules, which on optimization may help in economical storage andmore » regeneration of Hydrogen as a clean energy carrier.« less
NASA Astrophysics Data System (ADS)
Granade, Christopher; Wiebe, Nathan
2017-08-01
A major challenge facing existing sequential Monte Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results with equivalent probability. We address this problem here by proposing a form of particle filtering that clusters the particles that comprise the sequential Monte Carlo approximation to the posterior before applying a resampler. Through a new graphical approach to thinking about such models, we are able to devise an artificial-intelligence based strategy that automatically learns the shape and number of the clusters in the support of the posterior. We demonstrate the power of our approach by applying it to randomized gap estimation and a form of low circuit-depth phase estimation where existing methods from the physics literature either exhibit much worse performance or even fail completely.
Grover, Elise; Hossain, Mohammed Kamal; Uddin, Saker; Venkatesh, Mohini; Ram, Pavani K; Dreibelbis, Robert
2018-01-01
To determine the impact of environmental nudges on handwashing behaviours among primary school children as compared to a high-intensity hygiene education intervention. In a cluster-randomised trial (CRT), we compared the rates of handwashing with soap (HWWS) after a toileting event among primary school students in rural Bangladesh. Eligible schools (government run, on-site sanitation and water, no hygiene interventions in last year, fewer than 450 students) were identified, and 20 schools were randomly selected and allocated without blinding to one of four interventions, five schools per group: simultaneous handwashing infrastructure and nudge construction, sequential infrastructure then nudge construction, simultaneous infrastructure and high-intensity hygiene education (HE) and sequential handwashing infrastructure and HE. The primary outcome, incidence of HWWS after a toileting event, was compared between the intervention groups at different data collection points with robust-Poisson regression analysis with generalised estimating equations, adjusting for school-level clustering of outcomes. The nudge intervention and the HE intervention were found to be equally effective at sustained impact over 5 months post-intervention (adjusted IRR 0.81, 95% CI 0.61-1.09). When comparing intervention delivery timing, the simultaneous delivery of the HE intervention significantly outperformed the sequential HE delivery (adjusted IRR 1.58 CI 1.20-2.08), whereas no significant difference was observed between sequential and simultaneous nudge intervention delivery (adjusted IRR 0.75, 95% CI 0.48-1.17). Our trial demonstrates sustained improved handwashing behaviour 5 months after the nudge intervention. The nudge intervention's comparable performance to a high-intensity hygiene education intervention is encouraging. © 2017 John Wiley & Sons Ltd.
Group sequential designs for stepped-wedge cluster randomised trials
Grayling, Michael J; Wason, James MS; Mander, Adrian P
2017-01-01
Background/Aims: The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Methods: Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. Results: We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial’s type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. Conclusion: The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into stepped-wedge cluster randomised trials according to the needs of the particular trial. PMID:28653550
Group sequential designs for stepped-wedge cluster randomised trials.
Grayling, Michael J; Wason, James Ms; Mander, Adrian P
2017-10-01
The stepped-wedge cluster randomised trial design has received substantial attention in recent years. Although various extensions to the original design have been proposed, no guidance is available on the design of stepped-wedge cluster randomised trials with interim analyses. In an individually randomised trial setting, group sequential methods can provide notable efficiency gains and ethical benefits. We address this by discussing how established group sequential methodology can be adapted for stepped-wedge designs. Utilising the error spending approach to group sequential trial design, we detail the assumptions required for the determination of stepped-wedge cluster randomised trials with interim analyses. We consider early stopping for efficacy, futility, or efficacy and futility. We describe first how this can be done for any specified linear mixed model for data analysis. We then focus on one particular commonly utilised model and, using a recently completed stepped-wedge cluster randomised trial, compare the performance of several designs with interim analyses to the classical stepped-wedge design. Finally, the performance of a quantile substitution procedure for dealing with the case of unknown variance is explored. We demonstrate that the incorporation of early stopping in stepped-wedge cluster randomised trial designs could reduce the expected sample size under the null and alternative hypotheses by up to 31% and 22%, respectively, with no cost to the trial's type-I and type-II error rates. The use of restricted error maximum likelihood estimation was found to be more important than quantile substitution for controlling the type-I error rate. The addition of interim analyses into stepped-wedge cluster randomised trials could help guard against time-consuming trials conducted on poor performing treatments and also help expedite the implementation of efficacious treatments. In future, trialists should consider incorporating early stopping of some kind into stepped-wedge cluster randomised trials according to the needs of the particular trial.
Unsupervised classification of remote multispectral sensing data
NASA Technical Reports Server (NTRS)
Su, M. Y.
1972-01-01
The new unsupervised classification technique for classifying multispectral remote sensing data which can be either from the multispectral scanner or digitized color-separation aerial photographs consists of two parts: (a) a sequential statistical clustering which is a one-pass sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. Applications of the technique using an IBM-7094 computer on multispectral data sets over Purdue's Flight Line C-1 and the Yellowstone National Park test site have been accomplished. Comparisons between the classification maps by the unsupervised technique and the supervised maximum liklihood technique indicate that the classification accuracies are in agreement.
Berthias, F; Feketeová, L; Abdoul-Carime, H; Calvo, F; Farizon, B; Farizon, M; Märk, T D
2018-06-22
Velocity distributions of neutral water molecules evaporated after collision induced dissociation of protonated water clusters H+(H2O)n≤10 were measured using the combined correlated ion and neutral fragment time-of-flight (COINTOF) and velocity map imaging (VMI) techniques. As observed previously, all measured velocity distributions exhibit two contributions, with a low velocity part identified by statistical molecular dynamics (SMD) simulations as events obeying the Maxwell-Boltzmann statistics and a high velocity contribution corresponding to non-ergodic events in which energy redistribution is incomplete. In contrast to earlier studies, where the evaporation of a single molecule was probed, the present study is concerned with events involving the evaporation of up to five water molecules. In particular, we discuss here in detail the cases of two and three evaporated molecules. Evaporation of several water molecules after CID can be interpreted in general as a sequential evaporation process. In addition to the SMD calculations, a Monte Carlo (MC) based simulation was developed allowing the reconstruction of the velocity distribution produced by the evaporation of m molecules from H+(H2O)n≤10 cluster ions using the measured velocity distributions for singly evaporated molecules as the input. The observed broadening of the low-velocity part of the distributions for the evaporation of two and three molecules as compared to the width for the evaporation of a single molecule results from the cumulative recoil velocity of the successive ion residues as well as the intrinsically broader distributions for decreasingly smaller parent clusters. Further MC simulations were carried out assuming that a certain proportion of non-ergodic events is responsible for the first evaporation in such a sequential evaporation series, thereby allowing to model the entire velocity distribution.
A spatial scan statistic for multiple clusters.
Li, Xiao-Zhou; Wang, Jin-Feng; Yang, Wei-Zhong; Li, Zhong-Jie; Lai, Sheng-Jie
2011-10-01
Spatial scan statistics are commonly used for geographical disease surveillance and cluster detection. While there are multiple clusters coexisting in the study area, they become difficult to detect because of clusters' shadowing effect to each other. The recently proposed sequential method showed its better power for detecting the second weaker cluster, but did not improve the ability of detecting the first stronger cluster which is more important than the second one. We propose a new extension of the spatial scan statistic which could be used to detect multiple clusters. Through constructing two or more clusters in the alternative hypothesis, our proposed method accounts for other coexisting clusters in the detecting and evaluating process. The performance of the proposed method is compared to the sequential method through an intensive simulation study, in which our proposed method shows better power in terms of both rejecting the null hypothesis and accurately detecting the coexisting clusters. In the real study of hand-foot-mouth disease data in Pingdu city, a true cluster town is successfully detected by our proposed method, which cannot be evaluated to be statistically significant by the standard method due to another cluster's shadowing effect. Copyright © 2011 Elsevier Inc. All rights reserved.
An adaptive two-stage sequential design for sampling rare and clustered populations
Brown, J.A.; Salehi, M.M.; Moradi, M.; Bell, G.; Smith, D.R.
2008-01-01
How to design an efficient large-area survey continues to be an interesting question for ecologists. In sampling large areas, as is common in environmental studies, adaptive sampling can be efficient because it ensures survey effort is targeted to subareas of high interest. In two-stage sampling, higher density primary sample units are usually of more interest than lower density primary units when populations are rare and clustered. Two-stage sequential sampling has been suggested as a method for allocating second stage sample effort among primary units. Here, we suggest a modification: adaptive two-stage sequential sampling. In this method, the adaptive part of the allocation process means the design is more flexible in how much extra effort can be directed to higher-abundance primary units. We discuss how best to design an adaptive two-stage sequential sample. ?? 2008 The Society of Population Ecology and Springer.
NASA Technical Reports Server (NTRS)
Smedes, H. W.; Linnerud, H. J.; Woolaver, L. B.; Su, M. Y.; Jayroe, R. R.
1972-01-01
Two clustering techniques were used for terrain mapping by computer of test sites in Yellowstone National Park. One test was made with multispectral scanner data using a composite technique which consists of (1) a strictly sequential statistical clustering which is a sequential variance analysis, and (2) a generalized K-means clustering. In this composite technique, the output of (1) is a first approximation of the cluster centers. This is the input to (2) which consists of steps to improve the determination of cluster centers by iterative procedures. Another test was made using the three emulsion layers of color-infrared aerial film as a three-band spectrometer. Relative film densities were analyzed using a simple clustering technique in three-color space. Important advantages of the clustering technique over conventional supervised computer programs are (1) human intervention, preparation time, and manipulation of data are reduced, (2) the computer map, gives unbiased indication of where best to select the reference ground control data, (3) use of easy to obtain inexpensive film, and (4) the geometric distortions can be easily rectified by simple standard photogrammetric techniques.
Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J
2009-04-01
Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67x3 (67 clusters of three observations) and a 33x6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67x3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis.
Stabilizing ultrasmall Au clusters for enhanced photoredox catalysis.
Weng, Bo; Lu, Kang-Qiang; Tang, Zichao; Chen, Hao Ming; Xu, Yi-Jun
2018-04-18
Recently, loading ligand-protected gold (Au) clusters as visible light photosensitizers onto various supports for photoredox catalysis has attracted considerable attention. However, the efficient control of long-term photostability of Au clusters on the metal-support interface remains challenging. Herein, we report a simple and efficient method for enhancing the photostability of glutathione-protected Au clusters (Au GSH clusters) loaded on the surface of SiO 2 sphere by utilizing multifunctional branched poly-ethylenimine (BPEI) as a surface charge modifying, reducing and stabilizing agent. The sequential coating of thickness controlled TiO 2 shells can further significantly improve the photocatalytic efficiency, while such structurally designed core-shell SiO 2 -Au GSH clusters-BPEI@TiO 2 composites maintain high photostability during longtime light illumination conditions. This joint strategy via interfacial modification and composition engineering provides a facile guideline for stabilizing ultrasmall Au clusters and rational design of Au clusters-based composites with improved activity toward targeting applications in photoredox catalysis.
NASA Technical Reports Server (NTRS)
Chapman, G. M. (Principal Investigator); Carnes, J. G.
1981-01-01
Several techniques which use clusters generated by a new clustering algorithm, CLASSY, are proposed as alternatives to random sampling to obtain greater precision in crop proportion estimation: (1) Proportional Allocation/relative count estimator (PA/RCE) uses proportional allocation of dots to clusters on the basis of cluster size and a relative count cluster level estimate; (2) Proportional Allocation/Bayes Estimator (PA/BE) uses proportional allocation of dots to clusters and a Bayesian cluster-level estimate; and (3) Bayes Sequential Allocation/Bayesian Estimator (BSA/BE) uses sequential allocation of dots to clusters and a Bayesian cluster level estimate. Clustering in an effective method in making proportion estimates. It is estimated that, to obtain the same precision with random sampling as obtained by the proportional sampling of 50 dots with an unbiased estimator, samples of 85 or 166 would need to be taken if dot sets with AI labels (integrated procedure) or ground truth labels, respectively were input. Dot reallocation provides dot sets that are unbiased. It is recommended that these proportion estimation techniques are maintained, particularly the PA/BE because it provides the greatest precision.
Zhang, Wei; Zhang, Xiaolong; Qiang, Yan; Tian, Qi; Tang, Xiaoxian
2017-01-01
The fast and accurate segmentation of lung nodule image sequences is the basis of subsequent processing and diagnostic analyses. However, previous research investigating nodule segmentation algorithms cannot entirely segment cavitary nodules, and the segmentation of juxta-vascular nodules is inaccurate and inefficient. To solve these problems, we propose a new method for the segmentation of lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise (DBSCAN). First, our method uses three-dimensional computed tomography image features of the average intensity projection combined with multi-scale dot enhancement for preprocessing. Hexagonal clustering and morphological optimized sequential linear iterative clustering (HMSLIC) for sequence image oversegmentation is then proposed to obtain superpixel blocks. The adaptive weight coefficient is then constructed to calculate the distance required between superpixels to achieve precise lung nodules positioning and to obtain the subsequent clustering starting block. Moreover, by fitting the distance and detecting the change in slope, an accurate clustering threshold is obtained. Thereafter, a fast DBSCAN superpixel sequence clustering algorithm, which is optimized by the strategy of only clustering the lung nodules and adaptive threshold, is then used to obtain lung nodule mask sequences. Finally, the lung nodule image sequences are obtained. The experimental results show that our method rapidly, completely and accurately segments various types of lung nodule image sequences. PMID:28880916
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mackey, Lester; Nachman, Benjamin; Schwartzman, Ariel
Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets . To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets , are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variablesmore » in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.« less
Mackey, Lester; Nachman, Benjamin; Schwartzman, Ariel; ...
2016-06-01
Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets . To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets , are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variablesmore » in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.« less
Statistical Significance for Hierarchical Clustering
Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.
2017-01-01
Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990
Kim, Da Hye; Kim, Hyun You; Ryu, Ji Hoon; Lee, Hyuck Mo
2009-07-07
This report on the solid-to-liquid transition region of an Ag-Pd bimetallic nanocluster is based on a constant energy microcanonical ensemble molecular dynamics simulation combined with a collision method. By varying the size and composition of an Ag-Pd bimetallic cluster, we obtained a complete solid-solution type of binary phase diagram of the Ag-Pd system. Irrespective of the size and composition of the cluster, the melting temperature of Ag-Pd bimetallic clusters is lower than that of the bulk state and rises as the cluster size and the Pd composition increase. Additionally, the slope of the phase boundaries (even though not exactly linear) is lowered when the cluster size is reduced on account of the complex relations of the surface tension, the bulk melting temperature, and the heat of fusion. The melting of the cluster initially starts at the surface layer. The initiation and propagation of a five-fold icosahedron symmetry is related to the sequential melting of the cluster.
Two-stage sequential sampling: A neighborhood-free adaptive sampling procedure
Salehi, M.; Smith, D.R.
2005-01-01
Designing an efficient sampling scheme for a rare and clustered population is a challenging area of research. Adaptive cluster sampling, which has been shown to be viable for such a population, is based on sampling a neighborhood of units around a unit that meets a specified condition. However, the edge units produced by sampling neighborhoods have proven to limit the efficiency and applicability of adaptive cluster sampling. We propose a sampling design that is adaptive in the sense that the final sample depends on observed values, but it avoids the use of neighborhoods and the sampling of edge units. Unbiased estimators of population total and its variance are derived using Murthy's estimator. The modified two-stage sampling design is easy to implement and can be applied to a wider range of populations than adaptive cluster sampling. We evaluate the proposed sampling design by simulating sampling of two real biological populations and an artificial population for which the variable of interest took the value either 0 or 1 (e.g., indicating presence and absence of a rare event). We show that the proposed sampling design is more efficient than conventional sampling in nearly all cases. The approach used to derive estimators (Murthy's estimator) opens the door for unbiased estimators to be found for similar sequential sampling designs. ?? 2005 American Statistical Association and the International Biometric Society.
Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J
2009-01-01
Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67×3 (67 clusters of three observations) and a 33×6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67×3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis. PMID:20011037
Applications of colored petri net and genetic algorithms to cluster tool scheduling
NASA Astrophysics Data System (ADS)
Liu, Tung-Kuan; Kuo, Chih-Jen; Hsiao, Yung-Chin; Tsai, Jinn-Tsong; Chou, Jyh-Horng
2005-12-01
In this paper, we propose a method, which uses Coloured Petri Net (CPN) and genetic algorithm (GA) to obtain an optimal deadlock-free schedule and to solve re-entrant problem for the flexible process of the cluster tool. The process of the cluster tool for producing a wafer usually can be classified into three types: 1) sequential process, 2) parallel process, and 3) sequential parallel process. But these processes are not economical enough to produce a variety of wafers in small volume. Therefore, this paper will propose the flexible process where the operations of fabricating wafers are randomly arranged to achieve the best utilization of the cluster tool. However, the flexible process may have deadlock and re-entrant problems which can be detected by CPN. On the other hand, GAs have been applied to find the optimal schedule for many types of manufacturing processes. Therefore, we successfully integrate CPN and GAs to obtain an optimal schedule with the deadlock and re-entrant problems for the flexible process of the cluster tool.
Optimal mode transformations for linear-optical cluster-state generation
Uskov, Dmitry B.; Lougovski, Pavel; Alsing, Paul M.; ...
2015-06-15
In this paper, we analyze the generation of linear-optical cluster states (LOCSs) via sequential addition of one and two qubits. Existing approaches employ the stochastic linear-optical two-qubit controlled-Z (CZ) gate with success rate of 1/9 per operation. The question of optimality of the CZ gate with respect to LOCS generation has remained open. We report that there are alternative schemes to the CZ gate that are exponentially more efficient and show that sequential LOCS growth is indeed globally optimal. We find that the optimal cluster growth operation is a state transformation on a subspace of the full Hilbert space. Finally,more » we show that the maximal success rate of postselected entangling n photonic qubits or m Bell pairs into a cluster is (1/2) n-1 and (1/4) m-1, respectively, with no ancilla photons, and we give an explicit optical description of the optimal mode transformations.« less
Unusual behavior in magnesium-copper cluster matter produced by helium droplet mediated deposition.
Emery, S B; Xin, Y; Ridge, C J; Buszek, R J; Boatz, J A; Boyle, J M; Little, B K; Lindsay, C M
2015-02-28
We demonstrate the ability to produce core-shell nanoclusters of materials that typically undergo intermetallic reactions using helium droplet mediated deposition. Composite structures of magnesium and copper were produced by sequential condensation of metal vapors inside the 0.4 K helium droplet baths and then gently deposited onto a substrate for analysis. Upon deposition, the individual clusters, with diameters ∼5 nm, form a cluster material which was subsequently characterized using scanning and transmission electron microscopies. Results of this analysis reveal the following about the deposited cluster material: it is in the un-alloyed chemical state, it maintains a stable core-shell 5 nm structure at sub-monolayer quantities, and it aggregates into unreacted structures of ∼75 nm during further deposition. Surprisingly, high angle annular dark field scanning transmission electron microscopy images revealed that the copper appears to displace the magnesium at the core of the composite cluster despite magnesium being the initially condensed species within the droplet. This phenomenon was studied further using preliminary density functional theory which revealed that copper atoms, when added sequentially to magnesium clusters, penetrate into the magnesium cores.
Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance
Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao
2018-01-01
Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600
Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.
Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao
2018-01-01
Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.
A Sequential Ensemble Prediction System at Convection Permitting Scales
NASA Astrophysics Data System (ADS)
Milan, M.; Simmer, C.
2012-04-01
A Sequential Assimilation Method (SAM) following some aspects of particle filtering with resampling, also called SIR (Sequential Importance Resampling), is introduced and applied in the framework of an Ensemble Prediction System (EPS) for weather forecasting on convection permitting scales, with focus to precipitation forecast. At this scale and beyond, the atmosphere increasingly exhibits chaotic behaviour and non linear state space evolution due to convectively driven processes. One way to take full account of non linear state developments are particle filter methods, their basic idea is the representation of the model probability density function by a number of ensemble members weighted by their likelihood with the observations. In particular particle filter with resampling abandons ensemble members (particles) with low weights restoring the original number of particles adding multiple copies of the members with high weights. In our SIR-like implementation we substitute the likelihood way to define weights and introduce a metric which quantifies the "distance" between the observed atmospheric state and the states simulated by the ensemble members. We also introduce a methodology to counteract filter degeneracy, i.e. the collapse of the simulated state space. To this goal we propose a combination of resampling taking account of simulated state space clustering and nudging. By keeping cluster representatives during resampling and filtering, the method maintains the potential for non linear system state development. We assume that a particle cluster with initially low likelihood may evolve in a state space with higher likelihood in a subsequent filter time thus mimicking non linear system state developments (e.g. sudden convection initiation) and remedies timing errors for convection due to model errors and/or imperfect initial condition. We apply a simplified version of the resampling, the particles with highest weights in each cluster are duplicated; for the model evolution for each particle pair one particle evolves using the forward model; the second particle, however, is nudged to the radar and satellite observation during its evolution based on the forward model.
Spatial location influences vocal interactions in bullfrog choruses
Bates, Mary E.; Cropp, Brett F.; Gonchar, Marina; Knowles, Jeffrey; Simmons, James A.; Simmons, Andrea Megela
2010-01-01
A multiple sensor array was employed to identify the spatial locations of all vocalizing male bullfrogs (Rana catesbeiana) in five natural choruses. Patterns of vocal activity collected with this array were compared with computer simulations of chorus activity. Bullfrogs were not randomly spaced within choruses, but tended to cluster into closely spaced groups of two to five vocalizing males. There were nonrandom, differing patterns of vocal interactions within clusters of closely spaced males and between different clusters. Bullfrogs located within the same cluster tended to overlap or alternate call notes with two or more other males in that cluster. These near-simultaneous calling bouts produced advertisement calls with more pronounced amplitude modulation than occurred in nonoverlapping notes or calls. Bullfrogs located in different clusters more often alternated entire calls or overlapped only small segments of their calls. They also tended to respond sequentially to calls of their farther neighbors compared to their nearer neighbors. Results of computational analyses showed that the observed patterns of vocal interactions were significantly different than expected based on random activity. The use of a multiple sensor array provides a richer view of the dynamics of choruses than available based on single microphone techniques. PMID:20370047
Novel high-fidelity realistic explosion damage simulation for urban environments
NASA Astrophysics Data System (ADS)
Liu, Xiaoqing; Yadegar, Jacob; Zhu, Youding; Raju, Chaitanya; Bhagavathula, Jaya
2010-04-01
Realistic building damage simulation has a significant impact in modern modeling and simulation systems especially in diverse panoply of military and civil applications where these simulation systems are widely used for personnel training, critical mission planning, disaster management, etc. Realistic building damage simulation should incorporate accurate physics-based explosion models, rubble generation, rubble flyout, and interactions between flying rubble and their surrounding entities. However, none of the existing building damage simulation systems sufficiently faithfully realize the criteria of realism required for effective military applications. In this paper, we present a novel physics-based high-fidelity and runtime efficient explosion simulation system to realistically simulate destruction to buildings. In the proposed system, a family of novel blast models is applied to accurately and realistically simulate explosions based on static and/or dynamic detonation conditions. The system also takes account of rubble pile formation and applies a generic and scalable multi-component based object representation to describe scene entities and highly scalable agent-subsumption architecture and scheduler to schedule clusters of sequential and parallel events. The proposed system utilizes a highly efficient and scalable tetrahedral decomposition approach to realistically simulate rubble formation. Experimental results demonstrate that the proposed system has the capability to realistically simulate rubble generation, rubble flyout and their primary and secondary impacts on surrounding objects including buildings, constructions, vehicles and pedestrians in clusters of sequential and parallel damage events.
Li, Ke; Ping, Xueliang; Wang, Huaqing; Chen, Peng; Cao, Yi
2013-06-21
A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well.
Li, Ke; Ping, Xueliang; Wang, Huaqing; Chen, Peng; Cao, Yi
2013-01-01
A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well. PMID:23793021
Underlying mathematics in diversification of human olfactory receptors in different loci.
Hassan, Sk Sarif; Choudhury, Pabitra Pal; Goswami, Arunava
2013-12-01
As per conservative estimate, approximately 51-105 Olfactory Receptors (ORs) loci are present in human genome occurring in clusters. These clusters are apparently unevenly spread as mosaics over 21 pairs of human chromosomes. Olfactory Receptor (OR) gene families which are thought to have expanded for the need to provide recognition capability for a huge number of pure and complex odorants, form the largest known multigene family in the human genome. Recent studies have shown that 388 full length and 414 OR pseudo-genes are present in these OR genomic clusters. In this paper, the authors report a classification method for all human ORs based on their sequential quantitative information like presence of poly strings of nucleotides bases, long range correlation and so on. An L-System generated sequence has been taken as an input into a star-model of specific subfamily members and resultant sequence has been mapped to a specific OR based on the classification scheme using fractal parameters like Hurst exponent and fractal dimensions.
Empirical Identification of Hierarchies.
ERIC Educational Resources Information Center
McCormick, Douglas; And Others
Outlining a cluster procedure which maximizes specific criteria while building scales from binary measures using a sequential, agglomerative, overlapping, non-hierarchic method results in indices giving truer results than exploratory facotr analyses or multidimensional scaling. In a series of eleven figures, patterns within cluster histories…
A mathematical programming approach for sequential clustering of dynamic networks
NASA Astrophysics Data System (ADS)
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
2016-02-01
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yuan, S; Lu, WG; Chen, YP
2015-03-11
A unique strategy, sequential linker installation (SLI), has been developed to construct multivariate MOFs with functional groups precisely positioned. PCN-700, a Zr-MOF with eight-connected Zr6O4(OH)(8)(H2O)(4) clusters, has been judiciously designed; the Zr-6 clusters in this MOF are arranged in such a fashion that, by replacement of terminal OH-/H2O ligands, subsequent insertion of linear dicarboxylate linkers is achieved. We demonstrate that linkers with distinct lengths and functionalities can be sequentially installed into PCN-700. Single-crystal to single-crystal transformation is realized so that the positions of the subsequently installed linkers are pinpointed via single-crystal X-ray diffraction analyses. This methodology provides a powerful toolmore » to construct multivariate MOFs with precisely positioned functionalities in the desired proximity, which would otherwise be difficult to achieve.« less
Unusual behavior in magnesium-copper cluster matter produced by helium droplet mediated deposition
DOE Office of Scientific and Technical Information (OSTI.GOV)
Emery, S. B., E-mail: samuel.emery@navy.mil; Little, B. K.; Air Force Research Laboratory, Munitions Directorate, 2306 Perimeter Rd., Eglin AFB, Florida 32542
2015-02-28
We demonstrate the ability to produce core-shell nanoclusters of materials that typically undergo intermetallic reactions using helium droplet mediated deposition. Composite structures of magnesium and copper were produced by sequential condensation of metal vapors inside the 0.4 K helium droplet baths and then gently deposited onto a substrate for analysis. Upon deposition, the individual clusters, with diameters ∼5 nm, form a cluster material which was subsequently characterized using scanning and transmission electron microscopies. Results of this analysis reveal the following about the deposited cluster material: it is in the un-alloyed chemical state, it maintains a stable core-shell 5 nm structuremore » at sub-monolayer quantities, and it aggregates into unreacted structures of ∼75 nm during further deposition. Surprisingly, high angle annular dark field scanning transmission electron microscopy images revealed that the copper appears to displace the magnesium at the core of the composite cluster despite magnesium being the initially condensed species within the droplet. This phenomenon was studied further using preliminary density functional theory which revealed that copper atoms, when added sequentially to magnesium clusters, penetrate into the magnesium cores.« less
Utilization of group theory in studies of molecular clusters
NASA Astrophysics Data System (ADS)
Ocak, Mahir E.
The structure of the molecular symmetry group of molecular clusters was analyzed and it is shown that the molecular symmetry group of a molecular cluster can be written as direct products and semidirect products of its subgroups. Symmetry adaptation of basis functions in direct product groups and semidirect product groups was considered in general and the sequential symmetry adaptation procedure which is already known for direct product groups was extended to the case of semidirect product groups. By using the sequential symmetry adaptation procedure a new method for calculating the VRT spectra of molecular clusters which is named as Monomer Basis Representation (MBR) method is developed. In the MBR method, calculations starts with a single monomer with the purpose of obtaining an optimized basis for that monomer as a linear combination of some primitive basis functions. Then, an optimized basis for each identical monomer is generated from the optimized basis of this monomer. By using the optimized bases of the monomers, a basis is generated generated for the solution of the full problem, and the VRT spectra of the cluster is obtained by using this basis. Since an optimized basis is used for each monomer which has a much smaller size than the primitive basis from which the optimized bases are generated, the MBR method leads to an exponential optimization in the size of the basis that is required for the calculations. Application of the MBR method has been illustrated by calculating the VRT spectra of water dimer by using the SAPT-5st potential surface of Groenenboom et al. The rest of the calculations are in good agreement with both the original calculations of Groenenboom et al. and also with the experimental results. Comparing the size of the optimized basis with the size of the primitive basis, it can be said that the method works efficiently. Because of its efficiency, the MBR method can be used for studies of clusters bigger than dimers. Thus, MBR method can be used for studying the many-body terms and for deriving accurate potential surfaces.
Sequential Organization and Room Reverberation for Speech Segregation
2012-02-28
we have proposed two algorithms for sequential organization, an unsupervised clustering algorithm applicable to monaural recordings and a binaural ...algorithm that integrates monaural and binaural analyses. In addition, we have conducted speech intelligibility tests that Firmly establish the...comprehensive version is currently under review for journal publication. A binaural approach in room reverberation Most existing approaches to binaural or
Identifying protein complexes in PPI network using non-cooperative sequential game.
Maulik, Ujjwal; Basu, Srinka; Ray, Sumanta
2017-08-21
Identifying protein complexes from protein-protein interaction (PPI) network is an important and challenging task in computational biology as it helps in better understanding of cellular mechanisms in various organisms. In this paper we propose a noncooperative sequential game based model for protein complex detection from PPI network. The key hypothesis is that protein complex formation is driven by mechanism that eventually optimizes the number of interactions within the complex leading to dense subgraph. The hypothesis is drawn from the observed network property named small world. The proposed multi-player game model translates the hypothesis into the game strategies. The Nash equilibrium of the game corresponds to a network partition where each protein either belong to a complex or form a singleton cluster. We further propose an algorithm to find the Nash equilibrium of the sequential game. The exhaustive experiment on synthetic benchmark and real life yeast networks evaluates the structural as well as biological significance of the network partitions.
Cluster Stability Estimation Based on a Minimal Spanning Trees Approach
NASA Astrophysics Data System (ADS)
Volkovich, Zeev (Vladimir); Barzily, Zeev; Weber, Gerhard-Wilhelm; Toledano-Kitai, Dvora
2009-08-01
Among the areas of data and text mining which are employed today in science, economy and technology, clustering theory serves as a preprocessing step in the data analyzing. However, there are many open questions still waiting for a theoretical and practical treatment, e.g., the problem of determining the true number of clusters has not been satisfactorily solved. In the current paper, this problem is addressed by the cluster stability approach. For several possible numbers of clusters we estimate the stability of partitions obtained from clustering of samples. Partitions are considered consistent if their clusters are stable. Clusters validity is measured as the total number of edges, in the clusters' minimal spanning trees, connecting points from different samples. Actually, we use the Friedman and Rafsky two sample test statistic. The homogeneity hypothesis, of well mingled samples within the clusters, leads to asymptotic normal distribution of the considered statistic. Resting upon this fact, the standard score of the mentioned edges quantity is set, and the partition quality is represented by the worst cluster corresponding to the minimal standard score value. It is natural to expect that the true number of clusters can be characterized by the empirical distribution having the shortest left tail. The proposed methodology sequentially creates the described value distribution and estimates its left-asymmetry. Numerical experiments, presented in the paper, demonstrate the ability of the approach to detect the true number of clusters.
Accelerating Information Retrieval from Profile Hidden Markov Model Databases.
Tamimi, Ahmad; Ashhab, Yaqoub; Tamimi, Hashem
2016-01-01
Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.
Molle, Thibaut; Moreau, Yohann; Clemancey, Martin; Forouhar, Farhad; Ravanat, Jean-Luc; Duraffourg, Nicolas; Fourmond, Vincent; Latour, Jean-Marc; Gambarelli, Serge; Mulliez, Etienne; Atta, Mohamed
2016-10-18
RimO, a radical-S-adenosylmethionine (SAM) enzyme, catalyzes the specific C 3 methylthiolation of the D89 residue in the ribosomal S 12 protein. Two intact iron-sulfur clusters and two SAM cofactors both are required for catalysis. By using electron paramagnetic resonance, Mössbauer spectroscopies, and site-directed mutagenesis, we show how two SAM molecules sequentially bind to the unique iron site of the radical-SAM cluster for two distinct chemical reactions in RimO. Our data establish that the two SAM molecules bind the radical-SAM cluster to the unique iron site, and spectroscopic evidence obtained under strongly reducing conditions supports a mechanism in which the first molecule of SAM causes the reoxidation of the reduced radical-SAM cluster, impeding reductive cleavage of SAM to occur and allowing SAM to methylate a HS - ligand bound to the additional cluster. Furthermore, by using density functional theory-based methods, we provide a description of the reaction mechanism that predicts the attack of the carbon radical substrate on the methylthio group attached to the additional [4Fe-4S] cluster.
2013-01-01
Background The paper presents the evaluation of soil contamination with total, water-available, mobile, semi-mobile and non-mobile Hg fractions in the surroundings of a former chlor-alkali plant in connection with several chemical soil characteristics. Principal Component Analysis and Cluster Analysis were used to evaluate the chemical composition variability of soil and factors influencing the fate of Hg in such areas. The sequential extraction EPA 3200-Method and the determination technique based on capacitively coupled microplasma optical emission spectrometry were checked. Results A case study was conducted in the Turda town, Romania. The results revealed a high contamination with Hg in the area of the former chlor-alkali plant and waste landfills, where soils were categorized as hazardous waste. The weight of the Hg fractions decreased in the order semi-mobile > non-mobile > mobile > water leachable. Principal Component Analysis revealed 7 factors describing chemical composition variability of soil, of which 3 attributed to Hg species. Total Hg, semi-mobile, non-mobile and mobile fractions were observed to have a strong influence, while the water leachable fraction a weak influence. The two-dimensional plot of PCs highlighted 3 groups of sites according to the Hg contamination factor. The statistical approach has shown that the Hg fate in soil is dependent on pH, content of organic matter, Ca, Fe, Mn, Cu and SO42- rather than natural components, such as aluminosilicates. Cluster analysis of soil characteristics revealed 3 clusters, one of which including Hg species. Soil contamination with Cu as sulfate and Zn as nitrate was also observed. Conclusions The approach based on speciation and statistical interpretation of data developed in this study could be useful in the investigation of other chlor-alkali contaminated areas. According to the Bland and Altman test the 3-step sequential extraction scheme is suitable for Hg speciation in soil, while the used determination method of Hg is appropriate. PMID:24252185
An empirical method to cluster objective nebulizer adherence data among adults with cystic fibrosis.
Hoo, Zhe H; Campbell, Michael J; Curley, Rachael; Wildman, Martin J
2017-01-01
The purpose of using preventative inhaled treatments in cystic fibrosis is to improve health outcomes. Therefore, understanding the relationship between adherence to treatment and health outcome is crucial. Temporal variability, as well as absolute magnitude of adherence affects health outcomes, and there is likely to be a threshold effect in the relationship between adherence and outcomes. We therefore propose a pragmatic algorithm-based clustering method of objective nebulizer adherence data to better understand this relationship, and potentially, to guide clinical decisions. This clustering method consists of three related steps. The first step is to split adherence data for the previous 12 months into four 3-monthly sections. The second step is to calculate mean adherence for each section and to score the section based on mean adherence. The third step is to aggregate the individual scores to determine the final cluster ("cluster 1" = very low adherence; "cluster 2" = low adherence; "cluster 3" = moderate adherence; "cluster 4" = high adherence), and taking into account adherence trend as represented by sequential individual scores. The individual scores should be displayed along with the final cluster for clinicians to fully understand the adherence data. We present three cases to illustrate the use of the proposed clustering method. This pragmatic clustering method can deal with adherence data of variable duration (ie, can be used even if 12 months' worth of data are unavailable) and can cluster adherence data in real time. Empirical support for some of the clustering parameters is not yet available, but the suggested classifications provide a structure to investigate parameters in future prospective datasets in which there are accurate measurements of nebulizer adherence and health outcomes.
ATP hydrolysis in Eg5 kinesin involves a catalytic two-water mechanism.
Parke, Courtney L; Wojcik, Edward J; Kim, Sunyoung; Worthylake, David K
2010-02-19
Motor proteins couple steps in ATP binding and hydrolysis to conformational switching both in and remote from the active site. In our kinesin.AMPPPNP crystal structure, closure of the active site results in structural transformations appropriate for microtubule binding and organizes an orthosteric two-water cluster. We conclude that a proton is shared between the lytic water, positioned for gamma-phosphate attack, and a second water that serves as a general base. To our knowledge, this is the first experimental detection of the catalytic base for any ATPase. Deprotonation of the second water by switch residues likely triggers subsequent large scale structural rearrangements. Therefore, the catalytic base is responsible for initiating nucleophilic attack of ATP and for relaying the positive charge over long distances to initiate mechanotransduction. Coordination of switch movements via sequential proton transfer along paired water clusters may be universal for nucleotide triphosphatases with conserved active sites, such as myosins and G-proteins.
Danwanichakul, Panu; Glandt, Eduardo D
2004-11-15
We applied the integral-equation theory to the connectedness problem. The method originally applied to the study of continuum percolation in various equilibrium systems was modified for our sequential quenching model, a particular limit of an irreversible adsorption. The development of the theory based on the (quenched-annealed) binary-mixture approximation includes the Ornstein-Zernike equation, the Percus-Yevick closure, and an additional term involving the three-body connectedness function. This function is simplified by introducing a Kirkwood-like superposition approximation. We studied the three-dimensional (3D) system of randomly placed spheres and 2D systems of square-well particles, both with a narrow and with a wide well. The results from our integral-equation theory are in good accordance with simulation results within a certain range of densities.
NASA Astrophysics Data System (ADS)
Danwanichakul, Panu; Glandt, Eduardo D.
2004-11-01
We applied the integral-equation theory to the connectedness problem. The method originally applied to the study of continuum percolation in various equilibrium systems was modified for our sequential quenching model, a particular limit of an irreversible adsorption. The development of the theory based on the (quenched-annealed) binary-mixture approximation includes the Ornstein-Zernike equation, the Percus-Yevick closure, and an additional term involving the three-body connectedness function. This function is simplified by introducing a Kirkwood-like superposition approximation. We studied the three-dimensional (3D) system of randomly placed spheres and 2D systems of square-well particles, both with a narrow and with a wide well. The results from our integral-equation theory are in good accordance with simulation results within a certain range of densities.
The capacity limitations of orientation summary statistics
Attarha, Mouna; Moore, Cathleen M.
2015-01-01
The simultaneous–sequential method was used to test the processing capacity of establishing mean orientation summaries. Four clusters of oriented Gabor patches were presented in the peripheral visual field. One of the clusters had a mean orientation that was tilted either left or right while the mean orientations of the other three clusters were roughly vertical. All four clusters were presented at the same time in the simultaneous condition whereas the clusters appeared in temporal subsets of two in the sequential condition. Performance was lower when the means of all four clusters had to be processed concurrently than when only two had to be processed in the same amount of time. The advantage for establishing fewer summaries at a given time indicates that the processing of mean orientation engages limited-capacity processes (Experiment 1). This limitation cannot be attributed to crowding, low target-distractor discriminability, or a limited-capacity comparison process (Experiments 2 and 3). In contrast to the limitations of establishing multiple summary representations, establishing a single summary representation unfolds without interference (Experiment 4). When interpreted in the context of recent work on the capacity of summary statistics, these findings encourage reevaluation of the view that early visual perception consists of summary statistic representations that unfold independently across multiple areas of the visual field. PMID:25810160
Tang, Jialin; Soua, Slim; Mares, Cristinel; Gan, Tat-Hean
2017-01-01
The identification of particular types of damage in wind turbine blades using acoustic emission (AE) techniques is a significant emerging field. In this work, a 45.7-m turbine blade was subjected to flap-wise fatigue loading for 21 days, during which AE was measured by internally mounted piezoelectric sensors. This paper focuses on using unsupervised pattern recognition methods to characterize different AE activities corresponding to different fracture mechanisms. A sequential feature selection method based on a k-means clustering algorithm is used to achieve a fine classification accuracy. The visualization of clusters in peak frequency−frequency centroid features is used to correlate the clustering results with failure modes. The positions of these clusters in time domain features, average frequency−MARSE, and average frequency−peak amplitude are also presented in this paper (where MARSE represents the Measured Area under Rectified Signal Envelope). The results show that these parameters are representative for the classification of the failure modes. PMID:29104245
Tang, Jialin; Soua, Slim; Mares, Cristinel; Gan, Tat-Hean
2017-11-01
The identification of particular types of damage in wind turbine blades using acoustic emission (AE) techniques is a significant emerging field. In this work, a 45.7-m turbine blade was subjected to flap-wise fatigue loading for 21 days, during which AE was measured by internally mounted piezoelectric sensors. This paper focuses on using unsupervised pattern recognition methods to characterize different AE activities corresponding to different fracture mechanisms. A sequential feature selection method based on a k-means clustering algorithm is used to achieve a fine classification accuracy. The visualization of clusters in peak frequency-frequency centroid features is used to correlate the clustering results with failure modes. The positions of these clusters in time domain features, average frequency-MARSE, and average frequency-peak amplitude are also presented in this paper (where MARSE represents the Measured Area under Rectified Signal Envelope). The results show that these parameters are representative for the classification of the failure modes.
ERIC Educational Resources Information Center
Rhee, Eunjeong; Lee, Bo Hyun; Kim, Boyoung; Ha, Gyuyoung; Lee, Sang Min
2016-01-01
The current study investigated how the five components of planned happenstance skills are related to vocational identity statuses. For determination of relationships, cluster and discriminant analyses were conducted sequentially on a sample of 515 university students in South Korea. Cluster analysis revealed vocational identity statuses to be…
Ji, N Y; Capone, G T; Kaufmann, W E
2011-11-01
The diagnostic validity of autism spectrum disorder (ASD) based on Diagnostic and Statistical Manual of Mental Disorders (DSM) has been challenged in Down syndrome (DS), because of the high prevalence of cognitive impairments in this population. Therefore, we attempted to validate DSM-based diagnoses via an unbiased categorisation of participants with a DSM-independent behavioural instrument. Based on scores on the Aberrant Behaviour Checklist - Community, we performed sequential factor (four DS-relevant factors: Autism-Like Behaviour, Disruptive Behaviour, Hyperactivity, Self-Injury) and cluster analyses on a 293-participant paediatric DS clinic cohort. The four resulting clusters were compared with DSM-delineated groups: DS + ASD, DS + None (no DSM diagnosis), DS + DBD (disruptive behaviour disorder) and DS + SMD (stereotypic movement disorder), the latter two as comparison groups. Two clusters were identified with DS + ASD: Cluster 1 (35.1%) with higher disruptive behaviour and Cluster 4 (48.2%) with more severe autistic behaviour and higher percentage of late onset ASD. The majority of participants in DS + None (71.9%) and DS + DBD (87.5%) were classified into Cluster 2 and 3, respectively, while participants in DS + SMD were relatively evenly distributed throughout the four clusters. Our unbiased, DSM-independent analyses, using a rating scale specifically designed for individuals with severe intellectual disability, demonstrated that DSM-based criteria of ASD are applicable to DS individuals despite their cognitive impairments. Two DS + ASD clusters were identified and supported the existence of at least two subtypes of ASD in DS, which deserve further characterisation. Despite the prominence of stereotypic behaviour in DS, the SMD diagnosis was not identified by cluster analysis, suggesting that high-level stereotypy is distributed throughout DS. Further supporting DSM diagnoses, typically behaving DS participants were easily distinguished as a group from those with maladaptive behaviours. © 2011 The Authors. Journal of Intellectual Disability Research © 2011 Blackwell Publishing Ltd.
GPU Accelerated Clustering for Arbitrary Shapes in Geoscience Data
NASA Astrophysics Data System (ADS)
Pankratius, V.; Gowanlock, M.; Rude, C. M.; Li, J. D.
2016-12-01
Clustering algorithms have become a vital component in intelligent systems for geoscience that helps scientists discover and track phenomena of various kinds. Here, we outline advances in Density-Based Spatial Clustering of Applications with Noise (DBSCAN) which detects clusters of arbitrary shape that are common in geospatial data. In particular, we propose a hybrid CPU-GPU implementation of DBSCAN and highlight new optimization approaches on the GPU that allows clustering detection in parallel while optimizing data transport during CPU-GPU interactions. We employ an efficient batching scheme between the host and GPU such that limited GPU memory is not prohibitive when processing large and/or dense datasets. To minimize data transfer overhead, we estimate the total workload size and employ an execution that generates optimized batches that will not overflow the GPU buffer. This work is demonstrated on space weather Total Electron Content (TEC) datasets containing over 5 million measurements from instruments worldwide, and allows scientists to spot spatially coherent phenomena with ease. Our approach is up to 30 times faster than a sequential implementation and therefore accelerates discoveries in large datasets. We acknowledge support from NSF ACI-1442997.
Che-Mendoza, Azael; Guillermo-May, Guillermo; Herrera-Bojórquez, Josué; Barrera-Pérez, Mario; Dzul-Manzanilla, Felipe; Gutierrez-Castro, Cipriano; Arredondo-Jiménez, Juan I.; Sánchez-Tejeda, Gustavo; Vazquez-Prokopec, Gonzalo; Ranson, Hilary; Lenhart, Audrey; Sommerfeld, Johannes; McCall, Philip J.; Kroeger, Axel; Manrique-Saide, Pablo
2015-01-01
Background Long-lasting insecticidal net screens (LLIS) fitted to domestic windows and doors in combination with targeted treatment (TT) of the most productive Aedes aegypti breeding sites were evaluated for their impact on dengue vector indices in a cluster-randomised trial in Mexico between 2011 and 2013. Methods Sequentially over 2 years, LLIS and TT were deployed in 10 treatment clusters (100 houses/cluster) and followed up over 24 months. Cross-sectional surveys quantified infestations of adult mosquitoes, immature stages at baseline (pre-intervention) and in four post-intervention samples at 6-monthly intervals. Identical surveys were carried out in 10 control clusters that received no treatment. Results LLIS clusters had significantly lower infestations compared to control clusters at 5 and 12 months after installation, as measured by adult (male and female) and pupal-based vector indices. After addition of TT to the intervention houses in intervention clusters, indices remained significantly lower in the treated clusters until 18 (immature and adult stage indices) and 24 months (adult indices only) post-intervention. Conclusions These safe, simple affordable vector control tools were well-accepted by study participants and are potentially suitable in many regions at risk from dengue worldwide. PMID:25604761
CAMPAIGN: an open-source library of GPU-accelerated data clustering algorithms.
Kohlhoff, Kai J; Sosnick, Marc H; Hsu, William T; Pande, Vijay S; Altman, Russ B
2011-08-15
Data clustering techniques are an essential component of a good data analysis toolbox. Many current bioinformatics applications are inherently compute-intense and work with very large datasets. Sequential algorithms are inadequate for providing the necessary performance. For this reason, we have created Clustering Algorithms for Massively Parallel Architectures, Including GPU Nodes (CAMPAIGN), a central resource for data clustering algorithms and tools that are implemented specifically for execution on massively parallel processing architectures. CAMPAIGN is a library of data clustering algorithms and tools, written in 'C for CUDA' for Nvidia GPUs. The library provides up to two orders of magnitude speed-up over respective CPU-based clustering algorithms and is intended as an open-source resource. New modules from the community will be accepted into the library and the layout of it is such that it can easily be extended to promising future platforms such as OpenCL. Releases of the CAMPAIGN library are freely available for download under the LGPL from https://simtk.org/home/campaign. Source code can also be obtained through anonymous subversion access as described on https://simtk.org/scm/?group_id=453. kjk33@cantab.net.
Algorithms for Large-Scale Astronomical Problems
2013-08-01
implemented as a succession of Hadoop MapReduce jobs and sequential programs written in Java . The sampling and splitting stages are implemented as...one MapReduce job, the partitioning and clustering phases make up another job. The merging stage is implemented as a stand-alone Java program. The...Merging. The merging stage is implemented as a sequential Java program that reads the files with the shell information, which were generated by
Imaging sequential dehydrogenation of methanol on Cu(110) with a scanning tunneling microscope.
Kitaguchi, Y; Shiotari, A; Okuyama, H; Hatta, S; Aruga, T
2011-05-07
Adsorption of methanol and its dehydrogenation on Cu(110) were studied by using a scanning tunneling microscope (STM). Upon adsorption at 12 K, methanol preferentially forms clusters on the surface. The STM could induce dehydrogenation of methanol sequentially to methoxy and formaldehyde. This enabled us to study the binding structures of these products in a single-molecule limit. Methoxy was imaged as a pair of protrusion and depression along the [001] direction. This feature is fully consistent with the previous result that it adsorbs on the short-bridge site with the C-O axis tilted along the [001] direction. The axis was induced to flip back and forth by vibrational excitations with the STM. Two configurations were observed for formaldehyde, whose structures were proposed based on their characteristic images and motions.
NASA Astrophysics Data System (ADS)
Wolfram, Markus; König, Stephan; Bandelow, Steffi; Fischer, Paul; Jankowski, Alexander; Marx, Gerrit; Schweikhard, Lutz
2018-02-01
Lead clusters {{{{Pb}}}{n}}+/- in the size range between about n = 15 and 40 have recently shown to exhibit complex dissociation spectra due to sequential and competing decays. In order to disentangle the pathways the exemplary {{{{Pb}}}31}+ clusters have been stored and size selected in a Penning trap and irradiated by nanosecond laser pulses. We present time-resolved measurements at time scales from several tens of microseconds to several hundreds of milliseconds. The study results in strong evidence that {{{{Pb}}}31}+ decays not only by neutral monomer evaporation but also by neutral heptamers breaking off. In addition, the decays are further followed to smaller products. The corresponding decay and growth times show that {{{{Pb}}}30}+ also dissociates by either monomer evaporation or heptamer break-off. Furthermore, the product {{{{Pb}}}17}+ may well be a result of heptamer break-off from {{{{Pb}}}24}+—as the second step of a sequential heptamer decay.
Ferrucci, Filomena; Salza, Pasquale; Sarro, Federica
2017-06-29
The need to improve the scalability of Genetic Algorithms (GAs) has motivated the research on Parallel Genetic Algorithms (PGAs), and different technologies and approaches have been used. Hadoop MapReduce represents one of the most mature technologies to develop parallel algorithms. Based on the fact that parallel algorithms introduce communication overhead, the aim of the present work is to understand if, and possibly when, the parallel GAs solutions using Hadoop MapReduce show better performance than sequential versions in terms of execution time. Moreover, we are interested in understanding which PGA model can be most effective among the global, grid, and island models. We empirically assessed the performance of these three parallel models with respect to a sequential GA on a software engineering problem, evaluating the execution time and the achieved speedup. We also analysed the behaviour of the parallel models in relation to the overhead produced by the use of Hadoop MapReduce and the GAs' computational effort, which gives a more machine-independent measure of these algorithms. We exploited three problem instances to differentiate the computation load and three cluster configurations based on 2, 4, and 8 parallel nodes. Moreover, we estimated the costs of the execution of the experimentation on a potential cloud infrastructure, based on the pricing of the major commercial cloud providers. The empirical study revealed that the use of PGA based on the island model outperforms the other parallel models and the sequential GA for all the considered instances and clusters. Using 2, 4, and 8 nodes, the island model achieves an average speedup over the three datasets of 1.8, 3.4, and 7.0 times, respectively. Hadoop MapReduce has a set of different constraints that need to be considered during the design and the implementation of parallel algorithms. The overhead of data store (i.e., HDFS) accesses, communication, and latency requires solutions that reduce data store operations. For this reason, the island model is more suitable for PGAs than the global and grid model, also in terms of costs when executed on a commercial cloud provider.
NASA Astrophysics Data System (ADS)
Venuti, L.; Prisinzano, L.; Sacco, G. G.; Flaccomio, E.; Bonito, R.; Damiani, F.; Micela, G.; Guarcello, M. G.; Randich, S.; Stauffer, J. R.; Cody, A. M.; Jeffries, R. D.; Alencar, S. H. P.; Alfaro, E. J.; Lanzafame, A. C.; Pancino, E.; Bayo, A.; Carraro, G.; Costado, M. T.; Frasca, A.; Jofré, P.; Morbidelli, L.; Sousa, S. G.; Zaggia, S.
2018-01-01
Context. Reconstructing the structure and history of young clusters is pivotal to understanding the mechanisms and timescales of early stellar evolution and planet formation. Recent studies suggest that star clusters often exhibit a hierarchical structure, possibly resulting from several star formation episodes occurring sequentially rather than a monolithic cloud collapse. Aims: We aim to explore the structure of the open cluster and star-forming region NGC 2264 ( 3 Myr), which is one of the youngest, richest and most accessible star clusters in the local spiral arm of our Galaxy; we link the spatial distribution of cluster members to other stellar properties such as age and evolutionary stage to probe the star formation history within the region. Methods: We combined spectroscopic data obtained as part of the Gaia-ESO Survey (GES) with multi-wavelength photometric data from the Coordinated Synoptic Investigation of NGC 2264 (CSI 2264) campaign. We examined a sample of 655 cluster members, with masses between 0.2 and 1.8 M⊙ and including both disk-bearing and disk-free young stars. We used Teff estimates from GES and g,r,i photometry from CSI 2264 to derive individual extinction and stellar parameters. Results: We find a significant age spread of 4-5 Myr among cluster members. Disk-bearing objects are statistically associated with younger isochronal ages than disk-free sources. The cluster has a hierarchical structure, with two main blocks along its latitudinal extension. The northern half develops around the O-type binary star S Mon; the southern half, close to the tip of the Cone Nebula, contains the most embedded regions of NGC 2264, populated mainly by objects with disks and ongoing accretion. The median ages of objects at different locations within the cluster, and the spatial distribution of disked and non-disked sources, suggest that star formation began in the north of the cluster, over 5 Myr ago, and was ignited in its southern region a few Myr later. Star formation is likely still ongoing in the most embedded regions of the cluster, while the outer regions host a widespread population of more evolved objects; these may be the result of an earlier star formation episode followed by outward migration on timescales of a few Myr. We find a detectable lag between the typical age of disk-bearing objects and that of accreting objects in the inner regions of NGC 2264: the first tend to be older than the second, but younger than disk-free sources at similar locations within the cluster. This supports earlier findings that the characteristic timescales of disk accretion are shorter than those of disk dispersal, and smaller than the average age of NGC 2264 (i.e., ≲3 Myr). At the same time, we note that disks in the north of the cluster tend to be shorter-lived ( 2.5 Myr) than elsewhere; this may reflect the impact of massive stars within the region (notably S Mon), that trigger rapid disk dispersal. Conclusions: Our results, consistent with earlier studies on NGC 2264 and other young clusters, support the idea of a star formation process that takes place sequentially over a prolonged span in a given region. A complete understanding of the dynamics of formation and evolution of star clusters requires accurate astrometric and kinematic characterization of its population; significant advance in this field is foreseen in the upcoming years thanks to the ongoing Gaia mission, coupled with extensive ground-based surveys like GES. Full Table B.1 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/609/A10
Corrected Mean-Field Model for Random Sequential Adsorption on Random Geometric Graphs
NASA Astrophysics Data System (ADS)
Dhara, Souvik; van Leeuwaarden, Johan S. H.; Mukherjee, Debankur
2018-03-01
A notorious problem in mathematics and physics is to create a solvable model for random sequential adsorption of non-overlapping congruent spheres in the d-dimensional Euclidean space with d≥ 2 . Spheres arrive sequentially at uniformly chosen locations in space and are accepted only when there is no overlap with previously deposited spheres. Due to spatial correlations, characterizing the fraction of accepted spheres remains largely intractable. We study this fraction by taking a novel approach that compares random sequential adsorption in Euclidean space to the nearest-neighbor blocking on a sequence of clustered random graphs. This random network model can be thought of as a corrected mean-field model for the interaction graph between the attempted spheres. Using functional limit theorems, we characterize the fraction of accepted spheres and its fluctuations.
ERIC Educational Resources Information Center
Sukkarieh, Jane Z.; von Davier, Matthias; Yamamoto, Kentaro
2012-01-01
This document describes a solution to a problem in the automatic content scoring of the multilingual character-by-character highlighting item type. This solution is language independent and represents a significant enhancement. This solution not only facilitates automatic scoring but plays an important role in clustering students' responses;…
Brief Report: Clustered Forward Chaining with Embedded Mastery Probes to Teach Recipe Following
ERIC Educational Resources Information Center
Chazin, Kate T.; Bartelmay, Danielle N.; Lambert, Joseph M.; Houchins-Juárez, Nealetta J.
2017-01-01
This study evaluated the effectiveness of a clustered forward chaining (CFC) procedure to teach a 23-year-old male with autism to follow written recipes. CFC incorporates elements of forward chaining (FC) and total task chaining (TTC) by teaching a small number of steps (i.e., units) using TTC, introducing new units sequentially (akin to FC), and…
A sequential-move game for enhancing safety and security cooperation within chemical clusters.
Pavlova, Yulia; Reniers, Genserik
2011-02-15
The present paper provides a game theoretic analysis of strategic cooperation on safety and security among chemical companies within a chemical industrial cluster. We suggest a two-stage sequential move game between adjacent chemical plants and the so-called Multi-Plant Council (MPC). The MPC is considered in the game as a leader player who makes the first move, and the individual chemical companies are the followers. The MPC's objective is to achieve full cooperation among players through establishing a subsidy system at minimum expense. The rest of the players rationally react to the subsidies proposed by the MPC and play Nash equilibrium. We show that such a case of conflict between safety and security, and social cooperation, belongs to the 'coordination with assurance' class of games, and we explore the role of cluster governance (fulfilled by the MPC) in achieving a full cooperative outcome in domino effects prevention negotiations. The paper proposes an algorithm that can be used by the MPC to develop the subsidy system. Furthermore, a stepwise plan to improve cross-company safety and security management in a chemical industrial cluster is suggested and an illustrative example is provided. Copyright © 2010 Elsevier B.V. All rights reserved.
Che-Mendoza, Azael; Guillermo-May, Guillermo; Herrera-Bojórquez, Josué; Barrera-Pérez, Mario; Dzul-Manzanilla, Felipe; Gutierrez-Castro, Cipriano; Arredondo-Jiménez, Juan I; Sánchez-Tejeda, Gustavo; Vazquez-Prokopec, Gonzalo; Ranson, Hilary; Lenhart, Audrey; Sommerfeld, Johannes; McCall, Philip J; Kroeger, Axel; Manrique-Saide, Pablo
2015-02-01
Long-lasting insecticidal net screens (LLIS) fitted to domestic windows and doors in combination with targeted treatment (TT) of the most productive Aedes aegypti breeding sites were evaluated for their impact on dengue vector indices in a cluster-randomised trial in Mexico between 2011 and 2013. Sequentially over 2 years, LLIS and TT were deployed in 10 treatment clusters (100 houses/cluster) and followed up over 24 months. Cross-sectional surveys quantified infestations of adult mosquitoes, immature stages at baseline (pre-intervention) and in four post-intervention samples at 6-monthly intervals. Identical surveys were carried out in 10 control clusters that received no treatment. LLIS clusters had significantly lower infestations compared to control clusters at 5 and 12 months after installation, as measured by adult (male and female) and pupal-based vector indices. After addition of TT to the intervention houses in intervention clusters, indices remained significantly lower in the treated clusters until 18 (immature and adult stage indices) and 24 months (adult indices only) post-intervention. These safe, simple affordable vector control tools were well-accepted by study participants and are potentially suitable in many regions at risk from dengue worldwide. © The author 2015. The World Health Organization has granted Oxford University Press permission for the reproduction of this article.
Scalable Static and Dynamic Community Detection Using Grappolo
DOE Office of Scientific and Technical Information (OSTI.GOV)
Halappanavar, Mahantesh; Lu, Hao; Kalyanaraman, Anantharaman
Graph clustering, popularly known as community detection, is a fundamental kernel for several applications of relevance to the Defense Advanced Research Projects Agency’s (DARPA) Hierarchical Identify Verify Exploit (HIVE) Pro- gram. Clusters or communities represent natural divisions within a network that are densely connected within a cluster and sparsely connected to the rest of the network. The need to compute clustering on large scale data necessitates the development of efficient algorithms that can exploit modern architectures that are fundamentally parallel in nature. How- ever, due to their irregular and inherently sequential nature, many of the current algorithms for community detectionmore » are challenging to parallelize. In response to the HIVE Graph Challenge, we present several parallelization heuristics for fast community detection using the Louvain method as the serial template. We implement all the heuristics in a software library called Grappolo. Using the inputs from the HIVE Challenge, we demonstrate superior performance and high quality solutions based on four parallelization heuristics. We use Grappolo on static graphs as the first step towards community detection on streaming graphs.« less
A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.
Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo
2017-05-11
Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.
Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems
Mudunuru, Maruti Kumar; Karra, Satish; Makedonska, Nataliia; ...
2017-09-05
Subsurface applications, including geothermal, geological carbon sequestration, and oil and gas, typically involve maximizing either the extraction of energy or the storage of fluids. Fractures form the main pathways for flow in these systems, and locating these fractures is critical for predicting flow. However, fracture characterization is a highly uncertain process, and data from multiple sources, such as flow and geophysical are needed to reduce this uncertainty. We present a nonintrusive, sequential inversion framework for integrating data from geophysical and flow sources to constrain fracture networks in the subsurface. In this framework, we first estimate bounds on the statistics formore » the fracture orientations using microseismic data. These bounds are estimated through a combination of a focal mechanism (physics-based approach) and clustering analysis (statistical approach) of seismic data. Then, the fracture lengths are constrained using flow data. In conclusion, the efficacy of this inversion is demonstrated through a representative example.« less
Sequential geophysical and flow inversion to characterize fracture networks in subsurface systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mudunuru, Maruti Kumar; Karra, Satish; Makedonska, Nataliia
Subsurface applications, including geothermal, geological carbon sequestration, and oil and gas, typically involve maximizing either the extraction of energy or the storage of fluids. Fractures form the main pathways for flow in these systems, and locating these fractures is critical for predicting flow. However, fracture characterization is a highly uncertain process, and data from multiple sources, such as flow and geophysical are needed to reduce this uncertainty. We present a nonintrusive, sequential inversion framework for integrating data from geophysical and flow sources to constrain fracture networks in the subsurface. In this framework, we first estimate bounds on the statistics formore » the fracture orientations using microseismic data. These bounds are estimated through a combination of a focal mechanism (physics-based approach) and clustering analysis (statistical approach) of seismic data. Then, the fracture lengths are constrained using flow data. In conclusion, the efficacy of this inversion is demonstrated through a representative example.« less
Improving cluster-based missing value estimation of DNA microarray data.
Brás, Lígia P; Menezes, José C
2007-06-01
We present a modification of the weighted K-nearest neighbours imputation method (KNNimpute) for missing values (MVs) estimation in microarray data based on the reuse of estimated data. The method was called iterative KNN imputation (IKNNimpute) as the estimation is performed iteratively using the recently estimated values. The estimation efficiency of IKNNimpute was assessed under different conditions (data type, fraction and structure of missing data) by the normalized root mean squared error (NRMSE) and the correlation coefficients between estimated and true values, and compared with that of other cluster-based estimation methods (KNNimpute and sequential KNN). We further investigated the influence of imputation on the detection of differentially expressed genes using SAM by examining the differentially expressed genes that are lost after MV estimation. The performance measures give consistent results, indicating that the iterative procedure of IKNNimpute can enhance the prediction ability of cluster-based methods in the presence of high missing rates, in non-time series experiments and in data sets comprising both time series and non-time series data, because the information of the genes having MVs is used more efficiently and the iterative procedure allows refining the MV estimates. More importantly, IKNN has a smaller detrimental effect on the detection of differentially expressed genes.
One-way quantum computing in superconducting circuits
NASA Astrophysics Data System (ADS)
Albarrán-Arriagada, F.; Alvarado Barrios, G.; Sanz, M.; Romero, G.; Lamata, L.; Retamal, J. C.; Solano, E.
2018-03-01
We propose a method for the implementation of one-way quantum computing in superconducting circuits. Measurement-based quantum computing is a universal quantum computation paradigm in which an initial cluster state provides the quantum resource, while the iteration of sequential measurements and local rotations encodes the quantum algorithm. Up to now, technical constraints have limited a scalable approach to this quantum computing alternative. The initial cluster state can be generated with available controlled-phase gates, while the quantum algorithm makes use of high-fidelity readout and coherent feedforward. With current technology, we estimate that quantum algorithms with above 20 qubits may be implemented in the path toward quantum supremacy. Moreover, we propose an alternative initial state with properties of maximal persistence and maximal connectedness, reducing the required resources of one-way quantum computing protocols.
Quasichemical analysis of the cluster-pair approximation for the thermodynamics of proton hydration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pollard, Travis; Beck, Thomas L.; Department of Physics, University of Cincinnati, Cincinnati, Ohio 45221
2014-06-14
A theoretical analysis of the cluster-pair approximation (CPA) is presented based on the quasichemical theory of solutions. The sought single-ion hydration free energy of the proton includes an interfacial potential contribution by definition. It is shown, however, that the CPA involves an extra-thermodynamic assumption that does not guarantee uniform convergence to a bulk free energy value with increasing cluster size. A numerical test of the CPA is performed using the classical polarizable AMOEBA force field and supporting quantum chemical calculations. The enthalpy and free energy differences are computed for the kosmotropic Na{sup +}/F{sup −} ion pair in water clusters ofmore » size n = 5, 25, 105. Additional calculations are performed for the chaotropic Rb{sup +}/I{sup −} ion pair. A small shift in the proton hydration free energy and a larger shift in the hydration enthalpy, relative to the CPA values, are predicted based on the n = 105 simulations. The shifts arise from a combination of sequential hydration and interfacial potential effects. The AMOEBA and quantum chemical results suggest an electrochemical surface potential of water in the range −0.4 to −0.5 V. The physical content of single-ion free energies and implications for ion-water force field development are also discussed.« less
Syndrome Surveillance Using Parametric Space-Time Clustering
DOE Office of Scientific and Technical Information (OSTI.GOV)
KOCH, MARK W.; MCKENNA, SEAN A.; BILISOLY, ROGER L.
2002-11-01
As demonstrated by the anthrax attack through the United States mail, people infected by the biological agent itself will give the first indication of a bioterror attack. Thus, a distributed information system that can rapidly and efficiently gather and analyze public health data would aid epidemiologists in detecting and characterizing emerging diseases, including bioterror attacks. We propose using clusters of adverse health events in space and time to detect possible bioterror attacks. Space-time clusters can indicate exposure to infectious diseases or localized exposure to toxins. Most space-time clustering approaches require individual patient data. To protect the patient's privacy, we havemore » extended these approaches to aggregated data and have embedded this extension in a sequential probability ratio test (SPRT) framework. The real-time and sequential nature of health data makes the SPRT an ideal candidate. The result of space-time clustering gives the statistical significance of a cluster at every location in the surveillance area and can be thought of as a ''health-index'' of the people living in this area. As a surrogate to bioterrorism data, we have experimented with two flu data sets. For both databases, we show that space-time clustering can detect a flu epidemic up to 21 to 28 days earlier than a conventional periodic regression technique. We have also tested using simulated anthrax attack data on top of a respiratory illness diagnostic category. Results show we do very well at detecting an attack as early as the second or third day after infected people start becoming severely symptomatic.« less
Room-temperature current blockade in atomically defined single-cluster junctions
NASA Astrophysics Data System (ADS)
Lovat, Giacomo; Choi, Bonnie; Paley, Daniel W.; Steigerwald, Michael L.; Venkataraman, Latha; Roy, Xavier
2017-11-01
Fabricating nanoscopic devices capable of manipulating and processing single units of charge is an essential step towards creating functional devices where quantum effects dominate transport characteristics. The archetypal single-electron transistor comprises a small conducting or semiconducting island separated from two metallic reservoirs by insulating barriers. By enabling the transfer of a well-defined number of charge carriers between the island and the reservoirs, such a device may enable discrete single-electron operations. Here, we describe a single-molecule junction comprising a redox-active, atomically precise cobalt chalcogenide cluster wired between two nanoscopic electrodes. We observe current blockade at room temperature in thousands of single-cluster junctions. Below a threshold voltage, charge transfer across the junction is suppressed. The device is turned on when the temporary occupation of the core states by a transiting carrier is energetically enabled, resulting in a sequential tunnelling process and an increase in current by a factor of ∼600. We perform in situ and ex situ cyclic voltammetry as well as density functional theory calculations to unveil a two-step process mediated by an orbital localized on the core of the cluster in which charge carriers reside before tunnelling to the collector reservoir. As the bias window of the junction is opened wide enough to include one of the cluster frontier orbitals, the current blockade is lifted and charge carriers can tunnel sequentially across the junction.
MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.
Gonzalez-Dominguez, Jorge; Martin, Maria J
2017-10-10
In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.
Energetics and solvation structure of a dihalogen dopant (I2) in (4)He clusters.
Pérez de Tudela, Ricardo; Barragán, Patricia; Valdés, Álvaro; Prosmiti, Rita
2014-08-21
The energetics and structure of small HeNI2 clusters are analyzed as the size of the system changes, with N up to 38. The full interaction between the I2 molecule and the He atoms is based on analytical ab initio He-I2 potentials plus the He-He interaction, obtained from first-principle calculations. The most stable structures, as a function of the number of solvent He atoms, are obtained by employing an evolutionary algorithm and compared with CCSD(T) and MP2 ab initio computations. Further, the classical description is completed by explicitly including thermal corrections and quantum features, such as zero-point-energy values and spatial delocalization. From quantum PIMC calculations, the binding energies and radial/angular probability density distributions of the thermal equilibrium state for selected-size clusters are computed at a low temperature. The sequential formation of regular shell structures is analyzed and discussed for both classical and quantum treatments.
Spatial expression of Hox cluster genes in the ontogeny of a sea urchin
NASA Technical Reports Server (NTRS)
Arenas-Mena, C.; Cameron, A. R.; Davidson, E. H.
2000-01-01
The Hox cluster of the sea urchin Strongylocentrous purpuratus contains ten genes in a 500 kb span of the genome. Only two of these genes are expressed during embryogenesis, while all of eight genes tested are expressed during development of the adult body plan in the larval stage. We report the spatial expression during larval development of the five 'posterior' genes of the cluster: SpHox7, SpHox8, SpHox9/10, SpHox11/13a and SpHox11/13b. The five genes exhibit a dynamic, largely mesodermal program of expression. Only SpHox7 displays extensive expression within the pentameral rudiment itself. A spatially sequential and colinear arrangement of expression domains is found in the somatocoels, the paired posterior mesodermal structures that will become the adult perivisceral coeloms. No such sequential expression pattern is observed in endodermal, epidermal or neural tissues of either the larva or the presumptive juvenile sea urchin. The spatial expression patterns of the Hox genes illuminate the evolutionary process by which the pentameral echinoderm body plan emerged from a bilateral ancestor.
NASA Astrophysics Data System (ADS)
Takuma, Takehisa; Masugi, Masao
2009-03-01
This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.
Heiles, Sven; Cooper, Richard J.; DiTucci, Matthew J.
2017-01-01
Sequential water molecule binding enthalpies, ΔH n,n–1, are important for a detailed understanding of competitive interactions between ions, water and solute molecules, and how these interactions affect physical properties of ion-containing nanodrops that are important in aerosol chemistry. Water molecule binding enthalpies have been measured for small clusters of many different ions, but these values for ion-containing nanodrops containing more than 20 water molecules are scarce. Here, ΔH n,n–1 values are deduced from high-precision ultraviolet photodissociation (UVPD) measurements as a function of ion identity, charge state and cluster size between 20–500 water molecules and for ions with +1, +2 and +3 charges. The ΔH n,n–1 values are obtained from the number of water molecules lost upon photoexcitation at a known wavelength, and modeling of the release of energy into the translational, rotational and vibrational motions of the products. The ΔH n,n–1 values range from 36.82 to 50.21 kJ mol–1. For clusters containing more than ∼250 water molecules, the binding enthalpies are between the bulk heat of vaporization (44.8 kJ mol–1) and the sublimation enthalpy of bulk ice (51.0 kJ mol–1). These values depend on ion charge state for clusters with fewer than 150 water molecules, but there is a negligible dependence at larger size. There is a minimum in the ΔH n,n–1 values that depends on the cluster size and ion charge state, which can be attributed to the competing effects of ion solvation and surface energy. The experimental ΔH n,n–1 values can be fit to the Thomson liquid drop model (TLDM) using bulk ice parameters. By optimizing the surface tension and temperature change of the logarithmic partial pressure for the TLDM, the experimental sequential water molecule binding enthalpies can be fit with an accuracy of ±3.3 kJ mol–1 over the entire range of cluster sizes. PMID:28451364
Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo
2011-03-04
Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.
Applying Sequential Analytic Methods to Self-Reported Information to Anticipate Care Needs.
Bayliss, Elizabeth A; Powers, J David; Ellis, Jennifer L; Barrow, Jennifer C; Strobel, MaryJo; Beck, Arne
2016-01-01
Identifying care needs for newly enrolled or newly insured individuals is important under the Affordable Care Act. Systematically collected patient-reported information can potentially identify subgroups with specific care needs prior to service use. We conducted a retrospective cohort investigation of 6,047 individuals who completed a 10-question needs assessment upon initial enrollment in Kaiser Permanente Colorado (KPCO), a not-for-profit integrated delivery system, through the Colorado State Individual Exchange. We used responses from the Brief Health Questionnaire (BHQ), to develop a predictive model for cost for receiving care in the top 25 percent, then applied cluster analytic techniques to identify different high-cost subpopulations. Per-member, per-month cost was measured from 6 to 12 months following BHQ response. BHQ responses significantly predictive of high-cost care included self-reported health status, functional limitations, medication use, presence of 0-4 chronic conditions, self-reported emergency department (ED) use during the prior year, and lack of prior insurance. Age, gender, and deductible-based insurance product were also predictive. The largest possible range of predicted probabilities of being in the top 25 percent of cost was 3.5 percent to 96.4 percent. Within the top cost quartile, examples of potentially actionable clusters of patients included those with high morbidity, prior utilization, depression risk and financial constraints; those with high morbidity, previously uninsured individuals with few financial constraints; and relatively healthy, previously insured individuals with medication needs. Applying sequential predictive modeling and cluster analytic techniques to patient-reported information can identify subgroups of individuals within heterogeneous populations who may benefit from specific interventions to optimize initial care delivery.
Cluster Correspondence Analysis.
van de Velden, M; D'Enza, A Iodice; Palumbo, F
2017-03-01
A method is proposed that combines dimension reduction and cluster analysis for categorical data by simultaneously assigning individuals to clusters and optimal scaling values to categories in such a way that a single between variance maximization objective is achieved. In a unified framework, a brief review of alternative methods is provided and we show that the proposed method is equivalent to GROUPALS applied to categorical data. Performance of the methods is appraised by means of a simulation study. The results of the joint dimension reduction and clustering methods are compared with the so-called tandem approach, a sequential analysis of dimension reduction followed by cluster analysis. The tandem approach is conjectured to perform worse when variables are added that are unrelated to the cluster structure. Our simulation study confirms this conjecture. Moreover, the results of the simulation study indicate that the proposed method also consistently outperforms alternative joint dimension reduction and clustering methods.
Kovacs, Gabor G; Xie, Sharon X; Robinson, John L; Lee, Edward B; Smith, Douglas H; Schuck, Theresa; Lee, Virginia M-Y; Trojanowski, John Q
2018-06-11
Aging-related tau astrogliopathy (ARTAG) describes tau pathology in astrocytes in different locations and anatomical regions. In the present study we addressed the question of whether sequential distribution patterns can be recognized for ARTAG or astroglial tau pathologies in both primary FTLD-tauopathies and non-FTLD-tauopathy cases. By evaluating 687 postmortem brains with diverse disorders we identified ARTAG in 455. We evaluated frequencies and hierarchical clustering of anatomical involvement and used conditional probability and logistic regression to model the sequential distribution of ARTAG and astroglial tau pathologies across different brain regions. For subpial and white matter ARTAG we recognize three and two patterns, respectively, each with three stages initiated or ending in the amygdala. Subependymal ARTAG does not show a clear sequential pattern. For grey matter (GM) ARTAG we recognize four stages including a striatal pathway of spreading towards the cortex and/or amygdala, and the brainstem, and an amygdala pathway, which precedes the involvement of the striatum and/or cortex and proceeds towards the brainstem. GM ARTAG and astrocytic plaque pathology in corticobasal degeneration follows a predominantly frontal-parietal cortical to temporal-occipital cortical, to subcortical, to brainstem pathway (four stages). GM ARTAG and tufted astrocyte pathology in progressive supranuclear palsy shows a striatum to frontal-parietal cortical to temporal to occipital, to amygdala, and to brainstem sequence (four stages). In Pick's disease cases with astroglial tau pathology an overlapping pattern with PSP can be appreciated. We conclude that tau-astrogliopathy type-specific sequential patterns cannot be simplified as neuron-based staging systems. The proposed cytopathological and hierarchical stages provide a conceptual approach to identify the initial steps of the pathogenesis of tau pathologies in ARTAG and primary FTLD-tauopathies.
Saito, Shota; Hirata, Yoshito; Sasahara, Kazutoshi; Suzuki, Hideyuki
2015-01-01
Micro-blogging services, such as Twitter, offer opportunities to analyse user behaviour. Discovering and distinguishing behavioural patterns in micro-blogging services is valuable. However, it is difficult and challenging to distinguish users, and to track the temporal development of collective attention within distinct user groups in Twitter. In this paper, we formulate this problem as tracking matrices decomposed by Nonnegative Matrix Factorisation for time-sequential matrix data, and propose a novel extension of Nonnegative Matrix Factorisation, which we refer to as Time Evolving Nonnegative Matrix Factorisation (TENMF). In our method, we describe users and words posted in some time interval by a matrix, and use several matrices as time-sequential data. Subsequently, we apply Time Evolving Nonnegative Matrix Factorisation to these time-sequential matrices. TENMF can decompose time-sequential matrices, and can track the connection among decomposed matrices, whereas previous NMF decomposes a matrix into two lower dimension matrices arbitrarily, which might lose the time-sequential connection. Our proposed method has an adequately good performance on artificial data. Moreover, we present several results and insights from experiments using real data from Twitter.
A field test of three LQAS designs to assess the prevalence of acute malnutrition.
Deitchler, Megan; Valadez, Joseph J; Egge, Kari; Fernandez, Soledad; Hennigan, Mary
2007-08-01
The conventional method for assessing the prevalence of Global Acute Malnutrition (GAM) in emergency settings is the 30 x 30 cluster-survey. This study describes alternative approaches: three Lot Quality Assurance Sampling (LQAS) designs to assess GAM. The LQAS designs were field-tested and their results compared with those from a 30 x 30 cluster-survey. Computer simulations confirmed that small clusters instead of a simple random sample could be used for LQAS assessments of GAM. Three LQAS designs were developed (33 x 6, 67 x 3, Sequential design) to assess GAM thresholds of 10, 15 and 20%. The designs were field-tested simultaneously with a 30 x 30 cluster-survey in Siraro, Ethiopia during June 2003. Using a nested study design, anthropometric, morbidity and vaccination data were collected on all children 6-59 months in sampled households. Hypothesis tests about GAM thresholds were conducted for each LQAS design. Point estimates were obtained for the 30 x 30 cluster-survey and the 33 x 6 and 67 x 3 LQAS designs. Hypothesis tests showed GAM as <10% for the 33 x 6 design and GAM as > or =10% for the 67 x 3 and Sequential designs. Point estimates for the 33 x 6 and 67 x 3 designs were similar to those of the 30 x 30 cluster-survey for GAM (6.7%, CI = 3.2-10.2%; 8.2%, CI = 4.3-12.1%, 7.4%, CI = 4.8-9.9%) and all other indicators. The CIs for the LQAS designs were only slightly wider than the CIs for the 30 x 30 cluster-survey; yet the LQAS designs required substantially less time to administer. The LQAS designs provide statistically appropriate alternatives to the more time-consuming 30 x 30 cluster-survey. However, additional field-testing is needed using independent samples rather than a nested study design.
Galvan, T L; Burkness, E C; Hutchison, W D
2007-06-01
To develop a practical integrated pest management (IPM) system for the multicolored Asian lady beetle, Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), in wine grapes, we assessed the spatial distribution of H. axyridis and developed eight sampling plans to estimate adult density or infestation level in grape clusters. We used 49 data sets collected from commercial vineyards in 2004 and 2005, in Minnesota and Wisconsin. Enumerative plans were developed using two precision levels (0.10 and 0.25); the six binomial plans reflected six unique action thresholds (3, 7, 12, 18, 22, and 31% of cluster samples infested with at least one H. axyridis). The spatial distribution of H. axyridis in wine grapes was aggregated, independent of cultivar and year, but it was more randomly distributed as mean density declined. The average sample number (ASN) for each sampling plan was determined using resampling software. For research purposes, an enumerative plan with a precision level of 0.10 (SE/X) resulted in a mean ASN of 546 clusters. For IPM applications, the enumerative plan with a precision level of 0.25 resulted in a mean ASN of 180 clusters. In contrast, the binomial plans resulted in much lower ASNs and provided high probabilities of arriving at correct "treat or no-treat" decisions, making these plans more efficient for IPM applications. For a tally threshold of one adult per cluster, the operating characteristic curves for the six action thresholds provided binomial sequential sampling plans with mean ASNs of only 19-26 clusters, and probabilities of making correct decisions between 83 and 96%. The benefits of the binomial sampling plans are discussed within the context of improving IPM programs for wine grapes.
MZmine 2 Data-Preprocessing To Enhance Molecular Networking Reliability.
Olivon, Florent; Grelier, Gwendal; Roussi, Fanny; Litaudon, Marc; Touboul, David
2017-08-01
Molecular networking is becoming more and more popular into the metabolomic community to organize tandem mass spectrometry (MS 2 ) data. Even though this approach allows the treatment and comparison of large data sets, several drawbacks related to the MS-Cluster tool routinely used on the Global Natural Product Social Molecular Networking platform (GNPS) limit its potential. MS-Cluster cannot distinguish between chromatography well-resolved isomers as retention times are not taken into account. Annotation with predicted chemical formulas is also not implemented and semiquantification is only based on the number of MS 2 scans. We propose to introduce a data-preprocessing workflow including the preliminary data treatment by MZmine 2 followed by a homemade Python script freely available to the community that clears the major previously mentioned GNPS drawbacks. The efficiency of this workflow is exemplified with the analysis of six fractions of increasing polarities obtained from a sequential supercritical CO 2 extraction of Stillingia lineata leaves.
Energy-efficient and fast data gathering protocols for indoor wireless sensor networks.
Tümer, Abdullah Erdal; Gündüz, Mesut
2010-01-01
Wireless Sensor Networks have become an important technology with numerous potential applications for the interaction of computers and the physical environment in civilian and military areas. In the routing protocols that are specifically designed for the applications used by sensor networks, the limited available power of the sensor nodes has been taken into consideration in order to extend the lifetime of the networks. In this paper, two protocols based on LEACH and called R-EERP and S-EERP with base and threshold values are presented. R-EERP and S-EERP are two efficient energy aware routing protocols that can be used for some critical applications such as detecting dangerous gases (methane, ammonium, carbon monoxide, etc.) in an indoor environment. In R-EERP, sensor nodes are deployed randomly in a field similar to LEACH. In S-EERP, nodes are deployed sequentially in the rooms of the flats of a multi-story building. In both protocols, nodes forming clusters do not change during a cluster change time, only the cluster heads change. Furthermore, an XOR operation is performed on the collected data in order to prevent the sending of the same data sensed by the nodes close to each other. Simulation results show that our proposed protocols are more energy-efficient than the conventional LEACH protocol.
Photon-Induced Thermal Desorption of CO from Small Metal-Carbonyl Clusters
NASA Astrophysics Data System (ADS)
Lüttgens, G.; Pontius, N.; Bechthold, P. S.; Neeb, M.; Eberhardt, W.
2002-02-01
Thermal CO desorption from photoexcited free metal-carbonyl clusters has been resolved in real time using two-color pump-probe photoelectron spectroscopy. Sequential energy dissipation steps between the initial photoexcitation and the final desorption event, e.g., electron relaxation and thermalization, have been resolved for Au2(CO)- and Pt2(CO)-5. The desorption rates for the two clusters differ considerably due to the different numbers of vibrational degrees of freedom. The unimolecular CO-desorption thresholds of Au2(CO)- and Pt2(CO)-5 have been approximated by means of a statistical Rice-Ramsperger-Kassel calculation using the experimentally derived desorption rate constants.
Jammed systems of oriented needles always percolate on square lattices
NASA Astrophysics Data System (ADS)
Kondrat, Grzegorz; Koza, Zbigniew; Brzeski, Piotr
2017-08-01
Random sequential adsorption (RSA) is a standard method of modeling adsorption of large molecules at the liquid-solid interface. Several studies have recently conjectured that in the RSA of rectangular needles, or k -mers, on a square lattice, percolation is impossible if the needles are sufficiently long (k of order of several thousand). We refute these claims and present rigorous proof that in any jammed configuration of nonoverlapping, fixed-length, horizontal, or vertical needles on a square lattice, all clusters are percolating clusters.
Classroom Dialogue and Science Achievement.
ERIC Educational Resources Information Center
Clarke, John A.
This study reports the application to classroom dialogue of the Thematic and Structural Analysis (TSA) Technique which has been used previously in the analysis of text materials. The TSA Technique identifies themes (word clusters) and their structural relationship throughout sequentially organized material. Dialogues from four Year 8 science…
Cluster: Carpentry. Course: Carpentry. Research Project.
ERIC Educational Resources Information Center
Sanford - Lee County Schools, NC.
The course on carpentry is divided into 14 sequential units, with several task packages within each, covering the following topics: carpentry hand tools; portable power tools; working machine tools; lumber; fasteners and adhesives; plans, specifications, and codes for houses; footings and foundations for a house; household cabinets; floor framing…
Rare-gas-cluster explosions under irradiation by intense short XUV pulses
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hoffmann, K.; Murphy, B.; Kandadai, N.
High-intensity, extreme-ultraviolet (XUV) femtosecond interactions with large rare-gas clusters of xenon and argon have been studied at a wavelength of 38 nm. Pulses of XUV radiation with nJ energy are produced by high-order harmonic conversion from a 35-fs, near-infrared, terawatt laser. Mass resolved ion spectra show charge states up to Xe{sup 8+} and Ar{sup 4+}. Kinetic-energy measurements of ions and electrons indicate that a nanoplasma is formed and a hydrodynamic cluster explosion ensues after heating by the short wavelength pulse. It appears that the observed charge states and electron temperatures are consistent with sequential, single-photon ionization and collisional ionization ofmore » ions that have had their ionization potential depressed by plasma continuum lowering in the cluster nanoplasma.« less
NASA Astrophysics Data System (ADS)
Fulmer, Leah M.; Gallagher, John S.; Hamann, Wolf-Rainer; Oskinova, Lida; Ramachandran, Varsha
2018-01-01
The low-density Wing of the Small Magellanic Cloud exhibits ongoing, active star formation despite a distinctive lack of dense ambient gas and dust, or resources from which to form stars. Our continued work in studying this region reveals that these paradoxical observations may be explained by a process of sequential star formation. We present photometric, clustering, and spatial analyses in support of this scenario, along with a proposed star formation history based on the following evidence: matches to isochrone models, stellar and ionized gas kinematics (VLT, SALT), and regional HI gas kinematics (ATCA, PKS).
The Ordered Clustered Travelling Salesman Problem: A Hybrid Genetic Algorithm
Ahmed, Zakir Hussain
2014-01-01
The ordered clustered travelling salesman problem is a variation of the usual travelling salesman problem in which a set of vertices (except the starting vertex) of the network is divided into some prespecified clusters. The objective is to find the least cost Hamiltonian tour in which vertices of any cluster are visited contiguously and the clusters are visited in the prespecified order. The problem is NP-hard, and it arises in practical transportation and sequencing problems. This paper develops a hybrid genetic algorithm using sequential constructive crossover, 2-opt search, and a local search for obtaining heuristic solution to the problem. The efficiency of the algorithm has been examined against two existing algorithms for some asymmetric and symmetric TSPLIB instances of various sizes. The computational results show that the proposed algorithm is very effective in terms of solution quality and computational time. Finally, we present solution to some more symmetric TSPLIB instances. PMID:24701148
Conformational Clusters of Phosphorylated Tyrosine.
Abdelrasoul, Maha; Ponniah, Komala; Mao, Alice; Warden, Meghan S; Elhefnawy, Wessam; Li, Yaohang; Pascal, Steven M
2017-12-06
Tyrosine phosphorylation plays an important role in many cellular and intercellular processes including signal transduction, subcellular localization, and regulation of enzymatic activity. In 1999, Blom et al., using the limited number of protein data bank (PDB) structures available at that time, reported that the side chain structures of phosphorylated tyrosine (pY) are partitioned into two conserved conformational clusters ( Blom, N.; Gammeltoft, S.; Brunak, S. J. Mol. Biol. 1999 , 294 , 1351 - 1362 ). We have used the spectral clustering algorithm to cluster the increasingly growing number of protein structures with pY sites, and have found that the pY residues cluster into three distinct side chain conformations. Two of these pY conformational clusters associate strongly with a narrow range of tyrosine backbone conformation. The novel cluster also highly correlates with the identity of the n + 1 residue, and is strongly associated with a sequential pYpY conformation which places two adjacent pY side chains in a specific relative orientation. Further analysis shows that the three pY clusters are associated with distinct distributions of cognate protein kinases.
Cunanan, Kristen M; Carlin, Bradley P; Peterson, Kevin A
2016-12-01
Many clinical trial designs are impractical for community-based clinical intervention trials. Stepped wedge trial designs provide practical advantages, but few descriptions exist of their clinical implementational features, statistical design efficiencies, and limitations. Enhance efficiency of stepped wedge trial designs by evaluating the impact of design characteristics on statistical power for the British Columbia Telehealth Trial. The British Columbia Telehealth Trial is a community-based, cluster-randomized, controlled clinical trial in rural and urban British Columbia. To determine the effect of an Internet-based telehealth intervention on healthcare utilization, 1000 subjects with an existing diagnosis of congestive heart failure or type 2 diabetes will be enrolled from 50 clinical practices. Hospital utilization is measured using a composite of disease-specific hospital admissions and emergency visits. The intervention comprises online telehealth data collection and counseling provided to support a disease-specific action plan developed by the primary care provider. The planned intervention is sequentially introduced across all participating practices. We adopt a fully Bayesian, Markov chain Monte Carlo-driven statistical approach, wherein we use simulation to determine the effect of cluster size, sample size, and crossover interval choice on type I error and power to evaluate differences in hospital utilization. For our Bayesian stepped wedge trial design, simulations suggest moderate decreases in power when crossover intervals from control to intervention are reduced from every 3 to 2 weeks, and dramatic decreases in power as the numbers of clusters decrease. Power and type I error performance were not notably affected by the addition of nonzero cluster effects or a temporal trend in hospitalization intensity. Stepped wedge trial designs that intervene in small clusters across longer periods can provide enhanced power to evaluate comparative effectiveness, while offering practical implementation advantages in geographic stratification, temporal change, use of existing data, and resource distribution. Current population estimates were used; however, models may not reflect actual event rates during the trial. In addition, temporal or spatial heterogeneity can bias treatment effect estimates. © The Author(s) 2016.
Patterns and Prevalence of Core Profile Types in the WPPSI Standardization Sample.
ERIC Educational Resources Information Center
Glutting, Joseph J.; McDermott, Paul A.
1990-01-01
Found most representative subtest profiles for 1,200 children comprising standardization sample of Wechsler Preschool and Primary Scale of Intelligence (WPPSI). Grouped scaled scores from WPPSI subtests according to similar level and shape using sequential minimum-variance cluster analysis with independent replications. Obtained final solution of…
The star-forming history of the young cluster NGC 2264
NASA Technical Reports Server (NTRS)
Adams, M. T.; Strom, K. M.; Strom, S. E.
1983-01-01
UBVRI H-alpha photographic photometry was obtained for a sample of low-mass stars in the young open cluster NGC 2264 in order to investigate the star-forming history of this region. A theoretical H-R diagram was constructed for the sample of probable cluster members. Isochrones and evolutionary tracks were adopted from Cohen and Kuhi (1979). Evidence for a significant age spread in the cluster was found amounting to over ten million yr. In addition, the derived star formation rate as a function of stellar mass suggests that the principal star-forming mass range in NGC 2264 has proceeded sequentially in time from the lowest to the highest masses. The low-mass cluster stars were the first cluster members to form in significant numbers, although their present birth rate is much lower now than it was about ten million yr ago. The star-formation rate has risen to a peak at successively higher masses and then declined.
Temporal texture of associative encoding modulates recall processes.
Tibon, Roni; Levy, Daniel A
2014-02-01
Binding aspects of an experience that are distributed over time is an important element of episodic memory. In the current study, we examined how the temporal complexity of an experience may govern the processes required for its retrieval. We recorded event-related potentials during episodic cued recall following pair associate learning of concurrently and sequentially presented object-picture pairs. Cued recall success effects over anterior and posterior areas were apparent in several time windows. In anterior locations, these recall success effects were similar for concurrently and sequentially encoded pairs. However, in posterior sites clustered over parietal scalp the effect was larger for the retrieval of sequentially encoded pairs. We suggest that anterior aspects of the mid-latency recall success effects may reflect working-with-memory operations or direct access recall processes, while more posterior aspects reflect recollective processes which are required for retrieval of episodes of greater temporal complexity. Copyright © 2013 Elsevier Inc. All rights reserved.
Aerosol Plume Detection Algorithm Based on Image Segmentation of Scanning Atmospheric Lidar Data
Weekley, R. Andrew; Goodrich, R. Kent; Cornman, Larry B.
2016-04-06
An image-processing algorithm has been developed to identify aerosol plumes in scanning lidar backscatter data. The images in this case consist of lidar data in a polar coordinate system. Each full lidar scan is taken as a fixed image in time, and sequences of such scans are considered functions of time. The data are analyzed in both the original backscatter polar coordinate system and a lagged coordinate system. The lagged coordinate system is a scatterplot of two datasets, such as subregions taken from the same lidar scan (spatial delay), or two sequential scans in time (time delay). The lagged coordinatemore » system processing allows for finding and classifying clusters of data. The classification step is important in determining which clusters are valid aerosol plumes and which are from artifacts such as noise, hard targets, or background fields. These cluster classification techniques have skill since both local and global properties are used. Furthermore, more information is available since both the original data and the lag data are used. Performance statistics are presented for a limited set of data processed by the algorithm, where results from the algorithm were compared to subjective truth data identified by a human.« less
Sequential analysis of hydrochemical data for watershed characterization.
Thyne, Geoffrey; Güler, Cüneyt; Poeter, Eileen
2004-01-01
A methodology for characterizing the hydrogeology of watersheds using hydrochemical data that combine statistical, geochemical, and spatial techniques is presented. Surface water and ground water base flow and spring runoff samples (180 total) from a single watershed are first classified using hierarchical cluster analysis. The statistical clusters are analyzed for spatial coherence confirming that the clusters have a geological basis corresponding to topographic flowpaths and showing that the fractured rock aquifer behaves as an equivalent porous medium on the watershed scale. Then principal component analysis (PCA) is used to determine the sources of variation between parameters. PCA analysis shows that the variations within the dataset are related to variations in calcium, magnesium, SO4, and HCO3, which are derived from natural weathering reactions, and pH, NO3, and chlorine, which indicate anthropogenic impact. PHREEQC modeling is used to quantitatively describe the natural hydrochemical evolution for the watershed and aid in discrimination of samples that have an anthropogenic component. Finally, the seasonal changes in the water chemistry of individual sites were analyzed to better characterize the spatial variability of vertical hydraulic conductivity. The integrated result provides a method to characterize the hydrogeology of the watershed that fully utilizes traditional data.
NASA Astrophysics Data System (ADS)
Sun, Alexander Y.; Morris, Alan P.; Mohanty, Sitakanta
2009-07-01
Estimated parameter distributions in groundwater models may contain significant uncertainties because of data insufficiency. Therefore, adaptive uncertainty reduction strategies are needed to continuously improve model accuracy by fusing new observations. In recent years, various ensemble Kalman filters have been introduced as viable tools for updating high-dimensional model parameters. However, their usefulness is largely limited by the inherent assumption of Gaussian error statistics. Hydraulic conductivity distributions in alluvial aquifers, for example, are usually non-Gaussian as a result of complex depositional and diagenetic processes. In this study, we combine an ensemble Kalman filter with grid-based localization and a Gaussian mixture model (GMM) clustering techniques for updating high-dimensional, multimodal parameter distributions via dynamic data assimilation. We introduce innovative strategies (e.g., block updating and dimension reduction) to effectively reduce the computational costs associated with these modified ensemble Kalman filter schemes. The developed data assimilation schemes are demonstrated numerically for identifying the multimodal heterogeneous hydraulic conductivity distributions in a binary facies alluvial aquifer. Our results show that localization and GMM clustering are very promising techniques for assimilating high-dimensional, multimodal parameter distributions, and they outperform the corresponding global ensemble Kalman filter analysis scheme in all scenarios considered.
EventThread: Visual Summarization and Stage Analysis of Event Sequence Data.
Guo, Shunan; Xu, Ke; Zhao, Rongwen; Gotz, David; Zha, Hongyuan; Cao, Nan
2018-01-01
Event sequence data such as electronic health records, a person's academic records, or car service records, are ordered series of events which have occurred over a period of time. Analyzing collections of event sequences can reveal common or semantically important sequential patterns. For example, event sequence analysis might reveal frequently used care plans for treating a disease, typical publishing patterns of professors, and the patterns of service that result in a well-maintained car. It is challenging, however, to visually explore large numbers of event sequences, or sequences with large numbers of event types. Existing methods focus on extracting explicitly matching patterns of events using statistical analysis to create stages of event progression over time. However, these methods fail to capture latent clusters of similar but not identical evolutions of event sequences. In this paper, we introduce a novel visualization system named EventThread which clusters event sequences into threads based on tensor analysis and visualizes the latent stage categories and evolution patterns by interactively grouping the threads by similarity into time-specific clusters. We demonstrate the effectiveness of EventThread through usage scenarios in three different application domains and via interviews with an expert user.
Reactivity Control of Rhodium Cluster Ions by Alloying with Tantalum Atoms.
Mafuné, Fumitaka; Tawaraya, Yuki; Kudoh, Satoshi
2016-02-18
Gas phase, bielement rhodium and tantalum clusters, RhnTam(+) (n + m = 6), were prepared by the double laser ablation of Rh and Ta rods in He carrier gas. The clusters were introduced into a reaction gas cell filled with nitric oxide (NO) diluted with He and were subjected to collisions with NO and He at room temperature. The product species were observed by mass spectrometry, demonstrating that the NO molecules were sequentially adsorbed on the RhnTam(+) clusters to form RhnTam(+)NxOx (x = 1, 2, 3, ...) species. In addition, oxide clusters, RhnTam(+)O2, were also observed, suggesting that the NO molecules were dissociatively adsorbed on the cluster, the N atoms migrated on the surface to form N2, and the N2 molecules were released from RhnTam(+)N2O2. The reactivity, leading to oxide formation, was composition dependent: oxide clusters were dominantly formed for the bielement clusters containing both Rh and Ta atoms, whereas such clusters were hardly formed for the single-element Rhn(+) and Tam(+) clusters. DFT calculations indicated that the Ta atoms induce dissociation of NO on the clusters by lowering the dissociation energy, whereas the Rh atoms enable release of N2 by lowering the binding energy of the N atoms on the clusters.
NASA Astrophysics Data System (ADS)
Sun, Y.; Luo, G.
2017-12-01
Seismicity in a region is usually characterized by earthquake clusters and earthquake migration along its major fault zones. However, we do not fully understand why and how earthquake clusters and spatio-temporal migration of earthquakes occur. The northeastern Tibetan Plateau is a good example for us to investigate these problems. In this study, we construct and use a three-dimensional viscoelastoplastic finite-element model to simulate earthquake cycles and spatio-temporal migration of earthquakes along major fault zones in northeastern Tibetan Plateau. We calculate stress evolution and fault interactions, and explore effects of topographic loading and viscosity of middle-lower crust and upper mantle on model results. Model results show that earthquakes and fault interactions increase Coulomb stress on the neighboring faults or segments, accelerating the future earthquakes in this region. Thus, earthquakes occur sequentially in a short time, leading to regional earthquake clusters. Through long-term evolution, stresses on some seismogenic faults, which are far apart, may almost simultaneously reach the critical state of fault failure, probably also leading to regional earthquake clusters and earthquake migration. Based on our model synthetic seismic catalog and paleoseismic data, we analyze probability of earthquake migration between major faults in northeastern Tibetan Plateau. We find that following the 1920 M 8.5 Haiyuan earthquake and the 1927 M 8.0 Gulang earthquake, the next big event (M≥7) in northeastern Tibetan Plateau would be most likely to occur on the Haiyuan fault.
NASA Astrophysics Data System (ADS)
Liu, Yue-Lin; Yu, Yang; Dai, Zhen-Hong
2015-01-01
Using first-principles calculations, we investigate the stabilities of He and Hen-vacancy (HenV) clusters in α-Fe and W. Vacancy formation energies are 2.08 eV in α-Fe and 3.11 eV in W, respectively. Single He in both α-Fe and W prefers to occupy the tetrahedral interstitial site. We recalculated the He solution energy considering the effect of zero-point energy (ZPE). The ZPEs of He in α-Fe and W at the tetrahedral (octahedral) interstitial site are 0.072 eV (0.031 eV) and 0.078 eV (0.034 eV), respectively. The trapping energies of single He at vacancy in α-Fe and W are -2.39 eV and -4.55 eV, respectively. By sequentially adding He into vacancy, a monovacancy trap up to 10 He atoms distributing in the vacancy vicinity. Based on the above results combined with statistical model, we evaluate the concentrations of all relevant HenV clusters as a function of He chemical potential. The critical HenV concentration is found to be ∼10-40 (atomic) at the critical temperature T = 600 K in α-Fe and T = 1600 K in W, respectively. Beyond the critical HenV concentrations, considerable HenV aggregate to form HenVm clusters. By further growing of HenVm, the HenVm clusters grow bigger resulting in the larger He bubble formation.
Optimal Sequential Rules for Computer-Based Instruction.
ERIC Educational Resources Information Center
Vos, Hans J.
1998-01-01
Formulates sequential rules for adapting the appropriate amount of instruction to learning needs in the context of computer-based instruction. Topics include Bayesian decision theory, threshold and linear-utility structure, psychometric model, optimal sequential number of test questions, and an empirical example of sequential instructional…
2017-01-01
Objective Anticipation of opponent actions, through the use of advanced (i.e., pre-event) kinematic information, can be trained using video-based temporal occlusion. Typically, this involves isolated opponent skills/shots presented as trials in a random order. However, two different areas of research concerning representative task design and contextual (non-kinematic) information, suggest this structure of practice restricts expert performance. The aim of this study was to examine the effect of a sequential structure of practice during video-based training of anticipatory behavior in tennis, as well as the transfer of these skills to the performance environment. Methods In a pre-practice-retention-transfer design, participants viewed life-sized video of tennis rallies across practice in either a sequential order (sequential group), in which participants were exposed to opponent skills/shots in the order they occur in the sport, or a non-sequential (non-sequential group) random order. Results In the video-based retention test, the sequential group was significantly more accurate in their anticipatory judgments when the retention condition replicated the sequential structure compared to the non-sequential group. In the non-sequential retention condition, the non-sequential group was more accurate than the sequential group. In the field-based transfer test, overall decision time was significantly faster in the sequential group compared to the non-sequential group. Conclusion Findings highlight the benefits of a sequential structure of practice for the transfer of anticipatory behavior in tennis. We discuss the role of contextual information, and the importance of representative task design, for the testing and training of perceptual-cognitive skills in sport. PMID:28355263
UNDERSTANDING VARIABILITY IN TIME SPENT IN SELECTED LOCATIONS FOR 7-12 YEAR OLD CHILDREN
This paper summarizes a series of analyses of clustered, sequential activity/location data collected by Harvard University for 160 children aged 7-12 in Southern California (Geyh et al., 2000). The main purpose of the paper is to understand intra- and inter-variability in the ti...
Comorbid forms of psychopathology: key patterns and future research directions.
Cerdá, Magdalena; Sagdeo, Aditi; Galea, Sandro
2008-01-01
The purpose of this review is to systematically appraise the peer-reviewed literature about clustered forms of psychopathology and to present a framework that can be useful for studying comorbid psychiatric disorders. The review focuses on four of the most prevalent types of mental health problems: anxiety, depression, conduct disorder, and substance abuse. The authors summarize existing empirical research on the distribution of concurrent and sequential comorbidity in children and adolescents and in adults, and they review existing knowledge about exogenous risk factors that influence comorbidity. The authors include articles that used a longitudinal study design and used psychiatric definitions of the disorders. A total of 58 articles met the inclusion criteria and were assessed. Current evidence demonstrates a reciprocal, sequential relation between most comorbid pairs, although the mechanisms that mediate such links remain to be explained. Methodological concerns include the inconsistency of measurement of the disorders across studies, small sample sizes, and restricted follow-up times. Given the significant mental health burden placed by comorbid disorders, and their high prevalence across populations, research on the key risk factors for clustering of psychopathology is needed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shukla, Anil; Bogdanov, Bogdan
2015-02-14
Small cationic and anionic clusters of lithium formate were generated by electrospray ionization and their fragmentations were studied by tandem mass spectrometry. Singly as well as multiply charged clusters were formed with the general formulae, (HCOOLi)nLi+, (HCOOLi)nLimm+, (HCOOLi)nHCOO- and (HCOOLi)n(HCOO)mm-. Several magic number cluster ions were observed in both the positive and negative ion modes although more predominant in the positive ion mode with (HCOOLi)3Li+ being the most abundant and stable cluster ions. Fragmentations of singly charged clusters proceed first by the loss of a dimer unit ((HCOOLi)2) followed by sequential loss of monomer units (HCOOLi). In the case ofmore » positive cluster ions, all fragmentations lead to the magic cluster (HCOOLi)3Li+ at higher collision energies which later fragments to dimer and monomer ions in lower abundance. Quantum mechanical calculations performed for smaller cluster ions showed that the trimer ion has a closed ring structure similar to the phenalenylium structure with three closed rings connected to the lithium ion. Further additions of monomer units result in similar symmetric structures for hexamer and nonamer cluster ions. Thermochemical calculations show that trimer cluster ion is relatively more stable than neighboring cluster ions, supporting the experimental observation of a magic number cluster with enhanced stability.« less
COMP Superscalar, an interoperable programming framework
NASA Astrophysics Data System (ADS)
Badia, Rosa M.; Conejero, Javier; Diaz, Carlos; Ejarque, Jorge; Lezzi, Daniele; Lordan, Francesc; Ramon-Cortes, Cristian; Sirvent, Raul
2015-12-01
COMPSs is a programming framework that aims to facilitate the parallelization of existing applications written in Java, C/C++ and Python scripts. For that purpose, it offers a simple programming model based on sequential development in which the user is mainly responsible for (i) identifying the functions to be executed as asynchronous parallel tasks and (ii) annotating them with annotations or standard Python decorators. A runtime system is in charge of exploiting the inherent concurrency of the code, automatically detecting and enforcing the data dependencies between tasks and spawning these tasks to the available resources, which can be nodes in a cluster, clouds or grids. In cloud environments, COMPSs provides scalability and elasticity features allowing the dynamic provision of resources.
Brief Report: Clustered Forward Chaining with Embedded Mastery Probes to Teach Recipe Following.
Chazin, Kate T; Bartelmay, Danielle N; Lambert, Joseph M; Houchins-Juárez, Nealetta J
2017-04-01
This study evaluated the effectiveness of a clustered forward chaining (CFC) procedure to teach a 23-year-old male with autism to follow written recipes. CFC incorporates elements of forward chaining (FC) and total task chaining (TTC) by teaching a small number of steps (i.e., units) using TTC, introducing new units sequentially (akin to FC), and prompting through untrained steps. Results indicated that CFC was effective for teaching the participant to follow written recipes. Results maintained with therapist support for 3-5 weeks for all recipes, and maintained when therapist support was removed.
Unusual Gene Order and Organization of the Sea Urchin Hox Cluster
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cameron, R A; Rowen, L; Nesbitt, R
2005-10-11
The highly consistent gene order and axial colinear expression patterns found in vertebrate hox gene clusters are less well conserved across the rest of bilaterians. We report the first deuterostome instance of an intact hox cluster with a unique gene order where the paralog groups are not expressed in a sequential manner. The finished sequence from BAC clones from the genome of the sea urchin, Strongylocentrotus purpuratus, reveals a gene order wherein the anterior genes (Hox1, Hox2 and Hox3) lie nearest the posterior genes in the cluster such that the most 3 gene is Hox5. (The gene order is :more » 5-Hox1, 2, 3, 11/13c, 11/13b, 11/13a, 9/10, 8, 7, 6, 5 - 3). The finished sequence result is corroborated by restriction mapping evidence and BAC-end scaffold analyses. Comparisons with a putative ancestral deuterostome Hox gene cluster suggest that the rearrangements leading to the sea urchin gene order were many and complex.« less
Unusual Gene Order and Organization of the Sea Urchin HoxCluster
DOE Office of Scientific and Technical Information (OSTI.GOV)
Richardson, Paul M.; Lucas, Susan; Cameron, R. Andrew
2005-05-10
The highly consistent gene order and axial colinear expression patterns found in vertebrate hox gene clusters are less well conserved across the rest of bilaterians. We report the first deuterostome instance of an intact hox cluster with a unique gene order where the paralog groups are not expressed in a sequential manner. The finished sequence from BAC clones from the genome of the sea urchin, Strongylocentrotus purpuratus, reveals a gene order wherein the anterior genes (Hox1, Hox2 and Hox3) lie nearest the posterior genes in the cluster such that the most 3' gene is Hox5. (The gene order is :more » 5'-Hox1,2, 3, 11/13c, 11/13b, '11/13a, 9/10, 8, 7, 6, 5 - 3)'. The finished sequence result is corroborated by restriction mapping evidence and BAC-end scaffold analyses. Comparisons with a putative ancestral deuterostome Hox gene cluster suggest that the rearrangements leading to the sea urchin gene order were many and complex.« less
Formation and emission mechanisms of Ag nanoclusters in the Ar matrix assembly cluster source
NASA Astrophysics Data System (ADS)
Zhao, Junlei; Cao, Lu; Palmer, Richard E.; Nordlund, Kai; Djurabekova, Flyura
2017-11-01
In this paper, we study the mechanisms of growth of Ag nanoclusters in a solid Ar matrix and the emission of these nanoclusters from the matrix by a combination of experimental and theoretical methods. The molecular dynamics simulations show that the cluster growth mechanism can be described as "thermal spike-enhanced clustering" in multiple sequential ion impact events. We further show that experimentally observed large sputtered metal clusters cannot be formed by direct sputtering of Ag mixed in the Ar. Instead, we describe the mechanism of emission of the metal nanocluster that, at first, is formed in the cryogenic matrix due to multiple ion impacts, and then is emitted as a result of the simultaneous effects of interface boiling and spring force. We also develop an analytical model describing this size-dependent cluster emission. The model bridges the atomistic simulations and experimental time and length scales, and allows increasing the controllability of fast generation of nanoclusters in experiments with a high production rate.
Zhou, Jinsong; Brum, Gustavo; González, Adom; Launikonis, Bradley S.; Stern, Michael D.; Ríos, Eduardo
2005-01-01
To signal cell responses, Ca2+ is released from storage through intracellular Ca2+ channels. Unlike most plasmalemmal channels, these are clustered in quasi-crystalline arrays, which should endow them with unique properties. Two distinct patterns of local activation of Ca2+ release were revealed in images of Ca2+ sparks in permeabilized cells of amphibian muscle. In the presence of sulfate, an anion that enters the SR and precipitates Ca2+, sparks became wider than in the conventional, glutamate-based solution. Some of these were “protoplatykurtic” (had a flat top from early on), suggesting an extensive array of channels that activate simultaneously. Under these conditions the rate of production of signal mass was roughly constant during the rise time of the spark and could be as high as 5 μm3 ms−1, consistent with a release current >50 pA since the beginning of the event. This pattern, called “concerted activation,” was observed also in rat muscle fibers. When sulfate was combined with a reduced cytosolic [Ca2+] (50 nM) these sparks coexisted (and interfered) with a sequential progression of channel opening, probably mediated by Ca2+-induced Ca2+ release (CICR). Sequential propagation, observed only in frogs, may require parajunctional channels, of RyR isoform β, which are absent in the rat. Concerted opening instead appears to be a property of RyR α in the amphibian and the homologous isoform 1 in the mammal. PMID:16186560
DOE Office of Scientific and Technical Information (OSTI.GOV)
Douberly, Gary E.; Miller, Roger E.; Xantheas, Sotiris S.
Water clusters are formed in helium droplets via the sequential capture of monomers. One or two neon atoms are added to each droplet prior to the addition of water. The infrared spectrum of the droplet ensemble reveals several signatures of polar, water tetramer clusters having dipole moments between 2D and 3D. Comparison with ab initio computations supports the assignment of the cluster networks to noncyclic “3+1” clusters, which are ~5.3 kcal/mol less stable than the global minimum nonpolar cyclic tetramer. The (H2O)3Ne + H2O ring insertion barrier is sufficiently large, such that evaporative helium cooling is capable of kinetically quenchingmore » the nonequilibrium tetramer system prior to its rearrangement to the lower energy cyclic species. To this end, the reported process results in the formation of exotic water cluster networks that are either higher in energy than the most stable gas-phase analogs or not even stable in the gas phase.« less
Boundary and object detection in real world images. [by means of algorithms
NASA Technical Reports Server (NTRS)
Yakimovsky, Y.
1974-01-01
A solution to the problem of automatic location of objects in digital pictures by computer is presented. A self-scaling local edge detector which can be applied in parallel on a picture is described. Clustering algorithms and boundary following algorithms which are sequential in nature process the edge data to locate images of objects.
Two generalizations of Kohonen clustering
NASA Technical Reports Server (NTRS)
Bezdek, James C.; Pal, Nikhil R.; Tsao, Eric C. K.
1993-01-01
The relationship between the sequential hard c-means (SHCM), learning vector quantization (LVQ), and fuzzy c-means (FCM) clustering algorithms is discussed. LVQ and SHCM suffer from several major problems. For example, they depend heavily on initialization. If the initial values of the cluster centers are outside the convex hull of the input data, such algorithms, even if they terminate, may not produce meaningful results in terms of prototypes for cluster representation. This is due in part to the fact that they update only the winning prototype for every input vector. The impact and interaction of these two families with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method, but which often leads ideas to clustering algorithms is discussed. Then two generalizations of LVQ that are explicitly designed as clustering algorithms are presented; these algorithms are referred to as generalized LVQ = GLVQ; and fuzzy LVQ = FLVQ. Learning rules are derived to optimize an objective function whose goal is to produce 'good clusters'. GLVQ/FLVQ (may) update every node in the clustering net for each input vector. Neither GLVQ nor FLVQ depends upon a choice for the update neighborhood or learning rate distribution - these are taken care of automatically. Segmentation of a gray tone image is used as a typical application of these algorithms to illustrate the performance of GLVQ/FLVQ.
Daivadanam, Meena; Wahlstrom, Rolf; Sundari Ravindran, T K; Sarma, P S; Sivasankaran, S; Thankappan, K R
2013-07-17
Interventions targeting lifestyle-related risk factors and non-communicable diseases have contributed to the mainstream knowledge necessary for action. However, there are gaps in how this knowledge can be translated for practical day-to-day use in complex multicultural settings like that in India. Here, we describe the design of the Behavioural Intervention for Diet study, which was developed as a community-based intervention to change dietary behaviour among middle-income households in rural Kerala. This was a cluster-randomized controlled trial to assess the effectiveness of a sequential stage-matched intervention to bring about dietary behaviour change by targeting the procurement and consumption of five dietary components: fruits, vegetables, salt, sugar, and oil. Following a step-wise process of pairing and exclusion of outliers, six out of 22 administrative units in the northern part of Trivandrum district, Kerala state were randomly selected and allocated to intervention or control arms. Trained community volunteers carried out the data collection and intervention delivery. An innovative tool was developed to assess household readiness-to-change, and a household measurement kit and easy formulas were introduced to facilitate the practical side of behaviour change. The 1-year intervention included a household component with sequential stage-matched intervention strategies at 0, 6, and 12 months along with counselling sessions, telephonic reminders, and home visits and a community component with general awareness sessions in the intervention arm. Households in the control arm received information on recommended levels of intake of the five dietary components and general dietary information leaflets. Formative research provided the knowledge to contextualise the design of the study in accordance with socio-cultural aspects, felt needs of the community, and the ground realities associated with existing dietary procurement, preparation, and consumption patterns. The study also addressed two key issues, namely the central role of the household as the decision unit and the long-term sustainability through the use of existing local and administrative networks and community volunteers.
Characteristic phasic evolution of convulsive seizure in PCDH19-related epilepsy.
Ikeda, Hiroko; Imai, Katsumi; Ikeda, Hitoshi; Shigematsu, Hideo; Takahashi, Yukitoshi; Inoue, Yushi; Higurashi, Norimichi; Hirose, Shinichi
2016-03-01
PCDH19-related epilepsy is a genetic disorder that was first described in 1971, then referred to as "epilepsy and mental retardation limited to females". PCDH19 has recently been identified as the responsible gene, but a detailed characterization of the seizure manifestation based on video-EEG recording is still limited. The purpose of this study was to elucidate features of the seizure semiology in children with PCDH19-related epilepsy. To do this, ictal video-EEG recordings of 26 convulsive seizures in three girls with PCDH19-related epilepsy were analysed. All seizures occurred in clusters, mainly during sleep accompanied by fever. The motor manifestations consisted of six sequential phases: "jerk", "reactive", "mild tonic", "fluttering", "mild clonic", and "postictal". Some phases were brief or lacking in some seizures, whereas others were long or pronounced. In the reactive phase, the patients looked fearful or startled with sudden jerks and turned over reactively. The tonic and clonic components were less intense compared with those of typical tonic-clonic seizures in other types of epilepsy. The fluttering phase was characterised initially by asymmetric, less rhythmic, and less synchronous tremulous movement and was then followed by the subtle clonic phase. Subtle oral automatism was observed in the postictal phase. The reactive, mild tonic, fluttering and mild clonic phases were most characteristic of seizures of PCDH19-related epilepsy. Ictal EEG started bilaterally and was symmetric in some patients but asymmetric in others. It showed asymmetric rhythmic discharges in some seizures at later phases. The electroclinical pattern of the phasic evolution of convulsive seizure suggests a focal onset seizure with secondary generalisation. Based on our findings, we propose that the six unique sequential phases in convulsive seizures suggest the diagnosis of PCDH19-related epilepsy when occurring in clusters with or without high fever in girls. [Published with video sequences online].
Orban, Pierre; Doyon, Julien; Petrides, Michael; Mennes, Maarten; Hoge, Richard; Bellec, Pierre
2015-01-01
Functional magnetic resonance imaging can measure distributed and subtle variations in brain responses associated with task performance. However, it is unclear whether the rich variety of responses observed across the brain is functionally meaningful and consistent across individuals. Here, we used a multivariate clustering approach that grouped brain regions into clusters based on the similarity of their task-evoked temporal responses at the individual level, and then established the spatial consistency of these individual clusters at the group level. We observed a stable pseudohierarchy of task-evoked networks in the context of a delayed sequential motor task, where the fractionation of networks was driven by a gradient of involvement in motor sequence preparation versus execution. In line with theories about higher-level cognitive functioning, this gradient evolved in a rostro-caudal manner in the frontal lobe. In addition, parcellations in the cerebellum and basal ganglia matched with known anatomical territories and fiber pathways with the cerebral cortex. These findings demonstrate that subtle variations in brain responses associated with task performance are systematic enough across subjects to define a pseudohierarchy of task-evoked networks. Such networks capture meaningful functional features of brain organization as shaped by a given cognitive context. PMID:24729172
Luongo, Francisco J.; Zimmerman, Chris A.; Horn, Meryl E.
2016-01-01
Sequential patterns of prefrontal activity are believed to mediate important behaviors, e.g., working memory, but it remains unclear exactly how they are generated. In accordance with previous studies of cortical circuits, we found that prefrontal microcircuits in young adult mice spontaneously generate many more stereotyped sequences of activity than expected by chance. However, the key question of whether these sequences depend on a specific functional organization within the cortical microcircuit, or emerge simply as a by-product of random interactions between neurons, remains unanswered. We observed that correlations between prefrontal neurons do follow a specific functional organization—they have a small-world topology. However, until now it has not been possible to directly link small-world topologies to specific circuit functions, e.g., sequence generation. Therefore, we developed a novel analysis to address this issue. Specifically, we constructed surrogate data sets that have identical levels of network activity at every point in time but nevertheless represent various network topologies. We call this method shuffling activity to rearrange correlations (SHARC). We found that only surrogate data sets based on the actual small-world functional organization of prefrontal microcircuits were able to reproduce the levels of sequences observed in actual data. As expected, small-world data sets contained many more sequences than surrogate data sets with randomly arranged correlations. Surprisingly, small-world data sets also outperformed data sets in which correlations were maximally clustered. Thus the small-world functional organization of cortical microcircuits, which effectively balances the random and maximally clustered regimes, is optimal for producing stereotyped sequential patterns of activity. PMID:26888108
ERIC Educational Resources Information Center
Lin, Yi-Chun; Hsieh, Ya-Hui; Hou, Huei-Tse
2015-01-01
The development of a usability evaluation method for educational systems or applications, called the self-report-based sequential analysis, is described herein. The method aims to extend the current practice by proposing self-report-based sequential analysis as a new usability method, which integrates the advantages of self-report in survey…
Zhang, Jingjing; Dennis, Todd E.
2015-01-01
We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known ‘artificial behaviours’ comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified. PMID:25922935
Zhang, Jingjing; O'Reilly, Kathleen M; Perry, George L W; Taylor, Graeme A; Dennis, Todd E
2015-01-01
We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known 'artificial behaviours' comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified.
Real-time observation of formation and relaxation dynamics of NH4 in (CH3OH)m(NH3)n clusters.
Yamada, Yuji; Nishino, Yoko; Fujihara, Akimasa; Ishikawa, Haruki; Fuke, Kiyokazu
2009-03-26
The formation and relaxation dynamics of NH4(CH3OH)m(NH3)n clusters produced by photolysis of ammonia-methanol mixed clusters has been observed by a time-resolved pump-probe method with femtosecond pulse lasers. From the detailed analysis of the time evolutions of the protonated cluster ions, NH4(+)(CH3OH)m(NH3)n, the kinetic model has been constructed, which consists of sequential three-step reaction: ultrafast hydrogen-atom transfer producing the radical pair (NH4-NH2)*, the relaxation process of radical-pair clusters, and dissociation of the solvated NH4 clusters. The initial hydrogen transfer hardly occurs between ammonia and methanol, implying the unfavorable formation of radical pair, (CH3OH2-NH2)*. The remarkable dependence of the time constants in each step on the number and composition of solvents has been explained by the following factors: hydrogen delocalization within the clusters, the internal conversion of the excited-state radical pair, and the stabilization of NH4 by solvation. The dependence of the time profiles on the probe wavelength is attributed to the different ionization efficiency of the NH4(CH3OH)m(NH3)n clusters.
Fe-S Cluster Hsp70 Chaperones: The ATPase Cycle and Protein Interactions.
Dutkiewicz, Rafal; Nowak, Malgorzata; Craig, Elizabeth A; Marszalek, Jaroslaw
2017-01-01
Hsp70 chaperones and their obligatory J-protein cochaperones function together in many cellular processes. Via cycles of binding to short stretches of exposed amino acids on substrate proteins, Hsp70/J-protein chaperones not only facilitate protein folding but also drive intracellular protein transport, biogenesis of cellular structures, and disassembly of protein complexes. The biogenesis of iron-sulfur (Fe-S) clusters is one of the critical cellular processes that require Hsp70/J-protein action. Fe-S clusters are ubiquitous cofactors critical for activity of proteins performing diverse functions in, for example, metabolism, RNA/DNA transactions, and environmental sensing. This biogenesis process can be divided into two sequential steps: first, the assembly of an Fe-S cluster on a conserved scaffold protein, and second, the transfer of the cluster from the scaffold to a recipient protein. The second step involves Hsp70/J-protein chaperones. Via binding to the scaffold, chaperones enable cluster transfer to recipient proteins. In eukaryotic cells mitochondria have a key role in Fe-S cluster biogenesis. In this review, we focus on methods that enabled us to dissect protein interactions critical for the function of Hsp70/J-protein chaperones in the mitochondrial process of Fe-S cluster biogenesis in the yeast Saccharomyces cerevisiae. © 2017 Elsevier Inc. All rights reserved.
Synthesis of cyclic, multivalent Arg-Gly-Asp using sequential thiol-ene/thiol-yne photoreactions
Aimetti, Alex A.; Feaver, Kristen R.
2014-01-01
A unique method has been developed for the formation of multivalent cyclic peptides. This procedure exploits on-resin peptide cyclization using a photoinitiated thiol-ene click reaction and subsequent clustering using thiol-yne photochemistry. Both reactions utilize the sulfhydryl group on natural cysteine amino acids to participate in the thiol-mediated reactions. PMID:20552127
ERIC Educational Resources Information Center
Saiegh-Haddad, Elinor; Kogan, Nadya; Walters, Joel
2010-01-01
The study tested phonemic awareness in the two languages of Russian (L1)-Hebrew (L2) sequential bilingual children (N = 20) using phoneme deletion tasks where the phoneme to be deleted occurred word initial, word final, as a singleton, or part of a cluster, in long and short words and stressed and unstressed syllables. The experiments were…
SURF Model Calibration Strategy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Menikoff, Ralph
2017-03-10
SURF and SURFplus are high explosive reactive burn models for shock initiation and propagation of detonation waves. They are engineering models motivated by the ignition & growth concept of high spots and for SURFplus a second slow reaction for the energy release from carbon clustering. A key feature of the SURF model is that there is a partial decoupling between model parameters and detonation properties. This enables reduced sets of independent parameters to be calibrated sequentially for the initiation and propagation regimes. Here we focus on a methodology for tting the initiation parameters to Pop plot data based on 1-Dmore » simulations to compute a numerical Pop plot. In addition, the strategy for tting the remaining parameters for the propagation regime and failure diameter is discussed.« less
Exploring the sequential lineup advantage using WITNESS.
Goodsell, Charles A; Gronlund, Scott D; Carlson, Curt A
2010-12-01
Advocates claim that the sequential lineup is an improvement over simultaneous lineup procedures, but no formal (quantitatively specified) explanation exists for why it is better. The computational model WITNESS (Clark, Appl Cogn Psychol 17:629-654, 2003) was used to develop theoretical explanations for the sequential lineup advantage. In its current form, WITNESS produced a sequential advantage only by pairing conservative sequential choosing with liberal simultaneous choosing. However, this combination failed to approximate four extant experiments that exhibited large sequential advantages. Two of these experiments became the focus of our efforts because the data were uncontaminated by likely suspect position effects. Decision-based and memory-based modifications to WITNESS approximated the data and produced a sequential advantage. The next step is to evaluate the proposed explanations and modify public policy recommendations accordingly.
A Computational Algorithm for Functional Clustering of Proteome Dynamics During Development
Wang, Yaqun; Wang, Ningtao; Hao, Han; Guo, Yunqian; Zhen, Yan; Shi, Jisen; Wu, Rongling
2014-01-01
Phenotypic traits, such as seed development, are a consequence of complex biochemical interactions among genes, proteins and metabolites, but the underlying mechanisms that operate in a coordinated and sequential manner remain elusive. Here, we address this issue by developing a computational algorithm to monitor proteome changes during the course of trait development. The algorithm is built within the mixture-model framework in which each mixture component is modeled by a specific group of proteins that display a similar temporal pattern of expression in trait development. A nonparametric approach based on Legendre orthogonal polynomials was used to fit dynamic changes of protein expression, increasing the power and flexibility of protein clustering. By analyzing a dataset of proteomic dynamics during early embryogenesis of the Chinese fir, the algorithm has successfully identified several distinct types of proteins that coordinate with each other to determine seed development in this forest tree commercially and environmentally important to China. The algorithm will find its immediate applications for the characterization of mechanistic underpinnings for any other biological processes in which protein abundance plays a key role. PMID:24955031
Duque, Ricardo E
2012-04-01
Flow cytometric analysis of cell suspensions involves the sequential 'registration' of intrinsic and extrinsic parameters of thousands of cells in list mode files. Thus, it is almost irresistible to describe phenomena in numerical terms or by 'ratios' that have the appearance of 'accuracy' due to the presence of numbers obtained from thousands of cells. The concepts involved in the detection and characterization of B cell lymphoproliferative processes are revisited in this paper by identifying parameters that, when analyzed appropriately, are both necessary and sufficient. The neoplastic process (cluster) can be visualized easily because the parameters that distinguish it form a cluster in multidimensional space that is unique and distinguishable from neighboring clusters that are not of diagnostic interest but serve to provide a background. For B cell neoplasia it is operationally necessary to identify the multidimensional space occupied by a cluster whose kappa:lambda ratio is 100:0 or 0:100. Thus, the concept of kappa:lambda ratio is without meaning and would not detect B cell neoplasia in an unacceptably high number of cases.
Efficient sequential and parallel algorithms for record linkage.
Mamun, Abdullah-Al; Mi, Tian; Aseltine, Robert; Rajasekaran, Sanguthevar
2014-01-01
Integrating data from multiple sources is a crucial and challenging problem. Even though there exist numerous algorithms for record linkage or deduplication, they suffer from either large time needs or restrictions on the number of datasets that they can integrate. In this paper we report efficient sequential and parallel algorithms for record linkage which handle any number of datasets and outperform previous algorithms. Our algorithms employ hierarchical clustering algorithms as the basis. A key idea that we use is radix sorting on certain attributes to eliminate identical records before any further processing. Another novel idea is to form a graph that links similar records and find the connected components. Our sequential and parallel algorithms have been tested on a real dataset of 1,083,878 records and synthetic datasets ranging in size from 50,000 to 9,000,000 records. Our sequential algorithm runs at least two times faster, for any dataset, than the previous best-known algorithm, the two-phase algorithm using faster computation of the edit distance (TPA (FCED)). The speedups obtained by our parallel algorithm are almost linear. For example, we get a speedup of 7.5 with 8 cores (residing in a single node), 14.1 with 16 cores (residing in two nodes), and 26.4 with 32 cores (residing in four nodes). We have compared the performance of our sequential algorithm with TPA (FCED) and found that our algorithm outperforms the previous one. The accuracy is the same as that of this previous best-known algorithm.
Interaction of boron cluster ions with water: Single collision dynamics and sequential etching
NASA Astrophysics Data System (ADS)
Hintz, Paul A.; Ruatta, Stephen A.; Anderson, Scott L.
1990-01-01
Reactions of mass-selected, cooled, boron cluster ions (B+n, n=1-14) with water have been studied for collision energies from 0.1 to 6.0 eV. Most work was done with D2O, however isotope effects were examined for selected reactant cluster ions. For all size clusters there are exoergic product channels, which in most cases have no activation barriers. Cross sections are generally large, however there are fluctuations with cluster size in total reactivity, collision energy dependences, and in product distributions. For small cluster ions, there is a multitude of product channels. For clusters larger than B+6, the product distributions are dominated by a single channel: Bn-1D++DBO. Under multiple collision conditions, the primary products undergo a remarkable sequence of secondary ``etching'' reactions. As these occur, boron atoms are continuously replaced by hydrogen, and the intermediate products retain the composition: Bn-mH+m. This highly efficient chemistry appears to continue unchanged as the composition changes from pure boron to mostly hydrogen. Comparison of these results is made with boron cluster ion reactions with O2 and D2, as well as reactions with water of aluminum and silicon cluster ions. Some discussion is given of the thermochemistry for these reactions, and a possible problem with the thermochemical data in the BOD/DBO system is discussed.
Reading Remediation Based on Sequential and Simultaneous Processing.
ERIC Educational Resources Information Center
Gunnison, Judy; And Others
1982-01-01
The theory postulating a dichotomy between sequential and simultaneous processing is reviewed and its implications for remediating reading problems are reviewed. Research is cited on sequential-simultaneous processing for early and advanced reading. A list of remedial strategies based on the processing dichotomy addresses decoding and lexical…
Rosende, Maria; Savonina, Elena Yu; Fedotov, Petr S; Miró, Manuel; Cerdà, Víctor; Wennrich, Rainer
2009-09-15
Dynamic fractionation has been recognized as an appealing alternative to conventional equilibrium-based sequential extraction procedures (SEPs) for partitioning of trace elements (TE) in environmental solid samples. This paper reports the first attempt for harmonization of flow-through dynamic fractionation using two novel methods, the so-called sequential injection microcolumn (SIMC) extraction and rotating coiled column (RCC) extraction. In SIMC extraction, a column packed with the solid sample is clustered in a sequential injection system, while in RCC, the particulate matter is retained under the action of centrifugal forces. In both methods, the leachants are continuously pumped through the solid substrates by the use of either peristaltic or syringe pumps. A five-step SEP was selected for partitioning of Cu, Pb and Zn in water soluble/exchangeable, acid-soluble, easily reducible, easily oxidizable and moderately reducible fractions from 0.2 to 0.5 g samples at an extractant flow rate of 1.0 mL min(-1) prior to leachate analysis by inductively coupled plasma-atomic emission spectrometry. Similarities and discrepancies between both dynamic approaches were ascertained by fractionation of TE in certified reference materials, namely, SRM 2711 Montana Soil and GBW 07311 sediment, and two real soil samples as well. Notwithstanding the different extraction conditions set by both methods, similar trends of metal distribution were in generally found. The most critical parameters for reliable assessment of mobilizable pools of TE in worse-case scenarios are the size-distribution of sample particles, the density of particles, the content of organic matter and the concentration of major elements. For reference materials and a soil rich in organic matter, the extraction in RCC results in slightly higher recoveries of environmentally relevant fractions of TE, whereas SIMC leaching is more effective for calcareous soils.
Peng, Zhihang; Bao, Changjun; Zhao, Yang; Yi, Honggang; Xia, Letian; Yu, Hao; Shen, Hongbing; Chen, Feng
2010-01-01
This paper first applies the sequential cluster method to set up the classification standard of infectious disease incidence state based on the fact that there are many uncertainty characteristics in the incidence course. Then the paper presents a weighted Markov chain, a method which is used to predict the future incidence state. This method assumes the standardized self-coefficients as weights based on the special characteristics of infectious disease incidence being a dependent stochastic variable. It also analyzes the characteristics of infectious diseases incidence via the Markov chain Monte Carlo method to make the long-term benefit of decision optimal. Our method is successfully validated using existing incidents data of infectious diseases in Jiangsu Province. In summation, this paper proposes ways to improve the accuracy of the weighted Markov chain, specifically in the field of infection epidemiology. PMID:23554632
Peng, Zhihang; Bao, Changjun; Zhao, Yang; Yi, Honggang; Xia, Letian; Yu, Hao; Shen, Hongbing; Chen, Feng
2010-05-01
This paper first applies the sequential cluster method to set up the classification standard of infectious disease incidence state based on the fact that there are many uncertainty characteristics in the incidence course. Then the paper presents a weighted Markov chain, a method which is used to predict the future incidence state. This method assumes the standardized self-coefficients as weights based on the special characteristics of infectious disease incidence being a dependent stochastic variable. It also analyzes the characteristics of infectious diseases incidence via the Markov chain Monte Carlo method to make the long-term benefit of decision optimal. Our method is successfully validated using existing incidents data of infectious diseases in Jiangsu Province. In summation, this paper proposes ways to improve the accuracy of the weighted Markov chain, specifically in the field of infection epidemiology.
Liao, Xiaolei; Zhao, Juanjuan; Jiao, Cheng; Lei, Lei; Qiang, Yan; Cui, Qiang
2016-01-01
Background Lung parenchyma segmentation is often performed as an important pre-processing step in the computer-aided diagnosis of lung nodules based on CT image sequences. However, existing lung parenchyma image segmentation methods cannot fully segment all lung parenchyma images and have a slow processing speed, particularly for images in the top and bottom of the lung and the images that contain lung nodules. Method Our proposed method first uses the position of the lung parenchyma image features to obtain lung parenchyma ROI image sequences. A gradient and sequential linear iterative clustering algorithm (GSLIC) for sequence image segmentation is then proposed to segment the ROI image sequences and obtain superpixel samples. The SGNF, which is optimized by a genetic algorithm (GA), is then utilized for superpixel clustering. Finally, the grey and geometric features of the superpixel samples are used to identify and segment all of the lung parenchyma image sequences. Results Our proposed method achieves higher segmentation precision and greater accuracy in less time. It has an average processing time of 42.21 seconds for each dataset and an average volume pixel overlap ratio of 92.22 ± 4.02% for four types of lung parenchyma image sequences. PMID:27532214
[Professor GAO Yuchun's experience on "sequential acupuncture leads to smooth movement of qi"].
Wang, Yanjun; Xing, Xiao; Cui, Linhua
2016-01-01
Professor GAO Yuchun is considered as the key successor of GAO's academic school of acupuncture and moxibustion in Yanzhao region. Professor GAO's clinical experience of, "sequential acupuncture" is introduced in details in this article. In Professor GAO's opinions, appropriate acupuncture sequence is the key to satisfactory clinical effects during treatment. Based on different acupoints, sequential acupuncture can achieve the aim of qi following needles and needles leading qi; based on different symptoms, sequential acupuncture can regulate qi movement; based on different body positions, sequential acupuncture can harmonize qi-blood and reinforcing deficiency and reducing excess. In all, according to the differences of disease condition and constitution, based on the accurate acupoint selection and appropriate manipulation, it is essential to capture the nature of diseases and make the order of acupuncture, which can achieve the aim of regulating qi movement and reinforcing deficiency and reducing excess.
TRIGGERED STAR FORMATION SURROUNDING WOLF-RAYET STAR HD 211853
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu Tie; Wu Yuefang; Zhang Huawei
The environment surrounding Wolf-Rayet (W-R) star HD 211853 is studied in molecular, infrared, as well as radio, and H I emission. The molecular ring consists of well-separated cores, which have a volume density of 10{sup 3} cm{sup -3} and kinematic temperature {approx}20 K. Most of the cores are under gravitational collapse due to external pressure from the surrounding ionized gas. From the spectral energy distribution modeling toward the young stellar objects, the sequential star formation is revealed on a large scale in space spreading from the W-R star to the molecular ring. A small-scale sequential star formation is revealed towardmore » core 'A', which harbors a very young star cluster. Triggered star formations are thus suggested. The presence of the photodissociation region, the fragmentation of the molecular ring, the collapse of the cores, and the large-scale sequential star formation indicate that the 'collect and collapse' process functions in this region. The star-forming activities in core 'A' seem to be affected by the 'radiation-driven implosion' process.« less
Harris, Christopher; Stace, Anthony J
2018-03-15
A series of experiments have been undertaken on the fragmentation of multiply charged ammonia clusters, (NH 3 ) n z+ , where z ≤ 8 and n ≤ 850, to establish Rayleigh instability limits, whereby clusters at certain critical sizes become unstable due to Coulomb repulsion between the resident charges. Experimental results on size-selected clusters are found to be in excellent agreement with theoretical predictions of Rayleigh instability limits at all values of the charge. Electrostatic theory has been used to help identify fragmentation patterns on the assumption that the clusters separate into two dielectric spheres, and the predicted Coulomb repulsion energies used to establish pathways and the sizes of cluster fragments. The results show that fragmentation is very asymmetric in terms of both the numbers of molecules involved and the amount of charge each fragment accommodates. For clusters carrying a charge ≤+4, the results show that fragmentation proceeds via the loss of small, singly charged clusters. When clusters carry a charge of +5 or more, the experimental observations suggest a marked switch in behavior. Although the laboratory measurements equate to fragmentation via the loss of a large dication cluster, electrostatic theory supports an interpretation that involves the sequential loss of two smaller, singly charged clusters possibly accompanied by the extensive evaporation of neutral molecules. It is suggested that this change in fragmentation pattern is driven by the channelling of Coulomb repulsion energy into intermolecular modes within these larger clusters. Overall, the results appear to support the ion evaporation model that is frequently used to interpret electrospray experiments.
Multi-Level Sequential Pattern Mining Based on Prime Encoding
NASA Astrophysics Data System (ADS)
Lianglei, Sun; Yun, Li; Jiang, Yin
Encoding is not only to express the hierarchical relationship, but also to facilitate the identification of the relationship between different levels, which will directly affect the efficiency of the algorithm in the area of mining the multi-level sequential pattern. In this paper, we prove that one step of division operation can decide the parent-child relationship between different levels by using prime encoding and present PMSM algorithm and CROSS-PMSM algorithm which are based on prime encoding for mining multi-level sequential pattern and cross-level sequential pattern respectively. Experimental results show that the algorithm can effectively extract multi-level and cross-level sequential pattern from the sequence database.
A Fault Tolerance Mechanism for On-Road Sensor Networks
Feng, Lei; Guo, Shaoyong; Sun, Jialu; Yu, Peng; Li, Wenjing
2016-01-01
On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N − x principle and the sensors’ failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%. PMID:27918483
Cost-effective GPU-grid for genome-wide epistasis calculations.
Pütz, B; Kam-Thong, T; Karbalai, N; Altmann, A; Müller-Myhsok, B
2013-01-01
Until recently, genotype studies were limited to the investigation of single SNP effects due to the computational burden incurred when studying pairwise interactions of SNPs. However, some genetic effects as simple as coloring (in plants and animals) cannot be ascribed to a single locus but only understood when epistasis is taken into account [1]. It is expected that such effects are also found in complex diseases where many genes contribute to the clinical outcome of affected individuals. Only recently have such problems become feasible computationally. The inherently parallel structure of the problem makes it a perfect candidate for massive parallelization on either grid or cloud architectures. Since we are also dealing with confidential patient data, we were not able to consider a cloud-based solution but had to find a way to process the data in-house and aimed to build a local GPU-based grid structure. Sequential epistatsis calculations were ported to GPU using CUDA at various levels. Parallelization on the CPU was compared to corresponding GPU counterparts with regards to performance and cost. A cost-effective solution was created by combining custom-built nodes equipped with relatively inexpensive consumer-level graphics cards with highly parallel GPUs in a local grid. The GPU method outperforms current cluster-based systems on a price/performance criterion, as a single GPU shows speed performance comparable up to 200 CPU cores. The outlined approach will work for problems that easily lend themselves to massive parallelization. Code for various tasks has been made available and ongoing development of tools will further ease the transition from sequential to parallel algorithms.
JAIL: a structure-based interface library for macromolecules.
Günther, Stefan; von Eichborn, Joachim; May, Patrick; Preissner, Robert
2009-01-01
The increasing number of solved macromolecules provides a solid number of 3D interfaces, if all types of molecular contacts are being considered. JAIL annotates three different kinds of macromolecular interfaces, those between interacting protein domains, interfaces of different protein chains and interfaces between proteins and nucleic acids. This results in a total number of about 184,000 database entries. All the interfaces can easily be identified by a detailed search form or by a hierarchical tree that describes the protein domain architectures classified by the SCOP database. Visual inspection of the interfaces is possible via an interactive protein viewer. Furthermore, large scale analyses are supported by an implemented sequential and by a structural clustering. Similar interfaces as well as non-redundant interfaces can be easily picked out. Additionally, the sequential conservation of binding sites was also included in the database and is retrievable via Jmol. A comprehensive download section allows the composition of representative data sets with user defined parameters. The huge data set in combination with various search options allow a comprehensive view on all interfaces between macromolecules included in the Protein Data Bank (PDB). The download of the data sets supports numerous further investigations in macromolecular recognition. JAIL is publicly available at http://bioinformatics.charite.de/jail.
Artificial gravity Mars spaceship
NASA Technical Reports Server (NTRS)
Clark, Benton C.
1989-01-01
Experience gained in the study of artificial gravity for a manned trip to Mars is reviewed, and a snowflake-configured interplanetary vehicle cluster of habitat modules, descent vehicles, and propulsion systems is presented. An evolutionary design is described which permits sequential upgrading from five to nine crew members, an increase of landers from one to as many a three per mission, and an orderly, phased incorporation of advanced technologies as they become available.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Webb-Robertson, Bobbie-Jo M.; Jarman, Kristin H.; Harvey, Scott D.
2005-05-28
A fundamental problem in analysis of highly multivariate spectral or chromatographic data is reduction of dimensionality. Principal components analysis (PCA), concerned with explaining the variance-covariance structure of the data, is a commonly used approach to dimension reduction. Recently an attractive alternative to PCA, sequential projection pursuit (SPP), has been introduced. Designed to elicit clustering tendencies in the data, SPP may be more appropriate when performing clustering or classification analysis. However, the existing genetic algorithm (GA) implementation of SPP has two shortcomings, computation time and inability to determine the number of factors necessary to explain the majority of the structure inmore » the data. We address both these shortcomings. First, we introduce a new SPP algorithm, a random scan sampling algorithm (RSSA), that significantly reduces computation time. We compare the computational burden of the RSS and GA implementation for SPP on a dataset containing Raman spectra of twelve organic compounds. Second, we propose a Bayes factor criterion, BFC, as an effective measure for selecting the number of factors needed to explain the majority of the structure in the data. We compare SPP to PCA on two datasets varying in type, size, and difficulty; in both cases SPP achieves a higher accuracy with a lower number of latent variables.« less
Efficient sequential and parallel algorithms for record linkage
Mamun, Abdullah-Al; Mi, Tian; Aseltine, Robert; Rajasekaran, Sanguthevar
2014-01-01
Background and objective Integrating data from multiple sources is a crucial and challenging problem. Even though there exist numerous algorithms for record linkage or deduplication, they suffer from either large time needs or restrictions on the number of datasets that they can integrate. In this paper we report efficient sequential and parallel algorithms for record linkage which handle any number of datasets and outperform previous algorithms. Methods Our algorithms employ hierarchical clustering algorithms as the basis. A key idea that we use is radix sorting on certain attributes to eliminate identical records before any further processing. Another novel idea is to form a graph that links similar records and find the connected components. Results Our sequential and parallel algorithms have been tested on a real dataset of 1 083 878 records and synthetic datasets ranging in size from 50 000 to 9 000 000 records. Our sequential algorithm runs at least two times faster, for any dataset, than the previous best-known algorithm, the two-phase algorithm using faster computation of the edit distance (TPA (FCED)). The speedups obtained by our parallel algorithm are almost linear. For example, we get a speedup of 7.5 with 8 cores (residing in a single node), 14.1 with 16 cores (residing in two nodes), and 26.4 with 32 cores (residing in four nodes). Conclusions We have compared the performance of our sequential algorithm with TPA (FCED) and found that our algorithm outperforms the previous one. The accuracy is the same as that of this previous best-known algorithm. PMID:24154837
SPMBR: a scalable algorithm for mining sequential patterns based on bitmaps
NASA Astrophysics Data System (ADS)
Xu, Xiwei; Zhang, Changhai
2013-12-01
Now some sequential patterns mining algorithms generate too many candidate sequences, and increase the processing cost of support counting. Therefore, we present an effective and scalable algorithm called SPMBR (Sequential Patterns Mining based on Bitmap Representation) to solve the problem of mining the sequential patterns for large databases. Our method differs from previous related works of mining sequential patterns. The main difference is that the database of sequential patterns is represented by bitmaps, and a simplified bitmap structure is presented firstly. In this paper, First the algorithm generate candidate sequences by SE(Sequence Extension) and IE(Item Extension), and then obtain all frequent sequences by comparing the original bitmap and the extended item bitmap .This method could simplify the problem of mining the sequential patterns and avoid the high processing cost of support counting. Both theories and experiments indicate that the performance of SPMBR is predominant for large transaction databases, the required memory size for storing temporal data is much less during mining process, and all sequential patterns can be mined with feasibility.
Application of dynamic topic models to toxicogenomics data.
Lee, Mikyung; Liu, Zhichao; Huang, Ruili; Tong, Weida
2016-10-06
All biological processes are inherently dynamic. Biological systems evolve transiently or sustainably according to sequential time points after perturbation by environment insults, drugs and chemicals. Investigating the temporal behavior of molecular events has been an important subject to understand the underlying mechanisms governing the biological system in response to, such as, drug treatment. The intrinsic complexity of time series data requires appropriate computational algorithms for data interpretation. In this study, we propose, for the first time, the application of dynamic topic models (DTM) for analyzing time-series gene expression data. A large time-series toxicogenomics dataset was studied. It contains over 3144 microarrays of gene expression data corresponding to rat livers treated with 131 compounds (most are drugs) at two doses (control and high dose) in a repeated schedule containing four separate time points (4-, 8-, 15- and 29-day). We analyzed, with DTM, the topics (consisting of a set of genes) and their biological interpretations over these four time points. We identified hidden patterns embedded in this time-series gene expression profiles. From the topic distribution for compound-time condition, a number of drugs were successfully clustered by their shared mode-of-action such as PPARɑ agonists and COX inhibitors. The biological meaning underlying each topic was interpreted using diverse sources of information such as functional analysis of the pathways and therapeutic uses of the drugs. Additionally, we found that sample clusters produced by DTM are much more coherent in terms of functional categories when compared to traditional clustering algorithms. We demonstrated that DTM, a text mining technique, can be a powerful computational approach for clustering time-series gene expression profiles with the probabilistic representation of their dynamic features along sequential time frames. The method offers an alternative way for uncovering hidden patterns embedded in time series gene expression profiles to gain enhanced understanding of dynamic behavior of gene regulation in the biological system.
Fragmentation pathways of tungsten hexacarbonyl clusters upon electron ionization.
Neustetter, M; Jabbour Al Maalouf, E; Limão-Vieira, P; Denifl, S
2016-08-07
Electron ionization of neat tungsten hexacarbonyl (W(CO)6) clusters has been investigated in a crossed electron-molecular beam experiment coupled with a mass spectrometer system. The molecule is used for nanofabrication processes through electron beam induced deposition and ion beam induced deposition techniques. Positive ion mass spectra of W(CO)6 clusters formed by electron ionization at 70 eV contain the ion series of the type W(CO)n (+) (0 ≤ n ≤ 6) and W2(CO)n (+) (0 ≤ n ≤ 12). In addition, a series of peaks are observed and have been assigned to WC(CO)n (+) (0 ≤ n ≤ 3) and W2C(CO)n (+) (0 ≤ n ≤ 10). A distinct change of relative fragment ion intensity can be observed for clusters compared to the single molecule. The characteristic fragmentation pattern obtained in the mass spectra can be explained by a sequential decay of the ionized organometallic, which is also supported by the study of the clusters when embedded in helium nanodroplets. In addition, appearance energies for the dissociative ionization channels for singly charged ions have been estimated from experimental ion efficiency curves.
Daivadanam, Meena; Wahlstrom, Rolf; Ravindran, T.K. Sundari; Sarma, P.S.; Sivasankaran, S.; Thankappan, K.R.
2013-01-01
Background Interventions targeting lifestyle-related risk factors and non-communicable diseases have contributed to the mainstream knowledge necessary for action. However, there are gaps in how this knowledge can be translated for practical day-to-day use in complex multicultural settings like that in India. Here, we describe the design of the Behavioural Intervention for Diet study, which was developed as a community-based intervention to change dietary behaviour among middle-income households in rural Kerala. Methods This was a cluster-randomized controlled trial to assess the effectiveness of a sequential stage-matched intervention to bring about dietary behaviour change by targeting the procurement and consumption of five dietary components: fruits, vegetables, salt, sugar, and oil. Following a step-wise process of pairing and exclusion of outliers, six out of 22 administrative units in the northern part of Trivandrum district, Kerala state were randomly selected and allocated to intervention or control arms. Trained community volunteers carried out the data collection and intervention delivery. An innovative tool was developed to assess household readiness-to-change, and a household measurement kit and easy formulas were introduced to facilitate the practical side of behaviour change. The 1-year intervention included a household component with sequential stage-matched intervention strategies at 0, 6, and 12 months along with counselling sessions, telephonic reminders, and home visits and a community component with general awareness sessions in the intervention arm. Households in the control arm received information on recommended levels of intake of the five dietary components and general dietary information leaflets. Discussion Formative research provided the knowledge to contextualise the design of the study in accordance with socio-cultural aspects, felt needs of the community, and the ground realities associated with existing dietary procurement, preparation, and consumption patterns. The study also addressed two key issues, namely the central role of the household as the decision unit and the long-term sustainability through the use of existing local and administrative networks and community volunteers. PMID:23866917
Estimation After a Group Sequential Trial.
Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert
2015-10-01
Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.
NASA Astrophysics Data System (ADS)
Malik, Riffat Naseem; Hashmi, Muhammad Zaffar
2017-10-01
Himalayan foothills streams, Pakistan play an important role in living water supply and irrigation of farmlands; thus, the water quality is closely related to public health. Multivariate techniques were applied to check spatial and seasonal trends, and metals contamination sources of the Himalayan foothills streams, Pakistan. Grab surface water samples were collected from different sites (5-15 cm water depth) in pre-washed polyethylene containers. Fast Sequential Atomic Absorption Spectrophotometer (Varian FSAA-240) was used to measure the metals concentration. Concentrations of Ni, Cu, and Mn were high in pre-monsoon season than the post-monsoon season. Cluster analysis identified impaired, moderately impaired and least impaired clusters based on water parameters. Discriminant function analysis indicated spatial variability in water was due to temperature, electrical conductivity, nitrates, iron and lead whereas seasonal variations were correlated with 16 physicochemical parameters. Factor analysis identified municipal and poultry waste, automobile activities, surface runoff, and soil weathering as major sources of contamination. Levels of Mn, Cr, Fe, Pb, Cd, Zn and alkalinity were above the WHO and USEPA standards for surface water. The results of present study will help to higher authorities for the management of the Himalayan foothills streams.
Felton, Jeremy A; Ray, Manisha; Waller, Sarah E; Kafader, Jared O; Jarrold, Caroline Chick
2014-10-30
Reactions between small cerium oxide cluster anions and deuterated water were monitored as a function of both water concentration and temperature in order to determine the temperature dependence of the rate constants. Sequential oxidation reactions of the Ce(x)O(y)⁻ (x = 2, 3) suboxide cluster anions were found to exhibit anti-Arrhenius behavior, with activation energies ranging from 0 to -18 kJ mol⁻¹. Direct oxidation of species up to y = x was observed, after which, -OD abstraction and D₂O addition reactions were observed. However, the stoichiometric Ce₂O₄⁻ and Ce₃O₆⁻ cluster anions also emerge in reactions between D₂O and the respective precursors, Ce₂O₃D⁻ and Ce₃O₅D₂⁻. Ce₂O₄⁻ and Ce₃O₆⁻ product intensities diminish relative to deuteroxide complex intensities with increasing temperature. The kinetics of these reactions are compared to the kinetics of the previously studied Mo(x)O(y)⁻ and W(x)O(y)⁻ reactions with water, and the possible implications for the reaction mechanisms are discussed.
Patterning in time and space: HoxB cluster gene expression in the developing chick embryo.
Gouveia, Analuce; Marcelino, Hugo M; Gonçalves, Lisa; Palmeirim, Isabel; Andrade, Raquel P
2015-01-01
The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space.
Patterning in time and space: HoxB cluster gene expression in the developing chick embryo
Gouveia, Analuce; Marcelino, Hugo M; Gonçalves, Lisa; Palmeirim, Isabel; Andrade, Raquel P
2015-01-01
The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space. PMID:25602523
Efficient Record Linkage Algorithms Using Complete Linkage Clustering.
Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar
2016-01-01
Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times.
Efficient Record Linkage Algorithms Using Complete Linkage Clustering
Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar
2016-01-01
Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times. PMID:27124604
The Star Schema Benchmark and Augmented Fact Table Indexing
NASA Astrophysics Data System (ADS)
O'Neil, Patrick; O'Neil, Elizabeth; Chen, Xuedong; Revilak, Stephen
We provide a benchmark measuring star schema queries retrieving data from a fact table with Where clause column restrictions on dimension tables. Clustering is crucial to performance with modern disk technology, since retrievals with filter factors down to 0.0005 are now performed most efficiently by sequential table search rather than by indexed access. DB2’s Multi-Dimensional Clustering (MDC) provides methods to "dice" the fact table along a number of orthogonal "dimensions", but only when these dimensions are columns in the fact table. The diced cells cluster fact rows on several of these "dimensions" at once so queries restricting several such columns can access crucially localized data, with much faster query response. Unfortunately, columns of dimension tables of a star schema are not usually represented in the fact table. In this paper, we show a simple way to adjoin physical copies of dimension columns to the fact table, dicing data to effectively cluster query retrieval, and explain how such dicing can be achieved on database products other than DB2. We provide benchmark measurements to show successful use of this methodology on three commercial database products.
Distal regulatory regions restrict the expression of cis-linked genes to the tapetal cells.
Franco, Luciana O; de O Manes, Carmem Lara; Hamdi, Said; Sachetto-Martins, Gilberto; de Oliveira, Dulce E
2002-04-24
The oleosin glycine-rich protein genes Atgrp-6, Atgrp-7, and Atgrp-8 occur in clusters in the Arabidopsis genome and are expressed specifically in the tapetum cells. The cis-regulatory regions involved in the tissue-specific gene expression were investigated by fusing different segments of the gene cluster to the uidA reporter gene. Common distal regulatory regions were identified that coordinate expression of the sequential genes. At least two of these genes were regulated spatially by proximal and distal sequences. The cis-acting elements (122 bp upstream of the transcriptional start point) drive the uidA expression to floral tissues, whereas distal 5' upstream regions restrict the gene activity to tapetal cells.
Size-restricted proton transfer within toluene-methanol cluster ions.
Chiang, Chi-Tung; Shores, Kevin S; Freindorf, Marek; Furlani, Thomas; DeLeon, Robert L; Garvey, James F
2008-11-20
To understand the interaction between toluene and methanol, the chemical reactivity of [(C6H5CH3)(CH3OH) n=1-7](+) cluster ions has been investigated via tandem quadrupole mass spectrometry and through calculations. Collision Induced Dissociation (CID) experiments show that the dissociated intracluster proton transfer reaction from the toluene cation to methanol clusters, forming protonated methanol clusters, only occurs for n = 2-4. For n = 5-7, CID spectra reveal that these larger clusters have to sequentially lose methanol monomers until they reach n = 4 to initiate the deprotonation of the toluene cation. Metastable decay data indicate that for n = 3 and n = 4 (CH3OH)3H(+) is the preferred fragment ion. The calculational results reveal that both the gross proton affinity of the methanol subcluster and the structure of the cluster itself play an important role in driving this proton transfer reaction. When n = 3, the cooperative effect of the methanols in the subcluster provides the most important contribution to allow the intracluster proton transfer reaction to occur with little or no energy barrier. As n >or= 4, the methanol subcluster is able to form ring structures to stabilize the cluster structures so that direct proton transfer is not a favored process. The preferred reaction product, the (CH3OH)3H(+) cluster ion, indicates that this size-restricted reaction is driven by both the proton affinity and the enhanced stability of the resulting product.
Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos
2017-11-09
Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less
A Parallel Point Matching Algorithm for Landmark Based Image Registration Using Multicore Platform
Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L.; Foran, David J.
2013-01-01
Point matching is crucial for many computer vision applications. Establishing the correspondence between a large number of data points is a computationally intensive process. Some point matching related applications, such as medical image registration, require real time or near real time performance if applied to critical clinical applications like image assisted surgery. In this paper, we report a new multicore platform based parallel algorithm for fast point matching in the context of landmark based medical image registration. We introduced a non-regular data partition algorithm which utilizes the K-means clustering algorithm to group the landmarks based on the number of available processing cores, which optimize the memory usage and data transfer. We have tested our method using the IBM Cell Broadband Engine (Cell/B.E.) platform. The results demonstrated a significant speed up over its sequential implementation. The proposed data partition and parallelization algorithm, though tested only on one multicore platform, is generic by its design. Therefore the parallel algorithm can be extended to other computing platforms, as well as other point matching related applications. PMID:24308014
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos
Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shukla, Anil, E-mail: Anil.Shukla@pnnl.gov; Bogdanov, Bogdan
2015-02-14
Small cationic and anionic clusters of lithium formate were generated by electrospray ionization and their fragmentations were studied by tandem mass spectrometry (collision-induced dissociation with N{sub 2}). Singly as well as multiply charged clusters were formed in both positive and negative ion modes with the general formulae, (HCOOLi){sub n}Li{sup +}, (HCOOLi){sub n}Li{sub m}{sup m+}, (HCOOLi){sub n}HCOO{sup −}, and (HCOOLi){sub n}(HCOO){sub m}{sup m−}. Several magic number cluster (MNC) ions were observed in both the positive and negative ion modes although more predominant in the positive ion mode with (HCOOLi){sub 3}Li{sup +} being the most abundant and stable cluster ion. Fragmentations ofmore » singly charged positive clusters proceed first by the loss of a dimer unit ((HCOOLi){sub 2}) followed by the loss of monomer units (HCOOLi) although the former remains the dominant dissociation process. In the case of positive cluster ions, all fragmentations lead to the magic cluster (HCOOLi){sub 3}Li{sup +} as the most abundant fragment ion at higher collision energies which then fragments further to dimer and monomer ions at lower abundances. In the negative ion mode, however, singly charged clusters dissociated via sequential loss of monomer units. Multiply charged clusters in both positive and negative ion modes dissociated mainly via Coulomb repulsion. Quantum chemical calculations performed for smaller cluster ions showed that the trimer ion has a closed ring structure similar to the phenalenylium structure with three closed rings connected to the central lithium ion. Further additions of monomer units result in similar symmetric structures for hexamer and nonamer cluster ions. Thermochemical calculations show that trimer cluster ion is relatively more stable than neighboring cluster ions, supporting the experimental observation of a magic number cluster with enhanced stability.« less
Evolutionary Glycomics: Characterization of Milk Oligosaccharides in Primates
Tao, Nannan; Wu, Shuai; Kim, Jaehan; An, Hyun Joo; Hinde, Katie; Power, Michael L.; Gagneux, Pascal; German, J. Bruce; Lebrilla, Carlito B.
2011-01-01
Free oligosaccharides are abundant components of mammalian milk and have primary roles as prebiotic compounds, in immune defense, and in brain development. Mass spectrometry-based technique is applied to profile milk oligosaccharides from apes (chimpanzee, gorilla, and siamang), new world monkeys (golden lion tamarin and common marmoset), and an old world monkey (rhesus). The purpose of this study was to evaluate the patterns of primate milk oligosaccharide composition from a phylogenetic perspective in order to assess the extent to which the compositions of hMOs derives from ancestral, primate patterns as opposed to more recent evolutionary events. Milk oligosaccharides were quantitated by nanoflow liquid chromatography on chip-based devices. The relative abundances of fucosylated and sialylated milk oligosaccharides in primates were also determined. For a systematic and comprehensive study of evolutionary patterns of milk oligosaccharides, cluster analysis of primate milk was performed using the chromatographic profile. In general, the oligosaccharides in primate milk, including humans, are more complex and exhibit greater diversity compared to the ones in non-primate milk. A detailed comparison of the oligosaccharides across evolution revealed non-sequential developmental pattern, i.e. that primate milk oligosaccharides do not necessarily cluster according to the primate phylogeny. This report represents the first comprehensive and quantitative effort to profile and elucidate the structures of free milk oligosaccharides so that they can be related to glycan function in different primates. PMID:21214271
Physics-based, Bayesian sequential detection method and system for radioactive contraband
Candy, James V; Axelrod, Michael C; Breitfeller, Eric F; Chambers, David H; Guidry, Brian L; Manatt, Douglas R; Meyer, Alan W; Sale, Kenneth E
2014-03-18
A distributed sequential method and system for detecting and identifying radioactive contraband from highly uncertain (noisy) low-count, radionuclide measurements, i.e. an event mode sequence (EMS), using a statistical approach based on Bayesian inference and physics-model-based signal processing based on the representation of a radionuclide as a monoenergetic decomposition of monoenergetic sources. For a given photon event of the EMS, the appropriate monoenergy processing channel is determined using a confidence interval condition-based discriminator for the energy amplitude and interarrival time and parameter estimates are used to update a measured probability density function estimate for a target radionuclide. A sequential likelihood ratio test is then used to determine one of two threshold conditions signifying that the EMS is either identified as the target radionuclide or not, and if not, then repeating the process for the next sequential photon event of the EMS until one of the two threshold conditions is satisfied.
Meisters, Julia; Diedenhofen, Birk; Musch, Jochen
2018-04-20
For decades, sequential lineups have been considered superior to simultaneous lineups in the context of eyewitness identification. However, most of the research leading to this conclusion was based on the analysis of diagnosticity ratios that do not control for the respondent's response criterion. Recent research based on the analysis of ROC curves has found either equal discriminability for sequential and simultaneous lineups, or higher discriminability for simultaneous lineups. Some evidence for potential position effects and for criterion shifts in sequential lineups has also been reported. Using ROC curve analysis, we investigated the effects of the suspect's position on discriminability and response criteria in both simultaneous and sequential lineups. We found that sequential lineups suffered from an unwanted position effect. Respondents employed a strict criterion for the earliest lineup positions, and shifted to a more liberal criterion for later positions. No position effects and no criterion shifts were observed in simultaneous lineups. This result suggests that sequential lineups are not superior to simultaneous lineups, and may give rise to unwanted position effects that have to be considered when conducting police lineups.
Ground and satellite observations of multiple sun-aligned auroral arcs on the duskside
NASA Astrophysics Data System (ADS)
Hosokawa, K.; Maggiolo, R.; Zhang, Y.; Fear, R. C.; Fontaine, D.; Cumnock, J. A.; Kullen, A.; Milan, S. E.; Kozlovsky, A.; Echim, M.; Shiokawa, K.
2014-12-01
Sun-aligned auroral arcs (SAAs) are one of the outstanding phenomena in the high-latitude region during periods of northward interplanetary magnetic field (IMF). Smaller scale SAAs tend to occur either in the duskside or dawnside of the polar cap and are known to drift in the dawn-dusk direction depending on the sign of the IMF By. Studies of SAAs are of particular importance because they represent dynamical characteristics of their source plasma in the magnetosphere, for example in the interaction region between the solar wind and magnetosphere or in the boundary between the plasma sheet and tail lobe. To date, however, very little has been known about the spatial structure and/or temporal evolution of the magnetospheric counterpart of SAAs. In order to gain more comprehensive understanding of the field-aligned plasma transport in the vicinity of SAAs, we have investigated an event of SAAs on November 10, 2005, during which multiple SAAs were detected by a ground-based all-sky camera at Resolute Bay, Canada. During this interval, several SAAs were detached from the duskside oval and moved poleward. The large-scale structure of these arcs was visualized by space-based imagers of TIMED/GUVI and DMSP/SSUSI. In addition to these optical observations, we employ the Cluster satellites to reveal the high-altitude particle signature corresponding to the small-scale SAAs. The ionospheric footprints of the 4 Cluster satellites encountered the SAAs sequentially and observed well correlated enhancements of electron fluxes at weak energies (< 1 keV). The Cluster satellites also detected signatures of upflowing beams of ions and electrons in the vicinity of the SAAs. This implies that these ions and electrons were accelerated upward by a quasi-stationary electric field existing in the vicinity of the SAAs and constitute a current system in the magnetosphere-ionosphere coupling system. Ionospheric convection measurement from one of the SuperDARN radars shows an indication that the SAAs are embedded in the lobe cell during northward IMF conditions. In the presentation, we will show the results of detailed comparison between the ground-based radio and optical signatures of the SAAs and those obtained by the Cluster spacecraft at magnetospheric altitudes.
NASA Astrophysics Data System (ADS)
Ye, Min; Wei, Zewen; Hu, Fei; Wang, Jianxin; Ge, Guanglu; Hu, Zhiyuan; Shao, Mingwang; Lee, Shuit-Tong; Liu, Jian
2015-08-01
It is currently a very active research area to develop new types of substrates which integrate various nanomaterials for surface-enhanced Raman scattering (SERS) techniques. Here we report a unique approach to prepare SERS substrates with reproducible performance. It features silicon mold-assisted magnetic assembling of superparamagnetic Fe3O4@Au nanoparticle clusters (NCs) into arrayed microstructures on a wafer scale. This approach enables the fabrication of both silicon-based and hydrogel-based substrates in a sequential manner. We have demonstrated that strong SERS signals can be harvested from these substrates due to an efficient coupling effect between Fe3O4@Au NCs, with enhancement factors >106. These substrates have been confirmed to provide reproducible SERS signals, with low variations in different locations or batches of samples. We investigate the spatial distributions of electromagnetic field enhancement around Fe3O4@Au NCs assemblies using finite-difference-time-domain (FDTD) simulations. The procedure to prepare the substrates is straightforward and fast. The silicon mold can be easily cleaned out and refilled with Fe3O4@Au NCs assisted by a magnet, therefore being re-useable for many cycles. Our approach has integrated microarray technologies and provided a platform for thousands of independently addressable SERS detection, in order to meet the requirements of a rapid, robust, and high throughput performance.It is currently a very active research area to develop new types of substrates which integrate various nanomaterials for surface-enhanced Raman scattering (SERS) techniques. Here we report a unique approach to prepare SERS substrates with reproducible performance. It features silicon mold-assisted magnetic assembling of superparamagnetic Fe3O4@Au nanoparticle clusters (NCs) into arrayed microstructures on a wafer scale. This approach enables the fabrication of both silicon-based and hydrogel-based substrates in a sequential manner. We have demonstrated that strong SERS signals can be harvested from these substrates due to an efficient coupling effect between Fe3O4@Au NCs, with enhancement factors >106. These substrates have been confirmed to provide reproducible SERS signals, with low variations in different locations or batches of samples. We investigate the spatial distributions of electromagnetic field enhancement around Fe3O4@Au NCs assemblies using finite-difference-time-domain (FDTD) simulations. The procedure to prepare the substrates is straightforward and fast. The silicon mold can be easily cleaned out and refilled with Fe3O4@Au NCs assisted by a magnet, therefore being re-useable for many cycles. Our approach has integrated microarray technologies and provided a platform for thousands of independently addressable SERS detection, in order to meet the requirements of a rapid, robust, and high throughput performance. Electronic supplementary information (ESI) available: XRD, reflection spectra, zeta potential, TEM images, evaluations of reproducibility, EDS, tables of EF and RSD values of different substrates. See DOI: 10.1039/c5nr02491a
Age, period, and cohort analysis of regular dental care behavior and edentulism: A marginal approach
2011-01-01
Background To analyze the regular dental care behavior and prevalence of edentulism in adult Danes, reported in sequential cross-sectional oral health surveys by the application of a marginal approach to consider the possible clustering effect of birth cohorts. Methods Data from four sequential cross-sectional surveys of non-institutionalized Danes conducted from 1975-2005 comprising 4330 respondents aged 15+ years in 9 birth cohorts were analyzed. The key study variables were seeking dental care on an annual basis (ADC) and edentulism. For the analysis of ADC, survey year, age, gender, socio-economic status (SES) group, denture-wearing, and school dental care (SDC) during childhood were considered. For the analysis of edentulism, only respondents aged 35+ years were included. Survey year, age, gender, SES group, ADC, and SDC during childhood were considered as the independent factors. To take into account the clustering effect of birth cohorts, marginal logistic regressions with an independent correlation structure in generalized estimating equations (GEE) were carried out, with PROC GENMOD in SAS software. Results The overall proportion of people seeking ADC increased from 58.8% in 1975 to 86.7% in 2005, while for respondents aged 35 years or older, the overall prevalence of edentulism (35+ years) decreased from 36.4% in 1975 to 5.0% in 2005. Females, respondents in the higher SES group, in more recent survey years, with no denture, and receiving SDC in all grades during childhood were associated with higher probability of seeking ADC regularly (P < 0.05). The interaction of SDC and age (P < 0.0001) was significant. The probabilities of seeking ADC were even higher among subjects with SDC in all grades and aged 45 years or older. Females, older age group, respondents in earlier survey years, not seeking ADC, lower SES group, and not receiving SDC in all grades were associated with higher probability of being edentulous (P < 0.05). Conclusions With the use of GEE, the potential clustering effect of birth cohorts in sequential cross-sectional oral health survey data could be appropriately considered. The success of Danish dental health policy was demonstrated by a continued increase of regular dental visiting habits and tooth retention in adults because school dental care was provided to Danes in their childhood. PMID:21410991
Calvo, F; Douady, J
2010-04-14
The structure and finite-temperature properties of hydrated nucleotide anion adenosine 5'-monophosphate (AMP) have been theoretically investigated with a variety of methods. Using a polarizable version of the Amber force field and replica-exchange molecular dynamics simulations, putative lowest-energy structures have been located for the AMP(-)(H(2)O)(n) cluster anions with n = 0-20. The hydration energies obtained with the molecular mechanics potential slightly overestimate experimental measurements. However, closer values are found after reoptimizing the structures locally at more sophisticated levels, namely semi-empirical (PM6) and density-functional theory (B3LYP/6-31+G*). Upon heating the complexes, various indicators such as the heat capacity, number of hydrogen bonds or surface area provide evidence that the water cluster melts below 200 K but remains bonded to the AMP anion. The sequential loss of water molecules after sudden heating has been studied using a statistical approach in which unimolecular evaporation is described using the orbiting transition state version of phase space theory, together with anharmonic densities of vibrational states. The evaporation rates are calibrated based on the results of molecular dynamics trajectories at high internal energy. Our results indicate that between 4 and 10 water molecules are lost from AMP(-)(H(2)O)(20) after one second depending on the initial heating in the 250-350 K range, with a concomitant cooling of the remaining cluster by 75-150 K.
Peptidoglycan architecture can specify division planes in Staphylococcus aureus.
Turner, Robert D; Ratcliffe, Emma C; Wheeler, Richard; Golestanian, Ramin; Hobbs, Jamie K; Foster, Simon J
2010-06-15
Division in Staphylococci occurs equatorially and on specific sequentially orthogonal planes in three dimensions, resulting, after incomplete cell separation, in the 'bunch of grapes' cluster organization that defines the genus. The shape of Staphylococci is principally maintained by peptidoglycan. In this study, we use Atomic Force Microscopy (AFM) and fluorescence microscopy with vancomycin labelling to examine purified peptidoglycan architecture and its dynamics in Staphylococcus aureus and correlate these with the cell cycle. At the presumptive septum, cells were found to form a large belt of peptidoglycan in the division plane before the centripetal formation of the septal disc; this often had a 'piecrust' texture. After division, the structures remain as orthogonal ribs, encoding the location of past division planes in the cell wall. We propose that this epigenetic information is used to enable S. aureus to divide in sequentially orthogonal planes, explaining how a spherical organism can maintain division plane localization with fidelity over many generations.
Picheny, Victor; Trépos, Ronan; Casadebaig, Pierre
2017-01-01
Accounting for the interannual climatic variations is a well-known issue for simulation-based studies of environmental systems. It often requires intensive sampling (e.g., averaging the simulation outputs over many climatic series), which hinders many sequential processes, in particular optimization algorithms. We propose here an approach based on a subset selection in a large basis of climatic series, using an ad-hoc similarity function and clustering. A non-parametric reconstruction technique is introduced to estimate accurately the distribution of the output of interest using only the subset sampling. The proposed strategy is non-intrusive and generic (i.e. transposable to most models with climatic data inputs), and can be combined to most “off-the-shelf” optimization solvers. We apply our approach to sunflower ideotype design using the crop model SUNFLO. The underlying optimization problem is formulated as a multi-objective one to account for risk-aversion. Our approach achieves good performances even for limited computational budgets, outperforming significantly standard strategies. PMID:28542198
A weight modification sequential method for VSC-MTDC power system state estimation
NASA Astrophysics Data System (ADS)
Yang, Xiaonan; Zhang, Hao; Li, Qiang; Guo, Ziming; Zhao, Kun; Li, Xinpeng; Han, Feng
2017-06-01
This paper presents an effective sequential approach based on weight modification for VSC-MTDC power system state estimation, called weight modification sequential method. The proposed approach simplifies the AC/DC system state estimation algorithm through modifying the weight of state quantity to keep the matrix dimension constant. The weight modification sequential method can also make the VSC-MTDC system state estimation calculation results more ccurate and increase the speed of calculation. The effectiveness of the proposed weight modification sequential method is demonstrated and validated in modified IEEE 14 bus system.
Sequential biases in accumulating evidence
Huggins, Richard; Dogo, Samson Henry
2015-01-01
Whilst it is common in clinical trials to use the results of tests at one phase to decide whether to continue to the next phase and to subsequently design the next phase, we show that this can lead to biased results in evidence synthesis. Two new kinds of bias associated with accumulating evidence, termed ‘sequential decision bias’ and ‘sequential design bias’, are identified. Both kinds of bias are the result of making decisions on the usefulness of a new study, or its design, based on the previous studies. Sequential decision bias is determined by the correlation between the value of the current estimated effect and the probability of conducting an additional study. Sequential design bias arises from using the estimated value instead of the clinically relevant value of an effect in sample size calculations. We considered both the fixed‐effect and the random‐effects models of meta‐analysis and demonstrated analytically and by simulations that in both settings the problems due to sequential biases are apparent. According to our simulations, the sequential biases increase with increased heterogeneity. Minimisation of sequential biases arises as a new and important research area necessary for successful evidence‐based approaches to the development of science. © 2015 The Authors. Research Synthesis Methods Published by John Wiley & Sons Ltd. PMID:26626562
Hajati, Omid; Zarrabi, Khalil; Karimi, Reza; Hajati, Azadeh
2012-01-01
There is still controversy over the differences in the patency rates of the sequential and individual coronary artery bypass grafting (CABG) techniques. The purpose of this paper was to non-invasively evaluate hemodynamic parameters using complete 3D computational fluid dynamics (CFD) simulations of the sequential and the individual methods based on the patient-specific data extracted from computed tomography (CT) angiography. For CFD analysis, the geometric model of coronary arteries was reconstructed using an ECG-gated 64-detector row CT. Modeling the sequential and individual bypass grafting, this study simulates the flow from the aorta to the occluded posterior descending artery (PDA) and the posterior left ventricle (PLV) vessel with six coronary branches based on the physiologically measured inlet flow as the boundary condition. The maximum calculated wall shear stress (WSS) in the sequential and the individual models were estimated to be 35.1 N/m(2) and 36.5 N/m(2), respectively. Compared to the individual bypass method, the sequential graft has shown a higher velocity at the proximal segment and lower spatial wall shear stress gradient (SWSSG) due to the flow splitting caused by the side-to-side anastomosis. Simulated results combined with its surgical benefits including the requirement of shorter vein length and fewer anastomoses advocate the sequential method as a more favorable CABG method.
NASA Astrophysics Data System (ADS)
Lee, Han Sang; Kim, Hyeun A.; Kim, Hyeonjin; Hong, Helen; Yoon, Young Cheol; Kim, Junmo
2016-03-01
In spite of its clinical importance in diagnosis of osteoarthritis, segmentation of cartilage in knee MRI remains a challenging task due to its shape variability and low contrast with surrounding soft tissues and synovial fluid. In this paper, we propose a multi-atlas segmentation of cartilage in knee MRI with sequential atlas registrations and locallyweighted voting (LWV). First, bone is segmented by sequential volume- and object-based registrations and LWV. Second, to overcome the shape variability of cartilage, cartilage is segmented by bone-mask-based registration and LWV. In experiments, the proposed method improved the bone segmentation by reducing misclassified bone region, and enhanced the cartilage segmentation by preventing cartilage leakage into surrounding similar intensity region, with the help of sequential registrations and LWV.
Mitochondrial redox and pH signaling occurs in axonal and synaptic organelle clusters.
Breckwoldt, Michael O; Armoundas, Antonis A; Aon, Miguel A; Bendszus, Martin; O'Rourke, Brian; Schwarzländer, Markus; Dick, Tobias P; Kurz, Felix T
2016-03-22
Redox switches are important mediators in neoplastic, cardiovascular and neurological disorders. We recently identified spontaneous redox signals in neurons at the single mitochondrion level where transients of glutathione oxidation go along with shortening and re-elongation of the organelle. We now have developed advanced image and signal-processing methods to re-assess and extend previously obtained data. Here we analyze redox and pH signals of entire mitochondrial populations. In total, we quantified the effects of 628 redox and pH events in 1797 mitochondria from intercostal axons and neuromuscular synapses using optical sensors (mito-Grx1-roGFP2; mito-SypHer). We show that neuronal mitochondria can undergo multiple redox cycles exhibiting markedly different signal characteristics compared to single redox events. Redox and pH events occur more often in mitochondrial clusters (medium cluster size: 34.1 ± 4.8 μm(2)). Local clusters possess higher mitochondrial densities than the rest of the axon, suggesting morphological and functional inter-mitochondrial coupling. We find that cluster formation is redox sensitive and can be blocked by the antioxidant MitoQ. In a nerve crush paradigm, mitochondrial clusters form sequentially adjacent to the lesion site and oxidation spreads between mitochondria. Our methodology combines optical bioenergetics and advanced signal processing and allows quantitative assessment of entire mitochondrial populations.
Efficiency of parallel direct optimization
NASA Technical Reports Server (NTRS)
Janies, D. A.; Wheeler, W. C.
2001-01-01
Tremendous progress has been made at the level of sequential computation in phylogenetics. However, little attention has been paid to parallel computation. Parallel computing is particularly suited to phylogenetics because of the many ways large computational problems can be broken into parts that can be analyzed concurrently. In this paper, we investigate the scaling factors and efficiency of random addition and tree refinement strategies using the direct optimization software, POY, on a small (10 slave processors) and a large (256 slave processors) cluster of networked PCs running LINUX. These algorithms were tested on several data sets composed of DNA and morphology ranging from 40 to 500 taxa. Various algorithms in POY show fundamentally different properties within and between clusters. All algorithms are efficient on the small cluster for the 40-taxon data set. On the large cluster, multibuilding exhibits excellent parallel efficiency, whereas parallel building is inefficient. These results are independent of data set size. Branch swapping in parallel shows excellent speed-up for 16 slave processors on the large cluster. However, there is no appreciable speed-up for branch swapping with the further addition of slave processors (>16). This result is independent of data set size. Ratcheting in parallel is efficient with the addition of up to 32 processors in the large cluster. This result is independent of data set size. c2001 The Willi Hennig Society.
NASA Astrophysics Data System (ADS)
Zhang, Xiaoli; Zou, Jie; Le, Daniel X.; Thoma, George
2010-01-01
"Investigator Names" is a newly required field in MEDLINE citations. It consists of personal names listed as members of corporate organizations in an article. Extracting investigator names automatically is necessary because of the increasing volume of articles reporting collaborative biomedical research in which a large number of investigators participate. In this paper, we present an SVM-based stacked sequential learning method in a novel application - recognizing named entities such as the first and last names of investigators from online medical journal articles. Stacked sequential learning is a meta-learning algorithm which can boost any base learner. It exploits contextual information by adding the predicted labels of the surrounding tokens as features. We apply this method to tag words in text paragraphs containing investigator names, and demonstrate that stacked sequential learning improves the performance of a nonsequential base learner such as an SVM classifier.
Fragmentation pathways of tungsten hexacarbonyl clusters upon electron ionization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Neustetter, M.; Jabbour Al Maalouf, E.; Denifl, S., E-mail: Stephan.Denifl@uibk.ac.at, E-mail: plimaovieira@fct.unl.pt
2016-08-07
Electron ionization of neat tungsten hexacarbonyl (W(CO){sub 6}) clusters has been investigated in a crossed electron-molecular beam experiment coupled with a mass spectrometer system. The molecule is used for nanofabrication processes through electron beam induced deposition and ion beam induced deposition techniques. Positive ion mass spectra of W(CO){sub 6} clusters formed by electron ionization at 70 eV contain the ion series of the type W(CO){sub n}{sup +} (0 ≤ n ≤ 6) and W{sub 2}(CO){sub n}{sup +} (0 ≤ n ≤ 12). In addition, a series of peaks are observed and have been assigned to WC(CO){sub n}{sup +} (0 ≤more » n ≤ 3) and W{sub 2}C(CO){sub n}{sup +} (0 ≤ n ≤ 10). A distinct change of relative fragment ion intensity can be observed for clusters compared to the single molecule. The characteristic fragmentation pattern obtained in the mass spectra can be explained by a sequential decay of the ionized organometallic, which is also supported by the study of the clusters when embedded in helium nanodroplets. In addition, appearance energies for the dissociative ionization channels for singly charged ions have been estimated from experimental ion efficiency curves.« less
NASA Astrophysics Data System (ADS)
Sarparandeh, Mohammadali; Hezarkhani, Ardeshir
2017-12-01
The use of efficient methods for data processing has always been of interest to researchers in the field of earth sciences. Pattern recognition techniques are appropriate methods for high-dimensional data such as geochemical data. Evaluation of the geochemical distribution of rare earth elements (REEs) requires the use of such methods. In particular, the multivariate nature of REE data makes them a good target for numerical analysis. The main subject of this paper is application of unsupervised pattern recognition approaches in evaluating geochemical distribution of REEs in the Kiruna type magnetite-apatite deposit of Se-Chahun. For this purpose, 42 bulk lithology samples were collected from the Se-Chahun iron ore deposit. In this study, 14 rare earth elements were measured with inductively coupled plasma mass spectrometry (ICP-MS). Pattern recognition makes it possible to evaluate the relations between the samples based on all these 14 features, simultaneously. In addition to providing easy solutions, discovery of the hidden information and relations of data samples is the advantage of these methods. Therefore, four clustering methods (unsupervised pattern recognition) - including a modified basic sequential algorithmic scheme (MBSAS), hierarchical (agglomerative) clustering, k-means clustering and self-organizing map (SOM) - were applied and results were evaluated using the silhouette criterion. Samples were clustered in four types. Finally, the results of this study were validated with geological facts and analysis results from, for example, scanning electron microscopy (SEM), X-ray diffraction (XRD), ICP-MS and optical mineralogy. The results of the k-means clustering and SOM methods have the best matches with reality, with experimental studies of samples and with field surveys. Since only the rare earth elements are used in this division, a good agreement of the results with lithology is considerable. It is concluded that the combination of the proposed methods and geological studies leads to finding some hidden information, and this approach has the best results compared to using only one of them.
Cloud-based Predictive Modeling System and its Application to Asthma Readmission Prediction
Chen, Robert; Su, Hang; Khalilia, Mohammed; Lin, Sizhe; Peng, Yue; Davis, Tod; Hirsh, Daniel A; Searles, Elizabeth; Tejedor-Sojo, Javier; Thompson, Michael; Sun, Jimeng
2015-01-01
The predictive modeling process is time consuming and requires clinical researchers to handle complex electronic health record (EHR) data in restricted computational environments. To address this problem, we implemented a cloud-based predictive modeling system via a hybrid setup combining a secure private server with the Amazon Web Services (AWS) Elastic MapReduce platform. EHR data is preprocessed on a private server and the resulting de-identified event sequences are hosted on AWS. Based on user-specified modeling configurations, an on-demand web service launches a cluster of Elastic Compute 2 (EC2) instances on AWS to perform feature selection and classification algorithms in a distributed fashion. Afterwards, the secure private server aggregates results and displays them via interactive visualization. We tested the system on a pediatric asthma readmission task on a de-identified EHR dataset of 2,967 patients. We conduct a larger scale experiment on the CMS Linkable 2008–2010 Medicare Data Entrepreneurs’ Synthetic Public Use File dataset of 2 million patients, which achieves over 25-fold speedup compared to sequential execution. PMID:26958172
Trial Sequential Methods for Meta-Analysis
ERIC Educational Resources Information Center
Kulinskaya, Elena; Wood, John
2014-01-01
Statistical methods for sequential meta-analysis have applications also for the design of new trials. Existing methods are based on group sequential methods developed for single trials and start with the calculation of a required information size. This works satisfactorily within the framework of fixed effects meta-analysis, but conceptual…
Treatment of mites folliculitis with an ornidazole-based sequential therapy: A randomized trial.
Luo, Yang; Sun, Yu-Jiao; Zhang, Li; Luan, Xiu-Li
2016-07-01
Treatment of Demodex infestations is often inadequate and associated with low effective rate. We sought to evaluate the efficacy of an ornidazole-based sequential therapy for mites folliculitis treatment. Two-hundred patients with mites folliculitis were sequentially treated with either an ornidazole- or metronidazole-based regimen. Sebum cutaneum was extruded from the sebaceous glands of each patient's nose and the presence of Demodex mites were examined by light microscopy. The clinical manifestations of relapse of mites folliculitis were recorded and the subjects were followed up at 2, 4, 8, and 12 weeks post-treatment. Patients treated with the ornidazole-based regimen showed an overall effective rate of 94.0%. Additionally, at the 2, 4, 8, and 12-week follow-up, these patients had significantly lower rates of Demodex mite relapse and new lesion occurrence compared with patients treated with the metronidazole-based regimen (P < 0.05). Sequential therapy using ornidazole, betamethasone, and recombinant bovine basic fibroblast growth factor (rbFGF) gel is highly effective for treating mites folliculitis.
NASA Astrophysics Data System (ADS)
Fienen, M. N.; Bradbury, K. R.; Kniffin, M.; Barlow, P. M.; Krause, J.; Westenbroek, S.; Leaf, A.
2015-12-01
The well-drained sandy soil in the Wisconsin Central Sands is ideal for growing potatoes, corn, and other vegetables. A shallow sand and gravel aquifer provides abundant water for agricultural irrigation but also supplies critical base flow to cold-water trout streams. These needs compete with one another, and stakeholders from various perspectives are collaborating to seek solutions. Stakeholders were engaged in providing and verifying data to guide construction of a groundwater flow model which was used with linear and sequential linear programming to evaluate optimal tradeoffs between agricultural pumping and ecologically based minimum base flow values. The connection between individual irrigation wells as well as industrial and municipal supply and streamflow depletion can be evaluated using the model. Rather than addressing 1000s of wells individually, a variety of well management groups were established through k-means clustering. These groups are based on location, potential impact, water-use categories, depletion potential, and other factors. Through optimization, pumping rates were reduced to attain mandated minimum base flows. This formalization enables exploration of possible solutions for the stakeholders, and provides a tool which is transparent and forms a basis for discussion and negotiation.
NASA Astrophysics Data System (ADS)
Marco, Amparo; Negueruela, Ignacio
2016-06-01
We study the area around the H II region Sh 2-234, including the young open cluster Stock 8, to investigate the extent and definition of the association Aur OB2 and the possible role of triggering in massive cluster formation. We obtained Strömgren and J, H, KS photometry for Stock 8 and Strömgren photometry for two other cluster candidates in the area, which we confirm as young open clusters and name Alicante 11 and Alicante 12. We took spectroscopy of ˜33 early-type stars in the area, including the brightest cluster members. We calculate a common distance of 2.80^{+0.27}_{-0.24} kpc for the three open clusters and surrounding association. We derive an age 4-6 Ma for Stock 8, and do not find a significantly different age for the other clusters or the association. The star LS V +34°23, with spectral type O8 II(f), is likely the main source of ionization of Sh 2-234. We observe an important population of pre-main-sequence stars, some of them with discs, associated with the B-type members lying on the main sequence. We interpret the region as an area of recent star formation with some residual and very localized ongoing star formation. We do not find evidence for sequential star formation on a large scale. The classical definition of Aur OB2 has to be reconsidered, because its two main open clusters, Stock 8 and NGC 1893, are not at the same distance. Stock 8 is probably located in the Perseus arm, but other nearby H II regions whose distances also place them in this arm show quite different distances and radial velocities and, therefore, are not connected.
Savoca, Marco; Lagutschenkov, Anita; Langer, Judith; Harding, Dan J; Fielicke, André; Dopfer, Otto
2013-02-14
Vibrational spectra of mixed silicon carbide clusters Si(m)C(n) with m + n = 6 in the gas phase are obtained by resonant infrared-vacuum-ultraviolet two-color ionization (IR-UV2CI for n ≤ 2) and density functional theory (DFT) calculations. Si(m)C(n) clusters are produced in a laser vaporization source, in which the silicon plasma reacts with methane. Subsequently, they are irradiated with tunable IR light from an IR free electron laser before they are ionized with UV photons from an F(2) laser. Resonant absorption of one or more IR photons leads to an enhanced ionization efficiency for Si(m)C(n) and provides the size-specific IR spectra. IR spectra measured for Si(6), Si(5)C, and Si(4)C(2) are assigned to their most stable isomers by comparison with calculated linear absorption spectra. The preferred Si(m)C(n) structures with m + n = 6 illustrate the systematic transition from chain-like geometries for bare C(6) to three-dimensional structures for bare Si(6). In contrast to bulk SiC, carbon atom segregation is observed already for the smallest n (n = 2).
Helix-packing motifs in membrane proteins.
Walters, R F S; DeGrado, W F
2006-09-12
The fold of a helical membrane protein is largely determined by interactions between membrane-imbedded helices. To elucidate recurring helix-helix interaction motifs, we dissected the crystallographic structures of membrane proteins into a library of interacting helical pairs. The pairs were clustered according to their three-dimensional similarity (rmsd =1.5 A), allowing 90% of the library to be assigned to clusters consisting of at least five members. Surprisingly, three quarters of the helical pairs belong to one of five tightly clustered motifs whose structural features can be understood in terms of simple principles of helix-helix packing. Thus, the universe of common transmembrane helix-pairing motifs is relatively simple. The largest cluster, which comprises 29% of the library members, consists of an antiparallel motif with left-handed packing angles, and it is frequently stabilized by packing of small side chains occurring every seven residues in the sequence. Right-handed parallel and antiparallel structures show a similar tendency to segregate small residues to the helix-helix interface but spaced at four-residue intervals. Position-specific sequence propensities were derived for the most populated motifs. These structural and sequential motifs should be quite useful for the design and structural prediction of membrane proteins.
A sampling and classification item selection approach with content balancing.
Chen, Pei-Hua
2015-03-01
Existing automated test assembly methods typically employ constrained combinatorial optimization. Constructing forms sequentially based on an optimization approach usually results in unparallel forms and requires heuristic modifications. Methods based on a random search approach have the major advantage of producing parallel forms sequentially without further adjustment. This study incorporated a flexible content-balancing element into the statistical perspective item selection method of the cell-only method (Chen et al. in Educational and Psychological Measurement, 72(6), 933-953, 2012). The new method was compared with a sequential interitem distance weighted deviation model (IID WDM) (Swanson & Stocking in Applied Psychological Measurement, 17(2), 151-166, 1993), a simultaneous IID WDM, and a big-shadow-test mixed integer programming (BST MIP) method to construct multiple parallel forms based on matching a reference form item-by-item. The results showed that the cell-only method with content balancing and the sequential and simultaneous versions of IID WDM yielded results comparable to those obtained using the BST MIP method. The cell-only method with content balancing is computationally less intensive than the sequential and simultaneous versions of IID WDM.
Meissner, Christian A; Tredoux, Colin G; Parker, Janat F; MacLin, Otto H
2005-07-01
Many eyewitness researchers have argued for the application of a sequential alternative to the traditional simultaneous lineup, given its role in decreasing false identifications of innocent suspects (sequential superiority effect). However, Ebbesen and Flowe (2002) have recently noted that sequential lineups may merely bring about a shift in response criterion, having no effect on discrimination accuracy. We explored this claim, using a method that allows signal detection theory measures to be collected from eyewitnesses. In three experiments, lineup type was factorially combined with conditions expected to influence response criterion and/or discrimination accuracy. Results were consistent with signal detection theory predictions, including that of a conservative criterion shift with the sequential presentation of lineups. In a fourth experiment, we explored the phenomenological basis for the criterion shift, using the remember-know-guess procedure. In accord with previous research, the criterion shift in sequential lineups was associated with a reduction in familiarity-based responding. It is proposed that the relative similarity between lineup members may create a context in which fluency-based processing is facilitated to a greater extent when lineup members are presented simultaneously.
NASA Astrophysics Data System (ADS)
Felder, Thomas; Gambogi, William; Stika, Katherine; Yu, Bao-Ling; Bradley, Alex; Hu, Hongjie; Garreau-Iles, Lucie; Trout, T. John
2016-09-01
DuPont has been working steadily to develop accelerated backsheet tests that correlate with solar panels observations in the field. This report updates efforts in sequential testing. Single exposure tests are more commonly used and can be completed more quickly, and certain tests provide helpful predictions of certain backsheet failure modes. DuPont recommendations for single exposure tests are based on 25-year exposure levels for UV and humidity/temperature, and form a good basis for sequential test development. We recommend a sequential exposure of damp heat followed by UV then repetitions of thermal cycling and UVA. This sequence preserves 25-year exposure levels for humidity/temperature and UV, and correlates well with a large body of field observations. Measurements can be taken at intervals in the test, although the full test runs 10 months. A second, shorter sequential test based on damp heat and thermal cycling tests mechanical durability and correlates with loss of mechanical properties seen in the field. Ongoing work is directed toward shorter sequential tests that preserve good correlation to field data.
NASA Astrophysics Data System (ADS)
Borglin, Johan; Guldbrand, Stina; Evenbratt, Hanne; Kirejev, Vladimir; Grönbeck, Henrik; Ericson, Marica B.
2015-12-01
Gold nanoparticles can be visualized in far-field multiphoton laser-scanning microscopy (MPM) based on the phenomena of multiphoton induced luminescence (MIL). This is of interest for biomedical applications, e.g., for cancer diagnostics, as MPM allows for working in the near-infrared (NIR) optical window of tissue. It is well known that the aggregation of particles causes a redshift of the plasmon resonance, but its implications for MIL applying far-field MPM should be further exploited. Here, we explore MIL from 10 nm gold nanospheres that are chemically deposited on glass substrates in controlled coverage gradients using MPM operating in NIR range. The substrates enable studies of MIL as a function of inter-particle distance and clustering. It was shown that MIL was only detected from areas on the substrates where the particle spacing was less than one particle diameter, or where the particles have aggregated. The results are interpreted in the context that the underlying physical phenomenon of MIL is a sequential two-photon absorption process, where the first event is driven by the plasmon resonance. It is evident that gold nanospheres in this size range have to be closely spaced or clustered to exhibit detectable MIL using far-field MPM operating in the NIR region.
Finding Statistically Significant Communities in Networks
Lancichinetti, Andrea; Radicchi, Filippo; Ramasco, José J.; Fortunato, Santo
2011-01-01
Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types of datasets and the subtleties of community structure. In this paper we present OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics. It is based on the local optimization of a fitness function expressing the statistical significance of clusters with respect to random fluctuations, which is estimated with tools of Extreme and Order Statistics. OSLOM can be used alone or as a refinement procedure of partitions/covers delivered by other techniques. We have also implemented sequential algorithms combining OSLOM with other fast techniques, so that the community structure of very large networks can be uncovered. Our method has a comparable performance as the best existing algorithms on artificial benchmark graphs. Several applications on real networks are shown as well. OSLOM is implemented in a freely available software (http://www.oslom.org), and we believe it will be a valuable tool in the analysis of networks. PMID:21559480
DOE Office of Scientific and Technical Information (OSTI.GOV)
Borglin, Johan; Department of Physics, University of Gothenburg, Kemivägen 10, 412 96 Gothenburg; Guldbrand, Stina
Gold nanoparticles can be visualized in far-field multiphoton laser-scanning microscopy (MPM) based on the phenomena of multiphoton induced luminescence (MIL). This is of interest for biomedical applications, e.g., for cancer diagnostics, as MPM allows for working in the near-infrared (NIR) optical window of tissue. It is well known that the aggregation of particles causes a redshift of the plasmon resonance, but its implications for MIL applying far-field MPM should be further exploited. Here, we explore MIL from 10 nm gold nanospheres that are chemically deposited on glass substrates in controlled coverage gradients using MPM operating in NIR range. The substrates enablemore » studies of MIL as a function of inter-particle distance and clustering. It was shown that MIL was only detected from areas on the substrates where the particle spacing was less than one particle diameter, or where the particles have aggregated. The results are interpreted in the context that the underlying physical phenomenon of MIL is a sequential two-photon absorption process, where the first event is driven by the plasmon resonance. It is evident that gold nanospheres in this size range have to be closely spaced or clustered to exhibit detectable MIL using far-field MPM operating in the NIR region.« less
Sequential and simultaneous SLAR block adjustment. [spline function analysis for mapping
NASA Technical Reports Server (NTRS)
Leberl, F.
1975-01-01
Two sequential methods of planimetric SLAR (Side Looking Airborne Radar) block adjustment, with and without splines, and three simultaneous methods based on the principles of least squares are evaluated. A limited experiment with simulated SLAR images indicates that sequential block formation with splines followed by external interpolative adjustment is superior to the simultaneous methods such as planimetric block adjustment with similarity transformations. The use of the sequential block formation is recommended, since it represents an inexpensive tool for satisfactory point determination from SLAR images.
Koning, Ina M; Maric, Marija; MacKinnon, David; Vollebergh, Wilma A M
2015-08-01
Previous work revealed that the combined parent-student alcohol prevention program (PAS) effectively postponed alcohol initiation through its hypothesized intermediate factors: increase in strict parental rule setting and adolescents' self-control (Koning, van den Eijnden, Verdurmen, Engels, & Vollebergh, 2011). This study examines whether the parental strictness precedes an increase in adolescents' self-control by testing a sequential mediation model. A cluster randomized trial including 3,245 Dutch early adolescents (M age = 12.68, SD = 0.50) and their parents randomized over 4 conditions: (1) parent intervention, (2) student intervention, (3) combined intervention, and (4) control group. Outcome measure was amount of weekly drinking measured at age 12 to 15; baseline assessment (T0) and 3 follow-up assessments (T1-T3). Main effects of the combined and parent intervention on weekly drinking at T3 were found. The effect of the combined intervention on weekly drinking (T3) was mediated via an increase in strict rule setting (T1) and adolescents' subsequent self-control (T2). In addition, the indirect effect of the combined intervention via rule setting (T1) was significant. No reciprocal sequential mediation (self-control at T1 prior to rules at T2) was found. The current study is 1 of the few studies reporting sequential mediation effects of youth intervention outcomes. It underscores the need of involving parents in youth alcohol prevention programs, and the need to target both parents and adolescents, so that change in parents' behavior enables change in their offspring. (c) 2015 APA, all rights reserved).
Hybrid Computerized Adaptive Testing: From Group Sequential Design to Fully Sequential Design
ERIC Educational Resources Information Center
Wang, Shiyu; Lin, Haiyan; Chang, Hua-Hua; Douglas, Jeff
2016-01-01
Computerized adaptive testing (CAT) and multistage testing (MST) have become two of the most popular modes in large-scale computer-based sequential testing. Though most designs of CAT and MST exhibit strength and weakness in recent large-scale implementations, there is no simple answer to the question of which design is better because different…
ERIC Educational Resources Information Center
Willson, Victor L.; And Others
1985-01-01
Presents results of confirmatory factor analysis of the Kaufman Assessment Battery for children which is based on the underlying theoretical model of sequential, simultaneous, and achievement factors. Found support for the two-factor, simultaneous and sequential processing model. (MCF)
Appraisal of jump distributions in ensemble-based sampling algorithms
NASA Astrophysics Data System (ADS)
Dejanic, Sanda; Scheidegger, Andreas; Rieckermann, Jörg; Albert, Carlo
2017-04-01
Sampling Bayesian posteriors of model parameters is often required for making model-based probabilistic predictions. For complex environmental models, standard Monte Carlo Markov Chain (MCMC) methods are often infeasible because they require too many sequential model runs. Therefore, we focused on ensemble methods that use many Markov chains in parallel, since they can be run on modern cluster architectures. Little is known about how to choose the best performing sampler, for a given application. A poor choice can lead to an inappropriate representation of posterior knowledge. We assessed two different jump moves, the stretch and the differential evolution move, underlying, respectively, the software packages EMCEE and DREAM, which are popular in different scientific communities. For the assessment, we used analytical posteriors with features as they often occur in real posteriors, namely high dimensionality, strong non-linear correlations or multimodality. For posteriors with non-linear features, standard convergence diagnostics based on sample means can be insufficient. Therefore, we resorted to an entropy-based convergence measure. We assessed the samplers by means of their convergence speed, robustness and effective sample sizes. For posteriors with strongly non-linear features, we found that the stretch move outperforms the differential evolution move, w.r.t. all three aspects.
NASA Astrophysics Data System (ADS)
Nugroho, P.
2018-02-01
Creative industries existence is inseparable from the underlying social construct which provides sources for creativity and innovation. The working of social capital in a society facilitates information exchange, knowledge transfer and technology acquisition within the industry through social networks. As a result, a socio-spatial divide exists in directing the growth of the creative industries. This paper aims to examine how such a socio-spatial divide contributes to the local creative industry development in Semarang and Kudus batik clusters. Explanatory sequential mixed methods approach covering a quantitative approach followed by a qualitative approach is chosen to understand better the interplay between tangible and intangible variables in the local batik clusters. Surveys on secondary data taken from the government statistics and reports, previous studies, and media exposures are completed in the former approach to identify clustering pattern of the local batik industry and the local embeddedness factors which have shaped the existing business environment. In-depth interviews, content analysis, and field observations are engaged in the latter approach to explore reciprocal relationships between the elements of social capital and the local batik cluster development. The result demonstrates that particular social ties have determined the forms of spatial proximity manifested in forward and backward business linkages. Trust, shared norms, and inherited traditions are the key social capital attributes that lead to such a socio-spatial divide. Therefore, the intermediating roles of the bridging actors are necessary to encouraging cooperation among the participating stakeholders for a better cluster development.
Treatment of mites folliculitis with an ornidazole-based sequential therapy
Luo, Yang; Sun, Yu-Jiao; Zhang, Li; Luan, Xiu-Li
2016-01-01
Abstract Objective: Treatment of Demodex infestations is often inadequate and associated with low effective rate. We sought to evaluate the efficacy of an ornidazole-based sequential therapy for mites folliculitis treatment. Methods: Two-hundred patients with mites folliculitis were sequentially treated with either an ornidazole- or metronidazole-based regimen. Sebum cutaneum was extruded from the sebaceous glands of each patient's nose and the presence of Demodex mites were examined by light microscopy. The clinical manifestations of relapse of mites folliculitis were recorded and the subjects were followed up at 2, 4, 8, and 12 weeks post-treatment. Results: Patients treated with the ornidazole-based regimen showed an overall effective rate of 94.0%. Additionally, at the 2, 4, 8, and 12-week follow-up, these patients had significantly lower rates of Demodex mite relapse and new lesion occurrence compared with patients treated with the metronidazole-based regimen (P < 0.05). Conclusion: Sequential therapy using ornidazole, betamethasone, and recombinant bovine basic fibroblast growth factor (rbFGF) gel is highly effective for treating mites folliculitis. PMID:27399141
Jarvik, Jeffrey G.; Comstock, Bryan A.; James, Kathryn T.; Avins, Andrew L.; Bresnahan, Brian W.; Deyo, Richard A.; Luetmer, Patrick H.; Friedly, Janna L.; Meier, Eric N.; Cherkin, Daniel C.; Gold, Laura S.; Rundell, Sean D.; Halabi, Safwan S.; Kallmes, David F.; Tan, Katherine W.; Turner, Judith A.; Kessler, Larry G.; Lavallee, Danielle C.; Stephens, Kari A.; Heagerty, Patrick J.
2015-01-01
Background Diagnostic imaging is often the first step in evaluating patients with back pain and likely functions as a “gateway” to a subsequent cascade of interventions. However, lumbar spine imaging frequently reveals incidental findings among normal, pain-free individuals suggesting that treatment of these “abnormalities” may not be warranted. Our prior work suggested that inserting the prevalence of imaging findings in patients without back pain into spine imaging reports may reduce subsequent interventions. We are now conducting a pragmatic cluster randomized clinical trial to test the hypothesis that inserting this prevalence data into lumbar spine imaging reports for studies ordered by primary care providers will reduce subsequent spine-related interventions. Methods/Design We are using a stepped wedge design that sequentially randomizes 100 primary care clinics at four health systems to receive either standard lumbar spine imaging reports, or reports containing prevalence data for common imaging findings in patients without back pain. We capture all outcomes passively through the electronic medical record. Our primary outcome is spine-related intervention intensity based on Relative Value Units (RVUs) during the following year. Secondary outcomes include subsequent prescriptions for opioid analgesics and cross-sectional lumbar spine re-imaging. Discussion If our study shows that adding prevalence data to spine imaging reports decreases subsequent back-related RVUs, this intervention could be easily generalized and applied to other kinds of testing, as well as other conditions where incidental findings may be common. Our study also serves as a model for cluster randomized trials that are minimal risk and highly pragmatic. PMID:26493088
Computerized Classification Testing with the Rasch Model
ERIC Educational Resources Information Center
Eggen, Theo J. H. M.
2011-01-01
If classification in a limited number of categories is the purpose of testing, computerized adaptive tests (CATs) with algorithms based on sequential statistical testing perform better than estimation-based CATs (e.g., Eggen & Straetmans, 2000). In these computerized classification tests (CCTs), the Sequential Probability Ratio Test (SPRT) (Wald,…
2013-08-01
in Sequential Design Optimization with Concurrent Calibration-Based Model Validation Dorin Drignei 1 Mathematics and Statistics Department...Validation 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Dorin Drignei; Zissimos Mourelatos; Vijitashwa Pandey
Introducing a Model for Optimal Design of Sequential Objective Structured Clinical Examinations
ERIC Educational Resources Information Center
Mortaz Hejri, Sara; Yazdani, Kamran; Labaf, Ali; Norcini, John J.; Jalili, Mohammad
2016-01-01
In a sequential OSCE which has been suggested to reduce testing costs, candidates take a short screening test and who fail the test, are asked to take the full OSCE. In order to introduce an effective and accurate sequential design, we developed a model for designing and evaluating screening OSCEs. Based on two datasets from a 10-station…
Gul, Sheraz; Desmond Ng, Jia Wei; Alonso-Mori, Roberto; Kern, Jan; Sokaras, Dimosthenis; Anzenberg, Eitan; Lassalle-Kaiser, Benedikt; Gorlin, Yelena; Weng, Tsu-Chien; Zwart, Petrus H.; Zhang, Jin Z.; Bergmann, Uwe; Yachandra, Vittal K.; Jaramillo, Thomas F.; Yano, Junko
2015-01-01
Multielectron catalytic reactions, such as water oxidation, nitrogen reduction, or hydrogen production in enzymes and inorganic catalysts often involve multimetallic clusters. In these systems, the reaction takes place between metals or metals and ligands to facilitate charge transfer, bond formation/breaking, substrate binding, and release of products. In this study, we present a method to detect X-ray emission signals from multiple elements simultaneously, which allows for the study of charge transfer and the sequential chemistry occurring between elements. Kβ X-ray emission spectroscopy (XES) probes charge and spin states of metals as well as their ligand environment. A wavelength-dispersive spectrometer based on the von Hamos geometry was used to disperse Kβ signals of multiple elements onto a position detector, enabling an XES spectrum to be measured in a single-shot mode. This overcomes the scanning needs of the scanning spectrometers, providing data free from temporal and normalization errors and therefore ideal to follow sequential chemistry at multiple sites. We have applied this method to study MnOx-based bifunctional electrocatalysts for the oxygen evolution reaction (OER) and the oxygen reduction reaction (ORR). In particular, we investigated the effects of adding a secondary element, Ni, to form MnNiOx and its impact on the chemical states and catalytic activity, by tracking the redox characteristics of each element upon sweeping the electrode potential. The detection scheme we describe here is general and can be applied to time-resolved studies of materials consisting of multiple elements, to follow the dynamics of catalytic and electron transfer reactions. PMID:25747045
Gul, Sheraz; Ng, Jia Wei Desmond; Alonso-Mori, Roberto; Kern, Jan; Sokaras, Dimosthenis; Anzenberg, Eitan; Lassalle-Kaiser, Benedikt; Gorlin, Yelena; Weng, Tsu-Chien; Zwart, Petrus H; Zhang, Jin Z; Bergmann, Uwe; Yachandra, Vittal K; Jaramillo, Thomas F; Yano, Junko
2015-04-14
Multielectron catalytic reactions, such as water oxidation, nitrogen reduction, or hydrogen production in enzymes and inorganic catalysts often involve multimetallic clusters. In these systems, the reaction takes place between metals or metals and ligands to facilitate charge transfer, bond formation/breaking, substrate binding, and release of products. In this study, we present a method to detect X-ray emission signals from multiple elements simultaneously, which allows for the study of charge transfer and the sequential chemistry occurring between elements. Kβ X-ray emission spectroscopy (XES) probes charge and spin states of metals as well as their ligand environment. A wavelength-dispersive spectrometer based on the von Hamos geometry was used to disperse Kβ signals of multiple elements onto a position detector, enabling an XES spectrum to be measured in a single-shot mode. This overcomes the scanning needs of the scanning spectrometers, providing data free from temporal and normalization errors and therefore ideal to follow sequential chemistry at multiple sites. We have applied this method to study MnOx-based bifunctional electrocatalysts for the oxygen evolution reaction (OER) and the oxygen reduction reaction (ORR). In particular, we investigated the effects of adding a secondary element, Ni, to form MnNiOx and its impact on the chemical states and catalytic activity, by tracking the redox characteristics of each element upon sweeping the electrode potential. The detection scheme we describe here is general and can be applied to time-resolved studies of materials consisting of multiple elements, to follow the dynamics of catalytic and electron transfer reactions.
Gul, Sheraz; Ng, Jia Wei Desmond; Alonso-Mori, Roberto; ...
2015-02-25
Multielectron catalytic reactions, such as water oxidation, nitrogen reduction, or hydrogen production in enzymes and inorganic catalysts often involve multimetallic clusters. In these systems, the reaction takes place between metals or metals and ligands to facilitate charge transfer, bond formation/breaking, substrate binding, and release of products. In this study, we present a method to detect X-ray emission signals from multiple elements simultaneously, which allows for the study of charge transfer and the sequential chemistry occurring between elements. Kβ X-ray emission spectroscopy (XES) probes charge and spin states of metals as well as their ligand environment. A wavelength-dispersive spectrometer based onmore » the von Hamos geometry was used to disperse Kβ signals of multiple elements onto a position detector, enabling an XES spectrum to be measured in a single-shot mode. This overcomes the scanning needs of the scanning spectrometers, providing data free from temporal and normalization errors and therefore ideal to follow sequential chemistry at multiple sites. We have applied this method to study MnOx-based bifunctional electrocatalysts for the oxygen evolution reaction (OER) and the oxygen reduction reaction (ORR). In particular, we investigated the effects of adding a secondary element, Ni, to form MnNiOx and its impact on the chemical states and catalytic activity, by tracking the redox characteristics of each element upon sweeping the electrode potential. In conclusion, the detection scheme we describe here is general and can be applied to time-resolved studies of materials consisting of multiple elements, to follow the dynamics of catalytic and electron transfer reactions.« less
Antigenic Patterns and Evolution of the Human Influenza A (H1N1) Virus
Liu, Mi; Zhao, Xiang; Hua, Sha; Du, Xiangjun; Peng, Yousong; Li, Xiyan; Lan, Yu; Wang, Dayan; Wu, Aiping; Shu, Yuelong; Jiang, Taijiao
2015-01-01
The influenza A (H1N1) virus causes seasonal epidemics that result in severe illnesses and deaths almost every year. A deep understanding of the antigenic patterns and evolution of human influenza A (H1N1) virus is extremely important for its effective surveillance and prevention. Through development of antigenicity inference method for human influenza A (H1N1), named PREDAC-H1, we systematically mapped the antigenic patterns and evolution of the human influenza A (H1N1) virus. Eight dominant antigenic clusters have been inferred for seasonal H1N1 viruses since 1977, which demonstrated sequential replacements over time with a similar pattern in Asia, Europe and North America. Among them, six clusters emerged first in Asia. As for China, three of the eight antigenic clusters were detected in South China earlier than in North China, indicating the leading role of South China in H1N1 transmission. The comprehensive view of the antigenic evolution of human influenza A (H1N1) virus can help formulate better strategy for its prevention and control. PMID:26412348
Antigenic Patterns and Evolution of the Human Influenza A (H1N1) Virus.
Liu, Mi; Zhao, Xiang; Hua, Sha; Du, Xiangjun; Peng, Yousong; Li, Xiyan; Lan, Yu; Wang, Dayan; Wu, Aiping; Shu, Yuelong; Jiang, Taijiao
2015-09-28
The influenza A (H1N1) virus causes seasonal epidemics that result in severe illnesses and deaths almost every year. A deep understanding of the antigenic patterns and evolution of human influenza A (H1N1) virus is extremely important for its effective surveillance and prevention. Through development of antigenicity inference method for human influenza A (H1N1), named PREDAC-H1, we systematically mapped the antigenic patterns and evolution of the human influenza A (H1N1) virus. Eight dominant antigenic clusters have been inferred for seasonal H1N1 viruses since 1977, which demonstrated sequential replacements over time with a similar pattern in Asia, Europe and North America. Among them, six clusters emerged first in Asia. As for China, three of the eight antigenic clusters were detected in South China earlier than in North China, indicating the leading role of South China in H1N1 transmission. The comprehensive view of the antigenic evolution of human influenza A (H1N1) virus can help formulate better strategy for its prevention and control.
A comparison of SuperLU solvers on the intel MIC architecture
NASA Astrophysics Data System (ADS)
Tuncel, Mehmet; Duran, Ahmet; Celebi, M. Serdar; Akaydin, Bora; Topkaya, Figen O.
2016-10-01
In many science and engineering applications, problems may result in solving a sparse linear system AX=B. For example, SuperLU_MCDT, a linear solver, was used for the large penta-diagonal matrices for 2D problems and hepta-diagonal matrices for 3D problems, coming from the incompressible blood flow simulation (see [1]). It is important to test the status and potential improvements of state-of-the-art solvers on new technologies. In this work, sequential, multithreaded and distributed versions of SuperLU solvers (see [2]) are examined on the Intel Xeon Phi coprocessors using offload programming model at the EURORA cluster of CINECA in Italy. We consider a portfolio of test matrices containing patterned matrices from UFMM ([3]) and randomly located matrices. This architecture can benefit from high parallelism and large vectors. We find that the sequential SuperLU benefited up to 45 % performance improvement from the offload programming depending on the sparse matrix type and the size of transferred and processed data.
The Sequential Probability Ratio Test and Binary Item Response Models
ERIC Educational Resources Information Center
Nydick, Steven W.
2014-01-01
The sequential probability ratio test (SPRT) is a common method for terminating item response theory (IRT)-based adaptive classification tests. To decide whether a classification test should stop, the SPRT compares a simple log-likelihood ratio, based on the classification bound separating two categories, to prespecified critical values. As has…
Distributed Immune Systems for Wireless Network Information Assurance
2010-04-26
ratio test (SPRT), where the goal is to optimize a hypothesis testing problem given a trade-off between the probability of errors and the...using cumulative sum (CUSUM) and Girshik-Rubin-Shiryaev (GRSh) statistics. In sequential versions of the problem the sequential probability ratio ...the more complicated problems, in particular those where no clear mean can be established. We developed algorithms based on the sequential probability
Otolith Dysfunction Alters Exploratory Movement in Mice
Blankenship, Philip A.; Cherep, Lucia A.; Donaldson, Tia N.; Brockman, Sarah N.; Trainer, Alexandria D.; Yoder, Ryan M.; Wallace, Douglas G.
2017-01-01
The organization of rodent exploratory behavior appears to depend on self-movement cue processing. As of yet, however, no studies have directly examined the vestibular system’s contribution to the organization of exploratory movement. The current study sequentially segmented open field behavior into progressions and stops in order to characterize differences in movement organization between control and otoconia-deficient tilted mice under conditions with and without access to visual cues. Under completely dark conditions, tilted mice exhibited similar distance traveled and stop times overall, but had significantly more circuitous progressions, larger changes in heading between progressions, and less stable clustering of home bases, relative to control mice. In light conditions, control and tilted mice were similar on all measures except for the change in heading between progressions. This pattern of results is consistent with otoconia-deficient tilted mice using visual cues to compensate for impaired self-movement cue processing. This work provides the first empirical evidence that signals from the otolithic organs mediate the organization of exploratory behavior, based on a novel assessment of spatial orientation. PMID:28235587
Modeling eye gaze patterns in clinician-patient interaction with lag sequential analysis.
Montague, Enid; Xu, Jie; Chen, Ping-Yu; Asan, Onur; Barrett, Bruce P; Chewning, Betty
2011-10-01
The aim of this study was to examine whether lag sequential analysis could be used to describe eye gaze orientation between clinicians and patients in the medical encounter. This topic is particularly important as new technologies are implemented into multiuser health care settings in which trust is critical and nonverbal cues are integral to achieving trust. This analysis method could lead to design guidelines for technologies and more effective assessments of interventions. Nonverbal communication patterns are important aspects of clinician-patient interactions and may affect patient outcomes. The eye gaze behaviors of clinicians and patients in 110 videotaped medical encounters were analyzed using the lag sequential method to identify significant behavior sequences. Lag sequential analysis included both event-based lag and time-based lag. Results from event-based lag analysis showed that the patient's gaze followed that of the clinician, whereas the clinician's gaze did not follow the patient's. Time-based sequential analysis showed that responses from the patient usually occurred within 2 s after the initial behavior of the clinician. Our data suggest that the clinician's gaze significantly affects the medical encounter but that the converse is not true. Findings from this research have implications for the design of clinical work systems and modeling interactions. Similar research methods could be used to identify different behavior patterns in clinical settings (physical layout, technology, etc.) to facilitate and evaluate clinical work system designs.
Modeling Eye Gaze Patterns in Clinician-Patient Interaction with Lag Sequential Analysis
Montague, E; Xu, J; Asan, O; Chen, P; Chewning, B; Barrett, B
2011-01-01
Objective The aim of this study was to examine whether lag-sequential analysis could be used to describe eye gaze orientation between clinicians and patients in the medical encounter. This topic is particularly important as new technologies are implemented into multi-user health care settings where trust is critical and nonverbal cues are integral to achieving trust. This analysis method could lead to design guidelines for technologies and more effective assessments of interventions. Background Nonverbal communication patterns are important aspects of clinician-patient interactions and may impact patient outcomes. Method Eye gaze behaviors of clinicians and patients in 110-videotaped medical encounters were analyzed using the lag-sequential method to identify significant behavior sequences. Lag-sequential analysis included both event-based lag and time-based lag. Results Results from event-based lag analysis showed that the patients’ gaze followed that of clinicians, while clinicians did not follow patients. Time-based sequential analysis showed that responses from the patient usually occurred within two seconds after the initial behavior of the clinician. Conclusion Our data suggest that the clinician’s gaze significantly affects the medical encounter but not the converse. Application Findings from this research have implications for the design of clinical work systems and modeling interactions. Similar research methods could be used to identify different behavior patterns in clinical settings (physical layout, technology, etc.) to facilitate and evaluate clinical work system designs. PMID:22046723
NASA Astrophysics Data System (ADS)
Gallagher, C. B.; Ferraro, A.
2018-05-01
A possible alternative to the standard model of measurement-based quantum computation (MBQC) is offered by the sequential model of MBQC—a particular class of quantum computation via ancillae. Although these two models are equivalent under ideal conditions, their relative resilience to noise in practical conditions is not yet known. We analyze this relationship for various noise models in the ancilla preparation and in the entangling-gate implementation. The comparison of the two models is performed utilizing both the gate infidelity and the diamond distance as figures of merit. Our results show that in the majority of instances the sequential model outperforms the standard one in regard to a universal set of operations for quantum computation. Further investigation is made into the performance of sequential MBQC in experimental scenarios, thus setting benchmarks for possible cavity-QED implementations.
Synthesizing genetic sequential logic circuit with clock pulse generator.
Chuang, Chia-Hua; Lin, Chun-Liang
2014-05-28
Rhythmic clock widely occurs in biological systems which controls several aspects of cell physiology. For the different cell types, it is supplied with various rhythmic frequencies. How to synthesize a specific clock signal is a preliminary but a necessary step to further development of a biological computer in the future. This paper presents a genetic sequential logic circuit with a clock pulse generator based on a synthesized genetic oscillator, which generates a consecutive clock signal whose frequency is an inverse integer multiple to that of the genetic oscillator. An analogous electronic waveform-shaping circuit is constructed by a series of genetic buffers to shape logic high/low levels of an oscillation input in a basic sinusoidal cycle and generate a pulse-width-modulated (PWM) output with various duty cycles. By controlling the threshold level of the genetic buffer, a genetic clock pulse signal with its frequency consistent to the genetic oscillator is synthesized. A synchronous genetic counter circuit based on the topology of the digital sequential logic circuit is triggered by the clock pulse to synthesize the clock signal with an inverse multiple frequency to the genetic oscillator. The function acts like a frequency divider in electronic circuits which plays a key role in the sequential logic circuit with specific operational frequency. A cascaded genetic logic circuit generating clock pulse signals is proposed. Based on analogous implement of digital sequential logic circuits, genetic sequential logic circuits can be constructed by the proposed approach to generate various clock signals from an oscillation signal.
Krewald, Vera; Neese, Frank; Pantazis, Dimitrios A
2016-04-28
The redox potential of synthetic oligonuclear transition metal complexes has been shown to correlate with the Lewis acidity of a redox-inactive cation connected to the redox-active transition metals of the cluster via oxo or hydroxo bridges. Such heterometallic clusters are important cofactors in many metalloenzymes, where it is speculated that the redox-inactive constituent ion of the cluster serves to optimize its redox potential for electron transfer or catalysis. A principal example is the oxygen-evolving complex in photosystem II of natural photosynthesis, a Mn4CaO5 cofactor that oxidizes water into dioxygen, protons and electrons. Calcium is critical for catalytic function, but its precise role is not yet established. In analogy to synthetic complexes it has been suggested that Ca(2+) fine-tunes the redox potential of the manganese cluster. Here we evaluate this hypothesis by computing the relative redox potentials of substituted derivatives of the oxygen-evolving complex with the cations Sr(2+), Gd(3+), Cd(2+), Zn(2+), Mg(2+), Sc(3+), Na(+) and Y(3+) for two sequential transitions of its catalytic cycle. The theoretical approach is validated with a series of experimentally well-characterized Mn3AO4 cubane complexes that are structural mimics of the enzymatic cluster. Our results reproduce perfectly the experimentally observed correlation between the redox potential and the Lewis acidities of redox-inactive cations for the synthetic complexes. However, it is conclusively demonstrated that this correlation does not hold for the oxygen evolving complex. In the enzyme the redox potential of the cluster only responds to the charge of the redox-inactive cations and remains otherwise insensitive to their precise identity, precluding redox-tuning of the metal cluster as a primary role for Ca(2+) in biological water oxidation.
de Oliveira, Saulo H P; Law, Eleanor C; Shi, Jiye; Deane, Charlotte M
2018-04-01
Most current de novo structure prediction methods randomly sample protein conformations and thus require large amounts of computational resource. Here, we consider a sequential sampling strategy, building on ideas from recent experimental work which shows that many proteins fold cotranslationally. We have investigated whether a pseudo-greedy search approach, which begins sequentially from one of the termini, can improve the performance and accuracy of de novo protein structure prediction. We observed that our sequential approach converges when fewer than 20 000 decoys have been produced, fewer than commonly expected. Using our software, SAINT2, we also compared the run time and quality of models produced in a sequential fashion against a standard, non-sequential approach. Sequential prediction produces an individual decoy 1.5-2.5 times faster than non-sequential prediction. When considering the quality of the best model, sequential prediction led to a better model being produced for 31 out of 41 soluble protein validation cases and for 18 out of 24 transmembrane protein cases. Correct models (TM-Score > 0.5) were produced for 29 of these cases by the sequential mode and for only 22 by the non-sequential mode. Our comparison reveals that a sequential search strategy can be used to drastically reduce computational time of de novo protein structure prediction and improve accuracy. Data are available for download from: http://opig.stats.ox.ac.uk/resources. SAINT2 is available for download from: https://github.com/sauloho/SAINT2. saulo.deoliveira@dtc.ox.ac.uk. Supplementary data are available at Bioinformatics online.
Is Statistical Learning Constrained by Lower Level Perceptual Organization?
Emberson, Lauren L.; Liu, Ran; Zevin, Jason D.
2013-01-01
In order for statistical information to aid in complex developmental processes such as language acquisition, learning from higher-order statistics (e.g. across successive syllables in a speech stream to support segmentation) must be possible while perceptual abilities (e.g. speech categorization) are still developing. The current study examines how perceptual organization interacts with statistical learning. Adult participants were presented with multiple exemplars from novel, complex sound categories designed to reflect some of the spectral complexity and variability of speech. These categories were organized into sequential pairs and presented such that higher-order statistics, defined based on sound categories, could support stream segmentation. Perceptual similarity judgments and multi-dimensional scaling revealed that participants only perceived three perceptual clusters of sounds and thus did not distinguish the four experimenter-defined categories, creating a tension between lower level perceptual organization and higher-order statistical information. We examined whether the resulting pattern of learning is more consistent with statistical learning being “bottom-up,” constrained by the lower levels of organization, or “top-down,” such that higher-order statistical information of the stimulus stream takes priority over the perceptual organization, and perhaps influences perceptual organization. We consistently find evidence that learning is constrained by perceptual organization. Moreover, participants generalize their learning to novel sounds that occupy a similar perceptual space, suggesting that statistical learning occurs based on regions of or clusters in perceptual space. Overall, these results reveal a constraint on learning of sound sequences, such that statistical information is determined based on lower level organization. These findings have important implications for the role of statistical learning in language acquisition. PMID:23618755
DOE Office of Scientific and Technical Information (OSTI.GOV)
Han, Chang W.; Iddir, Hakim; Uzun, Alper
To address the challenge of fast, direct atomic-scale visualization of the diffusion of atoms and clusters on surfaces, we used aberration-corrected scanning transmission electron microscopy (STEM) with high scan speeds (as little as ~0.1 s per frame) to visualize the diffusion of (1) a heavy atom (Ir) on the surface of a support consisting of light atoms, MgO(100), and (2) an Ir 3 cluster on MgO(110). Sequential Z-contrast images elucidate the diffusion mechanisms, including the hopping of Ir1 and the rotational migration of Ir 3 as two Ir atoms remain anchored to the surface. Density functional theory (DFT) calculations providedmore » estimates of the diffusion energy barriers and binding energies of the iridium species to the surfaces. The results show how the combination of fast-scan STEM and DFT calculations allow real-time visualization and fundamental understanding of surface diffusion phenomena pertaining to supported catalysts and other materials.« less
Liao, Yuan-Xi; Xing, Chun-Hui; Israel, Matthew; Hu, Qiao-Sheng
2011-01-01
Sequential aldol condensation of aldehydes with methyl ketones followed by transition metal-catalyzed addition reactions of arylboronic acids to form β-substituted ketones is described. By using the 1,1′-spirobiindane-7,7′-diol (SPINOL)-based phosphite, an asymmetric version of this type of sequential reaction, with up to 92% ee, was also realized. Our study provided an efficient method to access β-substituted ketones and might lead to the development of other sequential/tandem reactions with transition metal-catalyzed addition reactions as the key step. PMID:21417359
Liao, Yuan-Xi; Xing, Chun-Hui; Israel, Matthew; Hu, Qiao-Sheng
2011-04-15
Sequential aldol condensation of aldehydes with methyl ketones followed by transition metal-catalyzed addition reactions of arylboronic acids to form β-substituted ketones is described. By using the 1,1'-spirobiindane-7,7'-diol (SPINOL)-based phosphite, an asymmetric version of this type of sequential reaction, with up to 92% ee, was also realized. Our study provided an efficient method to access β-substituted ketones and might lead to the development of other sequential/tandem reactions with transition metal-catalyzed addition reactions as the key step. © 2011 American Chemical Society
Kent, Peter; Stochkendahl, Mette Jensen; Christensen, Henrik Wulff; Kongsted, Alice
2015-01-01
Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it.
Harold R. Offord
1966-01-01
Sequential sampling based on a negative binomial distribution of ribes populations required less than half the time taken by regular systematic line transect sampling in a comparison test. It gave the same control decision as the regular method in 9 of 13 field trials. A computer program that permits sequential plans to be built readily for other white pine regions is...
Computer-Based Instruction for TRIDENT FBM Training
1976-06-01
remote voice feedback to an operator. In this case it is possible to display text which represents the voice messages required during sequential ...provides two main services: (a) the preparation of missiles for sequential launching with self-guidance after launch, and (b) the coordination of...monitor- ing the status of the guidance system in each missile. FCS SWS coordina- tion consists of monitoring systems involved in sequential functions at
[Co-composting high moisture vegetable waste and flower waste in a sequential fed operation].
Zhang, Xiangfeng; Wang, Hongtao; Nie, Yongfeng
2003-11-01
Co-composting of high moisture vegetable wastes (celery and cabbage) and flower wastes (carnation) were studied in a sequential fed bed. The preliminary materials of composting were celery and carnation wastes. The sequential fed materials of composting were cabbage wastes and were fed every 4 days. Moisture content of mixture materials was between 60% and 70%. Composting was done in an aerobic static bed of composting based temperature feedback and control via aeration rate regulation. Aeration was ended when temperature of the pile was about 40 degrees C. Changes of composting of temperature, aeration rate, water content, organic matter, ash, pH, volume, NH4(+)-N, and NO3(-)-N were studied. Results show that co-composting of high moisture vegetable wastes and flower wastes, in a sequential fed aerobic static bed based temperature feedback and control via aeration rate regulation, can stabilize organic matter and removal water rapidly. The sequential fed operation are effective to overcome the difficult which traditional composting cannot applied successfully where high moisture vegetable wastes in more excess of flower wastes, such as Dianchi coastal.
Numerical study on the sequential Bayesian approach for radioactive materials detection
NASA Astrophysics Data System (ADS)
Qingpei, Xiang; Dongfeng, Tian; Jianyu, Zhu; Fanhua, Hao; Ge, Ding; Jun, Zeng
2013-01-01
A new detection method, based on the sequential Bayesian approach proposed by Candy et al., offers new horizons for the research of radioactive detection. Compared with the commonly adopted detection methods incorporated with statistical theory, the sequential Bayesian approach offers the advantages of shorter verification time during the analysis of spectra that contain low total counts, especially in complex radionuclide components. In this paper, a simulation experiment platform implanted with the methodology of sequential Bayesian approach was developed. Events sequences of γ-rays associating with the true parameters of a LaBr3(Ce) detector were obtained based on an events sequence generator using Monte Carlo sampling theory to study the performance of the sequential Bayesian approach. The numerical experimental results are in accordance with those of Candy. Moreover, the relationship between the detection model and the event generator, respectively represented by the expected detection rate (Am) and the tested detection rate (Gm) parameters, is investigated. To achieve an optimal performance for this processor, the interval of the tested detection rate as a function of the expected detection rate is also presented.
Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan
2018-02-01
In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.
ERIC Educational Resources Information Center
Wu, Sheng-Yi; Hou, Huei-Tse
2015-01-01
Cognitive styles play an important role in influencing the learning process, but to date no relevant study has been conducted using lag sequential analysis to assess knowledge construction learning patterns based on different cognitive styles in computer-supported collaborative learning activities in online collaborative discussions. This study…
Panahbehagh, B.; Smith, D.R.; Salehi, M.M.; Hornbach, D.J.; Brown, D.J.; Chan, F.; Marinova, D.; Anderssen, R.S.
2011-01-01
Assessing populations of rare species is challenging because of the large effort required to locate patches of occupied habitat and achieve precise estimates of density and abundance. The presence of a rare species has been shown to be correlated with presence or abundance of more common species. Thus, ecological community richness or abundance can be used to inform sampling of rare species. Adaptive sampling designs have been developed specifically for rare and clustered populations and have been applied to a wide range of rare species. However, adaptive sampling can be logistically challenging, in part, because variation in final sample size introduces uncertainty in survey planning. Two-stage sequential sampling (TSS), a recently developed design, allows for adaptive sampling, but avoids edge units and has an upper bound on final sample size. In this paper we present an extension of two-stage sequential sampling that incorporates an auxiliary variable (TSSAV), such as community attributes, as the condition for adaptive sampling. We develop a set of simulations to approximate sampling of endangered freshwater mussels to evaluate the performance of the TSSAV design. The performance measures that we are interested in are efficiency and probability of sampling a unit occupied by the rare species. Efficiency measures the precision of population estimate from the TSSAV design relative to a standard design, such as simple random sampling (SRS). The simulations indicate that the density and distribution of the auxiliary population is the most important determinant of the performance of the TSSAV design. Of the design factors, such as sample size, the fraction of the primary units sampled was most important. For the best scenarios, the odds of sampling the rare species was approximately 1.5 times higher for TSSAV compared to SRS and efficiency was as high as 2 (i.e., variance from TSSAV was half that of SRS). We have found that design performance, especially for adaptive designs, is often case-specific. Efficiency of adaptive designs is especially sensitive to spatial distribution. We recommend that simulations tailored to the application of interest are highly useful for evaluating designs in preparation for sampling rare and clustered populations.
Hospital's activity-based financing system and manager-physician [corrected] interaction.
Crainich, David; Leleu, Hervé; Mauleon, Ana
2011-10-01
This paper examines the consequences of the introduction of an activity-based reimbursement system on the behavior of physicians and hospital's managers. We consider a private for-profit sector where both hospitals and physicians are initially paid on a fee-for-service basis. We show that the benefit of the introduction of an activity-based system depends on the type of interaction between managers and physicians (simultaneous or sequential decision-making games). It is shown that, under the activity-based system, a sequential interaction with physician leader could be beneficial for both agents in the private sector. We further model an endogenous timing game à la Hamilton and Slutsky (Games Econ Behav 2: 29-46, 1990) in which the type of interaction is determined endogenously. We show that, under the activity-based system, the sequential interaction with physician leader is the unique subgame perfect equilibrium.
Dynamics of feature categorization.
Martí, Daniel; Rinzel, John
2013-01-01
In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. This grouping is preattentive and fast and is thought of as an elementary form of categorization by which objects sharing similar features are clustered in some abstract perceptual space. It is unclear what neuronal mechanisms underlie this fast categorization. Here we propose a neuromechanistic model of fast feature categorization based on the framework of continuous attractor networks. The mechanism for category formation does not rely on learning and is based on biologically plausible assumptions, for example, the existence of populations of neurons tuned to feature values, feature-specific interactions, and subthreshold-evoked responses upon the presentation of single objects. When the network is presented with a sequence of stimuli characterized by some feature, the network sums the evoked responses and provides a running estimate of the distribution of features in the input stream. If the distribution of features is structured into different components or peaks (i.e., is multimodal), recurrent excitation amplifies the response of activated neurons, and categories are singled out as emerging localized patterns of elevated neuronal activity (bumps), centered at the centroid of each cluster. The emergence of bump states through sequential, subthreshold activation and the dependence on input statistics is a novel application of attractor networks. We show that the extraction and representation of multiple categories are facilitated by the rich attractor structure of the network, which can sustain multiple stable activity patterns for a robust range of connectivity parameters compatible with cortical physiology.
A Bayesian sequential processor approach to spectroscopic portal system decisions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sale, K; Candy, J; Breitfeller, E
The development of faster more reliable techniques to detect radioactive contraband in a portal type scenario is an extremely important problem especially in this era of constant terrorist threats. Towards this goal the development of a model-based, Bayesian sequential data processor for the detection problem is discussed. In the sequential processor each datum (detector energy deposit and pulse arrival time) is used to update the posterior probability distribution over the space of model parameters. The nature of the sequential processor approach is that a detection is produced as soon as it is statistically justified by the data rather than waitingmore » for a fixed counting interval before any analysis is performed. In this paper the Bayesian model-based approach, physics and signal processing models and decision functions are discussed along with the first results of our research.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Briggs, Beverly D.; Palafox-Hernandez, J. Pablo; Li, Yue
Materials-binding peptides represent a unique avenue towards controlling the shape and size of nanoparticles (NPs) grown under aqueous conditions. Here, employing a bionanocombinatorics approach, two such materials-binding peptides were linked at either end of a photoswitchable spacer, forming a multi-domain materials-binding molecule to control the in situ synthesis and organization of Ag and Au NPs under ambient conditions. These multi-domain molecules retained the peptides’ ability to nucleate, grow, and stabilize Ag and Au NPs in aqueous media. Disordered co-assemblies of the two nanomaterials were observed by TEM imaging of dried samples after sequential growth of the two metals, and showedmore » a clustering behavior that was not observed without both metals and the linker molecules. While TEM evidence indicated the formation of AuNP/AgNP assemblies upon drying, SAXS analysis indicated that no extended assemblies existed in solution, suggesting that sample drying plays an important role in facilitating NP clustering. Molecular simulations and experimental data revealed tunable materials-binding based upon the isomerization state of the photoswitchable unit and metal employed. This work is a first step in generating externally actuated biomolecules with specific material-binding properties that could be used as the building blocks to achieve multi-material switchable NP assemblies.« less
Programmable Assembly of Hybrid Nanoclusters.
Ni, Songbo; Wolf, Heiko; Isa, Lucio
2018-02-20
Hybrid nanoparticle clusters (often metallic) are interesting plasmonic materials with tunable resonances and a near-field electromagnetic enhancement at interparticle junctions. Therefore, in recent years, we have witnessed a surge in both the interest in these materials and the efforts to obtain them. However, a versatile fabrication of hybrid nanoclusters, that is, combining more than one material, still remains an open challenge. Current lithographical or self-assembly methods are limited to the preparation of hybrid clusters with up to two different materials and typically to the fabrication of hybrid dimers. Here, we provide a novel strategy to deposit and align not only hybrid dimers but also hybrid nanoclusters possessing more complex shapes and compositions. Our strategy is based on the downscaling of sequential capillarity-assisted particle assembly over topographical templates. As a proof of concept, we demonstrate dimers, linear trimers, and 2D nanoclusters with programmable compositions from a range of metallic nanoparticles. Our process does not rely on any specific chemistry and can be extended to a large variety of particles and shapes. The template also simultaneously aligns the hybrid (often anisotropic) nanoclusters, which could facilitate device integration, for example, for optical readout after transfer to other substrates by a printing step. We envisage that this new fabrication route will enable the assembly and positioning of complex hybrid nanoclusters of different functional nanoparticles to study coupling effects not only locally but also at larger scales for new nanoscale optical devices.
Optimization of the gypsum-based materials by the sequential simplex method
NASA Astrophysics Data System (ADS)
Doleželová, Magdalena; Vimmrová, Alena
2017-11-01
The application of the sequential simplex optimization method for the design of gypsum based materials is described. The principles of simplex method are explained and several examples of the method usage for the optimization of lightweight gypsum and ternary gypsum based materials are given. By this method lightweight gypsum based materials with desired properties and ternary gypsum based material with higher strength (16 MPa) were successfully developed. Simplex method is a useful tool for optimizing of gypsum based materials, but the objective of the optimization has to be formulated appropriately.
Singh, Dadabhai T; Trehan, Rahul; Schmidt, Bertil; Bretschneider, Timo
2008-01-01
Preparedness for a possible global pandemic caused by viruses such as the highly pathogenic influenza A subtype H5N1 has become a global priority. In particular, it is critical to monitor the appearance of any new emerging subtypes. Comparative phyloinformatics can be used to monitor, analyze, and possibly predict the evolution of viruses. However, in order to utilize the full functionality of available analysis packages for large-scale phyloinformatics studies, a team of computer scientists, biostatisticians and virologists is needed--a requirement which cannot be fulfilled in many cases. Furthermore, the time complexities of many algorithms involved leads to prohibitive runtimes on sequential computer platforms. This has so far hindered the use of comparative phyloinformatics as a commonly applied tool in this area. In this paper the graphical-oriented workflow design system called Quascade and its efficient usage for comparative phyloinformatics are presented. In particular, we focus on how this task can be effectively performed in a distributed computing environment. As a proof of concept, the designed workflows are used for the phylogenetic analysis of neuraminidase of H5N1 isolates (micro level) and influenza viruses (macro level). The results of this paper are hence twofold. Firstly, this paper demonstrates the usefulness of a graphical user interface system to design and execute complex distributed workflows for large-scale phyloinformatics studies of virus genes. Secondly, the analysis of neuraminidase on different levels of complexity provides valuable insights of this virus's tendency for geographical based clustering in the phylogenetic tree and also shows the importance of glycan sites in its molecular evolution. The current study demonstrates the efficiency and utility of workflow systems providing a biologist friendly approach to complex biological dataset analysis using high performance computing. In particular, the utility of the platform Quascade for deploying distributed and parallelized versions of a variety of computationally intensive phylogenetic algorithms has been shown. Secondly, the analysis of the utilized H5N1 neuraminidase datasets at macro and micro levels has clearly indicated a pattern of spatial clustering of the H5N1 viral isolates based on geographical distribution rather than temporal or host range based clustering.
Invariant-feature-based adaptive automatic target recognition in obscured 3D point clouds
NASA Astrophysics Data System (ADS)
Khuon, Timothy; Kershner, Charles; Mattei, Enrico; Alverio, Arnel; Rand, Robert
2014-06-01
Target recognition and classification in a 3D point cloud is a non-trivial process due to the nature of the data collected from a sensor system. The signal can be corrupted by noise from the environment, electronic system, A/D converter, etc. Therefore, an adaptive system with a desired tolerance is required to perform classification and recognition optimally. The feature-based pattern recognition algorithm architecture as described below is particularly devised for solving a single-sensor classification non-parametrically. Feature set is extracted from an input point cloud, normalized, and classifier a neural network classifier. For instance, automatic target recognition in an urban area would require different feature sets from one in a dense foliage area. The figure above (see manuscript) illustrates the architecture of the feature based adaptive signature extraction of 3D point cloud including LIDAR, RADAR, and electro-optical data. This network takes a 3D cluster and classifies it into a specific class. The algorithm is a supervised and adaptive classifier with two modes: the training mode and the performing mode. For the training mode, a number of novel patterns are selected from actual or artificial data. A particular 3D cluster is input to the network as shown above for the decision class output. The network consists of three sequential functional modules. The first module is for feature extraction that extracts the input cluster into a set of singular value features or feature vector. Then the feature vector is input into the feature normalization module to normalize and balance it before being fed to the neural net classifier for the classification. The neural net can be trained by actual or artificial novel data until each trained output reaches the declared output within the defined tolerance. In case new novel data is added after the neural net has been learned, the training is then resumed until the neural net has incrementally learned with the new novel data. The associative memory capability of the neural net enables the incremental learning. The back propagation algorithm or support vector machine can be utilized for the classification and recognition.
Vapor Grown Perovskite Solar Cells
NASA Astrophysics Data System (ADS)
Abdussamad Abbas, Hisham
Perovskite solar cells has been the fastest growing solar cell material till date with verified efficiencies of over 22%. Most groups in the world focuses their research on solution based devices that has residual solvent in the material bulk. This work focuses extensively on the fabrication and properties of vapor based perovskite devices that is devoid of solvents. The initial part of my work focuses on the detailed fabrication of high efficiency consistent sequential vapor NIP devices made using P3HT as P-type Type II heterojunction. The sequential vapor devices experiences device anomalies like voltage evolution and IV hysteresis owing to charge trapping in TiO2. Hence, sequential PIN devices were fabricated using doped Type-II heterojunctions that had no device anomalies. The sequential PIN devices has processing restriction, as organic Type-II heterojunction materials cannot withstand high processing temperature, hence limiting device efficiency. Thereby bringing the need of co-evaporation for fabricating high efficiency consistent PIN devices, the approach has no-restriction on substrates and offers stoichiometric control. A comprehensive description of the fabrication, Co-evaporator setup and how to build it is described. The results of Co-evaporated devices clearly show that grain size, stoichiometry and doped transport layers are all critical for eliminating device anomalies and in fabricating high efficiency devices. Finally, Formamidinium based perovskite were fabricated using sequential approach. A thermal degradation study was conducted on Methyl Ammonium Vs. Formamidinium based perovskite films, Formamidinium based perovskites were found to be more stable. Lastly, inorganic films such as CdS and Nickel oxide were developed in this work.
Synthesizing genetic sequential logic circuit with clock pulse generator
2014-01-01
Background Rhythmic clock widely occurs in biological systems which controls several aspects of cell physiology. For the different cell types, it is supplied with various rhythmic frequencies. How to synthesize a specific clock signal is a preliminary but a necessary step to further development of a biological computer in the future. Results This paper presents a genetic sequential logic circuit with a clock pulse generator based on a synthesized genetic oscillator, which generates a consecutive clock signal whose frequency is an inverse integer multiple to that of the genetic oscillator. An analogous electronic waveform-shaping circuit is constructed by a series of genetic buffers to shape logic high/low levels of an oscillation input in a basic sinusoidal cycle and generate a pulse-width-modulated (PWM) output with various duty cycles. By controlling the threshold level of the genetic buffer, a genetic clock pulse signal with its frequency consistent to the genetic oscillator is synthesized. A synchronous genetic counter circuit based on the topology of the digital sequential logic circuit is triggered by the clock pulse to synthesize the clock signal with an inverse multiple frequency to the genetic oscillator. The function acts like a frequency divider in electronic circuits which plays a key role in the sequential logic circuit with specific operational frequency. Conclusions A cascaded genetic logic circuit generating clock pulse signals is proposed. Based on analogous implement of digital sequential logic circuits, genetic sequential logic circuits can be constructed by the proposed approach to generate various clock signals from an oscillation signal. PMID:24884665
Networked Workstations and Parallel Processing Utilizing Functional Languages
1993-03-01
program . This frees the programmer to concentrate on what the program is to do, not how the program is...traditional ’von Neumann’ architecture uses a timer based (e.g., the program counter), sequentially pro- grammed, single processor approach to problem...traditional ’von Neumann’ architecture uses a timer based (e.g., the program counter), sequentially programmed , single processor approach to
Cluster size selectivity in the product distribution of ethene dehydrogenation on niobium clusters.
Parnis, J Mark; Escobar-Cabrera, Eric; Thompson, Matthew G K; Jacula, J Paul; Lafleur, Rick D; Guevara-García, Alfredo; Martínez, Ana; Rayner, David M
2005-08-18
Ethene reactions with niobium atoms and clusters containing up to 25 constituent atoms have been studied in a fast-flow metal cluster reactor. The clusters react with ethene at about the gas-kinetic collision rate, indicating a barrierless association process as the cluster removal step. Exceptions are Nb8 and Nb10, for which a significantly diminished rate is observed, reflecting some cluster size selectivity. Analysis of the experimental primary product masses indicates dehydrogenation of ethene for all clusters save Nb10, yielding either Nb(n)C2H2 or Nb(n)C2. Over the range Nb-Nb6, the extent of dehydrogenation increases with cluster size, then decreases for larger clusters. For many clusters, secondary and tertiary product masses are also observed, showing varying degrees of dehydrogenation corresponding to net addition of C2H4, C2H2, or C2. With Nb atoms and several small clusters, formal addition of at least six ethene molecules is observed, suggesting a polymerization process may be active. Kinetic analysis of the Nb atom and several Nb(n) cluster reactions with ethene shows that the process is consistent with sequential addition of ethene units at rates corresponding approximately to the gas-kinetic collision frequency for several consecutive reacting ethene molecules. Some variation in the rate of ethene pick up is found, which likely reflects small energy barriers or steric constraints associated with individual mechanistic steps. Density functional calculations of structures of Nb clusters up to Nb(6), and the reaction products Nb(n)C2H2 and Nb(n)C2 (n = 1...6) are presented. Investigation of the thermochemistry for the dehydrogenation of ethene to form molecular hydrogen, for the Nb atom and clusters up to Nb6, demonstrates that the exergonicity of the formation of Nb(n)C2 species increases with cluster size over this range, which supports the proposal that the extent of dehydrogenation is determined primarily by thermodynamic constraints. Analysis of the structural variations present in the cluster species studied shows an increase in C-H bond lengths with cluster size that closely correlates with the increased thermodynamic drive to full dehydrogenation. This correlation strongly suggests that all steps in the reaction are barrierless, and that weakening of the C-H bonds is directly reflected in the thermodynamics of the overall dehydrogenation process. It is also demonstrated that reaction exergonicity in the initial partial dehydrogenation step must be carried through as excess internal energy into the second dehydrogenation step.
Ichikawa, Shota; Kamishima, Tamotsu; Sutherland, Kenneth; Fukae, Jun; Katayama, Kou; Aoki, Yuko; Okubo, Takanobu; Okino, Taichi; Kaneda, Takahiko; Takagi, Satoshi; Tanimura, Kazuhide
2017-10-01
We have developed a refined computer-based method to detect joint space narrowing (JSN) progression with the joint space narrowing progression index (JSNPI) by superimposing sequential hand radiographs. The purpose of this study is to assess the validity of a computer-based method using images obtained from multiple institutions in rheumatoid arthritis (RA) patients. Sequential hand radiographs of 42 patients (37 females and 5 males) with RA from two institutions were analyzed by a computer-based method and visual scoring systems as a standard of reference. The JSNPI above the smallest detectable difference (SDD) defined JSN progression on the joint level. The sensitivity and specificity of the computer-based method for JSN progression was calculated using the SDD and a receiver operating characteristic (ROC) curve. Out of 314 metacarpophalangeal joints, 34 joints progressed based on the SDD, while 11 joints widened. Twenty-one joints progressed in the computer-based method, 11 joints in the scoring systems, and 13 joints in both methods. Based on the SDD, we found lower sensitivity and higher specificity with 54.2 and 92.8%, respectively. At the most discriminant cutoff point according to the ROC curve, the sensitivity and specificity was 70.8 and 81.7%, respectively. The proposed computer-based method provides quantitative measurement of JSN progression using sequential hand radiographs and may be a useful tool in follow-up assessment of joint damage in RA patients.
Considering User's Access Pattern in Multimedia File Systems
NASA Astrophysics Data System (ADS)
Cho, KyoungWoon; Ryu, YeonSeung; Won, Youjip; Koh, Kern
2002-12-01
Legacy buffer cache management schemes for multimedia server are grounded at the assumption that the application sequentially accesses the multimedia file. However, user access pattern may not be sequential in some circumstances, for example, in distance learning application, where the user may exploit the VCR-like function(rewind and play) of the system and accesses the particular segments of video repeatedly in the middle of sequential playback. Such a looping reference can cause a significant performance degradation of interval-based caching algorithms. And thus an appropriate buffer cache management scheme is required in order to deliver desirable performance even under the workload that exhibits looping reference behavior. We propose Adaptive Buffer cache Management(ABM) scheme which intelligently adapts to the file access characteristics. For each opened file, ABM applies either the LRU replacement or the interval-based caching depending on the Looping Reference Indicator, which indicates that how strong temporally localized access pattern is. According to our experiment, ABM exhibits better buffer cache miss ratio than interval-based caching or LRU, especially when the workload exhibits not only sequential but also looping reference property.
Devaluation and sequential decisions: linking goal-directed and model-based behavior
Friedel, Eva; Koch, Stefan P.; Wendt, Jean; Heinz, Andreas; Deserno, Lorenz; Schlagenhauf, Florian
2014-01-01
In experimental psychology different experiments have been developed to assess goal–directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans. PMID:25136310
Bhardwaj, Anuja; Gupta, Payal; Kumar, Navin; Mishra, Jigni; Kumar, Ajai; Rakhee, Rajput; Misra, Kshipra
2017-01-01
This article presents a comparative gas chromatography (GC)-mass spectrometry (MS)-based metabolomic analysis of mycelia and fruiting bodies of the medicinal mushroom Ganoderma lucidum. Three aqueous extracts-mycelia, fruiting bodies, and a mixture of them-and their sequential fractions (methanolic and ethyl acetate), prepared using an accelerated solvent extractor, were characterized by GC-MS to determine volatile organic compounds and by high-performance thin-layer chromatography to quantify ascorbic acid, a potent antioxidant. In addition, these extracts and fractions were assessed against Candida albicans and C. glabrata biofilms via the XTT reduction assay, and their antioxidant potential was evaluated. Application of chemometrics (hierarchical cluster analysis and principal component analysis) to GC data revealed variability in volatile organic compound profiles among G. lucidum extracts and fractions. The mycelial aqueous extract demonstrated higher anti-Candida activity and ascorbic acid content among all the extracts and fractions. Thus, this study illustrates the preventive effect of G. lucidum against C. albicans and C. glabrata biofilms along with its nutritional value.
Computer-aided target tracking in motion analysis studies
NASA Astrophysics Data System (ADS)
Burdick, Dominic C.; Marcuse, M. L.; Mislan, J. D.
1990-08-01
Motion analysis studies require the precise tracking of reference objects in sequential scenes. In a typical situation, events of interest are captured at high frame rates using special cameras, and selected objects or targets are tracked on a frame by frame basis to provide necessary data for motion reconstruction. Tracking is usually done using manual methods which are slow and prone to error. A computer based image analysis system has been developed that performs tracking automatically. The objective of this work was to eliminate the bottleneck due to manual methods in high volume tracking applications such as the analysis of crash test films for the automotive industry. The system has proven to be successful in tracking standard fiducial targets and other objects in crash test scenes. Over 95 percent of target positions which could be located using manual methods can be tracked by the system, with a significant improvement in throughput over manual methods. Future work will focus on the tracking of clusters of targets and on tracking deformable objects such as airbags.
The transcriptional landscape of hematopoietic stem cell ontogeny
McKinney-Freeman, Shannon; Cahan, Patrick; Li, Hu; Lacadie, Scott A.; Huang, Hsuan-Ting; Curran, Matthew; Loewer, Sabine; Naveiras, Olaia; Kathrein, Katie L.; Konantz, Martina; Langdon, Erin M.; Lengerke, Claudia; Zon, Leonard I.; Collins, James J.; Daley, George Q.
2012-01-01
Transcriptome analysis of adult hematopoietic stem cells (HSC) and their progeny has revealed mechanisms of blood differentiation and leukemogenesis, but a similar analysis of HSC development is lacking. Here, we acquired the transcriptomes of developing HSC purified from >2500 murine embryos and adult mice. We found that embryonic hematopoietic elements clustered into three distinct transcriptional states characteristic of the definitive yolk sac, HSCs undergoing specification, and definitive HSCs. We applied a network biology-based analysis to reconstruct the gene regulatory networks of sequential stages of HSC development and functionally validated candidate transcriptional regulators of HSC ontogeny by morpholino-mediated knock-down in zebrafish embryos. Moreover, we found that HSCs from in vitro differentiated embryonic stem cells closely resemble definitive HSC, yet lack a Notch-signaling signature, likely accounting for their defective lymphopoiesis. Our analysis and web resource (http://hsc.hms.harvard.edu) will enhance efforts to identify regulators of HSC ontogeny and facilitate the engineering of hematopoietic specification. PMID:23122293
All-gas-phase synthesis of UiO-66 through modulated atomic layer deposition
NASA Astrophysics Data System (ADS)
Lausund, Kristian Blindheim; Nilsen, Ola
2016-11-01
Thin films of stable metal-organic frameworks (MOFs) such as UiO-66 have enormous application potential, for instance in microelectronics. However, all-gas-phase deposition techniques are currently not available for such MOFs. We here report on thin-film deposition of the thermally and chemically stable UiO-66 in an all-gas-phase process by the aid of atomic layer deposition (ALD). Sequential reactions of ZrCl4 and 1,4-benzenedicarboxylic acid produce amorphous organic-inorganic hybrid films that are subsequently crystallized to the UiO-66 structure by treatment in acetic acid vapour. We also introduce a new approach to control the stoichiometry between metal clusters and organic linkers by modulation of the ALD growth with additional acetic acid pulses. An all-gas-phase synthesis technique for UiO-66 could enable implementations in microelectronics that are not compatible with solvothermal synthesis. Since this technique is ALD-based, it could also give enhanced thickness control and the possibility to coat irregular substrates with high aspect ratios.
Gureckis, Todd M.; Love, Bradley C.
2009-01-01
We evaluate two broad classes of cognitive mechanisms that might support the learning of sequential patterns. According to the first, learning is based on the gradual accumulation of direct associations between events based on simple conditioning principles. The other view describes learning as the process of inducing the transformational structure that defines the material. Each of these learning mechanisms predict differences in the rate of acquisition for differently organized sequences. Across a set of empirical studies, we compare the predictions of each class of model with the behavior of human subjects. We find that learning mechanisms based on transformations of an internal state, such as recurrent network architectures (e.g., Elman, 1990), have difficulty accounting for the pattern of human results relative to a simpler (but more limited) learning mechanism based on learning direct associations. Our results suggest new constraints on the cognitive mechanisms supporting sequential learning behavior. PMID:20396653
LOW-METALLICITY YOUNG CLUSTERS IN THE OUTER GALAXY. II. SH 2-208
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yasui, Chikako; Kobayashi, Naoto; Izumi, Natsuko
We obtained deep near-infrared images of Sh 2-208, one of the lowest-metallicity H ii regions in the Galaxy, [O/H] = −0.8 dex. We detected a young cluster in the center of the H ii region with a limiting magnitude of K = 18.0 mag (10 σ ), which corresponds to a mass detection limit of ∼0.2 M {sub ⊙}. This enables the comparison of star-forming properties under low metallicity with those of the solar neighborhood. We identified 89 cluster members. From the fitting of the K -band luminosity function (KLF), the age and distance of the cluster are estimated to be ∼0.5more » Myr and ∼4 kpc, respectively. The estimated young age is consistent with the detection of strong CO emission in the cluster region and the estimated large extinction of cluster members ( A{sub V} ∼ 4–25 mag). The observed KLF suggests that the underlying initial mass function (IMF) of the low-metallicity cluster is not significantly different from canonical IMFs in the solar neighborhood in terms of both high-mass slope and IMF peak (characteristic mass). Despite the very young age, the disk fraction of the cluster is estimated at only 27% ± 6%, which is significantly lower than those in the solar metallicity. Those results are similar to Sh 2-207, which is another star-forming region close to Sh 2-208 with a separation of 12 pc, suggesting that their star-forming activities in low-metallicity environments are essentially identical to those in the solar neighborhood, except for the disk dispersal timescale. From large-scale mid-infrared images, we suggest that sequential star formation is taking place in Sh 2-207, Sh 2-208, and the surrounding region, triggered by an expanding bubble with a ∼30 pc radius.« less
2015-01-01
Lipoyl synthase (LS) catalyzes the final step in lipoyl cofactor biosynthesis: the insertion of two sulfur atoms at C6 and C8 of an (N6-octanoyl)-lysyl residue on a lipoyl carrier protein (LCP). LS is a member of the radical SAM superfamily, enzymes that use a [4Fe–4S] cluster to effect the reductive cleavage of S-adenosyl-l-methionine (SAM) to l-methionine and a 5′-deoxyadenosyl 5′-radical (5′-dA•). In the LS reaction, two equivalents of 5′-dA• are generated sequentially to abstract hydrogen atoms from C6 and C8 of the appended octanoyl group, initiating sulfur insertion at these positions. The second [4Fe–4S] cluster on LS, termed the auxiliary cluster, is proposed to be the source of the inserted sulfur atoms. Herein, we provide evidence for the formation of a covalent cross-link between LS and an LCP or synthetic peptide substrate in reactions in which insertion of the second sulfur atom is slowed significantly by deuterium substitution at C8 or by inclusion of limiting concentrations of SAM. The observation that the proteins elute simultaneously by anion-exchange chromatography but are separated by aerobic SDS-PAGE is consistent with their linkage through the auxiliary cluster that is sacrificed during turnover. Generation of the cross-linked species with a small, unlabeled (N6-octanoyl)-lysyl-containing peptide substrate allowed demonstration of both its chemical and kinetic competence, providing strong evidence that it is an intermediate in the LS reaction. Mössbauer spectroscopy of the cross-linked intermediate reveals that one of the [4Fe–4S] clusters, presumably the auxiliary cluster, is partially disassembled to a 3Fe-cluster with spectroscopic properties similar to those of reduced [3Fe–4S]0 clusters. PMID:24901788
Neel, Sean T
2014-11-01
A cost analysis was performed to evaluate the effect on physicians in the United States of a transition from delayed sequential cataract surgery to immediate sequential cataract surgery. Financial and efficiency impacts of this change were evaluated to determine whether efficiency gains could offset potential reduced revenue. A cost analysis using Medicare cataract surgery volume estimates, Medicare 2012 physician cataract surgery reimbursement schedules, and estimates of potential additional office visit revenue comparing immediate sequential cataract surgery with delayed sequential cataract surgery for a single specialty ophthalmology practice in West Tennessee. This model should give an indication of the effect on physicians on a national basis. A single specialty ophthalmology practice in West Tennessee was found to have a cataract surgery revenue loss of $126,000, increased revenue from office visits of $34,449 to $106,271 (minimum and maximum offset methods), and a net loss of $19,900 to $91,700 (base case) with the conversion to immediate sequential cataract surgery. Physicians likely stand to lose financially, and this loss cannot be offset by increased patient visits under the current reimbursement system. This may result in physician resistance to converting to immediate sequential cataract surgery, gaming, and supplier-induced demand.
Space-Time Fluid-Structure Interaction Computation of Flapping-Wing Aerodynamics
2013-12-01
SST-VMST." The structural mechanics computations are based on the Kirchhoff -Love shell model. We use a sequential coupling technique, which is...mechanics computations are based on the Kirchhoff -Love shell model. We use a sequential coupling technique, which is ap- plicable to some classes of FSI...we use the ST-VMS method in combination with the ST-SUPS method. The structural mechanics computations are mostly based on the Kirchhoff –Love shell
Kinematic evidence for feedback-driven star formation in NGC 1893
NASA Astrophysics Data System (ADS)
Lim, Beomdu; Sung, Hwankyung; Bessell, Michael S.; Lee, Sangwoo; Lee, Jae Joon; Oh, Heeyoung; Hwang, Narae; Park, Byeong-Gon; Hur, Hyeonoh; Hong, Kyeongsoo; Park, Sunkyung
2018-06-01
OB associations are the prevailing star-forming sites in the Galaxy. Up to now, the process of how OB associations were formed remained a mystery. A possible process is self-regulating star formation driven by feedback from massive stars. However, although a number of observational studies uncovered various signposts of feedback-driven star formation, the effectiveness of such feedback has been questioned. Stellar and gas kinematics is a promising tool to capture the relative motion of newborn stars and gas away from ionizing sources. We present high-resolution spectroscopy of stars and gas in the young open cluster NGC 1893. Our findings show that newborn stars and the tadpole nebula Sim 130 are moving away from the central cluster containing two O-type stars, and that the time-scale of sequential star formation is about 1 Myr within a 9 pc distance. The newborn stars formed by feedback from massive stars account for at least 18 per cent of the total stellar population in the cluster, suggesting that this process can play an important role in the formation of OB associations. These results support the self-regulating star formation model.
ERIC Educational Resources Information Center
Filippidis, Stavros K.; Tsoukalas, Ioannis A.
2009-01-01
An adaptive educational system that uses adaptive presentation is presented. In this system fragments of different images present the same content and the system can choose the one most relevant to the user based on the sequential-global dimension of Felder-Silverman's learning style theory. In order to retrieve the learning style of each student…
Stepwise sequential redox potential modulation possible on a single platform.
Pepiol, Ariadna; Teixidor, Francesc; Sillanpää, Reijo; Lupu, Marius; Viñas, Clara
2011-12-23
Step by step: The cluster [3,3'-Co(1,2-C(2)B(9)H(11))(2)](-) is an excellent platform for making a stepwise tunable redox potential system by dehydroiodination. With the addition of up to eight iodine substituents (purple; see picture), there is a fall in the E(1/2)(Co(III)/Co(II)) value from -1.80 V to -0.68 V (vs. Fc(+)/Fc; Fc = ferrocene). A practical application of this tunability has been observed in the growth of polypyrrole. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
NASA Astrophysics Data System (ADS)
Kasatkin, D. V.; Yanchuk, S.; Schöll, E.; Nekorkin, V. I.
2017-12-01
We report the phenomenon of self-organized emergence of hierarchical multilayered structures and chimera states in dynamical networks with adaptive couplings. This process is characterized by a sequential formation of subnetworks (layers) of densely coupled elements, the size of which is ordered in a hierarchical way, and which are weakly coupled between each other. We show that the hierarchical structure causes the decoupling of the subnetworks. Each layer can exhibit either a two-cluster state, a periodic traveling wave, or an incoherent state, and these states can coexist on different scales of subnetwork sizes.
Boixel, Julien; Guerchais, Véronique; Le Bozec, Hubert; Chantzis, Agisilaos; Jacquemin, Denis; Colombo, Alessia; Dragonetti, Claudia; Marinotto, Daniele; Roberto, Dominique
2015-05-07
An unprecedented DTE-based Pt(II) complex, 2(o), which stands as the first example of a sequential double nonlinear optical switch, induced first by protonation and next upon irradiation with UV light is presented.
Ciesielski, Szymon J; Schilke, Brenda; Marszalek, Jaroslaw; Craig, Elizabeth A
2016-04-01
Iron-sulfur (Fe-S) clusters, essential protein cofactors, are assembled on the mitochondrial scaffold protein Isu and then transferred to recipient proteins via a multistep process in which Isu interacts sequentially with multiple protein factors. This pathway is in part regulated posttranslationally by modulation of the degradation of Isu, whose abundance increases >10-fold upon perturbation of the biogenesis process. We tested a model in which direct interaction with protein partners protects Isu from degradation by the mitochondrial Lon-type protease. Using purified components, we demonstrated that Isu is indeed a substrate of the Lon-type protease and that it is protected from degradation by Nfs1, the sulfur donor for Fe-S cluster assembly, as well as by Jac1, the J-protein Hsp70 cochaperone that functions in cluster transfer from Isu. Nfs1 and Jac1 variants known to be defective in interaction with Isu were also defective in protecting Isu from degradation. Furthermore, overproduction of Jac1 protected Isu from degradation in vivo, as did Nfs1. Taken together, our results lead to a model of dynamic interplay between a protease and protein factors throughout the Fe-S cluster assembly and transfer process, leading to up-regulation of Isu levels under conditions when Fe-S cluster biogenesis does not meet cellular demands. © 2016 Ciesielski et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Simple and flexible SAS and SPSS programs for analyzing lag-sequential categorical data.
O'Connor, B P
1999-11-01
This paper describes simple and flexible programs for analyzing lag-sequential categorical data, using SAS and SPSS. The programs read a stream of codes and produce a variety of lag-sequential statistics, including transitional frequencies, expected transitional frequencies, transitional probabilities, adjusted residuals, z values, Yule's Q values, likelihood ratio tests of stationarity across time and homogeneity across groups or segments, transformed kappas for unidirectional dependence, bidirectional dependence, parallel and nonparallel dominance, and significance levels based on both parametric and randomization tests.
Making Career Decisions--A Sequential Elimination Approach.
ERIC Educational Resources Information Center
Gati, Itamar
1986-01-01
Presents a model for career decision making based on the sequential elimination of occupational alternatives, an adaptation for career decisions of Tversky's (1972) elimination-by-aspects theory of choice. The expected utility approach is reviewed as a representative compensatory model for career decisions. Advantages, disadvantages, and…
Pielström, Steffen; Roces, Flavio
2013-01-01
The Chaco leaf-cutting ant Atta vollenweideri (Forel) inhabits large and deep subterranean nests composed of a large number of fungus and refuse chambers. The ants dispose of the excavated soil by forming small pellets that are carried to the surface. For ants in general, the organisation of underground soil transport during nest building remains completely unknown. In the laboratory, we investigated how soil pellets are formed and transported, and whether their occurrence influences the spatial organisation of collective digging. Similar to leaf transport, we discovered size matching between soil pellet mass and carrier mass. Workers observed while digging excavated pellets at a rate of 26 per hour. Each excavator deposited its pellets in an individual cluster, independently of the preferred deposition sites of other excavators. Soil pellets were transported sequentially over 2 m, and the transport involved up to 12 workers belonging to three functionally distinct groups: excavators, several short-distance carriers that dropped the collected pellets after a few centimetres, and long-distance, last carriers that reached the final deposition site. When initiating a new excavation, the proportion of long-distance carriers increased from 18% to 45% within the first five hours, and remained unchanged over more than 20 hours. Accumulated, freshly-excavated pellets significantly influenced the workers' decision where to start digging in a choice experiment. Thus, pellets temporarily accumulated as a result of their sequential transport provide cues that spatially organise collective nest excavation.
Sookhak Lari, Kaveh; Johnston, Colin D; Rayner, John L; Davis, Greg B
2018-03-05
Remediation of subsurface systems, including groundwater, soil and soil gas, contaminated with light non-aqueous phase liquids (LNAPLs) is challenging. Field-scale pilot trials of multi-phase remediation were undertaken at a site to determine the effectiveness of recovery options. Sequential LNAPL skimming and vacuum-enhanced skimming, with and without water table drawdown were trialled over 78days; in total extracting over 5m 3 of LNAPL. For the first time, a multi-component simulation framework (including the multi-phase multi-component code TMVOC-MP and processing codes) was developed and applied to simulate the broad range of multi-phase remediation and recovery methods used in the field trials. This framework was validated against the sequential pilot trials by comparing predicted and measured LNAPL mass removal rates and compositional changes. The framework was tested on both a Cray supercomputer and a cluster. Simulations mimicked trends in LNAPL recovery rates (from 0.14 to 3mL/s) across all remediation techniques each operating over periods of 4-14days over the 78day trial. The code also approximated order of magnitude compositional changes of hazardous chemical concentrations in extracted gas during vacuum-enhanced recovery. The verified framework enables longer term prediction of the effectiveness of remediation approaches allowing better determination of remediation endpoints and long-term risks. Copyright © 2017 Commonwealth Scientific and Industrial Research Organisation. Published by Elsevier B.V. All rights reserved.
Sequential analysis applied to clinical trials in dentistry: a systematic review.
Bogowicz, P; Flores-Mir, C; Major, P W; Heo, G
2008-01-01
Clinical trials employ sequential analysis for the ethical and economic benefits it brings. In dentistry, as in other fields, resources are scarce and efforts are made to ensure that patients are treated ethically. The objective of this systematic review was to characterise the use of sequential analysis for clinical trials in dentistry. We searched various databases from 1900 through to January 2008. Articles were selected for review if they were clinical trials in the field of dentistry that had applied some form of sequential analysis. Selection was carried out independently by two of the authors. We included 18 trials from various specialties, which involved many different interventions. We conclude that sequential analysis seems to be underused in this field but that there are sufficient methodological resources in place for future applications.Evidence-Based Dentistry (2008) 9, 55-62. doi:10.1038/sj.ebd.6400587.
Li, Guoqi; Deng, Lei; Wang, Dong; Wang, Wei; Zeng, Fei; Zhang, Ziyang; Li, Huanglong; Song, Sen; Pei, Jing; Shi, Luping
2016-01-01
Chunking refers to a phenomenon whereby individuals group items together when performing a memory task to improve the performance of sequential memory. In this work, we build a bio-plausible hierarchical chunking of sequential memory (HCSM) model to explain why such improvement happens. We address this issue by linking hierarchical chunking with synaptic plasticity and neuromorphic engineering. We uncover that a chunking mechanism reduces the requirements of synaptic plasticity since it allows applying synapses with narrow dynamic range and low precision to perform a memory task. We validate a hardware version of the model through simulation, based on measured memristor behavior with narrow dynamic range in neuromorphic circuits, which reveals how chunking works and what role it plays in encoding sequential memory. Our work deepens the understanding of sequential memory and enables incorporating it for the investigation of the brain-inspired computing on neuromorphic architecture. PMID:28066223
DOE Office of Scientific and Technical Information (OSTI.GOV)
Man, Jun; Zhang, Jiangjiang; Li, Weixuan
2016-10-01
The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees ofmore » freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.« less
Effects of scalding method and sequential tanks on broiler processing wastewater loadings
USDA-ARS?s Scientific Manuscript database
The effects of scalding time and temperature, and sequential scalding tanks was evaluated based on impact to poultry processing wastewater (PPW) stream loading rates following the slaughter of commercially raised broilers. On 3 separate weeks (trials), broilers were obtained following feed withdrawa...
A Systematic Approach to Subgroup Classification in Intellectual Disability
ERIC Educational Resources Information Center
Schalock, Robert L.; Luckasson, Ruth
2015-01-01
This article describes a systematic approach to subgroup classification based on a classification framework and sequential steps involved in the subgrouping process. The sequential steps are stating the purpose of the classification, identifying the classification elements, using relevant information, and using clearly stated and purposeful…
C-learning: A new classification framework to estimate optimal dynamic treatment regimes.
Zhang, Baqun; Zhang, Min
2017-12-11
A dynamic treatment regime is a sequence of decision rules, each corresponding to a decision point, that determine that next treatment based on each individual's own available characteristics and treatment history up to that point. We show that identifying the optimal dynamic treatment regime can be recast as a sequential optimization problem and propose a direct sequential optimization method to estimate the optimal treatment regimes. In particular, at each decision point, the optimization is equivalent to sequentially minimizing a weighted expected misclassification error. Based on this classification perspective, we propose a powerful and flexible C-learning algorithm to learn the optimal dynamic treatment regimes backward sequentially from the last stage until the first stage. C-learning is a direct optimization method that directly targets optimizing decision rules by exploiting powerful optimization/classification techniques and it allows incorporation of patient's characteristics and treatment history to improve performance, hence enjoying advantages of both the traditional outcome regression-based methods (Q- and A-learning) and the more recent direct optimization methods. The superior performance and flexibility of the proposed methods are illustrated through extensive simulation studies. © 2017, The International Biometric Society.
Schneider, Francine; de Vries, Hein; van Osch, Liesbeth ADM; van Nierop, Peter WM; Kremers, Stef PJ
2012-01-01
Background Unhealthy lifestyle behaviors often co-occur and are related to chronic diseases. One effective method to change multiple lifestyle behaviors is web-based computer tailoring. Dropout from Internet interventions, however, is rather high, and it is challenging to retain participants in web-based tailored programs, especially programs targeting multiple behaviors. To date, it is unknown how much information people can handle in one session while taking part in a multiple behavior change intervention, which could be presented either sequentially (one behavior at a time) or simultaneously (all behaviors at once). Objectives The first objective was to compare dropout rates of 2 computer-tailored interventions: a sequential and a simultaneous strategy. The second objective was to assess which personal characteristics are associated with completion rates of the 2 interventions. Methods Using an RCT design, demographics, health status, physical activity, vegetable consumption, fruit consumption, alcohol intake, and smoking were self-assessed through web-based questionnaires among 3473 adults, recruited through Regional Health Authorities in the Netherlands in the autumn of 2009. First, a health risk appraisal was offered, indicating whether respondents were meeting the 5 national health guidelines. Second, psychosocial determinants of the lifestyle behaviors were assessed and personal advice was provided, about one or more lifestyle behaviors. Results Our findings indicate a high non-completion rate for both types of intervention (71.0%; n = 2167), with more incompletes in the simultaneous intervention (77.1%; n = 1169) than in the sequential intervention (65.0%; n = 998). In both conditions, discontinuation was predicted by a lower age (sequential condition: OR = 1.04; P < .001; CI = 1.02-1.05; simultaneous condition: OR = 1.04; P < .001; CI = 1.02-1.05) and an unhealthy lifestyle (sequential condition: OR = 0.86; P = .01; CI = 0.76-0.97; simultaneous condition: OR = 0.49; P < .001; CI = 0.42-0.58). In the sequential intervention, being male (OR = 1.27; P = .04; CI = 1.01-1.59) also predicted dropout. When respondents failed to adhere to at least 2 of the guidelines, those receiving the simultaneous intervention were more inclined to drop out than were those receiving the sequential intervention. Conclusion Possible reasons for the higher dropout rate in our simultaneous intervention may be the amount of time required and information overload. Strategies to optimize program completion as well as continued use of computer-tailored interventions should be studied. Trial Registration Dutch Trial Register NTR2168 PMID:22403770
Schulz, Daniela N; Schneider, Francine; de Vries, Hein; van Osch, Liesbeth A D M; van Nierop, Peter W M; Kremers, Stef P J
2012-03-08
Unhealthy lifestyle behaviors often co-occur and are related to chronic diseases. One effective method to change multiple lifestyle behaviors is web-based computer tailoring. Dropout from Internet interventions, however, is rather high, and it is challenging to retain participants in web-based tailored programs, especially programs targeting multiple behaviors. To date, it is unknown how much information people can handle in one session while taking part in a multiple behavior change intervention, which could be presented either sequentially (one behavior at a time) or simultaneously (all behaviors at once). The first objective was to compare dropout rates of 2 computer-tailored interventions: a sequential and a simultaneous strategy. The second objective was to assess which personal characteristics are associated with completion rates of the 2 interventions. Using an RCT design, demographics, health status, physical activity, vegetable consumption, fruit consumption, alcohol intake, and smoking were self-assessed through web-based questionnaires among 3473 adults, recruited through Regional Health Authorities in the Netherlands in the autumn of 2009. First, a health risk appraisal was offered, indicating whether respondents were meeting the 5 national health guidelines. Second, psychosocial determinants of the lifestyle behaviors were assessed and personal advice was provided, about one or more lifestyle behaviors. Our findings indicate a high non-completion rate for both types of intervention (71.0%; n = 2167), with more incompletes in the simultaneous intervention (77.1%; n = 1169) than in the sequential intervention (65.0%; n = 998). In both conditions, discontinuation was predicted by a lower age (sequential condition: OR = 1.04; P < .001; CI = 1.02-1.05; simultaneous condition: OR = 1.04; P < .001; CI = 1.02-1.05) and an unhealthy lifestyle (sequential condition: OR = 0.86; P = .01; CI = 0.76-0.97; simultaneous condition: OR = 0.49; P < .001; CI = 0.42-0.58). In the sequential intervention, being male (OR = 1.27; P = .04; CI = 1.01-1.59) also predicted dropout. When respondents failed to adhere to at least 2 of the guidelines, those receiving the simultaneous intervention were more inclined to drop out than were those receiving the sequential intervention. Possible reasons for the higher dropout rate in our simultaneous intervention may be the amount of time required and information overload. Strategies to optimize program completion as well as continued use of computer-tailored interventions should be studied. Dutch Trial Register NTR2168.
Liu, Zhao; Zhu, Yunhong; Wu, Chenxue
2016-01-01
Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users’ privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified. PMID:27508502
Description and effects of sequential behavior practice in teacher education.
Sharpe, T; Lounsbery, M; Bahls, V
1997-09-01
This study examined the effects of a sequential behavior feedback protocol on the practice-teaching experiences of undergraduate teacher trainees. The performance competencies of teacher trainees were analyzed using an alternative opportunities for appropriate action measure. Data support the added utility of sequential (Sharpe, 1997a, 1997b) behavior analysis information in systematic observation approaches to teacher education. One field-based undergraduate practicum using sequential behavior (i.e., field systems analysis) principles was monitored. Summarized are the key elements of the (a) classroom instruction provided as a precursor to the practice teaching experience, (b) practice teaching experience, and (c) field systems observation tool used for evaluation and feedback, including multiple-baseline data (N = 4) to support this approach to teacher education. Results point to (a) the strong relationship between sequential behavior feedback and the positive change in four preservice teachers' day-to-day teaching practices in challenging situational contexts, and (b) the relationship between changes in teacher practices and positive changes in the behavioral practices of gymnasium pupils. Sequential behavior feedback was also socially validated by the undergraduate participants and Professional Development School teacher supervisors in the study.
A new similarity index for nonlinear signal analysis based on local extrema patterns
NASA Astrophysics Data System (ADS)
Niknazar, Hamid; Motie Nasrabadi, Ali; Shamsollahi, Mohammad Bagher
2018-02-01
Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By adding time information of local extrema as well as fuzzifying quantized values, this work proposes a new similarity index for nonlinear and long-term signal analysis, which extends the SBLE method. These new features provide more information about signals and reduce noise sensitivity by fuzzifying them. A number of practical tests were performed to demonstrate the ability of the method in nonlinear signal clustering and classification on synthetic data. In addition, epileptic seizure detection based on electroencephalography (EEG) signal processing was done by the proposed similarity to feature the potentials of the method as a real-world application tool.
[Glossary of terms used by radiologists in image processing].
Rolland, Y; Collorec, R; Bruno, A; Ramée, A; Morcet, N; Haigron, P
1995-01-01
We give the definition of 166 words used in image processing. Adaptivity, aliazing, analog-digital converter, analysis, approximation, arc, artifact, artificial intelligence, attribute, autocorrelation, bandwidth, boundary, brightness, calibration, class, classification, classify, centre, cluster, coding, color, compression, contrast, connectivity, convolution, correlation, data base, decision, decomposition, deconvolution, deduction, descriptor, detection, digitization, dilation, discontinuity, discretization, discrimination, disparity, display, distance, distorsion, distribution dynamic, edge, energy, enhancement, entropy, erosion, estimation, event, extrapolation, feature, file, filter, filter floaters, fitting, Fourier transform, frequency, fusion, fuzzy, Gaussian, gradient, graph, gray level, group, growing, histogram, Hough transform, Houndsfield, image, impulse response, inertia, intensity, interpolation, interpretation, invariance, isotropy, iterative, JPEG, knowledge base, label, laplacian, learning, least squares, likelihood, matching, Markov field, mask, matching, mathematical morphology, merge (to), MIP, median, minimization, model, moiré, moment, MPEG, neural network, neuron, node, noise, norm, normal, operator, optical system, optimization, orthogonal, parametric, pattern recognition, periodicity, photometry, pixel, polygon, polynomial, prediction, pulsation, pyramidal, quantization, raster, reconstruction, recursive, region, rendering, representation space, resolution, restoration, robustness, ROC, thinning, transform, sampling, saturation, scene analysis, segmentation, separable function, sequential, smoothing, spline, split (to), shape, threshold, tree, signal, speckle, spectrum, spline, stationarity, statistical, stochastic, structuring element, support, syntaxic, synthesis, texture, truncation, variance, vision, voxel, windowing.
Unsteady, one-dimensional gas dynamics computations using a TVD type sequential solver
NASA Technical Reports Server (NTRS)
Thakur, Siddharth; Shyy, Wei
1992-01-01
The efficacy of high resolution convection schemes to resolve sharp gradient in unsteady, 1D flows is examined using the TVD concept based on a sequential solution algorithm. Two unsteady flow problems are considered which include the problem involving the interaction of the various waves in a shock tube with closed reflecting ends and the problem involving the unsteady gas dynamics in a tube with closed ends subject to an initial pressure perturbation. It is concluded that high accuracy convection schemes in a sequential solution framework are capable of resolving discontinuities in unsteady flows involving complex gas dynamics. However, a sufficient amount of dissipation is required to suppress oscillations near discontinuities in the sequential approach, which leads to smearing of the solution profiles.
Statistical Feature Extraction for Artifact Removal from Concurrent fMRI-EEG Recordings
Liu, Zhongming; de Zwart, Jacco A.; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H.
2011-01-01
We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphases are directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use a channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable by the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. PMID:22036675
Hughes, Robert W; Marsh, John E; Jones, Dylan M
2011-11-01
In two experiments, we examined the impact of the degree of match between sequential auditory perceptual organization processes and the demands of a short-term memory task (memory for order vs. item information). When a spoken sequence of digits was presented so as to promote its perceptual partitioning into two distinct streams by conveying it in alternating female (F) and male (M) voices (FMFMFMFM)--thereby disturbing the perception of true temporal order--recall of item order was greatly impaired (as compared to recall of item identity). Moreover, an order error type consistent with the formation of voice-based streams was committed more quickly in the alternating-voice condition (Exp. 1). In contrast, when the perceptual organization of the sequence mapped well onto an optimal two-group serial rehearsal strategy--by presenting the two voices in discrete clusters (FFFFMMMM)--order, but not item, recall was enhanced (Exp. 2). The results are consistent with the view that the degree of compatibility between perceptual and deliberate sequencing processes is a key determinant of serial short-term memory performance. Alternative accounts of talker variability effects in short-term memory, based on the concept of a dedicated phonological short-term store and a capacity-limited focus of attention, are also reviewed.
Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.
Liu, Zhongming; de Zwart, Jacco A; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H
2012-02-01
We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphasis is directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac timing markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable with the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. Published by Elsevier Inc.
NASA Astrophysics Data System (ADS)
Roche-Lima, Abiel; Thulasiram, Ruppa K.
2012-02-01
Finite automata, in which each transition is augmented with an output label in addition to the familiar input label, are considered finite-state transducers. Transducers have been used to analyze some fundamental issues in bioinformatics. Weighted finite-state transducers have been proposed to pairwise alignments of DNA and protein sequences; as well as to develop kernels for computational biology. Machine learning algorithms for conditional transducers have been implemented and used for DNA sequence analysis. Transducer learning algorithms are based on conditional probability computation. It is calculated by using techniques, such as pair-database creation, normalization (with Maximum-Likelihood normalization) and parameters optimization (with Expectation-Maximization - EM). These techniques are intrinsically costly for computation, even worse when are applied to bioinformatics, because the databases sizes are large. In this work, we describe a parallel implementation of an algorithm to learn conditional transducers using these techniques. The algorithm is oriented to bioinformatics applications, such as alignments, phylogenetic trees, and other genome evolution studies. Indeed, several experiences were developed using the parallel and sequential algorithm on Westgrid (specifically, on the Breeze cluster). As results, we obtain that our parallel algorithm is scalable, because execution times are reduced considerably when the data size parameter is increased. Another experience is developed by changing precision parameter. In this case, we obtain smaller execution times using the parallel algorithm. Finally, number of threads used to execute the parallel algorithm on the Breezy cluster is changed. In this last experience, we obtain as result that speedup is considerably increased when more threads are used; however there is a convergence for number of threads equal to or greater than 16.
Choi, Youngshim; Hur, Cheol-Goo; Park, Taesun
2013-01-01
The pathophysiological mechanisms underlying the development of obesity and metabolic diseases are not well understood. To gain more insight into the genetic mediators associated with the onset and progression of diet-induced obesity and metabolic diseases, we studied the molecular changes in response to a high-fat diet (HFD) by using a mode-of-action by network identification (MNI) analysis. Oligo DNA microarray analysis was performed on visceral and subcutaneous adipose tissues and muscles of male C57BL/6N mice fed a normal diet or HFD for 2, 4, 8, and 12 weeks. Each of these data was queried against the MNI algorithm, and the lists of top 5 highly ranked genes and gene ontology (GO)-annotated pathways that were significantly overrepresented among the 100 highest ranked genes at each time point in the 3 different tissues of mice fed the HFD were considered in the present study. The 40 highest ranked genes identified by MNI analysis at each time point in the different tissues of mice with diet-induced obesity were subjected to clustering based on their temporal patterns. On the basis of the above-mentioned results, we investigated the sequential induction of distinct olfactory receptors and the stimulation of cancer-related genes during the development of obesity in both adipose tissues and muscles. The top 5 genes recognized using the MNI analysis at each time point and gene cluster identified based on their temporal patterns in the peripheral tissues of mice provided novel and often surprising insights into the potential genetic mediators for obesity progression.
Maheshwari, Priya; Dutta, D; Muthulakshmi, T; Chakraborty, B; Raje, N; Pujari, P K
2017-02-08
The desorption mechanism of water from the hydrophilic mesopores of MCM-41 was studied using positron annihilation lifetime spectroscopy (PALS) and attenuated total reflection Fourier transform infrared spectroscopy supplemented with molecular dynamics (MD) simulation. PALS results indicated that water molecules do not undergo sequential evaporation in a simple layer-by-layer manner during desorption from MCM-41 mesopores. The results suggested that the water column inside the uniform cylindrical mesopore become stretched during desorption and induces cavitation (as seen in the case of ink-bottle type pores) inside it, keeping a dense water layer at the hydrophilic pore wall, as well as a water plug at both the open ends of the cylindrical pore, until the water was reduced to a certain volume fraction where the pore catastrophically empties. Before being emptied, the water molecules formed clusters inside the mesopores. The formation of molecular clusters below a certain level of hydration was corroborated by the MD simulation study. The results are discussed.
NASA Astrophysics Data System (ADS)
Siegel, Z.; Siegel, Edward Carl-Ludwig
2011-03-01
RANDOMNESS of Numbers cognitive-semantics DEFINITION VIA Cognition QUERY: WHAT???, NOT HOW?) VS. computer-``science" mindLESS number-crunching (Harrel-Sipser-...) algorithmics Goldreich "PSEUDO-randomness"[Not.AMS(02)] mea-culpa is ONLY via MAXWELL-BOLTZMANN CLASSICAL-STATISTICS(NOT FDQS!!!) "hot-plasma" REPULSION VERSUS Newcomb(1881)-Weyl(1914;1916)-Benford(1938) "NeWBe" logarithmic-law digit-CLUMPING/ CLUSTERING NON-Randomness simple Siegel[AMS Joint.Mtg.(02)-Abs. # 973-60-124] algebraic-inversion to THE QUANTUM and ONLY BEQS preferentially SEQUENTIALLY lower-DIGITS CLUMPING/CLUSTERING with d = 0 BEC, is ONLY VIA Siegel-Baez FUZZYICS=CATEGORYICS (SON OF TRIZ)/"Category-Semantics"(C-S), latter intersection/union of Lawvere(1964)-Siegel(1964)] category-theory (matrix: MORPHISMS V FUNCTORS) "+" cognitive-semantics'' (matrix: ANTONYMS V SYNONYMS) yields Siegel-Baez FUZZYICS=CATEGORYICS/C-S tabular list-format matrix truth-table analytics: MBCS RANDOMNESS TRUTH/EMET!!!
Hayashi, Koichiro; Nakamura, Michihiro; Miki, Hirokazu; Ozaki, Shuji; Abe, Masahiro; Matsumoto, Toshio; Sakamoto, Wataru; Yogo, Toshinobu; Ishimura, Kazunori
2014-01-01
We report the synthesis of smart nanoparticles (NPs) that generate heat in response to an alternating current magnetic field (ACMF) and that sequentially release an anticancer drug (doxorubicin, DOX). We further study the in vivo therapeutic efficacy of the combination of magnetic hyperthermia (MHT) and chemotherapy using the smart NPs for the treatment of multiple myeloma. The smart NPs are composed of a polymer with a glass-transition temperature (T g) of 44°C, which contains clustered Fe3O4 NPs and DOX. The clustered Fe3O4 NPs produce heat when the ACMF is applied and rise above 44°C, which softens the polymer phase and leads to the release of DOX. The combination of MHT and chemotherapy using the smart NPs destroys cancer cells in the entire tumor and achieves a complete cure in one treatment without the recurrence of malignancy. Furthermore, the smart NPs have no significant toxicity.
Multi-Target State Extraction for the SMC-PHD Filter
Si, Weijian; Wang, Liwei; Qu, Zhiyu
2016-01-01
The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated to be a favorable method for multi-target tracking. However, the time-varying target states need to be extracted from the particle approximation of the posterior PHD, which is difficult to implement due to the unknown relations between the large amount of particles and the PHD peaks representing potential target locations. To address this problem, a novel multi-target state extraction algorithm is proposed in this paper. By exploiting the information of measurements and particle likelihoods in the filtering stage, we propose a validation mechanism which aims at selecting effective measurements and particles corresponding to detected targets. Subsequently, the state estimates of the detected and undetected targets are performed separately: the former are obtained from the particle clusters directed by effective measurements, while the latter are obtained from the particles corresponding to undetected targets via clustering method. Simulation results demonstrate that the proposed method yields better estimation accuracy and reliability compared to existing methods. PMID:27322274
NASA Astrophysics Data System (ADS)
Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.
2017-06-01
This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.
Fang, Yuyu; Li, Caixia; Wu, Lei; Bai, Bing; Li, Xing; Jia, Yiming; Feng, Wen; Yuan, Lihua
2015-09-07
A novel non-symmetric pillar[5]arene bearing triazole-linked 8-oxyquinolines at one rim was synthesized and demonstrated as a sequential fluorescence sensor for thorium(iv) followed by fluoride ions with high sensitivity and selectivity.
Bedroom Rape: Sequences of Sexual Behavior in Stranger Assaults
ERIC Educational Resources Information Center
Fossi, Julia J.; Clarke, David D.; Lawrence, Claire
2005-01-01
This article examines the sequential, temporal, and interactional aspects of sexual assaults using sequential analysis. Fourteen statements taken from victims of bedroom-based assaults were analyzed to provide a comprehensive account of the behavioral patterns of individuals in sexually charged conflict situations. The cases were found to vary in…
Kim, Y S; Kim, S J; Yoon, J H; Suk, K T; Kim, J B; Kim, D J; Kim, D Y; Min, H J; Park, S H; Shin, W G; Kim, K H; Kim, H Y; Baik, G H
2011-11-01
The eradication rates of Helicobacter pylori (H. pylori) using a proton pump inhibitor (PPI)-based triple therapy have declined due to antibiotic resistance worldwide. To compare the eradication rate of the 10-day sequential therapy for H. pylori infection with that of the 14-day standard PPI-based triple therapy. This was a prospective, randomised, controlled study. A total of 409 patients with H. pylori infection were randomly assigned to receive either the 10-day sequential therapy regimen, which consisted of pantoprazole (40 mg) plus amoxicillin (1000 mg) twice a day for 5 days, then pantoprazole (40 mg) with clarithromycin (500 mg) and metronidazole (500 mg) twice a day for another five consecutive days or the 14-day PPI-based triple therapy regimen, which consisted of pantoprazole (40 mg) with amoxicillin (1000 mg) and clarithromycin (500 mg) twice a day for 14 days. The pre- and post-treatment H. pylori status were assessed by rapid urease test, urea breath test, or histology. Successful eradication was confirmed at least 4 weeks after finishing the treatment. In the intention-to-treat analysis, the eradication rates of the 10-day sequential therapy and of the 14-day PPI-based triple therapy were 85.9% (176/205) and 75.0% (153/205), respectively (P = 0.006). In the per-protocol analysis, the eradication rates were 92.6% (175/205) and 85% (153/204), respectively (P = 0.019). There was no statistically significant difference between the two investigated groups regarding the occurrence of adverse event rates (18.9% vs. 13.3%, P = 0.143). The 10-day sequential therapy achieved significantly higher eradication rates than the 14-day standard PPI-based triple therapy in Korea. © 2011 Blackwell Publishing Ltd.
Finding False Paths in Sequential Circuits
NASA Astrophysics Data System (ADS)
Matrosova, A. Yu.; Andreeva, V. V.; Chernyshov, S. V.; Rozhkova, S. V.; Kudin, D. V.
2018-02-01
Method of finding false paths in sequential circuits is developed. In contrast with heuristic approaches currently used abroad, the precise method based on applying operations on Reduced Ordered Binary Decision Diagrams (ROBDDs) extracted from the combinational part of a sequential controlling logic circuit is suggested. The method allows finding false paths when transfer sequence length is not more than the given value and obviates the necessity of investigation of combinational circuit equivalents of the given lengths. The possibilities of using of the developed method for more complicated circuits are discussed.
Test pattern generation for ILA sequential circuits
NASA Technical Reports Server (NTRS)
Feng, YU; Frenzel, James F.; Maki, Gary K.
1993-01-01
An efficient method of generating test patterns for sequential machines implemented using one-dimensional, unilateral, iterative logic arrays (ILA's) of BTS pass transistor networks is presented. Based on a transistor level fault model, the method affords a unique opportunity for real-time fault detection with improved fault coverage. The resulting test sets are shown to be equivalent to those obtained using conventional gate level models, thus eliminating the need for additional test patterns. The proposed method advances the simplicity and ease of the test pattern generation for a special class of sequential circuitry.
Park, Bo-Yong; Lee, Mi Ji; Lee, Seung-Hak; Cha, Jihoon; Chung, Chin-Sang; Kim, Sung Tae; Park, Hyunjin
2018-01-01
Migraineurs show an increased load of white matter hyperintensities (WMHs) and more rapid deep WMH progression. Previous methods for WMH segmentation have limited efficacy to detect small deep WMHs. We developed a new fully automated detection pipeline, DEWS (DEep White matter hyperintensity Segmentation framework), for small and superficially-located deep WMHs. A total of 148 non-elderly subjects with migraine were included in this study. The pipeline consists of three components: 1) white matter (WM) extraction, 2) WMH detection, and 3) false positive reduction. In WM extraction, we adjusted the WM mask to re-assign misclassified WMHs back to WM using many sequential low-level image processing steps. In WMH detection, the potential WMH clusters were detected using an intensity based threshold and region growing approach. For false positive reduction, the detected WMH clusters were classified into final WMHs and non-WMHs using the random forest (RF) classifier. Size, texture, and multi-scale deep features were used to train the RF classifier. DEWS successfully detected small deep WMHs with a high positive predictive value (PPV) of 0.98 and true positive rate (TPR) of 0.70 in the training and test sets. Similar performance of PPV (0.96) and TPR (0.68) was attained in the validation set. DEWS showed a superior performance in comparison with other methods. Our proposed pipeline is freely available online to help the research community in quantifying deep WMHs in non-elderly adults.
SOTXTSTREAM: Density-based self-organizing clustering of text streams.
Bryant, Avory C; Cios, Krzysztof J
2017-01-01
A streaming data clustering algorithm is presented building upon the density-based self-organizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based) density determinations. Additionally, many stream clustering algorithms use a two-phase clustering approach. In the first phase, a micro-clustering solution is maintained online, while in the second phase, the micro-clustering solution is clustered offline to produce a macro solution. By performing self-organization techniques on micro-clusters in the online phase, SOSTREAM is able to maintain a macro clustering solution in a single phase. Leveraging concepts from SOSTREAM, a new density-based self-organizing text stream clustering algorithm, SOTXTSTREAM, is presented that addresses several shortcomings of SOSTREAM. Gains in clustering performance of this new algorithm are demonstrated on several real-world text stream datasets.
Wittfoth, Matthias; Buck, Daniela; Fahle, Manfred; Herrmann, Manfred
2006-08-15
The present study aimed at characterizing the neural correlates of conflict resolution in two variations of the Simon effect. We introduced two different Simon tasks where subjects had to identify shapes on the basis of form-from-motion perception (FFMo) within a randomly moving dot field, while (1) motion direction (motion-based Simon task) or (2) stimulus location (location-based Simon task) had to be ignored. Behavioral data revealed that both types of Simon tasks induced highly significant interference effects. Using event-related fMRI, we could demonstrate that both tasks share a common cluster of activated brain regions during conflict resolution (pre-supplementary motor area (pre-SMA), superior parietal lobule (SPL), and cuneus) but also show task-specific activation patterns (left superior temporal cortex in the motion-based, and the left fusiform gyrus in the location-based Simon task). Although motion-based and location-based Simon tasks are conceptually very similar (Type 3 stimulus-response ensembles according to the taxonomy of [Kornblum, S., Stevens, G. (2002). Sequential effects of dimensional overlap: findings and issues. In: Prinz, W., Hommel., B. (Eds.), Common mechanism in perception and action. Oxford University Press, Oxford, pp. 9-54]) conflict resolution in both tasks results in the activation of different task-specific regions probably related to the different sources of task-irrelevant information. Furthermore, the present data give evidence those task-specific regions are most likely to detect the relationship between task-relevant and task-irrelevant information.
Sequential Multiplex Analyte Capturing for Phosphoprotein Profiling*
Poetz, Oliver; Henzler, Tanja; Hartmann, Michael; Kazmaier, Cornelia; Templin, Markus F.; Herget, Thomas; Joos, Thomas O.
2010-01-01
Microarray-based sandwich immunoassays can simultaneously detect dozens of proteins. However, their use in quantifying large numbers of proteins is hampered by cross-reactivity and incompatibilities caused by the immunoassays themselves. Sequential multiplex analyte capturing addresses these problems by repeatedly probing the same sample with different sets of antibody-coated, magnetic suspension bead arrays. As a miniaturized immunoassay format, suspension bead array-based assays fulfill the criteria of the ambient analyte theory, and our experiments reveal that the analyte concentrations are not significantly changed. The value of sequential multiplex analyte capturing was demonstrated by probing tumor cell line lysates for the abundance of seven different receptor tyrosine kinases and their degree of phosphorylation and by measuring the complex phosphorylation pattern of the epidermal growth factor receptor in the same sample from the same cavity. PMID:20682761
NASA Astrophysics Data System (ADS)
Dickens, J. K.
1991-04-01
The organic scintillation detector response code SCINFUL has been used to compute secondary-particle energy spectra, d(sigma)/dE, following nonelastic neutron interactions with C-12 for incident neutron energies between 15 and 60 MeV. The resulting spectra are compared with published similar spectra computed by Brenner and Prael who used an intranuclear cascade code, including alpha clustering, a particle pickup mechanism, and a theoretical approach to sequential decay via intermediate particle-unstable states. The similarities of and the differences between the results of the two approaches are discussed.
As-built design specification for proportion estimate software subsystem
NASA Technical Reports Server (NTRS)
Obrien, S. (Principal Investigator)
1980-01-01
The Proportion Estimate Processor evaluates four estimation techniques in order to get an improved estimate of the proportion of a scene that is planted in a selected crop. The four techniques to be evaluated were provided by the techniques development section and are: (1) random sampling; (2) proportional allocation, relative count estimate; (3) proportional allocation, Bayesian estimate; and (4) sequential Bayesian allocation. The user is given two options for computation of the estimated mean square error. These are referred to as the cluster calculation option and the segment calculation option. The software for the Proportion Estimate Processor is operational on the IBM 3031 computer.
Sequential enzymatic epoxidation involved in polyether lasalocid biosynthesis.
Minami, Atsushi; Shimaya, Mayu; Suzuki, Gaku; Migita, Akira; Shinde, Sandip S; Sato, Kyohei; Watanabe, Kenji; Tamura, Tomohiro; Oguri, Hiroki; Oikawa, Hideaki
2012-05-02
Enantioselective epoxidation followed by regioselective epoxide opening reaction are the key processes in construction of the polyether skeleton. Recent genetic analysis of ionophore polyether biosynthetic gene clusters suggested that flavin-containing monooxygenases (FMOs) could be involved in the oxidation steps. In vivo and in vitro analyses of Lsd18, an FMO involved in the biosynthesis of polyether lasalocid, using simple olefin or truncated diene of a putative substrate as substrate mimics demonstrated that enantioselective epoxidation affords natural type mono- or bis-epoxide in a stepwise manner. These findings allow us to figure out enzymatic polyether construction in lasalocid biosynthesis. © 2012 American Chemical Society
Parobek, Christian M.; Parr, Jonathan B.; Brazeau, Nicholas F.; Lon, Chanthap; Chaorattanakawee, Suwanna; Gosi, Panita; Barnett, Eric J.; Norris, Lauren D.; Meshnick, Steven R.; Spring, Michele D.; Lanteri, Charlotte A.; Bailey, Jeffrey A.; Saunders, David L.; Lin, Jessica T.
2017-01-01
Abstract Plasmodium falciparum in western Cambodia has developed resistance to artemisinin and its partner drugs, causing frequent treatment failure. Understanding this evolution can inform the deployment of new therapies. We investigated the genetic architecture of 78 falciparum isolates using whole-genome sequencing, correlating results to in vivo and ex vivo drug resistance and exploring the relationship between population structure, demographic history, and partner drug resistance. Principle component analysis, network analysis and demographic inference identified a diverse central population with three clusters of clonally expanding parasite populations, each associated with specific K13 artemisinin resistance alleles and partner drug resistance profiles which were consistent with the sequential deployment of artemisinin combination therapies in the region. One cluster displayed ex vivo piperaquine resistance and mefloquine sensitivity with a high rate of in vivo failure of dihydroartemisinin-piperaquine. Another cluster displayed ex vivo mefloquine resistance and piperaquine sensitivity with high in vivo efficacy of dihydroartemisinin-piperaquine. The final cluster was clonal and displayed intermediate sensitivity to both drugs. Variations in recently described piperaquine resistance markers did not explain the difference in mean IC90 or clinical failures between the high and intermediate piperaquine resistance groups, suggesting additional loci may be involved in resistance. The results highlight an important role for partner drug resistance in shaping the P. falciparum genetic landscape in Southeast Asia and suggest that further work is needed to evaluate for other mutations that drive piperaquine resistance. PMID:28854635
Rezzonico, Fabio; Smits, Theo H. M.; Duffy, Brion
2011-01-01
The clustered regularly interspaced short palindromic repeat (CRISPR)/Cas system confers acquired heritable immunity against mobile nucleic acid elements in prokaryotes, limiting phage infection and horizontal gene transfer of plasmids. In CRISPR arrays, characteristic repeats are interspersed with similarly sized nonrepetitive spacers derived from transmissible genetic elements and acquired when the cell is challenged with foreign DNA. New spacers are added sequentially and the number and type of CRISPR units can differ among strains, providing a record of phage/plasmid exposure within a species and giving a valuable typing tool. The aim of this work was to investigate CRISPR diversity in the highly homogeneous species Erwinia amylovora, the causal agent of fire blight. A total of 18 CRISPR genotypes were defined within a collection of 37 cosmopolitan strains. Strains from Spiraeoideae plants clustered in three major groups: groups II and III were composed exclusively of bacteria originating from the United States, whereas group I generally contained strains of more recent dissemination obtained in Europe, New Zealand, and the Middle East. Strains from Rosoideae and Indian hawthorn (Rhaphiolepis indica) clustered separately and displayed a higher intrinsic diversity than that of isolates from Spiraeoideae plants. Reciprocal exclusion was generally observed between plasmid content and cognate spacer sequences, supporting the role of the CRISPR/Cas system in protecting against foreign DNA elements. However, in several group III strains, retention of plasmid pEU30 is inconsistent with a functional CRISPR/Cas system. PMID:21460108
Rezzonico, Fabio; Smits, Theo H M; Duffy, Brion
2011-06-01
The clustered regularly interspaced short palindromic repeat (CRISPR)/Cas system confers acquired heritable immunity against mobile nucleic acid elements in prokaryotes, limiting phage infection and horizontal gene transfer of plasmids. In CRISPR arrays, characteristic repeats are interspersed with similarly sized nonrepetitive spacers derived from transmissible genetic elements and acquired when the cell is challenged with foreign DNA. New spacers are added sequentially and the number and type of CRISPR units can differ among strains, providing a record of phage/plasmid exposure within a species and giving a valuable typing tool. The aim of this work was to investigate CRISPR diversity in the highly homogeneous species Erwinia amylovora, the causal agent of fire blight. A total of 18 CRISPR genotypes were defined within a collection of 37 cosmopolitan strains. Strains from Spiraeoideae plants clustered in three major groups: groups II and III were composed exclusively of bacteria originating from the United States, whereas group I generally contained strains of more recent dissemination obtained in Europe, New Zealand, and the Middle East. Strains from Rosoideae and Indian hawthorn (Rhaphiolepis indica) clustered separately and displayed a higher intrinsic diversity than that of isolates from Spiraeoideae plants. Reciprocal exclusion was generally observed between plasmid content and cognate spacer sequences, supporting the role of the CRISPR/Cas system in protecting against foreign DNA elements. However, in several group III strains, retention of plasmid pEU30 is inconsistent with a functional CRISPR/Cas system.
Theoretical study of the NMR chemical shift of Xe in supercritical condition.
Lacerda, Evanildo G; Sauer, Stephan P A; Mikkelsen, Kurt V; Coutinho, Kaline; Canuto, Sylvio
2018-02-20
In this work we investigate the level of theory necessary for reproducing the non-linear variation of the 129 Xe nuclear magnetic resonance (NMR) chemical shift with the density of Xe in supercritical conditions. In detail we study how the 129 Xe chemical shift depends under supercritical conditions on electron correlation, relativistic and many-body effects. The latter are included using a sequential-QM/MM methodology, in which a classical MD simulation is performed first and the chemical shift is then obtained as an average of quantum calculations of 250 MD snapshots conformations carried out for Xe n clusters (n = 2 - 8 depending on the density). The analysis of the relativistic effects is made at the level of 4-component Hartree-Fock calculations (4c-HF) and electron correlation effects are considered using second order Møller-Plesset perturbation theory (MP2). To simplify the calculations of the relativistic and electron correlation effects we adopted an additive scheme, where the calculations on the Xe n clusters are carried out at the non-relativistic Hartree-Fock (HF) level, while electron correlation and relativistic corrections are added for all the pairs of Xe atoms in the clusters. Using this approach we obtain very good agreement with the experimental data, showing that the chemical shift of 129 Xe in supercritical conditions is very well described by cluster calculations at the HF level, with small contributions from relativistic and electron correlation effects.
ERIC Educational Resources Information Center
Heil, Leila
2017-01-01
This article describes a sequential approach to improvisation teaching that can be used with students at various age and ability levels by any educator, regardless of improvisation experience. The 2014 National Core Music Standards include improvisation as a central component in musical learning and promote instructional approaches that are…
Sequential Online Wellness Programming Is an Effective Strategy to Promote Behavior Change
ERIC Educational Resources Information Center
MacNab, Lindsay R.; Francis, Sarah L.
2015-01-01
The growing number of United States youth and adults categorized as overweight or obese illustrates a need for research-based family wellness interventions. Sequential, online, Extension-delivered family wellness interventions offer a time- and cost-effective approach for both participants and Extension educators. The 6-week, online Healthy…
Terminating Sequential Delphi Survey Data Collection
ERIC Educational Resources Information Center
Kalaian, Sema A.; Kasim, Rafa M.
2012-01-01
The Delphi survey technique is an iterative mail or electronic (e-mail or web-based) survey method used to obtain agreement or consensus among a group of experts in a specific field on a particular issue through a well-designed and systematic multiple sequential rounds of survey administrations. Each of the multiple rounds of the Delphi survey…
NASA Astrophysics Data System (ADS)
Thamvichai, Ratchaneekorn; Huang, Liang-Chih; Ashok, Amit; Gong, Qian; Coccarelli, David; Greenberg, Joel A.; Gehm, Michael E.; Neifeld, Mark A.
2017-05-01
We employ an adaptive measurement system, based on sequential hypotheses testing (SHT) framework, for detecting material-based threats using experimental data acquired on an X-ray experimental testbed system. This testbed employs 45-degree fan-beam geometry and 15 views over a 180-degree span to generate energy sensitive X-ray projection data. Using this testbed system, we acquire multiple view projection data for 200 bags. We consider an adaptive measurement design where the X-ray projection measurements are acquired in a sequential manner and the adaptation occurs through the choice of the optimal "next" source/view system parameter. Our analysis of such an adaptive measurement design using the experimental data demonstrates a 3x-7x reduction in the probability of error relative to a static measurement design. Here the static measurement design refers to the operational system baseline that corresponds to a sequential measurement using all the available sources/views. We also show that by using adaptive measurements it is possible to reduce the number of sources/views by nearly 50% compared a system that relies on static measurements.
On mining complex sequential data by means of FCA and pattern structures
NASA Astrophysics Data System (ADS)
Buzmakov, Aleksey; Egho, Elias; Jay, Nicolas; Kuznetsov, Sergei O.; Napoli, Amedeo; Raïssi, Chedy
2016-02-01
Nowadays data-sets are available in very complex and heterogeneous ways. Mining of such data collections is essential to support many real-world applications ranging from healthcare to marketing. In this work, we focus on the analysis of "complex" sequential data by means of interesting sequential patterns. We approach the problem using the elegant mathematical framework of formal concept analysis and its extension based on "pattern structures". Pattern structures are used for mining complex data (such as sequences or graphs) and are based on a subsumption operation, which in our case is defined with respect to the partial order on sequences. We show how pattern structures along with projections (i.e. a data reduction of sequential structures) are able to enumerate more meaningful patterns and increase the computing efficiency of the approach. Finally, we show the applicability of the presented method for discovering and analysing interesting patient patterns from a French healthcare data-set on cancer. The quantitative and qualitative results (with annotations and analysis from a physician) are reported in this use-case which is the main motivation for this work.
NASA Astrophysics Data System (ADS)
Dassekpo, Jean-Baptiste Mawulé; Zha, Xiaoxiong; Zhan, Jiapeng; Ning, Jiaqian
Geopolymer is an energy efficient and sustainable material that is currently used in construction industry as an alternative for Portland cement. As a new material, specific mix design method is essential and efforts have been made to develop a mix design procedure with the main focus on achieving better compressive strength and economy. In this paper, a sequential addition of synthesis parameters such as fly ash-sand, alkaline liquids, plasticizer and additional water at well-defined time intervals was investigated. A total of 4 mix procedures were used to study the compressive performance on fly ash-based geopolymer mortar and the results of each method were analyzed and discussed. Experimental results show that the sequential addition of sodium hydroxide (NaOH), sodium silicate (Na2SiO3), plasticizer (PL), followed by adding water (WA) increases considerably the compressive strengths of the geopolymer-based mortar. These results clearly demonstrate the high significant influence of sequential addition of synthesis parameters on geopolymer materials compressive properties, and also provide a new mixing method for the preparation of geopolymer paste, mortar and concrete.
NASA Technical Reports Server (NTRS)
Habibi, A.; Batson, B.
1976-01-01
Space Shuttle will be using a field-sequential color television system for the first few missions, but the present plans are to switch to a NTSC color TV system for future missions. The field-sequential color TV system uses a modified black and white camera, producing a TV signal with a digital bandwidth of about 60 Mbps. This article discusses the characteristics of the Shuttle TV systems and proposes a bandwidth-compression technique for the field-sequential color TV system that could operate at 13 Mbps to produce a high-fidelity signal. The proposed bandwidth-compression technique is based on a two-dimensional DPCM system that utilizes temporal, spectral, and spatial correlation inherent in the field-sequential color TV imagery. The proposed system requires about 60 watts and less than 200 integrated circuits.
Chen, Ching-Hsiang; Sarma, Loka Subramanyam; Chen, Jium-Ming; Shih, Shou-Chu; Wang, Guo-Rung; Liu, Din-Goa; Tang, Mau-Tsu; Lee, Jyh-Fu; Hwang, Bing-Joe
2007-09-01
In this study, we demonstrate the unique application of X-ray absorption spectroscopy (XAS) as a fundamental characterization tool to help in designing and controlling the architecture of Pd-Au bimetallic nanoparticles within a water-in-oil microemulsion system of water/sodium bis(2-ethylhexyl)sulfosuccinate (AOT)/n-heptane. Structural insights obtained from the in situ XAS measurements recorded at each step during the formation process revealed that Pd-Au bimetallic clusters with various Pd-Au atomic stackings are formed by properly performing hydrazine reduction and redox transmetalation reactions sequentially within water-in-oil microemulsions. A structural model is provided to explain reasonably each reaction step and to give detailed insight into the nucleation and growth mechanism of Pd-Au bimetallic clusters. The combination of in situ XAS analysis at both the Pd K-edge and the Au L(III)-edge and UV-vis absorption spectral features confirms that the formation of Pd-Au bimetallic clusters follows a (Pd(nuclei)-Au(stack))-Pd(surf) stacking. This result further implies that the thickness of Au(stack) and Pd(surf) layers may be modulated by varying the dosage of the Au precursor and hydrazine, respectively. In addition, a bimetallic (Pd-Au)(alloy) nanocluster with a (Pd(nuclei)-Au(stack))-(Pd-Au(alloy))(surf) stacking was also designed and synthesized in order to check the feasibility of Pd(surf) layer modification. The result reveals that the Pd(surf) layer of the stacked (Pd(nuclei)-Au)(stack) bimetallic clusters can be successfully modified to form a (Au-Pd alloy)(surf) layer by a co-reduction of Pd and Au ions by hydrazine. Further, we demonstrate the alloying extent or atomic distribution of Pd and Au in Pd-Au bimetallic nanoparticles from the derived XAS structural parameters. The complete XAS-based methodology, demonstrated here on the Pd-Au bimetallic system, can easily be extended to design and control the alloying extent or atomic distribution, atomic stacking, and electronic structure to construct many other types of bimetallic systems for interesting applications.
The sequential structure of brain activation predicts skill.
Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa
2016-01-29
In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.
Are judgments a form of data clustering? Reexamining contrast effects with the k-means algorithm.
Boillaud, Eric; Molina, Guylaine
2015-04-01
A number of theories have been proposed to explain in precise mathematical terms how statistical parameters and sequential properties of stimulus distributions affect category ratings. Various contextual factors such as the mean, the midrange, and the median of the stimuli; the stimulus range; the percentile rank of each stimulus; and the order of appearance have been assumed to influence judgmental contrast. A data clustering reinterpretation of judgmental relativity is offered wherein the influence of the initial choice of centroids on judgmental contrast involves 2 combined frequency and consistency tendencies. Accounts of the k-means algorithm are provided, showing good agreement with effects observed on multiple distribution shapes and with a variety of interaction effects relating to the number of stimuli, the number of response categories, and the method of skewing. Experiment 1 demonstrates that centroid initialization accounts for contrast effects obtained with stretched distributions. Experiment 2 demonstrates that the iterative convergence inherent to the k-means algorithm accounts for the contrast reduction observed across repeated blocks of trials. The concept of within-cluster variance minimization is discussed, as is the applicability of a backward k-means calculation method for inferring, from empirical data, the values of the centroids that would serve as a representation of the judgmental context. (c) 2015 APA, all rights reserved.
NASA Astrophysics Data System (ADS)
Yidana, Sandow Mark; Bawoyobie, Patrick; Sakyi, Patrick; Fynn, Obed Fiifi
2018-02-01
An evolutionary trend has been postulated through the analysis of hydrochemical data of a crystalline rock aquifer system in the Densu Basin, Southern Ghana. Hydrochemcial data from 63 groundwater samples, taken from two main groundwater outlets (Boreholes and hand dug wells) were used to postulate an evolutionary theory for the basin. Sequential factor and hierarchical cluster analysis were used to disintegrate the data into three factors and five clusters (spatial associations). These were used to characterize the controls on groundwater hydrochemistry and its evolution in the terrain. The dissolution of soluble salts and cation exchange processes are the dominant processes controlling groundwater hydrochemistry in the terrain. The trend of evolution of this set of processes follows the pattern of groundwater flow predicted by a calibrated transient groundwater model in the area. The data suggest that anthropogenic activities represent the second most important process in the hydrochemistry. Silicate mineral weathering is the third most important set of processes. Groundwater associations resulting from Q-mode hierarchical cluster analysis indicate an evolutionary pattern consistent with the general groundwater flow pattern in the basin. These key findings are at variance with results of previous investigations and indicate that when carefully done, groundwater hydrochemical data can be very useful for conceptualizing groundwater flow in basins.
Ioannou, Dimitrios; Millan, Nicole M; Jordan, Elizabeth; Tempest, Helen G
2017-01-31
The organization of chromosomes in sperm nuclei has been proposed to possess a unique "hairpin-loop" arrangement, which is hypothesized to aid in the ordered exodus of the paternal genome following fertilization. This study simultaneously assessed the 3D and 2D radial and longitudinal organization of telomeres, centromeres, and investigated whether chromosomes formed the same centromere clusters in sperm cells. Reproducible radial and longitudinal non-random organization was observed for all investigated loci using both 3D and 2D approaches in multiple subjects. We report novel findings, with telomeres and centromeres being localized throughout the nucleus but demonstrating roughly a 1:1 distribution in the nuclear periphery and the intermediate regions with <15% occupying the nuclear interior. Telomeres and centromeres were observed to aggregate in sperm nuclei, forming an average of 20 and 7 clusters, respectively. Reproducible longitudinal organization demonstrated preferential localization of telomeres and centromeres in the mid region of the sperm cell. Preliminary evidence is also provided to support the hypothesis that specific chromosomes preferentially form the same centromere clusters. The more segmental distribution of telomeres and centromeres as described in this study could more readily accommodate and facilitate the sequential exodus of paternal chromosomes following fertilization.
Ioannou, Dimitrios; Millan, Nicole M.; Jordan, Elizabeth; Tempest, Helen G.
2017-01-01
The organization of chromosomes in sperm nuclei has been proposed to possess a unique “hairpin-loop” arrangement, which is hypothesized to aid in the ordered exodus of the paternal genome following fertilization. This study simultaneously assessed the 3D and 2D radial and longitudinal organization of telomeres, centromeres, and investigated whether chromosomes formed the same centromere clusters in sperm cells. Reproducible radial and longitudinal non-random organization was observed for all investigated loci using both 3D and 2D approaches in multiple subjects. We report novel findings, with telomeres and centromeres being localized throughout the nucleus but demonstrating roughly a 1:1 distribution in the nuclear periphery and the intermediate regions with <15% occupying the nuclear interior. Telomeres and centromeres were observed to aggregate in sperm nuclei, forming an average of 20 and 7 clusters, respectively. Reproducible longitudinal organization demonstrated preferential localization of telomeres and centromeres in the mid region of the sperm cell. Preliminary evidence is also provided to support the hypothesis that specific chromosomes preferentially form the same centromere clusters. The more segmental distribution of telomeres and centromeres as described in this study could more readily accommodate and facilitate the sequential exodus of paternal chromosomes following fertilization. PMID:28139771
Locally Weighted Ensemble Clustering.
Huang, Dong; Wang, Chang-Dong; Lai, Jian-Huang
2018-05-01
Due to its ability to combine multiple base clusterings into a probably better and more robust clustering, the ensemble clustering technique has been attracting increasing attention in recent years. Despite the significant success, one limitation to most of the existing ensemble clustering methods is that they generally treat all base clusterings equally regardless of their reliability, which makes them vulnerable to low-quality base clusterings. Although some efforts have been made to (globally) evaluate and weight the base clusterings, yet these methods tend to view each base clustering as an individual and neglect the local diversity of clusters inside the same base clustering. It remains an open problem how to evaluate the reliability of clusters and exploit the local diversity in the ensemble to enhance the consensus performance, especially, in the case when there is no access to data features or specific assumptions on data distribution. To address this, in this paper, we propose a novel ensemble clustering approach based on ensemble-driven cluster uncertainty estimation and local weighting strategy. In particular, the uncertainty of each cluster is estimated by considering the cluster labels in the entire ensemble via an entropic criterion. A novel ensemble-driven cluster validity measure is introduced, and a locally weighted co-association matrix is presented to serve as a summary for the ensemble of diverse clusters. With the local diversity in ensembles exploited, two novel consensus functions are further proposed. Extensive experiments on a variety of real-world datasets demonstrate the superiority of the proposed approach over the state-of-the-art.
Efficient clustering aggregation based on data fragments.
Wu, Ou; Hu, Weiming; Maybank, Stephen J; Zhu, Mingliang; Li, Bing
2012-06-01
Clustering aggregation, known as clustering ensembles, has emerged as a powerful technique for combining different clustering results to obtain a single better clustering. Existing clustering aggregation algorithms are applied directly to data points, in what is referred to as the point-based approach. The algorithms are inefficient if the number of data points is large. We define an efficient approach for clustering aggregation based on data fragments. In this fragment-based approach, a data fragment is any subset of the data that is not split by any of the clustering results. To establish the theoretical bases of the proposed approach, we prove that clustering aggregation can be performed directly on data fragments under two widely used goodness measures for clustering aggregation taken from the literature. Three new clustering aggregation algorithms are described. The experimental results obtained using several public data sets show that the new algorithms have lower computational complexity than three well-known existing point-based clustering aggregation algorithms (Agglomerative, Furthest, and LocalSearch); nevertheless, the new algorithms do not sacrifice the accuracy.
NASA Astrophysics Data System (ADS)
Sigman, John B.; Barrowes, Benjamin E.; O'Neill, Kevin; Shubitidze, Fridon
2013-06-01
This paper details methods for automatic classification of Unexploded Ordnance (UXO) as applied to sensor data from the Spencer Range live site. The Spencer Range is a former military weapons range in Spencer, Tennessee. Electromagnetic Induction (EMI) sensing is carried out using the 5x5 Time-domain Electromagnetic Multi-sensor Towed Array Detection System (5x5 TEMTADS), which has 25 receivers and 25 co-located transmitters. Every transmitter is activated sequentially, each followed by measuring the magnetic field in all 25 receivers, from 100 microseconds to 25 milliseconds. From these data target extrinsic and intrinsic parameters are extracted using the Differential Evolution (DE) algorithm and the Ortho-Normalized Volume Magnetic Source (ONVMS) algorithms, respectively. Namely, the inversion provides x, y, and z locations and a time series of the total ONVMS principal eigenvalues, which are intrinsic properties of the objects. The eigenvalues are fit to a power-decay empirical model, the Pasion-Oldenburg model, providing 3 coefficients (k, b, and g) for each object. The objects are grouped geometrically into variably-sized clusters, in the k-b-g space, using clustering algorithms. Clusters matching a priori characteristics are identified as Targets of Interest (TOI), and larger clusters are automatically subclustered. Ground Truths (GT) at the center of each class are requested, and probability density functions are created for clusters that have centroid TOI using a Gaussian Mixture Model (GMM). The probability functions are applied to all remaining anomalies. All objects of UXO probability higher than a chosen threshold are placed in a ranked dig list. This prioritized list is scored and the results are demonstrated and analyzed.
Arend, Carlos Frederico; Arend, Ana Amalia; da Silva, Tiago Rodrigues
2014-06-01
The aim of our study was to systematically compare different methodologies to establish an evidence-based approach based on tendon thickness and structure for sonographic diagnosis of supraspinatus tendinopathy when compared to MRI. US was obtained from 164 symptomatic patients with supraspinatus tendinopathy detected at MRI and 42 asymptomatic controls with normal MRI. Diagnostic yield was calculated for either maximal supraspinatus tendon thickness (MSTT) and tendon structure as isolated criteria and using different combinations of parallel and sequential testing at US. Chi-squared tests were performed to assess sensitivity, specificity, and accuracy of different diagnostic approaches. Mean MSTT was 6.68 mm in symptomatic patients and 5.61 mm in asymptomatic controls (P<.05). When used as an isolated criterion, MSTT>6.0mm provided best results for accuracy (93.7%) when compared to other measurements of tendon thickness. Also as an isolated criterion, abnormal tendon structure (ATS) yielded 93.2% accuracy for diagnosis. The best overall yield was obtained by both parallel and sequential testing using either MSTT>6.0mm or ATS as diagnostic criteria at no particular order, which provided 99.0% accuracy, 100% sensitivity, and 95.2% specificity. Among these parallel and sequential tests that provided best overall yield, additional analysis revealed that sequential testing first evaluating tendon structure required assessment of 258 criteria (vs. 261 for sequential testing first evaluating tendon thickness and 412 for parallel testing) and demanded a mean of 16.1s to assess diagnostic criteria and reach the diagnosis (vs. 43.3s for sequential testing first evaluating tendon thickness and 47.4s for parallel testing). We found that using either MSTT>6.0mm or ATS as diagnostic criteria for both parallel and sequential testing provides the best overall yield for sonographic diagnosis of supraspinatus tendinopathy when compared to MRI. Among these strategies, a two-step sequential approach first assessing tendon structure was advantageous because it required a lower number of criteria to be assessed and demanded less time to assess diagnostic criteria and reach the diagnosis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Bursts and heavy tails in temporal and sequential dynamics of foraging decisions.
Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D; Jeong, Jaeseung
2014-08-01
A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.
Kotaki, Tomohiro; Yamanaka, Atsushi; Mulyatno, Kris Cahyo; Churrotin, Siti; Sucipto, Teguh Hari; Labiqah, Amaliah; Ahwanah, Nur Laila Fitriati; Soegijanto, Soegeng; Kameoka, Masanori; Konishi, Eiji
2016-01-01
Indonesia is one of the biggest dengue endemic countries, and, thus, is an important place to investigate the evolution of dengue virus (DENV). We have continuously isolated DENV in Surabaya, the second biggest city in Indonesia, since 2008. We previously reported sequential changes in the predominant serotype from DENV type 2 (DENV-2) to DENV type 1 (DENV-1) in November 2008 and from DENV-1 to DENV-2 in July 2013. The predominance of DENV-2 continued in 2014, but not in 2015. We herein phylogenetically investigated DENV-2 transitions in Surabaya between 2008 and 2014 to analyze the divergence and evolution of DENV-2 concomitant with serotype shifts. All DENV-2 isolated in Surabaya were classified into the Cosmopolitan genotype, and further divided into 6 clusters. Clusters 1-3, dominated by Surabaya strains, were defined as the "Surabaya lineage". Clusters 4-6, dominated by strains from Singapore, Malaysia, and many parts of Indonesia, were the "South East Asian lineage". The most recent common ancestor of these strains existed in 1988, coinciding with the time that an Indonesian dengue outbreak took place. Cluster 1 appeared to be unique because no other DENV-2 isolate was included in this cluster. The predominance of DENV-2 in 2008 and 2013-14 were caused by cluster 1, whereas clusters 2 and 3 sporadically emerged in 2011 and 2012. The characteristic amino acids of cluster 1, E-170V and E-282Y, may be responsible for its prevalence in Surabaya. No amino acid difference was observed in the envelope region between strains in 2008 and 2013-14, suggesting that the re-emergence of DENV-2 in Surabaya was due to the loss or decrease of herd immunity in the 5-year period when DENV-2 subsided. The South East Asian lineage primarily emerged in Surabaya in 2014, probably imported from other parts of Indonesia or foreign countries. Copyright © 2015 Elsevier B.V. All rights reserved.
Protein classification using sequential pattern mining.
Exarchos, Themis P; Papaloukas, Costas; Lampros, Christos; Fotiadis, Dimitrios I
2006-01-01
Protein classification in terms of fold recognition can be employed to determine the structural and functional properties of a newly discovered protein. In this work sequential pattern mining (SPM) is utilized for sequence-based fold recognition. One of the most efficient SPM algorithms, cSPADE, is employed for protein primary structure analysis. Then a classifier uses the extracted sequential patterns for classifying proteins of unknown structure in the appropriate fold category. The proposed methodology exhibited an overall accuracy of 36% in a multi-class problem of 17 candidate categories. The classification performance reaches up to 65% when the three most probable protein folds are considered.
Development of high-accuracy convection schemes for sequential solvers
NASA Technical Reports Server (NTRS)
Thakur, Siddharth; Shyy, Wei
1993-01-01
An exploration is conducted of the applicability of such high resolution schemes as TVD to the resolving of sharp flow gradients using a sequential solution approach borrowed from pressure-based algorithms. It is shown that by extending these high-resolution shock-capturing schemes to a sequential solver that treats the equations as a collection of scalar conservation equations, the speed of signal propagation in the solution has to be coordinated by assigning the local convection speed as the characteristic speed for the entire system. A higher amount of dissipation is therefore needed to eliminate oscillations near discontinuities.
Hasan, Maria; Kausar, Dilshad; Akhter, Gulraiz; Shah, Munir H
2018-01-01
Comparative distribution and mobility of selected essential and toxic metals in the paddy soil from district Sargodha, Pakistan was evaluated by the modified Community Bureau of Reference (mBCR) sequential extraction procedure. Most of the soil samples showed slightly alkaline nature while the soil texture was predominantly silty loam in nature. The metal contents were quantified in the exchangeable, reducible, oxidisable and residual fractions of the soil by flame atomic absorption spectrophotometry and the metal data were subjected to the statistical analyses in order to evaluate the mutual relationships among the metals in each fraction. Among the metals, Ca, Sr and Mn were found to be more mobile in the soil. A number of significant correlations between different metal pairs were noted in various fractions. Contamination factor, geoaccumulation index and enrichment factor revealed extremely severe enrichment/contamination for Cd; moderate to significant enrichment/contamination for Ni, Zn, Co and Pb while Cr, Sr, Cu and Mn revealed minimal to moderate contamination and accumulation in the soil. Multivariate cluster analysis showed significant anthropogenic intrusions of the metals in various fractions. Copyright © 2017 Elsevier Inc. All rights reserved.
Propagating probability distributions of stand variables using sequential Monte Carlo methods
Jeffrey H. Gove
2009-01-01
A general probabilistic approach to stand yield estimation is developed based on sequential Monte Carlo filters, also known as particle filters. The essential steps in the development of the sampling importance resampling (SIR) particle filter are presented. The SIR filter is then applied to simulated and observed data showing how the 'predictor - corrector'...
An Overview of Markov Chain Methods for the Study of Stage-Sequential Developmental Processes
ERIC Educational Resources Information Center
Kapland, David
2008-01-01
This article presents an overview of quantitative methodologies for the study of stage-sequential development based on extensions of Markov chain modeling. Four methods are presented that exemplify the flexibility of this approach: the manifest Markov model, the latent Markov model, latent transition analysis, and the mixture latent Markov model.…
ROC and Loss Function Analysis in Sequential Testing
ERIC Educational Resources Information Center
Muijtjens, Arno M. M.; Van Luijk, Scheltus J.; Van Der Vleuten, Cees P. M.
2006-01-01
Sequential testing is applied to reduce costs in SP-based tests (OSCEs). Initially, all candidates take a screening test consisting of a part of the OSCE. Candidates who fail the screen sit the complete test, whereas those who pass the screen are qualified as a pass of the complete test. The procedure may result in a reduction of testing…
Mauz, Elvira; von der Lippe, Elena; Allen, Jennifer; Schilling, Ralph; Müters, Stephan; Hoebel, Jens; Schmich, Patrick; Wetzstein, Matthias; Kamtsiuris, Panagiotis; Lange, Cornelia
2018-01-01
Population-based surveys currently face the problem of decreasing response rates. Mixed-mode designs are now being implemented more often to account for this, to improve sample composition and to reduce overall costs. This study examines whether a concurrent or sequential mixed-mode design achieves better results on a number of indicators of survey quality. Data were obtained from a population-based health interview survey of adults in Germany that was conducted as a methodological pilot study as part of the German Health Update (GEDA). Participants were randomly allocated to one of two surveys; each of the surveys had a different design. In the concurrent mixed-mode design ( n = 617) two types of self-administered questionnaires (SAQ-Web and SAQ-Paper) and computer-assisted telephone interviewing were offered simultaneously to the respondents along with the invitation to participate. In the sequential mixed-mode design ( n = 561), SAQ-Web was initially provided, followed by SAQ-Paper, with an option for a telephone interview being sent out together with the reminders at a later date. Finally, this study compared the response rates, sample composition, health indicators, item non-response, the scope of fieldwork and the costs of both designs. No systematic differences were identified between the two mixed-mode designs in terms of response rates, the socio-demographic characteristics of the achieved samples, or the prevalence rates of the health indicators under study. The sequential design gained a higher rate of online respondents. Very few telephone interviews were conducted for either design. With regard to data quality, the sequential design (which had more online respondents) showed less item non-response. There were minor differences between the designs in terms of their costs. Postage and printing costs were lower in the concurrent design, but labour costs were lower in the sequential design. No differences in health indicators were found between the two designs. Modelling these results for higher response rates and larger net sample sizes indicated that the sequential design was more cost and time-effective. This study contributes to the research available on implementing mixed-mode designs as part of public health surveys. Our findings show that SAQ-Paper and SAQ-Web questionnaires can be combined effectively. Sequential mixed-mode designs with higher rates of online respondents may be of greater benefit to studies with larger net sample sizes than concurrent mixed-mode designs.
All-gas-phase synthesis of UiO-66 through modulated atomic layer deposition
Lausund, Kristian Blindheim; Nilsen, Ola
2016-01-01
Thin films of stable metal-organic frameworks (MOFs) such as UiO-66 have enormous application potential, for instance in microelectronics. However, all-gas-phase deposition techniques are currently not available for such MOFs. We here report on thin-film deposition of the thermally and chemically stable UiO-66 in an all-gas-phase process by the aid of atomic layer deposition (ALD). Sequential reactions of ZrCl4 and 1,4-benzenedicarboxylic acid produce amorphous organic–inorganic hybrid films that are subsequently crystallized to the UiO-66 structure by treatment in acetic acid vapour. We also introduce a new approach to control the stoichiometry between metal clusters and organic linkers by modulation of the ALD growth with additional acetic acid pulses. An all-gas-phase synthesis technique for UiO-66 could enable implementations in microelectronics that are not compatible with solvothermal synthesis. Since this technique is ALD-based, it could also give enhanced thickness control and the possibility to coat irregular substrates with high aspect ratios. PMID:27876797
A hybrid parallel framework for the cellular Potts model simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jiang, Yi; He, Kejing; Dong, Shoubin
2009-01-01
The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approachmore » achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).« less
Bauermeister, José A; Zimmerman, Marc A; Johns, Michelle M; Glowacki, Pietreck; Stoddard, Sarah; Volz, Erik
2012-09-01
We used a web version of Respondent-Driven Sampling (webRDS) to recruit a sample of young adults (ages 18-24) and examined whether this strategy would result in alcohol and other drug (AOD) prevalence estimates comparable to national estimates (National Survey on Drug Use and Health [NSDUH]). We recruited 22 initial participants (seeds) via Facebook to complete a web survey examining AOD risk correlates. Sequential, incentivized recruitment continued until our desired sample size was achieved. After correcting for webRDS clustering effects, we contrasted our AOD prevalence estimates (past 30 days) to NSDUH estimates by comparing the 95% confidence intervals of prevalence estimates. We found comparable AOD prevalence estimates between our sample and NSDUH for the past 30 days for alcohol, marijuana, cocaine, Ecstasy (3,4-methylenedioxymethamphetamine, or MDMA), and hallucinogens. Cigarette use was lower than NSDUH estimates. WebRDS may be a suitable strategy to recruit young adults online. We discuss the unique strengths and challenges that may be encountered by public health researchers using webRDS methods.
Barry, Bridgette A; Cooper, Ian B; De Riso, Antonio; Brewer, Scott H; Vu, Dung M; Dyer, R Brian
2006-05-09
Photosynthetic oxygen production by photosystem II (PSII) is responsible for the maintenance of aerobic life on earth. The production of oxygen occurs at the PSII oxygen-evolving complex (OEC), which contains a tetranuclear manganese (Mn) cluster. Photo-induced electron transfer events in the reaction center lead to the accumulation of oxidizing equivalents on the OEC. Four sequential photooxidation reactions are required for oxygen production. The oxidizing complex cycles among five oxidation states, called the S(n) states, where n refers to the number of oxidizing equivalents stored. Oxygen release occurs during the S(3)-to-S(0) transition from an unstable intermediate, known as the S(4) state. In this report, we present data providing evidence for the production of an intermediate during each S state transition. These protein-derived intermediates are produced on the microsecond to millisecond time scale and are detected by time-resolved vibrational spectroscopy on the microsecond time scale. Our results suggest that a protein-derived conformational change or proton transfer reaction precedes Mn redox reactions during the S(2)-to-S(3) and S(3)-to-S(0) transitions.
Sequential time interleaved random equivalent sampling for repetitive signal.
Zhao, Yijiu; Liu, Jingjing
2016-12-01
Compressed sensing (CS) based sampling techniques exhibit many advantages over other existing approaches for sparse signal spectrum sensing; they are also incorporated into non-uniform sampling signal reconstruction to improve the efficiency, such as random equivalent sampling (RES). However, in CS based RES, only one sample of each acquisition is considered in the signal reconstruction stage, and it will result in more acquisition runs and longer sampling time. In this paper, a sampling sequence is taken in each RES acquisition run, and the corresponding block measurement matrix is constructed using a Whittaker-Shannon interpolation formula. All the block matrices are combined into an equivalent measurement matrix with respect to all sampling sequences. We implemented the proposed approach with a multi-cores analog-to-digital converter (ADC), whose ADC cores are time interleaved. A prototype realization of this proposed CS based sequential random equivalent sampling method has been developed. It is able to capture an analog waveform at an equivalent sampling rate of 40 GHz while sampled at 1 GHz physically. Experiments indicate that, for a sparse signal, the proposed CS based sequential random equivalent sampling exhibits high efficiency.
Improving data retrieval quality: Evidence based medicine perspective.
Kamalov, M; Dobrynin, V; Balykina, J; Kolbin, A; Verbitskaya, E; Kasimova, M
2015-01-01
The actively developing approach in modern medicine is the approach focused on principles of evidence-based medicine. The assessment of quality and reliability of studies is needed. However, in some cases studies corresponding to the first level of evidence may contain errors in randomized control trials (RCTs). Solution of the problem is the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Studies both in the fields of medicine and information retrieval are conducted for developing search engines for the MEDLINE database [1]; combined techniques for summarization and information retrieval targeted to solving problems of finding the best medication based on the levels of evidence are being developed [2]. Based on the relevance and demand for studies both in the field of medicine and information retrieval, it was decided to start the development of a search engine for the MEDLINE database search on the basis of the Saint-Petersburg State University with the support of Pavlov First Saint-Petersburg State Medical University and Tashkent Institute of Postgraduate Medical Education. Novelty and value of the proposed system are characterized by the use of ranking method of relevant abstracts. It is suggested that the system will be able to perform ranking based on studies level of evidence and to apply GRADE criteria for system evaluation. The assigned task falls within the domain of information retrieval and machine learning. Based on the results of implementation from previous work [3], in which the main goal was to cluster abstracts from MEDLINE database by subtypes of medical interventions, a set of algorithms for clustering in this study was selected: K-means, K-means ++, EM from the sklearn (http://scikit-learn.org) and WEKA (http://www.cs.waikato.ac.nz/~ml/weka/) libraries, together with the methods of Latent Semantic Analysis (LSA) [4] choosing the first 210 facts and the model "bag of words" [5] to represent clustered documents. During the process of abstracts classification, few algorithms were tested including: Complement Naive Bayes [6], Sequential Minimal Optimization (SMO) [7] and non linear SVM from the WEKA library. The first step of this study was to markup abstracts of articles from the MEDLINE by containing and not containing a medical intervention. For this purpose, based on our previous work [8] a web-crawler was modified to perform the necessary markuping. The next step was to evaluate the clustering algorithms at the markup abstracts. As a result of clustering abstracts by two groups, when applying the LSA and choosing first 210 facts, the following results were obtained:1) K-means: Purity = 0,5598, Normalized Entropy = 0.5994;2)K-means ++: Purity = 0,6743, Normalized Entropy = 0.4996;3)EM: Purity = 0,5443, Normalized Entropy = 0.6344.When applying the model "bag of words":1)K-means: Purity = 0,5134, Normalized Entropy = 0.6254;2)K-means ++: Purity = 0,5645, Normalized Entropy = 0.5299;3)EM: Purity = 0,5247, Normalized Entropy = 0.6345.Then, studies which contain medical intervention have been considered and classified by the subtypes of medical interventions. At the process of classification abstracts by subtypes of medical interventions, abstracts were presented as a "bag of words" model with the removal of stop words. 1)Complement Naive Bayes: macro F-measure = 0.6934, micro F-measure = 0.7234;2)Sequantial Minimal Optimization: macro F-measure = 0.6543, micro F-measure = 0.7042;3)Non linear SVM: macro F-measure = 0.6835, micro F-measure = 0.7642. Based on the results of computational experiments, the best results of abstract clustering by containing and not containing medical intervention were obtained using the K-Means ++ algorithm together with LSA, choosing the first 210 facts. The quality of classification abstracts by subtypes of medical interventions value for existing ones [8] has been improved using non linear SVM algorithm, with "bag of words" model and the removal of stop words. The results of clustering obtained in this study will help in grouping abstracts by levels of evidence, using the classification by subtypes of medical interventions and it will be possible to extract information from the abstracts on specific types of interventions.
Ordás, I; Domènech, E; Mañosa, M; García-Sánchez, V; Iglesias-Flores, E; Peñalva, M; Cañas-Ventura, A; Merino, O; Fernández-Bañares, F; Gomollón, F; Vera, M; Gutiérrez, A; Garcia-Planella, E; Chaparro, M; Aguas, M; Gento, E; Muñoz, F; Aguirresarobe, M; Muñoz, C; Fernández, L; Calvet, X; Jiménez, C E; Montoro, M A; Mir, A; De Castro, M L; García-Sepulcre, M F; Bermejo, F; Panés, J; Esteve, M
2017-11-01
To determine the efficacy and safety of cyclosporine (CyA) in a large national registry-based population of patients with steroid-refractory (SR) acute severe ulcerative colitis (ASUC) and to establish predictors of efficacy and adverse events. Multicenter study of SR-ASUC treated with CyA, based on data from the ENEIDA registry. SR-ASUC patients treated with infliximab (IFX) or sequential rescue therapy (CyA-IFX or IFX-CyA) were used as comparators. Of 740 SR-ASUC patients, 377 received CyA, 131 IFX and 63 sequential rescue therapy. The cumulative colectomy rate was higher in the CyA (24.1%) and sequential therapy (32.7%) than in the IFX group (14.5%; P=0.01) at 3 months and 5 years. There were no differences in early and late colectomy between CyA and IFX in patients treated after 2005. 62% of patients receiving CyA remained colectomy-free in the long term (median 71 months). There were no differences in mortality between CyA (2.4%), IFX (1.5%) and sequential therapy (0%; P=0.771). The proportion of patients with serious adverse events (SAEs) was lower in CyA (15.4%) than in IFX treated patients (26.5%) or sequential therapy (33.4%; P<0.001). This difference in favor of CyA was maintained when only patients treated after 2005 were analyzed. Treatment with CyA showed a lower rate of SAE and a similar efficacy to that of IFX thereby supporting the use of either CyA or IFX in SR-ASUC. In addition, the risk-benefit of sequential CyA-IFX for CyA non-responders is acceptable.
The properties of small Ag clusters bound to DNA bases.
Soto-Verdugo, Víctor; Metiu, Horia; Gwinn, Elisabeth
2010-05-21
We study the binding of neutral silver clusters, Ag(n) (n=1-6), to the DNA bases adenine (A), cytosine (C), guanine (G), and thymine (T) and the absorption spectra of the silver cluster-base complexes. Using density functional theory (DFT), we find that the clusters prefer to bind to the doubly bonded ring nitrogens and that binding to T is generally much weaker than to C, G, and A. Ag(3) and Ag(4) make the stronger bonds. Bader charge analysis indicates a mild electron transfer from the base to the clusters for all bases, except T. The donor bases (C, G, and A) bind to the sites on the cluster where the lowest unoccupied molecular orbital has a pronounced protrusion. The site where cluster binds to the base is controlled by the shape of the higher occupied states of the base. Time-dependent DFT calculations show that different base-cluster isomers may have very different absorption spectra. In particular, we find new excitations in base-cluster molecules, at energies well below those of the isolated components, and with strengths that depend strongly on the orientations of planar clusters with respect to the base planes. Our results suggest that geometric constraints on binding, imposed by designed DNA structures, may be a feasible route to engineering the selection of specific cluster-base assemblies.
Developing a new Bayesian Risk Index for risk evaluation of soil contamination.
Albuquerque, M T D; Gerassis, S; Sierra, C; Taboada, J; Martín, J E; Antunes, I M H R; Gallego, J R
2017-12-15
Industrial and agricultural activities heavily constrain soil quality. Potentially Toxic Elements (PTEs) are a threat to public health and the environment alike. In this regard, the identification of areas that require remediation is crucial. In the herein research a geochemical dataset (230 samples) comprising 14 elements (Cu, Pb, Zn, Ag, Ni, Mn, Fe, As, Cd, V, Cr, Ti, Al and S) was gathered throughout eight different zones distinguished by their main activity, namely, recreational, agriculture/livestock and heavy industry in the Avilés Estuary (North of Spain). Then a stratified systematic sampling method was used at short, medium, and long distances from each zone to obtain a representative picture of the total variability of the selected attributes. The information was then combined in four risk classes (Low, Moderate, High, Remediation) following reference values from several sediment quality guidelines (SQGs). A Bayesian analysis, inferred for each zone, allowed the characterization of PTEs correlations, the unsupervised learning network technique proving to be the best fit. Based on the Bayesian network structure obtained, Pb, As and Mn were selected as key contamination parameters. For these 3 elements, the conditional probability obtained was allocated to each observed point, and a simple, direct index (Bayesian Risk Index-BRI) was constructed as a linear rating of the pre-defined risk classes weighted by the previously obtained probability. Finally, the BRI underwent geostatistical modeling. One hundred Sequential Gaussian Simulations (SGS) were computed. The Mean Image and the Standard Deviation maps were obtained, allowing the definition of High/Low risk clusters (Local G clustering) and the computation of spatial uncertainty. High-risk clusters are mainly distributed within the area with the highest altitude (agriculture/livestock) showing an associated low spatial uncertainty, clearly indicating the need for remediation. Atmospheric emissions, mainly derived from the metallurgical industry, contribute to soil contamination by PTEs. Copyright © 2017 Elsevier B.V. All rights reserved.
Multivariate Statistical Analysis of Water Quality data in Indian River Lagoon, Florida
NASA Astrophysics Data System (ADS)
Sayemuzzaman, M.; Ye, M.
2015-12-01
The Indian River Lagoon, is part of the longest barrier island complex in the United States, is a region of particular concern to the environmental scientist because of the rapid rate of human development throughout the region and the geographical position in between the colder temperate zone and warmer sub-tropical zone. Thus, the surface water quality analysis in this region always brings the newer information. In this present study, multivariate statistical procedures were applied to analyze the spatial and temporal water quality in the Indian River Lagoon over the period 1998-2013. Twelve parameters have been analyzed on twelve key water monitoring stations in and beside the lagoon on monthly datasets (total of 27,648 observations). The dataset was treated using cluster analysis (CA), principle component analysis (PCA) and non-parametric trend analysis. The CA was used to cluster twelve monitoring stations into four groups, with stations on the similar surrounding characteristics being in the same group. The PCA was then applied to the similar groups to find the important water quality parameters. The principal components (PCs), PC1 to PC5 was considered based on the explained cumulative variances 75% to 85% in each cluster groups. Nutrient species (phosphorus and nitrogen), salinity, specific conductivity and erosion factors (TSS, Turbidity) were major variables involved in the construction of the PCs. Statistical significant positive or negative trends and the abrupt trend shift were detected applying Mann-Kendall trend test and Sequential Mann-Kendall (SQMK), for each individual stations for the important water quality parameters. Land use land cover change pattern, local anthropogenic activities and extreme climate such as drought might be associated with these trends. This study presents the multivariate statistical assessment in order to get better information about the quality of surface water. Thus, effective pollution control/management of the surface waters can be undertaken.
Shi, Yanwei; Ling, Wencui; Qiang, Zhimin
2013-01-01
The effect of chlorine dioxide (ClO2) oxidation on the formation of disinfection by-products (DBPs) during sequential (ClO2 pre-oxidation for 30 min) and simultaneous disinfection processes with free chlorine (FC) or monochloramine (MCA) was investigated. The formation of DBPs from synthetic humic acid (HA) water and three natural surface waters containing low bromide levels (11-27 microg/L) was comparatively examined in the FC-based (single FC, sequential ClO2-FC, and simultaneous ClO2/FC) and MCA-based (single MCA, ClO2-MCA, and ClO2/MCA) disinfection processes. The results showed that much more DBPs were formed from the synthetic HA water than from the three natural surface waters with comparative levels of dissolved organic carbon. In the FC-based processes, ClO2 oxidation could reduce trihalomethanes (THMs) by 27-35% and haloacetic acids (HAAs) by 14-22% in the three natural surface waters, but increased THMs by 19% and HAAs by 31% in the synthetic HA water after an FC contact time of 48 h. In the MCA-based processes, similar trends were observed although DBPs were produced at a much lower level. There was an insignificant difference in DBPs formation between the sequential and simultaneous processes. The presence of a high level of bromide (320 microg/L) remarkably promoted the DBPs formation in the FC-based processes. Therefore, the simultaneous disinfection process of ClO2/MCA is recommended particularly for waters with a high bromide level.
The energy landscape of glassy dynamics on the amorphous hafnium diboride surface
NASA Astrophysics Data System (ADS)
Nguyen, Duc; Mallek, Justin; Cloud, Andrew N.; Abelson, John R.; Girolami, Gregory S.; Lyding, Joseph; Gruebele, Martin
2014-11-01
Direct visualization of the dynamics of structural glasses and amorphous solids on the sub-nanometer scale provides rich information unavailable from bulk or conventional single molecule techniques. We study the surface of hafnium diboride, a conductive ultrahigh temperature ceramic material that can be grown in amorphous films. Our scanning tunneling movies have a second-to-hour dynamic range and single-point current measurements extend that to the millisecond-to-minute time scale. On the a-HfB2 glass surface, two-state hopping of 1-2 nm diameter cooperatively rearranging regions or "clusters" occurs from sub-milliseconds to hours. We characterize individual clusters in detail through high-resolution (<0.5 nm) imaging, scanning tunneling spectroscopy and voltage modulation, ruling out individual atoms, diffusing adsorbates, or pinned charges as the origin of the observed two-state hopping. Smaller clusters are more likely to hop, larger ones are more likely to be immobile. HfB2 has a very high bulk glass transition temperature Tg, and we observe no three-state hopping or sequential two-state hopping previously seen on lower Tg glass surfaces. The electronic density of states of clusters does not change when they hop up or down, allowing us to calibrate an accurate relative z-axis scale. By directly measuring and histogramming single cluster vertical displacements, we can reconstruct the local free energy landscape of individual clusters, complete with activation barrier height, a reaction coordinate in nanometers, and the shape of the free energy landscape basins between which hopping occurs. The experimental images are consistent with the compact shape of α-relaxors predicted by random first order transition theory, whereas the rapid hopping rate, even taking less confined motion at the surface into account, is consistent with β-relaxations. We make a proposal of how "mixed" features can show up in surface dynamics of glasses.
Schmies, Matthias; Patzer, Alexander; Schütz, Markus; Miyazaki, Mitsuhiko; Fujii, Masaaki; Dopfer, Otto
2014-05-07
Infrared photodissociation (IRPD) spectra of mass-selected cluster ions of acetanilide (N-phenylacetamide), AA(+)-Ln, with the ligands L = He (n = 1-2), Ar (n = 1-7), and N2 (n = 1-10) are recorded in the hydride stretch (amide A, νNH, νCH) and fingerprint (amide I-III) ranges of AA(+) in its (2)A'' ground electronic state. Cold AA(+)-Ln clusters are generated in an electron impact ion source, which predominantly produces the most stable isomer of a given cluster ion. Systematic vibrational frequency shifts of the N-H stretch fundamentals (νNH) provide detailed information about the sequential microsolvation process of AA(+) in a nonpolar (L = He and Ar) and quadrupolar (L = N2) solvent. In the most stable AA(+)-Ln clusters, the first ligand forms a hydrogen bond (H-bond) with the N-H proton of trans-AA(+) (t-AA(+)), whereas further ligands bind weakly to the aromatic ring (π-stacking). There is no experimental evidence for complexes with the less stable cis-AA(+) isomer. Quantum chemical calculations at the M06-2X/aug-cc-pVTZ level confirm the cluster growth sequence derived from the IR spectra. The calculated binding energies of De(H) = 720 and 1227 cm(-1) for H-bonded and De(π) = 585 and 715 cm(-1) for π-bonded Ar and N2 ligands in t-AA(+)-L are consistent with the observed photofragmentation branching ratios of AA(+)-Ln. Comparison between charged and neutral AA((+))-L dimers indicates that ionization switches the preferred ion-ligand binding motif from π-stacking to H-bonding. Electron removal from the HOMO of AA(+) delocalized over both the aromatic ring and the amide group significantly strengthens the C[double bond, length as m-dash]O bond and weakens the N-H bond of the amide group.
Zhang, Zhaoyang; Fang, Hua; Wang, Honggang
2016-06-01
Web-delivered trials are an important component in eHealth services. These trials, mostly behavior-based, generate big heterogeneous data that are longitudinal, high dimensional with missing values. Unsupervised learning methods have been widely applied in this area, however, validating the optimal number of clusters has been challenging. Built upon our multiple imputation (MI) based fuzzy clustering, MIfuzzy, we proposed a new multiple imputation based validation (MIV) framework and corresponding MIV algorithms for clustering big longitudinal eHealth data with missing values, more generally for fuzzy-logic based clustering methods. Specifically, we detect the optimal number of clusters by auto-searching and -synthesizing a suite of MI-based validation methods and indices, including conventional (bootstrap or cross-validation based) and emerging (modularity-based) validation indices for general clustering methods as well as the specific one (Xie and Beni) for fuzzy clustering. The MIV performance was demonstrated on a big longitudinal dataset from a real web-delivered trial and using simulation. The results indicate MI-based Xie and Beni index for fuzzy-clustering are more appropriate for detecting the optimal number of clusters for such complex data. The MIV concept and algorithms could be easily adapted to different types of clustering that could process big incomplete longitudinal trial data in eHealth services.
Zhang, Zhaoyang; Wang, Honggang
2016-01-01
Web-delivered trials are an important component in eHealth services. These trials, mostly behavior-based, generate big heterogeneous data that are longitudinal, high dimensional with missing values. Unsupervised learning methods have been widely applied in this area, however, validating the optimal number of clusters has been challenging. Built upon our multiple imputation (MI) based fuzzy clustering, MIfuzzy, we proposed a new multiple imputation based validation (MIV) framework and corresponding MIV algorithms for clustering big longitudinal eHealth data with missing values, more generally for fuzzy-logic based clustering methods. Specifically, we detect the optimal number of clusters by auto-searching and -synthesizing a suite of MI-based validation methods and indices, including conventional (bootstrap or cross-validation based) and emerging (modularity-based) validation indices for general clustering methods as well as the specific one (Xie and Beni) for fuzzy clustering. The MIV performance was demonstrated on a big longitudinal dataset from a real web-delivered trial and using simulation. The results indicate MI-based Xie and Beni index for fuzzy-clustering is more appropriate for detecting the optimal number of clusters for such complex data. The MIV concept and algorithms could be easily adapted to different types of clustering that could process big incomplete longitudinal trial data in eHealth services. PMID:27126063
Reliability-based trajectory optimization using nonintrusive polynomial chaos for Mars entry mission
NASA Astrophysics Data System (ADS)
Huang, Yuechen; Li, Haiyang
2018-06-01
This paper presents the reliability-based sequential optimization (RBSO) method to settle the trajectory optimization problem with parametric uncertainties in entry dynamics for Mars entry mission. First, the deterministic entry trajectory optimization model is reviewed, and then the reliability-based optimization model is formulated. In addition, the modified sequential optimization method, in which the nonintrusive polynomial chaos expansion (PCE) method and the most probable point (MPP) searching method are employed, is proposed to solve the reliability-based optimization problem efficiently. The nonintrusive PCE method contributes to the transformation between the stochastic optimization (SO) and the deterministic optimization (DO) and to the approximation of trajectory solution efficiently. The MPP method, which is used for assessing the reliability of constraints satisfaction only up to the necessary level, is employed to further improve the computational efficiency. The cycle including SO, reliability assessment and constraints update is repeated in the RBSO until the reliability requirements of constraints satisfaction are satisfied. Finally, the RBSO is compared with the traditional DO and the traditional sequential optimization based on Monte Carlo (MC) simulation in a specific Mars entry mission to demonstrate the effectiveness and the efficiency of the proposed method.
20 CFR 416.924b - Age as a factor of evaluation in the sequential evaluation process for children.
Code of Federal Regulations, 2011 CFR
2011-04-01
... infants. We generally use chronological age (that is, a child's age based on birth date) when we decide... chronological age. When we evaluate the development or linear growth of a child born prematurely, we may use a... sequential evaluation process for children. 416.924b Section 416.924b Employees' Benefits SOCIAL SECURITY...
20 CFR 416.924b - Age as a factor of evaluation in the sequential evaluation process for children.
Code of Federal Regulations, 2013 CFR
2013-04-01
... infants. We generally use chronological age (that is, a child's age based on birth date) when we decide... chronological age. When we evaluate the development or linear growth of a child born prematurely, we may use a... sequential evaluation process for children. 416.924b Section 416.924b Employees' Benefits SOCIAL SECURITY...
20 CFR 416.924b - Age as a factor of evaluation in the sequential evaluation process for children.
Code of Federal Regulations, 2010 CFR
2010-04-01
... infants. We generally use chronological age (that is, a child's age based on birth date) when we decide... chronological age. When we evaluate the development or linear growth of a child born prematurely, we may use a... sequential evaluation process for children. 416.924b Section 416.924b Employees' Benefits SOCIAL SECURITY...
20 CFR 416.924b - Age as a factor of evaluation in the sequential evaluation process for children.
Code of Federal Regulations, 2014 CFR
2014-04-01
... infants. We generally use chronological age (that is, a child's age based on birth date) when we decide... chronological age. When we evaluate the development or linear growth of a child born prematurely, we may use a... sequential evaluation process for children. 416.924b Section 416.924b Employees' Benefits SOCIAL SECURITY...
20 CFR 416.924b - Age as a factor of evaluation in the sequential evaluation process for children.
Code of Federal Regulations, 2012 CFR
2012-04-01
... infants. We generally use chronological age (that is, a child's age based on birth date) when we decide... chronological age. When we evaluate the development or linear growth of a child born prematurely, we may use a... sequential evaluation process for children. 416.924b Section 416.924b Employees' Benefits SOCIAL SECURITY...
ERIC Educational Resources Information Center
Chen, Chin-Chih; McComas, Jennifer J.; Hartman, Ellie; Symons, Frank J.
2011-01-01
Research Findings: In early childhood education, the social ecology of the child is considered critical for healthy behavioral development. There is, however, relatively little information based on directly observing what children do that describes the moment-by-moment (i.e., sequential) relation between physical aggression and peer rejection acts…
Evidence-Based Clinical Recommendations for the Administration of the Sequential Motion Rates Task
ERIC Educational Resources Information Center
Icht, Michal; Ben-David, Boaz M.
2018-01-01
The sequential motion rates (SMR) task, that involves rapid and accurate repetitions of a syllable sequence, /pataka/, is a commonly used evaluation tool for oro-motor abilities. Although the SMR is a well-known tool, some aspects of its administration protocol are unspecified. We address the following factors and their role in the SMR protocol:…
Enhancing Sequential Time Perception and Storytelling Ability of Deaf and Hard of Hearing Children
ERIC Educational Resources Information Center
Ingber, Sara; Eden, Sigal
2011-01-01
A 3-month intervention was conducted to enhance the sequential time perception and storytelling ability of young children with hearing loss. The children were trained to arrange pictorial episodes of temporal scripts and tell the stories they created. Participants (N = 34, aged 4-7 years) were divided into 2 groups based on whether their…
Sequential memory: Binding dynamics
NASA Astrophysics Data System (ADS)
Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail
2015-10-01
Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories—episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.
Sequential memory: Binding dynamics.
Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail
2015-10-01
Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories-episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.
Bioerodible System for Sequential Release of Multiple Drugs
Sundararaj, Sharath C.; Thomas, Mark V.; Dziubla, Thomas D.; Puleo, David A.
2013-01-01
Because many complex physiological processes are controlled by multiple biomolecules, comprehensive treatment of certain disease conditions may be more effectively achieved by administration of more than one type of drug. Thus, the objective of the present research was to develop a multilayered, polymer-based system for sequential delivery of multiple drugs. The polymers used were cellulose acetate phthalate (CAP) complexed with Pluronic F-127 (P). After evaluating morphology of the resulting CAPP system, in vitro release of small molecule drugs and a model protein was studied from both single and multilayered devices. Drug release from single-layered CAPP films followed zero-order kinetics related to surface erosion of the association polymer. Release studies from multilayered CAPP devices showed the possibility of achieving intermittent release of one type of drug as well as sequential release of more than one type of drug. Mathematical modeling accurately predicted the release profiles for both single layer and multilayered devices. The present CAPP association polymer-based multilayer devices can be used for localized, sequential delivery of multiple drugs for the possible treatment of complex disease conditions, and perhaps for tissue engineering applications, that require delivery of more than one type of biomolecule. PMID:24096151
Satínský, Dalibor; Huclová, Jitka; Ferreira, Raquel L C; Montenegro, Maria Conceição B S M; Solich, Petr
2006-02-13
The porous monolithic columns show high performance at relatively low pressure. The coupling of short monoliths with sequential injection technique (SIA) results in a new approach to implementation of separation step to non-separation low-pressure method. In this contribution, a new separation method for simultaneous determination of ambroxol, methylparaben and benzoic acid was developed based on a novel reversed-phase sequential injection chromatography (SIC) technique with UV detection. A Chromolith SpeedROD RP-18e, 50-4.6 mm column with 10 mm precolumn and a FIAlab 3000 system with a six-port selection valve and 5 ml syringe were used for sequential injection chromatographic separations in our study. The mobile phase used was acetonitrile-tetrahydrofuran-0.05M acetic acid (10:10:90, v/v/v), pH 3.75 adjusted with triethylamine, flow rate 0.48 mlmin(-1), UV-detection was at 245 nm. The analysis time was <11 min. A new SIC method was validated and compared with HPLC. The method was found to be useful for the routine analysis of the active compounds ambroxol and preservatives (methylparaben or benzoic acid) in various pharmaceutical syrups and drops.
A cross-species bi-clustering approach to identifying conserved co-regulated genes.
Sun, Jiangwen; Jiang, Zongliang; Tian, Xiuchun; Bi, Jinbo
2016-06-15
A growing number of studies have explored the process of pre-implantation embryonic development of multiple mammalian species. However, the conservation and variation among different species in their developmental programming are poorly defined due to the lack of effective computational methods for detecting co-regularized genes that are conserved across species. The most sophisticated method to date for identifying conserved co-regulated genes is a two-step approach. This approach first identifies gene clusters for each species by a cluster analysis of gene expression data, and subsequently computes the overlaps of clusters identified from different species to reveal common subgroups. This approach is ineffective to deal with the noise in the expression data introduced by the complicated procedures in quantifying gene expression. Furthermore, due to the sequential nature of the approach, the gene clusters identified in the first step may have little overlap among different species in the second step, thus difficult to detect conserved co-regulated genes. We propose a cross-species bi-clustering approach which first denoises the gene expression data of each species into a data matrix. The rows of the data matrices of different species represent the same set of genes that are characterized by their expression patterns over the developmental stages of each species as columns. A novel bi-clustering method is then developed to cluster genes into subgroups by a joint sparse rank-one factorization of all the data matrices. This method decomposes a data matrix into a product of a column vector and a row vector where the column vector is a consistent indicator across the matrices (species) to identify the same gene cluster and the row vector specifies for each species the developmental stages that the clustered genes co-regulate. Efficient optimization algorithm has been developed with convergence analysis. This approach was first validated on synthetic data and compared to the two-step method and several recent joint clustering methods. We then applied this approach to two real world datasets of gene expression during the pre-implantation embryonic development of the human and mouse. Co-regulated genes consistent between the human and mouse were identified, offering insights into conserved functions, as well as similarities and differences in genome activation timing between the human and mouse embryos. The R package containing the implementation of the proposed method in C ++ is available at: https://github.com/JavonSun/mvbc.git and also at the R platform https://www.r-project.org/ jinbo@engr.uconn.edu. © The Author 2016. Published by Oxford University Press.
PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.
Xia, Jing; Wang, Michelle Yongmei
Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Ray -Bing; Wang, Weichung; Jeff Wu, C. F.
A numerical method, called OBSM, was recently proposed which employs overcomplete basis functions to achieve sparse representations. While the method can handle non-stationary response without the need of inverting large covariance matrices, it lacks the capability to quantify uncertainty in predictions. We address this issue by proposing a Bayesian approach which first imposes a normal prior on the large space of linear coefficients, then applies the MCMC algorithm to generate posterior samples for predictions. From these samples, Bayesian credible intervals can then be obtained to assess prediction uncertainty. A key application for the proposed method is the efficient construction ofmore » sequential designs. Several sequential design procedures with different infill criteria are proposed based on the generated posterior samples. As a result, numerical studies show that the proposed schemes are capable of solving problems of positive point identification, optimization, and surrogate fitting.« less
Chen, Ray -Bing; Wang, Weichung; Jeff Wu, C. F.
2017-04-12
A numerical method, called OBSM, was recently proposed which employs overcomplete basis functions to achieve sparse representations. While the method can handle non-stationary response without the need of inverting large covariance matrices, it lacks the capability to quantify uncertainty in predictions. We address this issue by proposing a Bayesian approach which first imposes a normal prior on the large space of linear coefficients, then applies the MCMC algorithm to generate posterior samples for predictions. From these samples, Bayesian credible intervals can then be obtained to assess prediction uncertainty. A key application for the proposed method is the efficient construction ofmore » sequential designs. Several sequential design procedures with different infill criteria are proposed based on the generated posterior samples. As a result, numerical studies show that the proposed schemes are capable of solving problems of positive point identification, optimization, and surrogate fitting.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stoupin, Stanislav, E-mail: sstoupin@aps.anl.gov; Shvyd’ko, Yuri; Trakhtenberg, Emil
2016-07-27
We report progress on implementation and commissioning of sequential X-ray diffraction topography at 1-BM Optics Testing Beamline of the Advanced Photon Source to accommodate growing needs of strain characterization in diffractive crystal optics and other semiconductor single crystals. The setup enables evaluation of strain in single crystals in the nearly-nondispersive double-crystal geometry. Si asymmetric collimator crystals of different crystallographic orientations were designed, fabricated and characterized using in-house capabilities. Imaging the exit beam using digital area detectors permits rapid sequential acquisition of X-ray topographs at different angular positions on the rocking curve of a crystal under investigation. Results on sensitivity andmore » spatial resolution are reported based on experiments with high-quality Si and diamond crystals. The new setup complements laboratory-based X-ray topography capabilities of the Optics group at the Advanced Photon Source.« less
Sensitivity Analysis in Sequential Decision Models.
Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet
2017-02-01
Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.
Bursts and Heavy Tails in Temporal and Sequential Dynamics of Foraging Decisions
Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D.; Jeong, Jaeseung
2014-01-01
A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices. PMID:25122498
Tait, Jamie L; Duckham, Rachel L; Milte, Catherine M; Main, Luana C; Daly, Robin M
2017-01-01
Emerging research indicates that exercise combined with cognitive training may improve cognitive function in older adults. Typically these programs have incorporated sequential training, where exercise and cognitive training are undertaken separately. However, simultaneous or dual-task training, where cognitive and/or motor training are performed simultaneously with exercise, may offer greater benefits. This review summary provides an overview of the effects of combined simultaneous vs. sequential training on cognitive function in older adults. Based on the available evidence, there are inconsistent findings with regard to the cognitive benefits of sequential training in comparison to cognitive or exercise training alone. In contrast, simultaneous training interventions, particularly multimodal exercise programs in combination with secondary tasks regulated by sensory cues, have significantly improved cognition in both healthy older and clinical populations. However, further research is needed to determine the optimal characteristics of a successful simultaneous training program for optimizing cognitive function in older people.
2012-05-30
annealing-based or Bayesian sequential simulation approaches B. Dafflon1,2 and W. Barrash1 Received 13 May 2011; revised 12 March 2012; accepted 17 April 2012...the withheld porosity log are also withheld for this estimation process. For both cases we do this for two wells having locally variable stratigraphy ...borehole location is given at the bottom of each log comparison panel. For comparison with stratigraphy at the BHRS, contacts between Units 1 to 4
MotionFlow: Visual Abstraction and Aggregation of Sequential Patterns in Human Motion Tracking Data.
Jang, Sujin; Elmqvist, Niklas; Ramani, Karthik
2016-01-01
Pattern analysis of human motions, which is useful in many research areas, requires understanding and comparison of different styles of motion patterns. However, working with human motion tracking data to support such analysis poses great challenges. In this paper, we propose MotionFlow, a visual analytics system that provides an effective overview of various motion patterns based on an interactive flow visualization. This visualization formulates a motion sequence as transitions between static poses, and aggregates these sequences into a tree diagram to construct a set of motion patterns. The system also allows the users to directly reflect the context of data and their perception of pose similarities in generating representative pose states. We provide local and global controls over the partition-based clustering process. To support the users in organizing unstructured motion data into pattern groups, we designed a set of interactions that enables searching for similar motion sequences from the data, detailed exploration of data subsets, and creating and modifying the group of motion patterns. To evaluate the usability of MotionFlow, we conducted a user study with six researchers with expertise in gesture-based interaction design. They used MotionFlow to explore and organize unstructured motion tracking data. Results show that the researchers were able to easily learn how to use MotionFlow, and the system effectively supported their pattern analysis activities, including leveraging their perception and domain knowledge.
Soh, Harold; Demiris, Yiannis
2014-01-01
Human beings not only possess the remarkable ability to distinguish objects through tactile feedback but are further able to improve upon recognition competence through experience. In this work, we explore tactile-based object recognition with learners capable of incremental learning. Using the sparse online infinite Echo-State Gaussian process (OIESGP), we propose and compare two novel discriminative and generative tactile learners that produce probability distributions over objects during object grasping/palpation. To enable iterative improvement, our online methods incorporate training samples as they become available. We also describe incremental unsupervised learning mechanisms, based on novelty scores and extreme value theory, when teacher labels are not available. We present experimental results for both supervised and unsupervised learning tasks using the iCub humanoid, with tactile sensors on its five-fingered anthropomorphic hand, and 10 different object classes. Our classifiers perform comparably to state-of-the-art methods (C4.5 and SVM classifiers) and findings indicate that tactile signals are highly relevant for making accurate object classifications. We also show that accurate "early" classifications are possible using only 20-30 percent of the grasp sequence. For unsupervised learning, our methods generate high quality clusterings relative to the widely-used sequential k-means and self-organising map (SOM), and we present analyses into the differences between the approaches.
A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.
Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L
2016-03-01
Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015 Cognitive Science Society, Inc.
An efficient and practical approach to obtain a better optimum solution for structural optimization
NASA Astrophysics Data System (ADS)
Chen, Ting-Yu; Huang, Jyun-Hao
2013-08-01
For many structural optimization problems, it is hard or even impossible to find the global optimum solution owing to unaffordable computational cost. An alternative and practical way of thinking is thus proposed in this research to obtain an optimum design which may not be global but is better than most local optimum solutions that can be found by gradient-based search methods. The way to reach this goal is to find a smaller search space for gradient-based search methods. It is found in this research that data mining can accomplish this goal easily. The activities of classification, association and clustering in data mining are employed to reduce the original design space. For unconstrained optimization problems, the data mining activities are used to find a smaller search region which contains the global or better local solutions. For constrained optimization problems, it is used to find the feasible region or the feasible region with better objective values. Numerical examples show that the optimum solutions found in the reduced design space by sequential quadratic programming (SQP) are indeed much better than those found by SQP in the original design space. The optimum solutions found in a reduced space by SQP sometimes are even better than the solution found using a hybrid global search method with approximate structural analyses.
Multiscale methods for gore curvature calculations from FSI modeling of spacecraft parachutes
NASA Astrophysics Data System (ADS)
Takizawa, Kenji; Tezduyar, Tayfun E.; Kolesar, Ryan; Boswell, Cody; Kanai, Taro; Montel, Kenneth
2014-12-01
There are now some sophisticated and powerful methods for computer modeling of parachutes. These methods are capable of addressing some of the most formidable computational challenges encountered in parachute modeling, including fluid-structure interaction (FSI) between the parachute and air flow, design complexities such as those seen in spacecraft parachutes, and operational complexities such as use in clusters and disreefing. One should be able to extract from a reliable full-scale parachute modeling any data or analysis needed. In some cases, however, the parachute engineers may want to perform quickly an extended or repetitive analysis with methods based on simplified models. Some of the data needed by a simplified model can very effectively be extracted from a full-scale computer modeling that serves as a pilot. A good example of such data is the circumferential curvature of a parachute gore, where a gore is the slice of the parachute canopy between two radial reinforcement cables running from the parachute vent to the skirt. We present the multiscale methods we devised for gore curvature calculation from FSI modeling of spacecraft parachutes. The methods include those based on the multiscale sequentially-coupled FSI technique and using NURBS meshes. We show how the methods work for the fully-open and two reefed stages of the Orion spacecraft main and drogue parachutes.
Trap configuration and spacing influences parameter estimates in spatial capture-recapture models
Sun, Catherine C.; Fuller, Angela K.; Royle, J. Andrew
2014-01-01
An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.
Schulz, Daniela N; Kremers, Stef P J; Vandelanotte, Corneel; van Adrichem, Mathieu J G; Schneider, Francine; Candel, Math J J M; de Vries, Hein
2014-01-27
Web-based computer-tailored interventions for multiple health behaviors can have a significant public health impact. Yet, few randomized controlled trials have tested this assumption. The objective of this paper was to test the effects of a sequential and simultaneous Web-based tailored intervention on multiple lifestyle behaviors. A randomized controlled trial was conducted with 3 tailoring conditions (ie, sequential, simultaneous, and control conditions) in the Netherlands in 2009-2012. Follow-up measurements took place after 12 and 24 months. The intervention content was based on the I-Change model. In a health risk appraisal, all respondents (N=5055) received feedback on their lifestyle behaviors that indicated whether they complied with the Dutch guidelines for physical activity, vegetable consumption, fruit consumption, alcohol intake, and smoking. Participants in the sequential (n=1736) and simultaneous (n=1638) conditions received tailored motivational feedback to change unhealthy behaviors one at a time (sequential) or all at the same time (simultaneous). Mixed model analyses were performed as primary analyses; regression analyses were done as sensitivity analyses. An overall risk score was used as outcome measure, then effects on the 5 individual lifestyle behaviors were assessed and a process evaluation was performed regarding exposure to and appreciation of the intervention. Both tailoring strategies were associated with small self-reported behavioral changes. The sequential condition had the most significant effects compared to the control condition after 12 months (T1, effect size=0.28). After 24 months (T2), the simultaneous condition was most effective (effect size=0.18). All 5 individual lifestyle behaviors changed over time, but few effects differed significantly between the conditions. At both follow-ups, the sequential condition had significant changes in smoking abstinence compared to the simultaneous condition (T1 effect size=0.31; T2 effect size=0.41). The sequential condition was more effective in decreasing alcohol consumption than the control condition at 24 months (effect size=0.27). Change was predicted by the amount of exposure to the intervention (total visiting time: beta=-.06; P=.01; total number of visits: beta=-.11; P<.001). Both interventions were appreciated well by respondents without significant differences between conditions. Although evidence was found for the effectiveness of both programs, no simple conclusive finding could be drawn about which intervention mode was more effective. The best kind of intervention may depend on the behavior that is targeted or on personal preferences and motivation. Further research is needed to identify moderators of intervention effectiveness. The results need to be interpreted in view of the high and selective dropout rates, multiple comparisons, and modest effect sizes. However, a large number of people were reached at low cost and behavioral change was achieved after 2 years. Nederlands Trial Register: NTR 2168; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2168 (Archived by WebCite at http://www.webcitation.org/6MbUqttYB).
Orlando, Kelly A; Iosue, Christine L; Leone, Sarah G; Davies, Danielle L; Wykoff, Dennis D
2015-10-15
Inorganic phosphate is required for a range of cellular processes, such as DNA/RNA synthesis and intracellular signalling. The phosphate starvation-inducible phosphatase activity of Candida glabrata is encoded by the gene CgPMU2 (C. glabrata phosphomutase-like protein). CgPMU2 is part of a three-gene family (∼75% identical) created through gene duplication in the C. glabrata clade; only CgPmu2 is a PHO-regulated broad range acid phosphatase. We identified amino acids that confer broad range phosphatase activity on CgPmu2 by creating fusions of sections of CgPMU2 with CgPMU1, a paralogue with little broad range phosphatase activity. We used site-directed mutagenesis on various fusions to sequentially convert CgPmu1 to CgPmu2. Based on molecular modelling of the Pmu proteins on to a histidine phosphatase crystal structure, clusters of amino acids were found in two distinct regions that were able to confer phosphatase activity. Substitutions in these two regions together conferred broad phosphatase activity on CgPmu1. Interestingly, one change is a histidine adjacent to the active site histidine of CgPmu2 and it exhibits a novel ability to partially replace the conserved active site histidine in CgPmu2. Additionally, a second amino acid change was able to confer nt phosphatase activity to CgPmu1, suggesting single amino acid changes neofunctionalize CgPmu2. © 2015 Authors; published by Portland Press Limited.
Adaptive sampling in behavioral surveys.
Thompson, S K
1997-01-01
Studies of populations such as drug users encounter difficulties because the members of the populations are rare, hidden, or hard to reach. Conventionally designed large-scale surveys detect relatively few members of the populations so that estimates of population characteristics have high uncertainty. Ethnographic studies, on the other hand, reach suitable numbers of individuals only through the use of link-tracing, chain referral, or snowball sampling procedures that often leave the investigators unable to make inferences from their sample to the hidden population as a whole. In adaptive sampling, the procedure for selecting people or other units to be in the sample depends on variables of interest observed during the survey, so the design adapts to the population as encountered. For example, when self-reported drug use is found among members of the sample, sampling effort may be increased in nearby areas. Types of adaptive sampling designs include ordinary sequential sampling, adaptive allocation in stratified sampling, adaptive cluster sampling, and optimal model-based designs. Graph sampling refers to situations with nodes (for example, people) connected by edges (such as social links or geographic proximity). An initial sample of nodes or edges is selected and edges are subsequently followed to bring other nodes into the sample. Graph sampling designs include network sampling, snowball sampling, link-tracing, chain referral, and adaptive cluster sampling. A graph sampling design is adaptive if the decision to include linked nodes depends on variables of interest observed on nodes already in the sample. Adjustment methods for nonsampling errors such as imperfect detection of drug users in the sample apply to adaptive as well as conventional designs.
Giant Virus Megavirus chilensis Encodes the Biosynthetic Pathway for Uncommon Acetamido Sugars*
Piacente, Francesco; De Castro, Cristina; Jeudy, Sandra; Molinaro, Antonio; Salis, Annalisa; Damonte, Gianluca; Bernardi, Cinzia; Abergel, Chantal; Tonetti, Michela G.
2014-01-01
Giant viruses mimicking microbes, by the sizes of their particles and the heavily glycosylated fibrils surrounding their capsids, infect Acanthamoeba sp., which are ubiquitous unicellular eukaryotes. The glycans on fibrils are produced by virally encoded enzymes, organized in gene clusters. Like Mimivirus, Megavirus glycans are mainly composed of virally synthesized N-acetylglucosamine (GlcNAc). They also contain N-acetylrhamnosamine (RhaNAc), a rare sugar; the enzymes involved in its synthesis are encoded by a gene cluster specific to Megavirus close relatives. We combined activity assays on two enzymes of the pathway with mass spectrometry and NMR studies to characterize their specificities. Mg534 is a 4,6-dehydratase 5-epimerase; its three-dimensional structure suggests that it belongs to a third subfamily of inverting dehydratases. Mg535, next in the pathway, is a bifunctional 3-epimerase 4-reductase. The sequential activity of the two enzymes leads to the formation of UDP-l-RhaNAc. This study is another example of giant viruses performing their glycan synthesis using enzymes different from their cellular counterparts, raising again the question of the origin of these pathways. PMID:25035429
Maïssa, Nawal; Covarelli, Valentina; Janel, Sébastien; Durel, Beatrice; Simpson, Nandi; Bernard, Sandra C.; Pardo-Lopez, Liliana; Bouzinba-Ségard, Haniaa; Faure, Camille; Scott, Mark G.H.; Coureuil, Mathieu; Morand, Philippe C.; Lafont, Frank; Nassif, Xavier; Marullo, Stefano; Bourdoulous, Sandrine
2017-01-01
Neisseria meningitidis (meningococcus) is an invasive bacterial pathogen that colonizes human vessels, causing thrombotic lesions and meningitis. Establishment of tight interactions with endothelial cells is crucial for meningococci to resist haemodynamic forces. Two endothelial receptors, CD147 and the β2-adrenergic receptor (β2AR), are sequentially engaged by meningococci to adhere and promote signalling events leading to vascular colonization, but their spatiotemporal coordination is unknown. Here we report that CD147 and β2AR form constitutive hetero-oligomeric complexes. The scaffolding protein α-actinin-4 directly binds to the cytosolic tail of CD147 and governs the assembly of CD147–β2AR complexes in highly ordered clusters at bacterial adhesion sites. This multimolecular assembly process increases the binding strength of meningococci to endothelial cells under shear stress, and creates molecular platforms for the elongation of membrane protrusions surrounding adherent bacteria. Thus, the specific organization of cellular receptors has major impacts on host–pathogen interaction. PMID:28569760
Washio, Kana; Oka, Takashi; Abdalkader, Lamia; Muraoka, Michiko; Shimada, Akira; Oda, Megumi; Sato, Hiaki; Takata, Katsuyoshi; Kagami, Yoshitoyo; Shimizu, Norio; Kato, Seiichi; Kimura, Hiroshi; Nishizaki, Kazunori; Yoshino, Tadashi; Tsukahara, Hirokazu
2017-11-01
The human herpes virus, Epstein-Barr virus (EBV), is a known oncogenic virus and plays important roles in life-threatening T/NK-cell lymphoproliferative disorders (T/NK-cell LPD) such as hypersensitivity to mosquito bite (HMB), chronic active EBV infection (CAEBV), and NK/T-cell lymphoma/leukemia. During the clinical courses of HMB and CAEBV, patients frequently develop malignant lymphomas and the diseases passively progress sequentially. In the present study, gene expression of CD16 (-) CD56 (+) -, EBV (+) HMB, CAEBV, NK-lymphoma, and NK-leukemia cell lines, which were established from patients, was analyzed using oligonucleotide microarrays and compared to that of CD56 bright CD16 dim/- NK cells from healthy donors. Principal components analysis showed that CAEBV and NK-lymphoma cells were relatively closely located, indicating that they had similar expression profiles. Unsupervised hierarchal clustering analyses of microarray data and gene ontology analysis revealed specific gene clusters and identified several candidate genes responsible for disease that can be used to discriminate each category of NK-LPD and NK-cell lymphoma/leukemia.
Modi, Mehrab N; Dhawale, Ashesh K; Bhalla, Upinder S
2014-01-01
Animals can learn causal relationships between pairs of stimuli separated in time and this ability depends on the hippocampus. Such learning is believed to emerge from alterations in network connectivity, but large-scale connectivity is difficult to measure directly, especially during learning. Here, we show that area CA1 cells converge to time-locked firing sequences that bridge the two stimuli paired during training, and this phenomenon is coupled to a reorganization of network correlations. Using two-photon calcium imaging of mouse hippocampal neurons we find that co-time-tuned neurons exhibit enhanced spontaneous activity correlations that increase just prior to learning. While time-tuned cells are not spatially organized, spontaneously correlated cells do fall into distinct spatial clusters that change as a result of learning. We propose that the spatial re-organization of correlation clusters reflects global network connectivity changes that are responsible for the emergence of the sequentially-timed activity of cell-groups underlying the learned behavior. DOI: http://dx.doi.org/10.7554/eLife.01982.001 PMID:24668171
A fluidic diode, valves, and a sequential-loading circuit fabricated on layered paper.
Chen, Hong; Cogswell, Jeremy; Anagnostopoulos, Constantine; Faghri, Mohammad
2012-08-21
Current microfluidic paper-based devices lack crucial components for fluid manipulation. We created a fluidic diode fabricated entirely on a single layer of paper to control the wicking of fluids. The fluidic diode is a two-terminal component that promotes or stops wicking along a paper channel. We further constructed a trigger and a delay valve based on the fluidic diode. Furthermore, we demonstrated a high-level functional circuit, consisting of a diode and a delay valve, to manipulate two fluids in a sequential manner. Our study provides new, transformative tools to manipulate fluid in microfluidic paper-based devices.
Extreme ionization of Xe clusters driven by ultraintense laser fields
DOE Office of Scientific and Technical Information (OSTI.GOV)
Heidenreich, Andreas; Last, Isidore; Jortner, Joshua
We applied theoretical models and molecular dynamics simulations to explore extreme multielectron ionization in Xe{sub n} clusters (n=2-2171, initial cluster radius R{sub 0}=2.16-31.0 A ring ) driven by ultraintense infrared Gaussian laser fields (peak intensity I{sub M}=10{sup 15}-10{sup 20} W cm{sup -2}, temporal pulse length {tau}=10-100 fs, and frequency {nu}=0.35 fs{sup -1}). Cluster compound ionization was described by three processes of inner ionization, nanoplasma formation, and outer ionization. Inner ionization gives rise to high ionization levels (with the formation of (Xe{sup q+}){sub n} with q=2-36), which are amenable to experimental observation. The cluster size and laser intensity dependence of themore » inner ionization levels are induced by a superposition of barrier suppression ionization (BSI) and electron impact ionization (EII). The BSI was induced by a composite field involving the laser field and an inner field of the ions and electrons, which manifests ignition enhancement and screening retardation effects. EII was treated using experimental cross sections, with a proper account of sequential impact ionization. At the highest intensities (I{sub M}=10{sup 18}-10{sup 20} W cm{sup -2}) inner ionization is dominated by BSI. At lower intensities (I{sub M}=10{sup 15}-10{sup 16} W cm{sup -2}), where the nanoplasma is persistent, the EII contribution to the inner ionization yield is substantial. It increases with increasing the cluster size, exerts a marked effect on the increase of the (Xe{sup q+}){sub n} ionization level, is most pronounced in the cluster center, and manifests a marked increase with increasing the pulse length (i.e., becoming the dominant ionization channel (56%) for Xe{sub 2171} at {tau}=100 fs). The EII yield and the ionization level enhancement decrease with increasing the laser intensity. The pulse length dependence of the EII yield at I{sub M}=10{sup 15}-10{sup 16} W cm{sup -2} establishes an ultraintense laser pulse length control mechanism of extreme ionization products.« less
Saeed, Faisal; Salim, Naomie; Abdo, Ammar
2013-07-01
Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Managing numerical errors in random sequential adsorption
NASA Astrophysics Data System (ADS)
Cieśla, Michał; Nowak, Aleksandra
2016-09-01
Aim of this study is to examine the influence of a finite surface size and a finite simulation time on a packing fraction estimated using random sequential adsorption simulations. The goal of particular interest is providing hints on simulation setup to achieve desired level of accuracy. The analysis is based on properties of saturated random packing of disks on continuous and flat surfaces of different sizes.
ERIC Educational Resources Information Center
Polat, Ahmet; Dogan, Soner; Demir, Selçuk Besir
2016-01-01
The present study was undertaken to investigate the quality of education based on the views of the students attending social studies education departments at the Faculties of Education and to determine the existing problems and present suggestions for their solutions. The study was conducted according to exploratory sequential mixed method. In…
ERIC Educational Resources Information Center
Polat, Ahmet; Dogan, Soner; Demir, Selçuk Besir
2016-01-01
The present study was undertaken to investigate the quality of education based on the views of the students attending social studies education departments at the Faculties of Education and to determine the existing problems and present suggestions for their solutions. The study was conducted according to exploratory sequential mixed method. In…
ERIC Educational Resources Information Center
Kamphaus, Randy W.; And Others
The development of two types of mental processing (sequential and simultaneous) in preschool and elementary children was examined in this study. Specifically, the aims of the study were to develop a revised set of tasks based upon previous findings (Naglieri, Kaufman, Kaufman, & Kamphaus, 1981; Kaufman, Kaufman, Kamphaus, & Naglieri, in…
A Fast Density-Based Clustering Algorithm for Real-Time Internet of Things Stream
Ying Wah, Teh
2014-01-01
Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets. PMID:25110753
A fast density-based clustering algorithm for real-time Internet of Things stream.
Amini, Amineh; Saboohi, Hadi; Wah, Teh Ying; Herawan, Tutut
2014-01-01
Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.
Yoo, Myung Hoon; Lim, Won Sub; Park, Joo Hyun; Kwon, Joong Keun; Lee, Tae-Hoon; An, Yong-Hwi; Kim, Young-Jin; Kim, Jong Yang; Lim, Hyun Woo; Park, Hong Ju
2016-01-01
Severe-to-profound sudden sensorineural hearing loss (SSNHL) has a poor prognosis. We aimed to compare the efficacy of simultaneous and sequential oral and intratympanic steroids for this condition. Fifty patients with severe-to-profound SSNHL (>70 dB HL) were included from 7 centers. The simultaneous group (27 patients) received oral and intratympanic steroid injections for 2 weeks. The sequential group (23 patients) was treated with oral steroids for 2 weeks and intratympanic steroids for the subsequent 2 weeks. Pure-tone averages (PTA) and word discrimination scores (WDS) were compared before treatment and 2 weeks and 1 and 2 months after treatment. Treatment outcomes according to the modified American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) criteria were also analyzed. The improvement in PTA and WDS at the 2-week follow-up was 23 ± 21 dB HL and 20 ± 39% in the simultaneous group and 31 ± 29 dB HL and 37 ± 42% in the sequential group; this was not statistically significant. Complete or partial recovery at the 2-week follow-up was observed in 26% of the simultaneous group and 30% of the sequential group; this was also not significant. The improvement in PTA and WDS at the 2-month follow-up was 40 ± 20 dB HL and 37 ± 35% in the simultaneous group and 41 ± 25 dB HL and 48 ± 41% in the sequential group; this was not statistically significant. Complete or partial recovery at the 2-month follow-up was observed in 33% of the simultaneous group and 35% of the sequential group; this was also not significant. Seven patients in the sequential group did not need intratympanic steroid injections for sufficient improvement after oral steroids alone. Simultaneous oral/intratympanic steroid treatment yielded a recovery similar to that produced by sequential treatment. Because the addition of intratympanic steroids can be decided upon based on the improvement after an oral steroid, the sequential regimen can be recommended to avoid unnecessary intratympanic injections. © 2017 S. Karger AG, Basel.
A Weight-Adaptive Laplacian Embedding for Graph-Based Clustering.
Cheng, De; Nie, Feiping; Sun, Jiande; Gong, Yihong
2017-07-01
Graph-based clustering methods perform clustering on a fixed input data graph. Thus such clustering results are sensitive to the particular graph construction. If this initial construction is of low quality, the resulting clustering may also be of low quality. We address this drawback by allowing the data graph itself to be adaptively adjusted in the clustering procedure. In particular, our proposed weight adaptive Laplacian (WAL) method learns a new data similarity matrix that can adaptively adjust the initial graph according to the similarity weight in the input data graph. We develop three versions of these methods based on the L2-norm, fuzzy entropy regularizer, and another exponential-based weight strategy, that yield three new graph-based clustering objectives. We derive optimization algorithms to solve these objectives. Experimental results on synthetic data sets and real-world benchmark data sets exhibit the effectiveness of these new graph-based clustering methods.
Saxena, Raghvendra; Chandra, Amaresh
2011-11-01
Transferability of sequence-tagged-sites (STS) markers was assessed for genetic relationships study among accessions of marvel grass (Dichanthium annulatum Forsk.). In total, 17 STS primers of Stylosanthes origin were tested for their reactivity with thirty accessions of Dichanthium annulatum. Of these, 14 (82.4%) reacted and a total 106 (84 polymorphic) bands were scored. The number of bands generated by individual primer pairs ranged from 4 to 11 with an average of 7.57 bands, whereas polymorphic bands ranged from 4 to 9 with an average of 6.0 bands accounts to an average polymorphism of 80.1%. Polymorphic information content (PIC) ranged from 0.222 to 0.499 and marker index (MI) from 1.33 to 4.49. Utilizing Dice coefficient of genetic similarity dendrogram was generated through un-weighted pairgroup method with arithmetic mean (UPGMA) algorithm. Further, clustering through sequential agglomerative hierarchical and nested (SAHN) method resulted three main clusters constituted all accessions except IGBANG-D-2. Though there was intermixing of few accessions of one agro-climatic region to another, largely groupings of accessions were with their regions of collections. Bootstrap analysis at 1000 scale also showed large number of nodes (11 to 17) having strong clustering (> 50). Thus, results demonstrate the utility of STS markers of Stylosanthes in studying the genetic relationships among accessions of Dichanthium.
Zhou, Qi; Gong, Wei-Chao; Xie, Lu; Zheng, Cun-Gong; Zhang, Wei; Wang, Bin; Zhang, Yong-Fan; Huang, Xin
2014-01-03
Density functional theory (DFT) calculations are performed to study the structural and electronic properties of tri-rhenium oxide clusters Re3On(-/0) (n=1-6). Generalized Koopmans' theorem is applied to predict the vertical detachment energies (VDEs) and simulate the photoelectron spectra (PES). Theoretical calculations at the B3LYP level are carried out to search for the global minima for both the anions and the neutrals. For the anions, the first two O atoms prefer the same corner position of a Re3 triangle. Whereas, Re3O3(-) possesses a C2v symmetry with one bridging and two terminal O atoms. The next three O atoms (n=4-6) are adding sequentially on the basis of Re3O3(-) motif, i.e., adding one terminal O atom for Re3O4(-), one terminal and one bridging O atoms for Re3O5(-), and one terminal and two bridging O atoms for Re3O6(-), respectively. Their corresponding neutral species are similar to the anions in geometry except Re3O4 and Re3O5. Molecular orbital analyses are employed to investigate the chemical bonding and structural evolution in these tri-rhenium oxide clusters. Copyright © 2013 Elsevier B.V. All rights reserved.
2014-01-01
Background Perinatal mortality and morbidity in the Netherlands is relatively high compared to other European countries. Our country has a unique system with an independent primary care providing care to low-risk pregnancies and a secondary/tertiary care responsible for high-risk pregnancies. About 65% of pregnant women in the Netherlands will be referred from primary to secondary care implicating multiple medical handovers. Dutch audits concluded that in the entire obstetric collaborative network process parameters could be improved. Studies have shown that obstetric team training improves perinatal outcome and that simulation-based obstetric team training implementing crew resource management (CRM) improves team performance. In addition, deliberate practice (DP) improves medical skills. The aim of this study is to analyse whether transmural multiprofessional simulation-based obstetric team training improves perinatal outcome. Methods/Design The study will be implemented in the south-eastern part of the Netherlands with an annual delivery rate of over 9,000. In this area secondary care is provided by four hospitals. Each hospital with referring primary care practices will form a cluster (study group). Within each cluster, teams will be formed of different care providers representing the obstetric collaborative network. CRM and elements of DP will be implemented in the training. To analyse the quality of care as perceived by patients, the Pregnancy and Childbirth Questionnaire (PCQ) will be used. Furthermore, self-reported collaboration between care providers will be assessed. Team performance will be measured by the Clinical Teamwork Scale (CTS). We employ a stepped-wedge trial design with a sequential roll-out of the trainings for the different study groups. Primary outcome will be perinatal mortality and/or admission to a NICU. Secondary outcome will be team performance, quality of care as perceived by patients, and collaboration among care providers. Conclusion The effect of transmural multiprofessional simulation-based obstetric team training on perinatal outcome has never been studied. We hypothesise that this training will improve perinatal outcome, team performance, and quality of care as perceived by patients and care providers. Trial registration The Netherlands National Trial Register, http://www.trialregister.nl/NTR4576, registered June 1, 2014 PMID:25145317
Colligan, Lacey; Anderson, Janet E; Potts, Henry W W; Berman, Jonathan
2010-01-07
Many quality and safety improvement methods in healthcare rely on a complete and accurate map of the process. Process mapping in healthcare is often achieved using a sequential flow diagram, but there is little guidance available in the literature about the most effective type of process map to use. Moreover there is evidence that the organisation of information in an external representation affects reasoning and decision making. This exploratory study examined whether the type of process map - sequential or hierarchical - affects healthcare practitioners' judgments. A sequential and a hierarchical process map of a community-based anti coagulation clinic were produced based on data obtained from interviews, talk-throughs, attendance at a training session and examination of protocols and policies. Clinic practitioners were asked to specify the parts of the process that they judged to contain quality and safety concerns. The process maps were then shown to them in counter-balanced order and they were asked to circle on the diagrams the parts of the process where they had the greatest quality and safety concerns. A structured interview was then conducted, in which they were asked about various aspects of the diagrams. Quality and safety concerns cited by practitioners differed depending on whether they were or were not looking at a process map, and whether they were looking at a sequential diagram or a hierarchical diagram. More concerns were identified using the hierarchical diagram compared with the sequential diagram and more concerns were identified in relation to clinical work than administrative work. Participants' preference for the sequential or hierarchical diagram depended on the context in which they would be using it. The difficulties of determining the boundaries for the analysis and the granularity required were highlighted. The results indicated that the layout of a process map does influence perceptions of quality and safety problems in a process. In quality improvement work it is important to carefully consider the type of process map to be used and to consider using more than one map to ensure that different aspects of the process are captured.
Feature Selection based on Machine Learning in MRIs for Hippocampal Segmentation
NASA Astrophysics Data System (ADS)
Tangaro, Sabina; Amoroso, Nicola; Brescia, Massimo; Cavuoti, Stefano; Chincarini, Andrea; Errico, Rosangela; Paolo, Inglese; Longo, Giuseppe; Maglietta, Rosalia; Tateo, Andrea; Riccio, Giuseppe; Bellotti, Roberto
2015-01-01
Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic resonance imaging (MRI) scans can show these variations and therefore can be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimer disease and other neurological and psychiatric diseases. However, it requires accurate, robust, and reproducible delineation of hippocampal structures. Fully automatic methods are usually the voxel based approach; for each voxel a number of local features were calculated. In this paper, we compared four different techniques for feature selection from a set of 315 features extracted for each voxel: (i) filter method based on the Kolmogorov-Smirnov test; two wrapper methods, respectively, (ii) sequential forward selection and (iii) sequential backward elimination; and (iv) embedded method based on the Random Forest Classifier on a set of 10 T1-weighted brain MRIs and tested on an independent set of 25 subjects. The resulting segmentations were compared with manual reference labelling. By using only 23 feature for each voxel (sequential backward elimination) we obtained comparable state-of-the-art performances with respect to the standard tool FreeSurfer.
Flexible sequential designs for multi-arm clinical trials.
Magirr, D; Stallard, N; Jaki, T
2014-08-30
Adaptive designs that are based on group-sequential approaches have the benefit of being efficient as stopping boundaries can be found that lead to good operating characteristics with test decisions based solely on sufficient statistics. The drawback of these so called 'pre-planned adaptive' designs is that unexpected design changes are not possible without impacting the error rates. 'Flexible adaptive designs' on the other hand can cope with a large number of contingencies at the cost of reduced efficiency. In this work, we focus on two different approaches for multi-arm multi-stage trials, which are based on group-sequential ideas, and discuss how these 'pre-planned adaptive designs' can be modified to allow for flexibility. We then show how the added flexibility can be used for treatment selection and sample size reassessment and evaluate the impact on the error rates in a simulation study. The results show that an impressive overall procedure can be found by combining a well chosen pre-planned design with an application of the conditional error principle to allow flexible treatment selection. Copyright © 2014 John Wiley & Sons, Ltd.
Dynamics of Sequential Decision Making
NASA Astrophysics Data System (ADS)
Rabinovich, Mikhail I.; Huerta, Ramón; Afraimovich, Valentin
2006-11-01
We suggest a new paradigm for intelligent decision-making suitable for dynamical sequential activity of animals or artificial autonomous devices that depends on the characteristics of the internal and external world. To do it we introduce a new class of dynamical models that are described by ordinary differential equations with a finite number of possibilities at the decision points, and also include rules solving this uncertainty. Our approach is based on the competition between possible cognitive states using their stable transient dynamics. The model controls the order of choosing successive steps of a sequential activity according to the environment and decision-making criteria. Two strategies (high-risk and risk-aversion conditions) that move the system out of an erratic environment are analyzed.
A roadmap of clustering algorithms: finding a match for a biomedical application.
Andreopoulos, Bill; An, Aijun; Wang, Xiaogang; Schroeder, Michael
2009-05-01
Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable clustering features that are used as evaluation criteria for clustering algorithms. We review 40 different clustering algorithms of all approaches and datatypes. We compare algorithms on the basis of desirable clustering features, and outline algorithms' benefits and drawbacks as a basis for matching them to biomedical applications.
NASA Astrophysics Data System (ADS)
Neichel, B.; Samal, M. R.; Plana, H.; Zavagno, A.; Bernard, A.; Fusco, T.
2015-04-01
Aims: We investigate the star formation activity in a young star forming cluster embedded at the edge of the RCW 41 H ii region. As a complementary goal, we aim to demonstrate the gain provided by wide-field adaptive optics (WFAO) instruments to study young clusters. Methods: We used deep, JHKs images from the newly commissioned Gemini-GeMS/GSAOI instrument, complemented with Spitzer IRAC observations, in order to study the photometric properties of the young stellar cluster. GeMS is a WFAO instrument that delivers almost diffraction-limited images over a field of ~2' across. The exquisite angular resolution allows us to reach a limiting magnitude of J ~ 22 for 98% completeness. The combination of the IRAC photometry with our JHKs catalog is used to build color-color diagrams, and select young stellar object (YSO) candidates. The JHKs photometry is also used in conjunction with pre-main sequence evolutionary models to infer masses and ages. The K-band luminosity function is derived, and then used to build the initial mass function (IMF) of the cluster. Results: We detect the presence of 80 YSO candidates. Those YSOs are used to infer the cluster age, which is found to be in the range 1 to 5 Myr. More precisely, we find that 1/3 of the YSOs are in a range between 3 to 5 Myr, while 2/3 of the YSO are ≤3 Myr. When looking at the spatial distribution of these two populations, we find evidence of a potential age gradient across the field that suggests sequential star formation. We construct the IMF and show that we can sample the mass distribution well into the brown dwarf regime (down to ~0.01 M⊙). The logarithmic mass function rises to peak at ~0.3 M⊙, before turning over and declining into the brown dwarf regime. The total cluster mass derived is estimated to be 78 ± 18 M⊙, while the ratio derived of brown dwarfs to star is 18 ± 5%. When comparing it with other young clusters, we find that the IMF shape of the young cluster embedded within RCW 41 is consistent with those of Trapezium, IC 348, or Chamaeleon I, except for the IMF peak, which happens to be at higher mass. This characteristic is also seen in clusters like NGC 6611 or even Taurus. These results suggest that the medium-to-low mass end of the IMF possibly depends on environment.
A fast and accurate online sequential learning algorithm for feedforward networks.
Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N
2006-11-01
In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.
Milburn, Rebecca K; Hopkinson, Alan C; Bohme, Diethard K
2005-09-21
Experimental results are reported that track the kinetics of gas-phase reactions initiated by Mg+*, (c-C5H5)Mg+ and (c-C5H5)2Mg+* in hydrogen cyanide and cyanoacetylene. The experiments were performed with a selected-ion flow tube (SIFT) tandem mass spectrometer at a helium buffer-gas pressure of 0.35 +/- 0.01 Torr and at 294 +/- 3 K. The observed chemistries of Mg+* and (c-C5H5)Mg+ are dominated by sequential ligation, while that of (c-C5H5)2Mg+* is by ligand switching. The rate-coefficient measurements for sequential addition of cyanoacetylene to Mg+* indicate an extraordinary pattern in alternating chemical reactivity while multiple-collision induced dissociation experiments revealed an extraordinary stability for the Mg(HC3N)4+* cluster ion. Molecular orbital calculations with density functional theory (DFT) at the B3LYP level, Hartree-Fock (HF) and second-order Mphiller-Plesset (MP2) levels, all performed with a 6-31+G(d) basis set, have been used to calculate structures and energies for the observed Mg(HC3N)1-4(+)* cations. These calculations indicate that the path of formation of Mg(HC3N)4+* involves ligand-ligand interactions leading to two cyclic (HC3N)2 ligands which then interact to form 2,4,6,8-tetracyanosemibullvalene-Mg+ or 1,2,5,6-tetracyano-1,3,5,7-cyclooctatetraene-Mg+ cations. A case is made for the formation of similar complex organomagnesium ions in the upper atmosphere of Titan where subsequent electron-ion recombination may produce cyano derivatives of large unsaturated hydrocarbons. In contrast, circumstellar environments with their much higher relative content of free electrons are less likely to give rise to such chemistry.
Nihira, Takanori; Suzuki, Erika; Kitaoka, Motomitsu; Nishimoto, Mamoru; Ohtsubo, Ken'ichi; Nakai, Hiroyuki
2013-09-20
A gene cluster involved in N-glycan metabolism was identified in the genome of Bacteroides thetaiotaomicron VPI-5482. This gene cluster encodes a major facilitator superfamily transporter, a starch utilization system-like transporter consisting of a TonB-dependent oligosaccharide transporter and an outer membrane lipoprotein, four glycoside hydrolases (α-mannosidase, β-N-acetylhexosaminidase, exo-α-sialidase, and endo-β-N-acetylglucosaminidase), and a phosphorylase (BT1033) with unknown function. It was demonstrated that BT1033 catalyzed the reversible phosphorolysis of β-1,4-D-mannosyl-N-acetyl-D-glucosamine in a typical sequential Bi Bi mechanism. These results indicate that BT1033 plays a crucial role as a key enzyme in the N-glycan catabolism where β-1,4-D-mannosyl-N-acetyl-D-glucosamine is liberated from N-glycans by sequential glycoside hydrolase-catalyzed reactions, transported into the cell, and intracellularly converted into α-D-mannose 1-phosphate and N-acetyl-D-glucosamine. In addition, intestinal anaerobic bacteria such as Bacteroides fragilis, Bacteroides helcogenes, Bacteroides salanitronis, Bacteroides vulgatus, Prevotella denticola, Prevotella dentalis, Prevotella melaninogenica, Parabacteroides distasonis, and Alistipes finegoldii were also suggested to possess the similar metabolic pathway for N-glycans. A notable feature of the new metabolic pathway for N-glycans is the more efficient use of ATP-stored energy, in comparison with the conventional pathway where β-mannosidase and ATP-dependent hexokinase participate, because it is possible to directly phosphorylate the D-mannose residue of β-1,4-D-mannosyl-N-acetyl-D-glucosamine to enter glycolysis. This is the first report of a metabolic pathway for N-glycans that includes a phosphorylase. We propose 4-O-β-D-mannopyranosyl-N-acetyl-D-glucosamine:phosphate α-D-mannosyltransferase as the systematic name and β-1,4-D-mannosyl-N-acetyl-D-glucosamine phosphorylase as the short name for BT1033.
Bahnasy, Mahmoud F; Lucy, Charles A
2012-12-07
A sequential surfactant bilayer/diblock copolymer coating was previously developed for the separation of proteins. The coating is formed by flushing the capillary with the cationic surfactant dioctadecyldimethylammonium bromide (DODAB) followed by the neutral polymer poly-oxyethylene (POE) stearate. Herein we show the method development and optimization for capillary isoelectric focusing (cIEF) separations based on the developed sequential coating. Electroosmotic flow can be tuned by varying the POE chain length which allows optimization of resolution and analysis time. DODAB/POE 40 stearate can be used to perform single-step cIEF, while both DODAB/POE 40 and DODAB/POE 100 stearate allow performing two-step cIEF methodologies. A set of peptide markers is used to assess the coating performance. The sequential coating has been applied successfully to cIEF separations using different capillary lengths and inner diameters. A linear pH gradient is established only in two-step CIEF methodology using 3-10 pH 2.5% (v/v) carrier ampholyte. Hemoglobin A(0) and S variants are successfully resolved on DODAB/POE 40 stearate sequentially coated capillaries. Copyright © 2012 Elsevier B.V. All rights reserved.
A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images.
Yao, Libo; Liu, Yong; He, You
2018-06-22
The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In this paper, a novel ship-tracking method in GF-4 satellite sequential imagery is proposed. The algorithm has three stages. First, a local visual saliency map based on local peak signal-to-noise ratio (PSNR) is used to detect ships in a single frame of GF-4 satellite sequential images. Second, the accuracy positioning of each potential target is realized by a dynamic correction using the rational polynomial coefficients (RPCs) and automatic identification system (AIS) data of ships. Finally, an improved multiple hypotheses tracking (MHT) algorithm with amplitude information is used to track ships by further removing the false targets, and to estimate ships’ motion parameters. The algorithm has been tested using GF-4 sequential images and AIS data. The results of the experiment demonstrate that the algorithm achieves good tracking performance in GF-4 satellite sequential images and estimates the motion information of ships accurately.
Chung, Sukhoon; Rhee, Hyunsill; Suh, Yongmoo
2010-01-01
Objectives This study sought to find answers to the following questions: 1) Can we predict whether a patient will revisit a healthcare center? 2) Can we anticipate diseases of patients who revisit the center? Methods For the first question, we applied 5 classification algorithms (decision tree, artificial neural network, logistic regression, Bayesian networks, and Naïve Bayes) and the stacking-bagging method for building classification models. To solve the second question, we performed sequential pattern analysis. Results We determined: 1) In general, the most influential variables which impact whether a patient of a public healthcare center will revisit it or not are personal burden, insurance bill, period of prescription, age, systolic pressure, name of disease, and postal code. 2) The best plain classification model is dependent on the dataset. 3) Based on average of classification accuracy, the proposed stacking-bagging method outperformed all traditional classification models and our sequential pattern analysis revealed 16 sequential patterns. Conclusions Classification models and sequential patterns can help public healthcare centers plan and implement healthcare service programs and businesses that are more appropriate to local residents, encouraging them to revisit public health centers. PMID:21818426
Development of New Lipid-Based Paclitaxel Nanoparticles Using Sequential Simplex Optimization
Dong, Xiaowei; Mattingly, Cynthia A.; Tseng, Michael; Cho, Moo; Adams, Val R.; Mumper, Russell J.
2008-01-01
The objective of these studies was to develop Cremophor-free lipid-based paclitaxel (PX) nanoparticle formulations prepared from warm microemulsion precursors. To identify and optimize new nanoparticles, experimental design was performed combining Taguchi array and sequential simplex optimization. The combination of Taguchi array and sequential simplex optimization efficiently directed the design of paclitaxel nanoparticles. Two optimized paclitaxel nanoparticles (NPs) were obtained: G78 NPs composed of glyceryl tridodecanoate (GT) and polyoxyethylene 20-stearyl ether (Brij 78), and BTM NPs composed of Miglyol 812, Brij 78 and D-alpha-tocopheryl polyethylene glycol 1000 succinate (TPGS). Both nanoparticles successfully entrapped paclitaxel at a final concentration of 150 μg/ml (over 6% drug loading) with particle sizes less than 200 nm and over 85% of entrapment efficiency. These novel paclitaxel nanoparticles were stable at 4°C over three months and in PBS at 37°C over 102 hours as measured by physical stability. Release of paclitaxel was slow and sustained without initial burst release. Cytotoxicity studies in MDA-MB-231 cancer cells showed that both nanoparticles have similar anticancer activities compared to Taxol®. Interestingly, PX BTM nanocapsules could be lyophilized without cryoprotectants. The lyophilized powder comprised only of PX BTM NPs in water could be rapidly rehydrated with complete retention of original physicochemical properties, in-vitro release properties, and cytotoxicity profile. Sequential Simplex Optimization has been utilized to identify promising new lipid-based paclitaxel nanoparticles having useful attributes. PMID:19111929
Sequential programmable self-assembly: Role of cooperative interactions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jonathan D. Halverson; Tkachenko, Alexei V.
Here, we propose a general strategy of “sequential programmable self-assembly” that enables a bottom-up design of arbitrary multi-particle architectures on nano- and microscales. We show that a naive realization of this scheme, based on the pairwise additive interactions between particles, has fundamental limitations that lead to a relatively high error rate. This can be overcome by using cooperative interparticle binding. The cooperativity is a well known feature of many biochemical processes, responsible, e.g., for signaling and regulations in living systems. Here we propose to utilize a similar strategy for high precision self-assembly, and show that DNA-mediated interactions provide a convenientmore » platform for its implementation. In particular, we outline a specific design of a DNA-based complex which we call “DNA spider,” that acts as a smart interparticle linker and provides a built-in cooperativity of binding. We demonstrate versatility of the sequential self-assembly based on spider-functionalized particles by designing several mesostructures of increasing complexity and simulating their assembly process. This includes a number of finite and repeating structures, in particular, the so-called tetrahelix and its several derivatives. Due to its generality, this approach allows one to design and successfully self-assemble virtually any structure made of a “GEOMAG” magnetic construction toy, out of nanoparticles. According to our results, once the binding cooperativity is strong enough, the sequential self-assembly becomes essentially error-free.« less
Sequential programmable self-assembly: Role of cooperative interactions
Jonathan D. Halverson; Tkachenko, Alexei V.
2016-03-04
Here, we propose a general strategy of “sequential programmable self-assembly” that enables a bottom-up design of arbitrary multi-particle architectures on nano- and microscales. We show that a naive realization of this scheme, based on the pairwise additive interactions between particles, has fundamental limitations that lead to a relatively high error rate. This can be overcome by using cooperative interparticle binding. The cooperativity is a well known feature of many biochemical processes, responsible, e.g., for signaling and regulations in living systems. Here we propose to utilize a similar strategy for high precision self-assembly, and show that DNA-mediated interactions provide a convenientmore » platform for its implementation. In particular, we outline a specific design of a DNA-based complex which we call “DNA spider,” that acts as a smart interparticle linker and provides a built-in cooperativity of binding. We demonstrate versatility of the sequential self-assembly based on spider-functionalized particles by designing several mesostructures of increasing complexity and simulating their assembly process. This includes a number of finite and repeating structures, in particular, the so-called tetrahelix and its several derivatives. Due to its generality, this approach allows one to design and successfully self-assemble virtually any structure made of a “GEOMAG” magnetic construction toy, out of nanoparticles. According to our results, once the binding cooperativity is strong enough, the sequential self-assembly becomes essentially error-free.« less
Automatic Clustering Using Multi-objective Particle Swarm and Simulated Annealing
Abubaker, Ahmad; Baharum, Adam; Alrefaei, Mahmoud
2015-01-01
This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, “MOPSOSA”. The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-Objective Simulated Annealing (MOSA). Three cluster validity indices were optimized simultaneously to establish the suitable number of clusters and the appropriate clustering for a dataset. The first cluster validity index is centred on Euclidean distance, the second on the point symmetry distance, and the last cluster validity index is based on short distance. A number of algorithms have been compared with the MOPSOSA algorithm in resolving clustering problems by determining the actual number of clusters and optimal clustering. Computational experiments were carried out to study fourteen artificial and five real life datasets. PMID:26132309
ERIC Educational Resources Information Center
Boekkooi-Timminga, Ellen
Nine methods for automated test construction are described. All are based on the concepts of information from item response theory. Two general kinds of methods for the construction of parallel tests are presented: (1) sequential test design; and (2) simultaneous test design. Sequential design implies that the tests are constructed one after the…
Brief Lags in Interrupted Sequential Performance: Evaluating a Model and Model Evaluation Method
2015-01-05
rehearsal mechanism in the model. To evaluate the model we developed a simple new goodness-of-fit test based on analysis of variance that offers an...repeated step). Sequen- tial constraints are common in medicine, equipment maintenance, computer programming and technical support, data analysis ...legal analysis , accounting, and many other home and workplace environ- ments. Sequential constraints also play a role in such basic cognitive processes
EEG Classification with a Sequential Decision-Making Method in Motor Imagery BCI.
Liu, Rong; Wang, Yongxuan; Newman, Geoffrey I; Thakor, Nitish V; Ying, Sarah
2017-12-01
To develop subject-specific classifier to recognize mental states fast and reliably is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this paper, a sequential decision-making strategy is explored in conjunction with an optimal wavelet analysis for EEG classification. The subject-specific wavelet parameters based on a grid-search method were first developed to determine evidence accumulative curve for the sequential classifier. Then we proposed a new method to set the two constrained thresholds in the sequential probability ratio test (SPRT) based on the cumulative curve and a desired expected stopping time. As a result, it balanced the decision time of each class, and we term it balanced threshold SPRT (BTSPRT). The properties of the method were illustrated on 14 subjects' recordings from offline and online tests. Results showed the average maximum accuracy of the proposed method to be 83.4% and the average decision time of 2.77[Formula: see text]s, when compared with 79.2% accuracy and a decision time of 3.01[Formula: see text]s for the sequential Bayesian (SB) method. The BTSPRT method not only improves the classification accuracy and decision speed comparing with the other nonsequential or SB methods, but also provides an explicit relationship between stopping time, thresholds and error, which is important for balancing the speed-accuracy tradeoff. These results suggest that BTSPRT would be useful in explicitly adjusting the tradeoff between rapid decision-making and error-free device control.
Karp, J E; Humphrey, R L; Burke, P J
1981-03-01
Malignant plasma cell proliferation and induced humoral stimulatory activity (HSA) occur in vivo at a predictable time following drug administration. Sequential sera from 11 patients with poor-risk multiple myeloma (MM) undergoing treatment with Cytoxan (CY) 2400 mq/sq m were assayed for their in vitro effects on malignant bone marrow plasma cell tritiated thymidine (3HTdR) incorporation. Peak HSA was detected day 9 following CY. Sequential changes in marrow malignant plasma cell 3HTdR-labeling indices (LI) paralleled changes in serum activity, with peak LI occurring at the time of peak HS. An in vitro model of chemotherapy demonstrated that malignant plasma cell proliferation was enhanced by HSA, as determined by 3HTdR incorporation assay, 3HTdR LI, and tumor cells counts, and that stimulated plasma cells were more sensitive to cytotoxic effects of adriamycin (ADR) than were cells cultured in autologous pretreatment serum. Based on these studies, we designed a clinical trial to treat 12 CY-refractory poor-risk patients with MM in which ADR (60 mg/sq m) was administered at the time of peak HSA and residual tumor cell LI (day 9) following initial CY, 2400 mg/m (CY1ADR9). Eight of 12 (67%) responded to timed sequential chemotherapy with a greater than 50% decrement in monoclonal protein marker and a median survival projected to be greater than 8 mo duration (range 4-21+ mo). These clinical results using timed sequential CY1ADR9 compare favorably with results obtained using ADR in nonsequential chemotherapeutic regimens.
Liu, Rong
2017-01-01
Obtaining a fast and reliable decision is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this study, the EEG signals were firstly analyzed with a power projective base method. Then we were applied a decision-making model, the sequential probability ratio testing (SPRT), for single-trial classification of motor imagery movement events. The unique strength of this proposed classification method lies in its accumulative process, which increases the discriminative power as more and more evidence is observed over time. The properties of the method were illustrated on thirteen subjects' recordings from three datasets. Results showed that our proposed power projective method outperformed two benchmark methods for every subject. Moreover, with sequential classifier, the accuracies across subjects were significantly higher than that with nonsequential ones. The average maximum accuracy of the SPRT method was 84.1%, as compared with 82.3% accuracy for the sequential Bayesian (SB) method. The proposed SPRT method provides an explicit relationship between stopping time, thresholds, and error, which is important for balancing the time-accuracy trade-off. These results suggest SPRT would be useful in speeding up decision-making while trading off errors in BCI. PMID:29348781
An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.
Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei
2013-05-01
Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.
Revisiting Pneumatic Nail Gun Trigger Recommendations.
Albers, James; Lowe, Brian; Lipscomb, Hester; Hudock, Stephen; Dement, John; Evanoff, Bradley; Fullen, Mark; Gillen, Matt; Kaskutas, Vicki; Nolan, James; Patterson, Dennis; Platner, James; Pompeii, Lisa; Schoenfisch, Ashley
2015-03-01
Use of a pneumatic nail gun with a sequential actuation trigger (SAT) significantly diminishes the risk for acute traumatic injury compared to use of a contact actuation trigger (CAT) nail gun. A theoretically-based increased risk of work-related musculoskeletal disorders from use of a SAT nail gun, relative to CAT, appears unlikely and remains unproven. Based on current knowledge, the use of CAT nail guns cannot be justified as a safe alternative to SAT nail guns. This letter provides a perspective of ergonomists and occupational safety researchers recommending the use of the sequential actuation trigger for all nail gun tasks in the construction industry.
Network-based spatial clustering technique for exploring features in regional industry
NASA Astrophysics Data System (ADS)
Chou, Tien-Yin; Huang, Pi-Hui; Yang, Lung-Shih; Lin, Wen-Tzu
2008-10-01
In the past researches, industrial cluster mainly focused on single or particular industry and less on spatial industrial structure and mutual relations. Industrial cluster could generate three kinds of spillover effects, including knowledge, labor market pooling, and input sharing. In addition, industrial cluster indeed benefits industry development. To fully control the status and characteristics of district industrial cluster can facilitate to improve the competitive ascendancy of district industry. The related researches on industrial spatial cluster were of great significance for setting up industrial policies and promoting district economic development. In this study, an improved model, GeoSOM, that combines DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and SOM (Self-Organizing Map) was developed for analyzing industrial cluster. Different from former distance-based algorithm for industrial cluster, the proposed GeoSOM model can calculate spatial characteristics between firms based on DBSCAN algorithm and evaluate the similarity between firms based on SOM clustering analysis. The demonstrative data sets, the manufacturers around Taichung County in Taiwan, were analyzed for verifying the practicability of the proposed model. The analyzed results indicate that GeoSOM is suitable for evaluating spatial industrial cluster.
Qi, Hong; Qiao, Yao-Bin; Ren, Ya-Tao; Shi, Jing-Wen; Zhang, Ze-Yu; Ruan, Li-Ming
2016-10-17
Sequential quadratic programming (SQP) is used as an optimization algorithm to reconstruct the optical parameters based on the time-domain radiative transfer equation (TD-RTE). Numerous time-resolved measurement signals are obtained using the TD-RTE as forward model. For a high computational efficiency, the gradient of objective function is calculated using an adjoint equation technique. SQP algorithm is employed to solve the inverse problem and the regularization term based on the generalized Gaussian Markov random field (GGMRF) model is used to overcome the ill-posed problem. Simulated results show that the proposed reconstruction scheme performs efficiently and accurately.
Jahanshahi-Anbuhi, Sana; Henry, Aleah; Leung, Vincent; Sicard, Clémence; Pennings, Kevin; Pelton, Robert; Brennan, John D; Filipe, Carlos D M
2014-01-07
Water soluble pullulan films were formatted into paper-based microfluidic devices, serving as a controlled time shutoff valve. The utility of the valve was demonstrated by a one-step, fully automatic implementation of a complex pesticide assay requiring timed, sequential exposure of an immobilized enzyme layer to separate liquid streams. Pullulan film dissolution and the capillary wicking of aqueous solutions through the device were measured and modeled providing valve design criteria. The films dissolve mainly by surface erosion, meaning the film thickness mainly controls the shutoff time. This method can also provide time-dependent sequential release of reagents without compromising the simplicity and low cost of paper-based devices.
Efficient Agent-Based Cluster Ensembles
NASA Technical Reports Server (NTRS)
Agogino, Adrian; Tumer, Kagan
2006-01-01
Numerous domains ranging from distributed data acquisition to knowledge reuse need to solve the cluster ensemble problem of combining multiple clusterings into a single unified clustering. Unfortunately current non-agent-based cluster combining methods do not work in a distributed environment, are not robust to corrupted clusterings and require centralized access to all original clusterings. Overcoming these issues will allow cluster ensembles to be used in fundamentally distributed and failure-prone domains such as data acquisition from satellite constellations, in addition to domains demanding confidentiality such as combining clusterings of user profiles. This paper proposes an efficient, distributed, agent-based clustering ensemble method that addresses these issues. In this approach each agent is assigned a small subset of the data and votes on which final cluster its data points should belong to. The final clustering is then evaluated by a global utility, computed in a distributed way. This clustering is also evaluated using an agent-specific utility that is shown to be easier for the agents to maximize. Results show that agents using the agent-specific utility can achieve better performance than traditional non-agent based methods and are effective even when up to 50% of the agents fail.
Extended recency effect extended: blocking, presentation mode, and retention interval.
Glidden, L M; Pawelski, C; Mar, H; Zigman, W
1979-07-01
The effect of blocking of stimulus items on the free recall of EMR adolescents was examined. In Experiment 1 a multitrial free-recall list of 15 pictures was presented either simultaneously in groups of 3, or sequentially, one at a time. Consistent ordering was used in both conditions, so that on each trial, each item in each set of 3 pictures was presented contiguously with the other 2 items from that set. In addition, recall came immediately or after a filled or unfilled delay of 24.5 seconds. Results showed that simultaneous presentation led to higher recall, subjective organization, and clustering than did sequential presentation, but analysis of serial-position curves showed a much reduced extended recency effect in comparison with previous studies. Experiment 2 was designed to determine whether the cause of the reduced extended recency was the use of pictures rather than words as stimuli. Stimuli were presented either as pictures, as pictures with auditory labels, or as words with auditory labels, with both simultaneous and consistent ordering for all conditions. Results indicated a strong extended recency effect for all groups, eliminating presentation mode as a causal factor in the data of Experiment 1. We concluded that blocking leads to increased organization and recall over a variety of presentation modes, rates, and block sizes.
Random covering of the circle: the configuration-space of the free deposition process
NASA Astrophysics Data System (ADS)
Huillet, Thierry
2003-12-01
Consider a circle of circumference 1. Throw at random n points, sequentially, on this circle and append clockwise an arc (or rod) of length s to each such point. The resulting random set (the free gas of rods) is a collection of a random number of clusters with random sizes. It models a free deposition process on a 1D substrate. For such processes, we shall consider the occurrence times (number of rods) and probabilities, as n grows, of the following configurations: those avoiding rod overlap (the hard-rod gas), those for which the largest gap is smaller than rod length s (the packing gas), those (parking configurations) for which hard rod and packing constraints are both fulfilled and covering configurations. Special attention is paid to the statistical properties of each such (rare) configuration in the asymptotic density domain when ns = rgr, for some finite density rgr of points. Using results from spacings in the random division of the circle, explicit large deviation rate functions can be computed in each case from state equations. Lastly, a process consisting in selecting at random one of these specific equilibrium configurations (called the observable) can be modelled. When particularized to the parking model, this system produces parking configurations differently from Rényi's random sequential adsorption model.
Framework for Parallel Preprocessing of Microarray Data Using Hadoop
2018-01-01
Nowadays, microarray technology has become one of the popular ways to study gene expression and diagnosis of disease. National Center for Biology Information (NCBI) hosts public databases containing large volumes of biological data required to be preprocessed, since they carry high levels of noise and bias. Robust Multiarray Average (RMA) is one of the standard and popular methods that is utilized to preprocess the data and remove the noises. Most of the preprocessing algorithms are time-consuming and not able to handle a large number of datasets with thousands of experiments. Parallel processing can be used to address the above-mentioned issues. Hadoop is a well-known and ideal distributed file system framework that provides a parallel environment to run the experiment. In this research, for the first time, the capability of Hadoop and statistical power of R have been leveraged to parallelize the available preprocessing algorithm called RMA to efficiently process microarray data. The experiment has been run on cluster containing 5 nodes, while each node has 16 cores and 16 GB memory. It compares efficiency and the performance of parallelized RMA using Hadoop with parallelized RMA using affyPara package as well as sequential RMA. The result shows the speed-up rate of the proposed approach outperforms the sequential approach and affyPara approach. PMID:29796018
Bhoomiboonchoo, Piraya; Nisalak, Ananda; Chansatiporn, Natkamol; Yoon, In-Kyu; Kalayanarooj, Siripen; Thipayamongkolgul, Mathuros; Endy, Timothy; Rothman, Alan L; Green, Sharone; Srikiatkhachorn, Anon; Buddhari, Darunee; Mammen, Mammen P; Gibbons, Robert V
2015-03-14
The effect of prior dengue virus (DENV) exposure on subsequent heterologous infection can be beneficial or detrimental depending on many factors including timing of infection. We sought to evaluate this effect by examining a large database of DENV infections captured by both active and passive surveillance encompassing a wide clinical spectrum of disease. We evaluated datasets from 17 years of hospital-based passive surveillance and nine years of cohort studies, including clinical and subclinical DENV infections, to assess the outcomes of sequential heterologous infections. Chi square or Fisher's exact test was used to compare proportions of infection outcomes such as disease severity; ANOVA was used for continuous variables. Multivariate logistic regression was used to assess risk factors for infection outcomes. Of 38,740 DENV infections, two or more infections were detected in 502 individuals; 14 had three infections. The mean ages at the time of the first and second detected infections were 7.6 ± 3.0 and 11.2 ± 3.0 years. The shortest time between sequential infections was 66 days. A longer time interval between sequential infections was associated with dengue hemorrhagic fever (DHF) in the second detected infection (OR 1.3, 95% CI 1.2-1.4). All possible sequential serotype pairs were observed among 201 subjects with DHF at the second detected infection, except DENV-4 followed by DENV-3. Among DENV infections detected in cohort subjects by active study surveillance and subsequent non-study hospital-based passive surveillance, hospitalization at the first detected infection increased the likelihood of hospitalization at the second detected infection. Increasing time between sequential DENV infections was associated with greater severity of the second detected infection, supporting the role of heterotypic immunity in both protection and enhancement. Hospitalization was positively associated between the first and second detected infections, suggesting a possible predisposition in some individuals to more severe dengue disease.
Dinavahi, Saketh S; Noory, Mohammad A; Gowda, Raghavendra; Drabick, Joseph J; Berg, Arthur; Neves, Rogerio I; Robertson, Gavin P
2018-03-01
Drug combinations acting synergistically to kill cancer cells have become increasingly important in melanoma as an approach to manage the recurrent resistant disease. Protein kinase B (AKT) is a major target in this disease but its inhibitors are not effective clinically, which is a major concern. Targeting AKT in combination with WEE1 (mitotic inhibitor kinase) seems to have potential to make AKT-based therapeutics effective clinically. Since agents targeting AKT and WEE1 have been tested individually in the clinic, the quickest way to move the drug combination to patients would be to combine these agents sequentially, enabling the use of existing phase I clinical trial toxicity data. Therefore, a rapid preclinical approach is needed to evaluate whether simultaneous or sequential drug treatment has maximal therapeutic efficacy, which is based on a mechanistic rationale. To develop this approach, melanoma cell lines were treated with AKT inhibitor AZD5363 [4-amino- N -[(1 S )-1-(4-chlorophenyl)-3-hydroxypropyl]-1-(7 H -pyrrolo[2,3- d ]pyrimidin-4-yl)piperidine-4-carboxamide] and WEE1 inhibitor AZD1775 [2-allyl-1-(6-(2-hydroxypropan-2-yl)pyridin-2-yl)-6-((4-(4-methylpiperazin-1-yl)phenyl)amino)-1 H -pyrazolo[3,4- d ]pyrimidin-3(2 H )-one] using simultaneous and sequential dosing schedules. Simultaneous treatment synergistically reduced melanoma cell survival and tumor growth. In contrast, sequential treatment was antagonistic and had a minimal tumor inhibitory effect compared with individual agents. Mechanistically, simultaneous targeting of AKT and WEE1 enhanced deregulation of the cell cycle and DNA damage repair pathways by modulating transcription factors p53 and forkhead box M1, which was not observed with sequential treatment. Thus, this study identifies a rapid approach to assess the drug combinations with a mechanistic basis for selection, which suggests that combining AKT and WEE1 inhibitors is needed for maximal efficacy. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.
Bianchi, Federico; Praplan, Arnaud P; Sarnela, Nina; Dommen, Josef; Kürten, Andreas; Ortega, Ismael K; Schobesberger, Siegfried; Junninen, Heikki; Simon, Mario; Tröstl, Jasmin; Jokinen, Tuija; Sipilä, Mikko; Adamov, Alexey; Amorim, Antonio; Almeida, Joao; Breitenlechner, Martin; Duplissy, Jonathan; Ehrhart, Sebastian; Flagan, Richard C; Franchin, Alessandro; Hakala, Jani; Hansel, Armin; Heinritzi, Martin; Kangasluoma, Juha; Keskinen, Helmi; Kim, Jaeseok; Kirkby, Jasper; Laaksonen, Ari; Lawler, Michael J; Lehtipalo, Katrianne; Leiminger, Markus; Makhmutov, Vladimir; Mathot, Serge; Onnela, Antti; Petäjä, Tuukka; Riccobono, Francesco; Rissanen, Matti P; Rondo, Linda; Tomé, António; Virtanen, Annele; Viisanen, Yrjö; Williamson, Christina; Wimmer, Daniela; Winkler, Paul M; Ye, Penglin; Curtius, Joachim; Kulmala, Markku; Worsnop, Douglas R; Donahue, Neil M; Baltensperger, Urs
2014-12-02
We investigated the nucleation of sulfuric acid together with two bases (ammonia and dimethylamine), at the CLOUD chamber at CERN. The chemical composition of positive, negative, and neutral clusters was studied using three Atmospheric Pressure interface-Time Of Flight (APi-TOF) mass spectrometers: two were operated in positive and negative mode to detect the chamber ions, while the third was equipped with a nitrate ion chemical ionization source allowing detection of neutral clusters. Taking into account the possible fragmentation that can happen during the charging of the ions or within the first stage of the mass spectrometer, the cluster formation proceeded via essentially one-to-one acid-base addition for all of the clusters, independent of the type of the base. For the positive clusters, the charge is carried by one excess protonated base, while for the negative clusters it is carried by a deprotonated acid; the same is true for the neutral clusters after these have been ionized. During the experiments involving sulfuric acid and dimethylamine, it was possible to study the appearance time for all the clusters (positive, negative, and neutral). It appeared that, after the formation of the clusters containing three molecules of sulfuric acid, the clusters grow at a similar speed, independent of their charge. The growth rate is then probably limited by the arrival rate of sulfuric acid or cluster-cluster collision.
Membership determination of open clusters based on a spectral clustering method
NASA Astrophysics Data System (ADS)
Gao, Xin-Hua
2018-06-01
We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.
Kremers, Stef PJ; Vandelanotte, Corneel; van Adrichem, Mathieu JG; Schneider, Francine; Candel, Math JJM; de Vries, Hein
2014-01-01
Background Web-based computer-tailored interventions for multiple health behaviors can have a significant public health impact. Yet, few randomized controlled trials have tested this assumption. Objective The objective of this paper was to test the effects of a sequential and simultaneous Web-based tailored intervention on multiple lifestyle behaviors. Methods A randomized controlled trial was conducted with 3 tailoring conditions (ie, sequential, simultaneous, and control conditions) in the Netherlands in 2009-2012. Follow-up measurements took place after 12 and 24 months. The intervention content was based on the I-Change model. In a health risk appraisal, all respondents (N=5055) received feedback on their lifestyle behaviors that indicated whether they complied with the Dutch guidelines for physical activity, vegetable consumption, fruit consumption, alcohol intake, and smoking. Participants in the sequential (n=1736) and simultaneous (n=1638) conditions received tailored motivational feedback to change unhealthy behaviors one at a time (sequential) or all at the same time (simultaneous). Mixed model analyses were performed as primary analyses; regression analyses were done as sensitivity analyses. An overall risk score was used as outcome measure, then effects on the 5 individual lifestyle behaviors were assessed and a process evaluation was performed regarding exposure to and appreciation of the intervention. Results Both tailoring strategies were associated with small self-reported behavioral changes. The sequential condition had the most significant effects compared to the control condition after 12 months (T1, effect size=0.28). After 24 months (T2), the simultaneous condition was most effective (effect size=0.18). All 5 individual lifestyle behaviors changed over time, but few effects differed significantly between the conditions. At both follow-ups, the sequential condition had significant changes in smoking abstinence compared to the simultaneous condition (T1 effect size=0.31; T2 effect size=0.41). The sequential condition was more effective in decreasing alcohol consumption than the control condition at 24 months (effect size=0.27). Change was predicted by the amount of exposure to the intervention (total visiting time: beta=–.06; P=.01; total number of visits: beta=–.11; P<.001). Both interventions were appreciated well by respondents without significant differences between conditions. Conclusions Although evidence was found for the effectiveness of both programs, no simple conclusive finding could be drawn about which intervention mode was more effective. The best kind of intervention may depend on the behavior that is targeted or on personal preferences and motivation. Further research is needed to identify moderators of intervention effectiveness. The results need to be interpreted in view of the high and selective dropout rates, multiple comparisons, and modest effect sizes. However, a large number of people were reached at low cost and behavioral change was achieved after 2 years. Trial Registration Nederlands Trial Register: NTR 2168; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2168 (Archived by WebCite at http://www.webcitation.org/6MbUqttYB). PMID:24472854
Structure based alignment and clustering of proteins (STRALCP)
Zemla, Adam T.; Zhou, Carol E.; Smith, Jason R.; Lam, Marisa W.
2013-06-18
Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.
NASA Astrophysics Data System (ADS)
Chaudhary, A.; Payne, T.; Kinateder, K.; Dao, P.; Beecher, E.; Boone, D.; Elliott, B.
The objective of on-line flagging in this paper is to perform interactive assessment of geosynchronous satellites anomalies such as cross-tagging of a satellites in a cluster, solar panel offset change, etc. This assessment will utilize a Bayesian belief propagation procedure and will include automated update of baseline signature data for the satellite, while accounting for the seasonal changes. Its purpose is to enable an ongoing, automated assessment of satellite behavior through its life cycle using the photometry data collected during the synoptic search performed by a ground or space-based sensor as a part of its metrics mission. The change in the satellite features will be reported along with the probabilities of Type I and Type II errors. The objective of adaptive sequential hypothesis testing in this paper is to define future sensor tasking for the purpose of characterization of fine features of the satellite. The tasking will be designed in order to maximize new information with the least number of photometry data points to be collected during the synoptic search by a ground or space-based sensor. Its calculation is based on the utilization of information entropy techniques. The tasking is defined by considering a sequence of hypotheses in regard to the fine features of the satellite. The optimal observation conditions are then ordered in order to maximize new information about a chosen fine feature. The combined objective of on-line flagging and adaptive sequential hypothesis testing is to progressively discover new information about the features of a geosynchronous satellites by leveraging the regular but sparse cadence of data collection during the synoptic search performed by a ground or space-based sensor. Automated Algorithm to Detect Changes in Geostationary Satellite's Configuration and Cross-Tagging Phan Dao, Air Force Research Laboratory/RVB By characterizing geostationary satellites based on photometry and color photometry, analysts can evaluate satellite operational status and affirm its true identity. The process of ingesting photometry data and deriving satellite physical characteristics can be directed by analysts in a batch mode, meaning using a batch of recent data, or by automated algorithms in an on-line mode in which the assessment is updated with each new data point. Tools used for detecting change to satellite's status or identity, whether performed with a human in the loop or automated algorithms, are generally not built to detect with minimum latency and traceable confidence intervals. To alleviate those deficiencies, we investigate the use of Hidden Markov Models (HMM), in a Bayesian Network framework, to infer the hidden state (changed or unchanged) of a three-axis stabilized geostationary satellite using broadband and color photometry. Unlike frequentist statistics which exploit only the stationary statistics of the observables in the database, HMM also exploits the temporal pattern of the observables as well. The algorithm also operates in “learning” mode to gradually evolve the HMM and accommodate natural changes such as due to the seasonal dependence of GEO satellite's light curve. Our technique is designed to operate with missing color data. The version that ingests both panchromatic and color data can accommodate gaps in color photometry data. That attribute is important because while color indices, e.g. Johnson R and B, enhance the belief (probability) of a hidden state, in real world situations, flux data is collected sporadically in an untasked collect, and color data is limited and sometimes absent. Fluxes are measured with experimental error whose effect on the algorithm will be studied. Photometry data in the AFRL's Geo Color Photometry Catalog and Geo Observations with Latitudinal Diversity Simultaneously (GOLDS) data sets are used to simulate a wide variety of operational changes and identity cross tags. The algorithm is tested against simulated sequences of observed magnitudes, mimicking both the cadence of untasked SSN and other ground sensors, occasional operational changes and possible occurrence of cross tags of in-cluster satellites. We would like to show that the on-line algorithm can detect change; sometimes right after the first post-change data point is analyzed, for zero latency. We also want to show the unsupervised “learning” capability that allows the HMM to evolve with time without user's assistance. For example, the users are not required to “label” the true state of the data points.
Force Sensitivity in Saccharomyces cerevisiae Flocculins.
Chan, Cho X J; El-Kirat-Chatel, Sofiane; Joseph, Ivor G; Jackson, Desmond N; Ramsook, Caleen B; Dufrêne, Yves F; Lipke, Peter N
2016-01-01
Many fungal adhesins have short, β-aggregation-prone sequences that play important functional roles, and in the Candida albicans adhesin Als5p, these sequences cluster the adhesins after exposure to shear force. Here, we report that Saccharomyces cerevisiae flocculins Flo11p and Flo1p have similar β-aggregation-prone sequences and are similarly stimulated by shear force, despite being nonhomologous. Shear from vortex mixing induced the formation of small flocs in cells expressing either adhesin. After the addition of Ca(2+), yeast cells from vortex-sheared populations showed greatly enhanced flocculation and displayed more pronounced thioflavin-bright surface nanodomains. At high concentrations, amyloidophilic dyes inhibited Flo1p- and Flo11p-mediated agar invasion and the shear-induced increase in flocculation. Consistent with these results, atomic force microscopy of Flo11p showed successive force-distance peaks characteristic of sequentially unfolding tandem repeat domains, like Flo1p and Als5p. Flo11p-expressing cells bound together through homophilic interactions with adhesion forces of up to 700 pN and rupture lengths of up to 600 nm. These results are consistent with the potentiation of yeast flocculation by shear-induced formation of high-avidity domains of clustered adhesins at the cell surface, similar to the activation of Candida albicans adhesin Als5p. Thus, yeast adhesins from three independent gene families use similar force-dependent interactions to drive cell adhesion. IMPORTANCE The Saccharomyces cerevisiae flocculins mediate the formation of cellular aggregates and biofilm-like mats, useful in clearing yeast from fermentations. An important property of fungal adhesion proteins, including flocculins, is the ability to form catch bonds, i.e., bonds that strengthen under tension. This strengthening is based, at least in part, on increased avidity of binding due to clustering of adhesins in cell surface nanodomains. This clustering depends on amyloid-like β-aggregation of short amino acid sequences in the adhesins. In Candida albicans adhesin Als5, shear stress from vortex mixing can unfold part of the protein to expose aggregation-prone sequences, and then adhesins aggregate into nanodomains. We therefore tested whether shear stress from mixing can increase flocculation activity by potentiating similar protein remodeling and aggregation in the flocculins. The results demonstrate the applicability of the Als adhesin model and provide a rational framework for the enhancement or inhibition of flocculation in industrial applications.
Kilbourne, Amy M; Almirall, Daniel; Eisenberg, Daniel; Waxmonsky, Jeanette; Goodrich, David E; Fortney, John C; Kirchner, JoAnn E; Solberg, Leif I; Main, Deborah; Bauer, Mark S; Kyle, Julia; Murphy, Susan A; Nord, Kristina M; Thomas, Marshall R
2014-09-30
Despite the availability of psychosocial evidence-based practices (EBPs), treatment and outcomes for persons with mental disorders remain suboptimal. Replicating Effective Programs (REP), an effective implementation strategy, still resulted in less than half of sites using an EBP. The primary aim of this cluster randomized trial is to determine, among sites not initially responding to REP, the effect of adaptive implementation strategies that begin with an External Facilitator (EF) or with an External Facilitator plus an Internal Facilitator (IF) on improved EBP use and patient outcomes in 12 months. This study employs a sequential multiple assignment randomized trial (SMART) design to build an adaptive implementation strategy. The EBP to be implemented is life goals (LG) for patients with mood disorders across 80 community-based outpatient clinics (N = 1,600 patients) from different U.S. regions. Sites not initially responding to REP (defined as < 50% patients receiving ≥ 3 EBP sessions) will be randomized to receive additional support from an EF or both EF/IF. Additionally, sites randomized to EF and still not responsive will be randomized to continue with EF alone or to receive EF/IF. The EF provides technical expertise in adapting LG in routine practice, whereas the on-site IF has direct reporting relationships to site leadership to support LG use in routine practice. The primary outcome is mental health-related quality of life; secondary outcomes include receipt of LG sessions, mood symptoms, implementation costs, and organizational change. This study design will determine whether an off-site EF alone versus the addition of an on-site IF improves EBP uptake and patient outcomes among sites that do not respond initially to REP. It will also examine the value of delaying the provision of EF/IF for sites that continue to not respond despite EF. ClinicalTrials.gov identifier: NCT02151331.
Sequential Anaerobic/Aerobic Digestion for Enhanced Carbon/Nitrogen Removal and Cake Odor Reduction.
Ahmad, Muneer; Denee, Marco Abel; Jiang, Hao; Eskicioglu, Cigdem; Kadota, Paul; Gregonia, Theresa
2016-12-01
Anaerobic digestion (AD) has been proven to be an effective process for the treatment of wastewater sludge. However, it produces high levels of ammonia in the digester effluent, which may jeopardize meeting stringent nutrient discharge limits. In this study, the effect of a sequential anaerobic/aerobic (AN/AERO) digestion and a single-stage conventional AN digestion (as control) was investigated on mixed (primary + secondary) sludge generated by the Annacis Island wastewater treatment plant (WWTP) (BC, Canada). An overall sludge retention time (SRT) of 22.5 days under three different scenarios was chosen based on the current operational SRT of the digesters at the Annacis Island WWTP. The steady state results have shown that sequential AN/AERO digestion configurations achieved up to 11% higher volatile solids (VS) removal and 72% lower ammonia generation over single-stage conventional AN digestion. Furthermore, sequential AN/AERO system also showed enhanced dewaterability, improved fecal coliform destruction and reduced digested cake odors over control digesters.
Pihlajaniemi, Ville; Sipponen, Satu; Sipponen, Mika H; Pastinen, Ossi; Laakso, Simo
2014-02-01
In the enzymatic hydrolysis of lignocellulose materials, the recycling of the solid residue has previously been considered within the context of enzyme recycling. In this study, a steady state investigation of a solids-recycling process was made with pretreated wheat straw and compared to sequential and batch hydrolysis at constant reaction times, substrate feed and liquid and enzyme consumption. Compared to batch hydrolysis, the recycling and sequential processes showed roughly equal hydrolysis yields, while the volumetric productivity was significantly increased. In the 72h process the improvement was 90% due to an increased reaction consistency, while the solids feed was 16% of the total process constituents. The improvement resulted primarily from product removal, which was equally efficient in solids-recycling and sequential hydrolysis processes. No evidence of accumulation of enzymes beyond the accumulation of the substrate was found in recycling. A mathematical model of solids-recycling was constructed, based on a geometrical series. Copyright © 2013 Elsevier Ltd. All rights reserved.
Middlebrooks, Catherine D; Castel, Alan D
2018-05-01
Learners make a number of decisions when attempting to study efficiently: they must choose which information to study, for how long to study it, and whether to restudy it later. The current experiments examine whether documented impairments to self-regulated learning when studying information sequentially, as opposed to simultaneously, extend to the learning of and memory for valuable information. In Experiment 1, participants studied lists of words ranging in value from 1-10 points sequentially or simultaneously at a preset presentation rate; in Experiment 2, study was self-paced and participants could choose to restudy. Although participants prioritized high-value over low-value information, irrespective of presentation, those who studied the items simultaneously demonstrated superior value-based prioritization with respect to recall, study selections, and self-pacing. The results of the present experiments support the theory that devising, maintaining, and executing efficient study agendas is inherently different under sequential formatting than simultaneous. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Tait, Jamie L.; Duckham, Rachel L.; Milte, Catherine M.; Main, Luana C.; Daly, Robin M.
2017-01-01
Emerging research indicates that exercise combined with cognitive training may improve cognitive function in older adults. Typically these programs have incorporated sequential training, where exercise and cognitive training are undertaken separately. However, simultaneous or dual-task training, where cognitive and/or motor training are performed simultaneously with exercise, may offer greater benefits. This review summary provides an overview of the effects of combined simultaneous vs. sequential training on cognitive function in older adults. Based on the available evidence, there are inconsistent findings with regard to the cognitive benefits of sequential training in comparison to cognitive or exercise training alone. In contrast, simultaneous training interventions, particularly multimodal exercise programs in combination with secondary tasks regulated by sensory cues, have significantly improved cognition in both healthy older and clinical populations. However, further research is needed to determine the optimal characteristics of a successful simultaneous training program for optimizing cognitive function in older people. PMID:29163146
Friston, Karl J.; Dolan, Raymond J.
2017-01-01
Normative models of human cognition often appeal to Bayesian filtering, which provides optimal online estimates of unknown or hidden states of the world, based on previous observations. However, in many cases it is necessary to optimise beliefs about sequences of states rather than just the current state. Importantly, Bayesian filtering and sequential inference strategies make different predictions about beliefs and subsequent choices, rendering them behaviourally dissociable. Taking data from a probabilistic reversal task we show that subjects’ choices provide strong evidence that they are representing short sequences of states. Between-subject measures of this implicit sequential inference strategy had a neurobiological underpinning and correlated with grey matter density in prefrontal and parietal cortex, as well as the hippocampus. Our findings provide, to our knowledge, the first evidence for sequential inference in human cognition, and by exploiting between-subject variation in this measure we provide pointers to its neuronal substrates. PMID:28486504
Dong, Yuwen; Deshpande, Sunil; Rivera, Daniel E; Downs, Danielle S; Savage, Jennifer S
2014-06-01
Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or "just-in-time" behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components.
Sequential single shot X-ray photon correlation spectroscopy at the SACLA free electron laser
Lehmkühler, Felix; Kwaśniewski, Paweł; Roseker, Wojciech; ...
2015-11-27
In this study, hard X-ray free electron lasers allow for the first time to access dynamics of condensed matter samples ranging from femtoseconds to several hundred seconds. In particular, the exceptional large transverse coherence of the X-ray pulses and the high time-averaged flux promises to reach time and length scales that have not been accessible up to now with storage ring based sources. However, due to the fluctuations originating from the stochastic nature of the self-amplified spontaneous emission (SASE) process the application of well established techniques such as X-ray photon correlation spectroscopy (XPCS) is challenging. Here we demonstrate a single-shotmore » based sequential XPCS study on a colloidal suspension with a relaxation time comparable to the SACLA free-electron laser pulse repetition rate. High quality correlation functions could be extracted without any indications for sample damage. This opens the way for systematic sequential XPCS experiments at FEL sources.« less
Shi, Ruijia; Xu, Cunshuan
2011-06-01
The study of rat proteins is an indispensable task in experimental medicine and drug development. The function of a rat protein is closely related to its subcellular location. Based on the above concept, we construct the benchmark rat proteins dataset and develop a combined approach for predicting the subcellular localization of rat proteins. From protein primary sequence, the multiple sequential features are obtained by using of discrete Fourier analysis, position conservation scoring function and increment of diversity, and these sequential features are selected as input parameters of the support vector machine. By the jackknife test, the overall success rate of prediction is 95.6% on the rat proteins dataset. Our method are performed on the apoptosis proteins dataset and the Gram-negative bacterial proteins dataset with the jackknife test, the overall success rates are 89.9% and 96.4%, respectively. The above results indicate that our proposed method is quite promising and may play a complementary role to the existing predictors in this area.
Sequential single shot X-ray photon correlation spectroscopy at the SACLA free electron laser
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lehmkühler, Felix; Kwaśniewski, Paweł; Roseker, Wojciech
In this study, hard X-ray free electron lasers allow for the first time to access dynamics of condensed matter samples ranging from femtoseconds to several hundred seconds. In particular, the exceptional large transverse coherence of the X-ray pulses and the high time-averaged flux promises to reach time and length scales that have not been accessible up to now with storage ring based sources. However, due to the fluctuations originating from the stochastic nature of the self-amplified spontaneous emission (SASE) process the application of well established techniques such as X-ray photon correlation spectroscopy (XPCS) is challenging. Here we demonstrate a single-shotmore » based sequential XPCS study on a colloidal suspension with a relaxation time comparable to the SACLA free-electron laser pulse repetition rate. High quality correlation functions could be extracted without any indications for sample damage. This opens the way for systematic sequential XPCS experiments at FEL sources.« less
Liu, Ying; ZENG, Donglin; WANG, Yuanjia
2014-01-01
Summary Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each point where a clinical decision is made based on each patient’s time-varying characteristics and intermediate outcomes observed at earlier points in time. The complexity, patient heterogeneity, and chronicity of mental disorders call for learning optimal DTRs to dynamically adapt treatment to an individual’s response over time. The Sequential Multiple Assignment Randomized Trial (SMARTs) design allows for estimating causal effects of DTRs. Modern statistical tools have been developed to optimize DTRs based on personalized variables and intermediate outcomes using rich data collected from SMARTs; these statistical methods can also be used to recommend tailoring variables for designing future SMART studies. This paper introduces DTRs and SMARTs using two examples in mental health studies, discusses two machine learning methods for estimating optimal DTR from SMARTs data, and demonstrates the performance of the statistical methods using simulated data. PMID:25642116
Fan, X Q
2017-08-11
Retinoblastoma (RB) is the most common intraocular malignancy in childhood. It may seriously affect vision, and even threaten the life. The early diagnosis rate of RB in China remains low, and the majority of patients are at late phase with high rates of enucleation and mortality. The International Intraocular Retinoblastoma Classification and TNM staging system are guidances for therapeutic choices and bases for prognosis evaluation. Based on the sequential multi-method treatment modality, chemotherapy combined with local therapy is the mainstream in dealing with RB, which may maximize the results of eye saving and even vision retaining. New therapeutic techniques including supra-selective ophthalmic artery interventional chemotherapy and intravitreal chemotherapy can further improve the efficacy of treatment, especially the eye salvage rate. The overall level of RB treatment should be improved by promoting the international staging, new therapeutic techniques, and the sequential multiple modality treatment. (Chin J Ophthalmol, 2017, 53: 561 - 565) .
Long, Zi-Jie; Hu, Yuan; Li, Xu-Dong; He, Yi; Xiao, Ruo-Zhi; Fang, Zhi-Gang; Wang, Dong-Ning; Liu, Jia-Jun; Yan, Jin-Song; Huang, Ren-Wei; Lin, Dong-Jun; Liu, Quentin
2014-01-01
The combination of all-trans retinoic acid (ATRA) and arsenic trioxide (As2O3, ATO) has been effective in obtaining high clinical complete remission (CR) rates in acute promyelocytic leukemia (APL), but the long-term efficacy and safety among newly diagnosed APL patients are unclear. In this retrospective study, total 45 newly diagnosed APL patients received ATRA/chemotherapy combination regimen to induce remission. Among them, 43 patients (95.6%) achieved complete remission (CR) after induction therapy, followed by ATO/ATRA/anthracycline-based chemotherapy sequential consolidation treatment with a median follow-up of 55 months. In these patients, the estimated overall survival (OS) and the relapse-free survival (RFS) were 94.4% ± 3.9% and 94.6 ± 3.7%, respectively. The toxicity profile was mild and reversible. No secondary carcinoma was observed. These results demonstrated the high efficacy and minimal toxicity of ATO/ATRA/anthracycline-based chemotherapy sequential consolidation treatment for newly diagnosed APL in long-term follow-up, suggesting a potential frontline therapy for APL.
Improved solution accuracy for TDRSS-based TOPEX/Poseidon orbit determination
NASA Technical Reports Server (NTRS)
Doll, C. E.; Mistretta, G. D.; Hart, R. C.; Oza, D. H.; Bolvin, D. T.; Cox, C. M.; Nemesure, M.; Niklewski, D. J.; Samii, M. V.
1994-01-01
Orbit determination results are obtained by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD) using a batch-least-squares estimator available in the Goddard Trajectory Determination System (GTDS) and an extended Kalman filter estimation system to process Tracking and Data Relay Satellite (TDRS) System (TDRSS) measurements. GTDS is the operational orbit determination system used by the FDD in support of the Ocean Topography Experiment (TOPEX)/Poseidon spacecraft navigation and health and safety operations. The extended Kalman filter was implemented in an orbit determination analysis prototype system, closely related to the Real-Time Orbit Determination System/Enhanced (RTOD/E) system. In addition, the Precision Orbit Determination (POD) team within the GSFC Space Geodesy Branch generated an independent set of high-accuracy trajectories to support the TOPEX/Poseidon scientific data. These latter solutions use the geodynamics (GEODYN) orbit determination system with laser ranging and Doppler Orbitography and Radiopositioning integrated by satellite (DORIS) tracking measurements. The TOPEX/Poseidon trajectories were estimated for November 7 through November 11, 1992, the timeframe under study. Independent assessments were made of the consistencies of solutions produced by the batch and sequential methods. The batch-least-squares solutions were assessed based on the solution residuals, while the sequential solutions were assessed based on primarily the estimated covariances. The batch-least-squares and sequential orbit solutions were compared with the definitive POD orbit solutions. The solution differences were generally less than 2 meters for the batch-least-squares and less than 13 meters for the sequential estimation solutions. After the sequential estimation solutions were processed with a smoother algorithm, position differences with POD orbit solutions of less than 7 meters were obtained. The differences among the POD, GTDS, and filter/smoother solutions can be traced to differences in modeling and tracking data types, which are being analyzed in detail.
Cluster Size Optimization in Sensor Networks with Decentralized Cluster-Based Protocols
Amini, Navid; Vahdatpour, Alireza; Xu, Wenyao; Gerla, Mario; Sarrafzadeh, Majid
2011-01-01
Network lifetime and energy-efficiency are viewed as the dominating considerations in designing cluster-based communication protocols for wireless sensor networks. This paper analytically provides the optimal cluster size that minimizes the total energy expenditure in such networks, where all sensors communicate data through their elected cluster heads to the base station in a decentralized fashion. LEACH, LEACH-Coverage, and DBS comprise three cluster-based protocols investigated in this paper that do not require any centralized support from a certain node. The analytical outcomes are given in the form of closed-form expressions for various widely-used network configurations. Extensive simulations on different networks are used to confirm the expectations based on the analytical results. To obtain a thorough understanding of the results, cluster number variability problem is identified and inspected from the energy consumption point of view. PMID:22267882
A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.
Gui, Jinsong; Zhou, Kai; Xiong, Naixue
2016-09-25
Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.
A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks
Gui, Jinsong; Zhou, Kai; Xiong, Naixue
2016-01-01
Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731
Sequential Objective Structured Clinical Examination based on item response theory in Iran.
Hejri, Sara Mortaz; Jalili, Mohammad
2017-01-01
In a sequential objective structured clinical examination (OSCE), all students initially take a short screening OSCE. Examinees who pass are excused from further testing, but an additional OSCE is administered to the remaining examinees. Previous investigations of sequential OSCE were based on classical test theory. We aimed to design and evaluate screening OSCEs based on item response theory (IRT). We carried out a retrospective observational study. At each station of a 10-station OSCE, the students' performance was graded on a Likert-type scale. Since the data were polytomous, the difficulty parameters, discrimination parameters, and students' ability were calculated using a graded response model. To design several screening OSCEs, we identified the 5 most difficult stations and the 5 most discriminative ones. For each test, 5, 4, or 3 stations were selected. Normal and stringent cut-scores were defined for each test. We compared the results of each of the 12 screening OSCEs to the main OSCE and calculated the positive and negative predictive values (PPV and NPV), as well as the exam cost. A total of 253 students (95.1%) passed the main OSCE, while 72.6% to 94.4% of examinees passed the screening tests. The PPV values ranged from 0.98 to 1.00, and the NPV values ranged from 0.18 to 0.59. Two tests effectively predicted the results of the main exam, resulting in financial savings of 34% to 40%. If stations with the highest IRT-based discrimination values and stringent cut-scores are utilized in the screening test, sequential OSCE can be an efficient and convenient way to conduct an OSCE.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dickens, J.K.
1991-04-01
The organic scintillation detector response code SCINFUL has been used to compute secondary-particle energy spectra, d{sigma}/dE, following nonelastic neutron interactions with {sup 12}C for incident neutron energies between 15 and 60 MeV. The resulting spectra are compared with published similar spectra computed by Brenner and Prael who used an intranuclear cascade code, including alpha clustering, a particle pickup mechanism, and a theoretical approach to sequential decay via intermediate particle-unstable states. The similarities of and the differences between the results of the two approaches are discussed. 16 refs., 44 figs., 2 tabs.
Everyday robotic action: lessons from human action control
de Kleijn, Roy; Kachergis, George; Hommel, Bernhard
2014-01-01
Robots are increasingly capable of performing everyday human activities such as cooking, cleaning, and doing the laundry. This requires the real-time planning and execution of complex, temporally extended sequential actions under high degrees of uncertainty, which provides many challenges to traditional approaches to robot action control. We argue that important lessons in this respect can be learned from research on human action control. We provide a brief overview of available psychological insights into this issue and focus on four principles that we think could be particularly beneficial for robot control: the integration of symbolic and subsymbolic planning of action sequences, the integration of feedforward and feedback control, the clustering of complex actions into subcomponents, and the contextualization of action-control structures through goal representations. PMID:24672474
Internal Cluster Validation on Earthquake Data in the Province of Bengkulu
NASA Astrophysics Data System (ADS)
Rini, D. S.; Novianti, P.; Fransiska, H.
2018-04-01
K-means method is an algorithm for cluster n object based on attribute to k partition, where k < n. There is a deficiency of algorithms that is before the algorithm is executed, k points are initialized randomly so that the resulting data clustering can be different. If the random value for initialization is not good, the clustering becomes less optimum. Cluster validation is a technique to determine the optimum cluster without knowing prior information from data. There are two types of cluster validation, which are internal cluster validation and external cluster validation. This study aims to examine and apply some internal cluster validation, including the Calinski-Harabasz (CH) Index, Sillhouette (S) Index, Davies-Bouldin (DB) Index, Dunn Index (D), and S-Dbw Index on earthquake data in the Bengkulu Province. The calculation result of optimum cluster based on internal cluster validation is CH index, S index, and S-Dbw index yield k = 2, DB Index with k = 6 and Index D with k = 15. Optimum cluster (k = 6) based on DB Index gives good results for clustering earthquake in the Bengkulu Province.
NASA Astrophysics Data System (ADS)
Feuerstein, Sophie; Plevin, Michael J.; Willbold, Dieter; Brutscher, Bernhard
2012-01-01
An experiment, iHADAMAC, is presented that yields information on the amino-acid type of individual residues in a protein by editing the 1H- 15N correlations into seven different 2D spectra, each corresponding to a different class of amino-acid types. Amino-acid type discrimination is realized via a Hadamard encoding scheme based on four different spin manipulations as recently introduced in the context of the sequential HADAMAC experiment. Both sequential and intra-residue HADAMAC experiments yield highly complementary information that greatly facilitate resonance assignment of proteins with high frequency degeneracy, as demonstrated here for a 188-residue intrinsically disordered protein fragment of the hepatitis C virus protein NS5A.
Stem cells and regenerative medicine for diabetes mellitus.
Sumi, Shoichiro; Gu, Yuanjun; Hiura, Akihito; Inoue, Kazutomo
2004-10-01
A profound knowledge of the development and differentiation of pancreatic tissues, especially islets of Langerhans, is necessary for developing regenerative therapy for severe diabetes mellitus. A recent developmental study showed that PTF-1a is expressed in almost all parts of pancreatic tissues, in addition to PDX-1, a well-known transcription factor that is essential for pancreas development. Another study suggested that alpha cells and beta cells individually, but not sequentially, differentiated from neurogenin-3--expressing precursor cells. Under strong induction of pancreas regeneration, it is likely that pancreatic duct cells dedifferentiate to grow, express PDX-1, and re-differentiate toward other cell types including islet cells. Duct epithelium-like cells can be cultivated from crude pancreatic exocrine cells and can be induced to differentiate toward islet-like cell clusters under some culture conditions. These cell clusters made from murine pancreas have been shown to control hyperglycemia when transplanted into diabetic mice. Liver-derived oval cells and their putative precursor H-CFU-C have been shown to differentiate toward pancreatic cells. Furthermore, extrapancreatic cells contained in bone marrow and amniotic membrane are reported to become insulin-producing cells. However, their exact characterization and relationship between these cell types remain to be elucidated. Our recent study has shown that islet-like cell clusters can be differentiated from mouse embryonic stem cells. Transplantation of these clusters could ameliorate hyperglycemia of STZ-induced diabetic mice without forming teratomas. Interestingly, these cells expressed several genes specific to exocrine pancreatic tissue in addition to islet-related genes, suggesting that stable and efficient differentiation toward certain tissues can only be achieved through a process mimicking normal development of the tissue. Perhaps recent developments in these fields may rapidly lead to an established regenerative therapy for diabetes mellitus.
Chang, Young-Soo; Hong, Sung Hwa; Kim, Eun Yeon; Choi, Ji Eun; Chung, Won-Ho; Cho, Yang-Sun; Moon, Il Joon
2018-05-18
Despite recent advancement in the prediction of cochlear implant outcome, the benefit of bilateral procedures compared to bimodal stimulation and how we predict speech perception outcomes of sequential bilateral cochlear implant based on bimodal auditory performance in children remain unclear. This investigation was performed: (1) to determine the benefit of sequential bilateral cochlear implant and (2) to identify the associated factors for the outcome of sequential bilateral cochlear implant. Observational and retrospective study. We retrospectively analyzed 29 patients with sequential cochlear implant following bimodal-fitting condition. Audiological evaluations were performed; the categories of auditory performance scores, speech perception with monosyllable and disyllables words, and the Korean version of Ling. Audiological evaluations were performed before sequential cochlear implant with the bimodal fitting condition (CI1+HA) and one year after the sequential cochlear implant with bilateral cochlear implant condition (CI1+CI2). The good Performance Group (GP) was defined as follows; 90% or higher in monosyllable and bisyllable tests with auditory-only condition or 20% or higher improvement of the scores with CI1+CI2. Age at first implantation, inter-implant interval, categories of auditory performance score, and various comorbidities were analyzed by logistic regression analysis. Compared to the CI1+HA, CI1+CI2 provided significant benefit in categories of auditory performance, speech perception, and Korean version of Ling results. Preoperative categories of auditory performance scores were the only associated factor for being GP (odds ratio=4.38, 95% confidence interval - 95%=1.07-17.93, p=0.04). The children with limited language development in bimodal condition should be considered as the sequential bilateral cochlear implant and preoperative categories of auditory performance score could be used as the predictor in speech perception after sequential cochlear implant. Copyright © 2018 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.
Richard, Jonathan; Pacheco, Beatriz; Gohain, Neelakshi; Veillette, Maxime; Ding, Shilei; Alsahafi, Nirmin; Tolbert, William D; Prévost, Jérémie; Chapleau, Jean-Philippe; Coutu, Mathieu; Jia, Manxue; Brassard, Nathalie; Park, Jongwoo; Courter, Joel R; Melillo, Bruno; Martin, Loïc; Tremblay, Cécile; Hahn, Beatrice H; Kaufmann, Daniel E; Wu, Xueling; Smith, Amos B; Sodroski, Joseph; Pazgier, Marzena; Finzi, Andrés
2016-10-01
Human immunodeficiency virus type 1 (HIV-1) has evolved a sophisticated strategy to conceal conserved epitopes of its envelope glycoproteins (Env) recognized by antibody-dependent cellular cytotoxicity (ADCC)-mediating antibodies. These antibodies, which are present in the sera of most HIV-1-infected individuals, preferentially recognize Env in its CD4-bound conformation. Accordingly, recent studies showed that small CD4-mimetics (CD4mc) able to "push" Env into this conformation sensitize HIV-1-infected cells to ADCC mediated by HIV+ sera. Here we test whether CD4mc also expose epitopes recognized by anti-cluster A monoclonal antibodies such as A32, thought to be responsible for the majority of ADCC activity present in HIV+ sera and linked to decreased HIV-1 transmission in the RV144 trial. We made the surprising observation that CD4mc are unable to enhance recognition of HIV-1-infected cells by this family of antibodies in the absence of antibodies such as 17b, which binds a highly conserved CD4-induced epitope overlapping the co-receptor binding site (CoRBS). Our results indicate that CD4mc initially open the trimeric Env enough to allow the binding of CoRBS antibodies but not anti-cluster A antibodies. CoRBS antibody binding further opens the trimeric Env, allowing anti-cluster A antibody interaction and sensitization of infected cells to ADCC. Therefore, ADCC responses mediated by cluster A antibodies in HIV-positive sera involve a sequential opening of the Env trimer on the surface of HIV-1-infected cells. The understanding of the conformational changes required to expose these vulnerable Env epitopes might be important in the design of new strategies aimed at fighting HIV-1. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nguyen, Duc; Girolami, Gregory S.; Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
Direct visualization of the dynamics of structural glasses and amorphous solids on the sub-nanometer scale provides rich information unavailable from bulk or conventional single molecule techniques. We study the surface of hafnium diboride, a conductive ultrahigh temperature ceramic material that can be grown in amorphous films. Our scanning tunneling movies have a second-to-hour dynamic range and single-point current measurements extend that to the millisecond-to-minute time scale. On the a-HfB{sub 2} glass surface, two-state hopping of 1–2 nm diameter cooperatively rearranging regions or “clusters” occurs from sub-milliseconds to hours. We characterize individual clusters in detail through high-resolution (<0.5 nm) imaging, scanning tunnelingmore » spectroscopy and voltage modulation, ruling out individual atoms, diffusing adsorbates, or pinned charges as the origin of the observed two-state hopping. Smaller clusters are more likely to hop, larger ones are more likely to be immobile. HfB{sub 2} has a very high bulk glass transition temperature T{sub g}, and we observe no three-state hopping or sequential two-state hopping previously seen on lower T{sub g} glass surfaces. The electronic density of states of clusters does not change when they hop up or down, allowing us to calibrate an accurate relative z-axis scale. By directly measuring and histogramming single cluster vertical displacements, we can reconstruct the local free energy landscape of individual clusters, complete with activation barrier height, a reaction coordinate in nanometers, and the shape of the free energy landscape basins between which hopping occurs. The experimental images are consistent with the compact shape of α-relaxors predicted by random first order transition theory, whereas the rapid hopping rate, even taking less confined motion at the surface into account, is consistent with β-relaxations. We make a proposal of how “mixed” features can show up in surface dynamics of glasses.« less
Yano, Naomine; Muramoto, Kazumasa; Shimada, Atsuhiro; Takemura, Shuhei; Baba, Junpei; Fujisawa, Hidenori; Mochizuki, Masao; Shinzawa-Itoh, Kyoko; Yamashita, Eiki; Tsukihara, Tomitake; Yoshikawa, Shinya
2016-01-01
Bovine heart cytochrome c oxidase (CcO) pumps four proton equivalents per catalytic cycle through the H-pathway, a proton-conducting pathway, which includes a hydrogen bond network and a water channel operating in tandem. Protons are transferred by H3O+ through the water channel from the N-side into the hydrogen bond network, where they are pumped to the P-side by electrostatic repulsion between protons and net positive charges created at heme a as a result of electron donation to O2 bound to heme a3. To block backward proton movement, the water channel remains closed after O2 binding until the sequential four-proton pumping process is complete. Thus, the hydrogen bond network must collect four proton equivalents before O2 binding. However, a region with the capacity to accept four proton equivalents was not discernable in the x-ray structures of the hydrogen bond network. The present x-ray structures of oxidized/reduced bovine CcO are improved from 1.8/1.9 to 1.5/1.6 Å resolution, increasing the structural information by 1.7/1.6 times and revealing that a large water cluster, which includes a Mg2+ ion, is linked to the H-pathway. The cluster contains enough proton acceptor groups to retain four proton equivalents. The redox-coupled x-ray structural changes in Glu198, which bridges the Mg2+ and CuA (the initial electron acceptor from cytochrome c) sites, suggest that the CuA-Glu198-Mg2+ system drives redox-coupled transfer of protons pooled in the water cluster to the H-pathway. Thus, these x-ray structures indicate that the Mg2+-containing water cluster is the crucial structural element providing the effective proton pumping in bovine CcO. PMID:27605664
Yano, Naomine; Muramoto, Kazumasa; Shimada, Atsuhiro; Takemura, Shuhei; Baba, Junpei; Fujisawa, Hidenori; Mochizuki, Masao; Shinzawa-Itoh, Kyoko; Yamashita, Eiki; Tsukihara, Tomitake; Yoshikawa, Shinya
2016-11-11
Bovine heart cytochrome c oxidase (CcO) pumps four proton equivalents per catalytic cycle through the H-pathway, a proton-conducting pathway, which includes a hydrogen bond network and a water channel operating in tandem. Protons are transferred by H 3 O + through the water channel from the N-side into the hydrogen bond network, where they are pumped to the P-side by electrostatic repulsion between protons and net positive charges created at heme a as a result of electron donation to O 2 bound to heme a 3 To block backward proton movement, the water channel remains closed after O 2 binding until the sequential four-proton pumping process is complete. Thus, the hydrogen bond network must collect four proton equivalents before O 2 binding. However, a region with the capacity to accept four proton equivalents was not discernable in the x-ray structures of the hydrogen bond network. The present x-ray structures of oxidized/reduced bovine CcO are improved from 1.8/1.9 to 1.5/1.6 Å resolution, increasing the structural information by 1.7/1.6 times and revealing that a large water cluster, which includes a Mg 2+ ion, is linked to the H-pathway. The cluster contains enough proton acceptor groups to retain four proton equivalents. The redox-coupled x-ray structural changes in Glu 198 , which bridges the Mg 2+ and Cu A (the initial electron acceptor from cytochrome c) sites, suggest that the Cu A -Glu 198 -Mg 2+ system drives redox-coupled transfer of protons pooled in the water cluster to the H-pathway. Thus, these x-ray structures indicate that the Mg 2+ -containing water cluster is the crucial structural element providing the effective proton pumping in bovine CcO. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
Hemodynamic analysis of sequential graft from right coronary system to left coronary system.
Wang, Wenxin; Mao, Boyan; Wang, Haoran; Geng, Xueying; Zhao, Xi; Zhang, Huixia; Xie, Jinsheng; Zhao, Zhou; Lian, Bo; Liu, Youjun
2016-12-28
Sequential and single grafting are two surgical procedures of coronary artery bypass grafting. However, it remains unclear if the sequential graft can be used between the right and left coronary artery system. The purpose of this paper is to clarify the possibility of right coronary artery system anastomosis to left coronary system. A patient-specific 3D model was first reconstructed based on coronary computed tomography angiography (CCTA) images. Two different grafts, the normal multi-graft (Model 1) and the novel multi-graft (Model 2), were then implemented on this patient-specific model using virtual surgery techniques. In Model 1, the single graft was anastomosed to right coronary artery (RCA) and the sequential graft was adopted to anastomose left anterior descending (LAD) and left circumflex artery (LCX). While in Model 2, the single graft was anastomosed to LAD and the sequential graft was adopted to anastomose RCA and LCX. A zero-dimensional/three-dimensional (0D/3D) coupling method was used to realize the multi-scale simulation of both the pre-operative and two post-operative models. Flow rates in the coronary artery and grafts were obtained. The hemodynamic parameters were also showed, including wall shear stress (WSS) and oscillatory shear index (OSI). The area of low WSS and OSI in Model 1 was much less than that in Model 2. Model 1 shows optimistic hemodynamic modifications which may enhance the long-term patency of grafts. The anterior segments of sequential graft have better long-term patency than the posterior segments. With rational spatial position of the heart vessels, the last anastomosis of sequential graft should be connected to the main branch.
A Survey on the Taxonomy of Cluster-Based Routing Protocols for Homogeneous Wireless Sensor Networks
Naeimi, Soroush; Ghafghazi, Hamidreza; Chow, Chee-Onn; Ishii, Hiroshi
2012-01-01
The past few years have witnessed increased interest among researchers in cluster-based protocols for homogeneous networks because of their better scalability and higher energy efficiency than other routing protocols. Given the limited capabilities of sensor nodes in terms of energy resources, processing and communication range, the cluster-based protocols should be compatible with these constraints in either the setup state or steady data transmission state. With focus on these constraints, we classify routing protocols according to their objectives and methods towards addressing the shortcomings of clustering process on each stage of cluster head selection, cluster formation, data aggregation and data communication. We summarize the techniques and methods used in these categories, while the weakness and strength of each protocol is pointed out in details. Furthermore, taxonomy of the protocols in each phase is given to provide a deeper understanding of current clustering approaches. Ultimately based on the existing research, a summary of the issues and solutions of the attributes and characteristics of clustering approaches and some open research areas in cluster-based routing protocols that can be further pursued are provided. PMID:22969350
Naeimi, Soroush; Ghafghazi, Hamidreza; Chow, Chee-Onn; Ishii, Hiroshi
2012-01-01
The past few years have witnessed increased interest among researchers in cluster-based protocols for homogeneous networks because of their better scalability and higher energy efficiency than other routing protocols. Given the limited capabilities of sensor nodes in terms of energy resources, processing and communication range, the cluster-based protocols should be compatible with these constraints in either the setup state or steady data transmission state. With focus on these constraints, we classify routing protocols according to their objectives and methods towards addressing the shortcomings of clustering process on each stage of cluster head selection, cluster formation, data aggregation and data communication. We summarize the techniques and methods used in these categories, while the weakness and strength of each protocol is pointed out in details. Furthermore, taxonomy of the protocols in each phase is given to provide a deeper understanding of current clustering approaches. Ultimately based on the existing research, a summary of the issues and solutions of the attributes and characteristics of clustering approaches and some open research areas in cluster-based routing protocols that can be further pursued are provided.
Inference from clustering with application to gene-expression microarrays.
Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M
2002-01-01
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.
Canonical PSO Based K-Means Clustering Approach for Real Datasets.
Dey, Lopamudra; Chakraborty, Sanjay
2014-01-01
"Clustering" the significance and application of this technique is spread over various fields. Clustering is an unsupervised process in data mining, that is why the proper evaluation of the results and measuring the compactness and separability of the clusters are important issues. The procedure of evaluating the results of a clustering algorithm is known as cluster validity measure. Different types of indexes are used to solve different types of problems and indices selection depends on the kind of available data. This paper first proposes Canonical PSO based K-means clustering algorithm and also analyses some important clustering indices (intercluster, intracluster) and then evaluates the effects of those indices on real-time air pollution database, wholesale customer, wine, and vehicle datasets using typical K-means, Canonical PSO based K-means, simple PSO based K-means, DBSCAN, and Hierarchical clustering algorithms. This paper also describes the nature of the clusters and finally compares the performances of these clustering algorithms according to the validity assessment. It also defines which algorithm will be more desirable among all these algorithms to make proper compact clusters on this particular real life datasets. It actually deals with the behaviour of these clustering algorithms with respect to validation indexes and represents their results of evaluation in terms of mathematical and graphical forms.
Pfeiffenberger, Erik; Chaleil, Raphael A.G.; Moal, Iain H.
2017-01-01
ABSTRACT Reliable identification of near‐native poses of docked protein–protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein–protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near‐native from incorrect clusters. The results show that our approach is able to identify clusters containing near‐native protein–protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528–543. © 2016 Wiley Periodicals, Inc. PMID:27935158
Automatic Spike Sorting Using Tuning Information
Ventura, Valérie
2011-01-01
Current spike sorting methods focus on clustering neurons’ characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes’ identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only. PMID:19548802
Automatic spike sorting using tuning information.
Ventura, Valérie
2009-09-01
Current spike sorting methods focus on clustering neurons' characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes' identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only.
NASA Astrophysics Data System (ADS)
Wei, Xiaohui; Li, Weishan; Tian, Hailong; Li, Hongliang; Xu, Haixiao; Xu, Tianfu
2015-07-01
The numerical simulation of multiphase flow and reactive transport in the porous media on complex subsurface problem is a computationally intensive application. To meet the increasingly computational requirements, this paper presents a parallel computing method and architecture. Derived from TOUGHREACT that is a well-established code for simulating subsurface multi-phase flow and reactive transport problems, we developed a high performance computing THC-MP based on massive parallel computer, which extends greatly on the computational capability for the original code. The domain decomposition method was applied to the coupled numerical computing procedure in the THC-MP. We designed the distributed data structure, implemented the data initialization and exchange between the computing nodes and the core solving module using the hybrid parallel iterative and direct solver. Numerical accuracy of the THC-MP was verified through a CO2 injection-induced reactive transport problem by comparing the results obtained from the parallel computing and sequential computing (original code). Execution efficiency and code scalability were examined through field scale carbon sequestration applications on the multicore cluster. The results demonstrate successfully the enhanced performance using the THC-MP on parallel computing facilities.
Xiao, Jianhu; Zhang, Shengping; Luo, Minghao; Zou, Yi; Zhang, Yihua; Lai, Yisheng
2015-07-01
Dysregulation of the B-cell receptor (BCR) signaling pathway plays a vital role in the pathogenesis and development of B-cell malignancies. Bruton's tyrosine kinase (BTK), a key component in the BCR signaling, has been validated as a valuable target for the treatment of B-cell malignancies. In an attempt to find novel and potent BTK inhibitors, both ligand- and structure-based pharmacophore models were generated using Discovery Studio 2.5 and Ligandscout 3.11 with the aim of screening the ChemBridge database. The resulting hits were then subjected to sequential docking experiments using two independent docking programs, CDOCKER and Glide. Molecules displaying high glide scores and H-bond interactions with the key residue Met477 in both of the docking programs were retained. Drug-like criteria including Lipinski's rule of five and ADMET properties filters were employed for further refinement of the retrieved hits. By clustering, eight promising compounds with novel chemical scaffolds were finally selected and the top two ranking compounds were evaluated by molecular dynamics simulation. We believe that these compounds are of great potential in BTK inhibition and will be used for further investigation. Copyright © 2015 Elsevier Inc. All rights reserved.
Bauermeister, José A.; Zimmerman, Marc A.; Johns, Michelle M.; Glowacki, Pietreck; Stoddard, Sarah; Volz, Erik
2012-01-01
Objective: We used a web version of Respondent-Driven Sampling (webRDS) to recruit a sample of young adults (ages 18–24) and examined whether this strategy would result in alcohol and other drug (AOD) prevalence estimates comparable to national estimates (National Survey on Drug Use and Health [NSDUH]). Method: We recruited 22 initial participants (seeds) via Facebook to complete a web survey examining AOD risk correlates. Sequential, incentivized recruitment continued until our desired sample size was achieved. After correcting for webRDS clustering effects, we contrasted our AOD prevalence estimates (past 30 days) to NSDUH estimates by comparing the 95% confidence intervals of prevalence estimates. Results: We found comparable AOD prevalence estimates between our sample and NSDUH for the past 30 days for alcohol, marijuana, cocaine, Ecstasy (3,4-methylenedioxymethamphetamine, or MDMA), and hallucinogens. Cigarette use was lower than NSDUH estimates. Conclusions: WebRDS may be a suitable strategy to recruit young adults online. We discuss the unique strengths and challenges that may be encountered by public health researchers using webRDS methods. PMID:22846248
Optimization of atmospheric transport models on HPC platforms
NASA Astrophysics Data System (ADS)
de la Cruz, Raúl; Folch, Arnau; Farré, Pau; Cabezas, Javier; Navarro, Nacho; Cela, José María
2016-12-01
The performance and scalability of atmospheric transport models on high performance computing environments is often far from optimal for multiple reasons including, for example, sequential input and output, synchronous communications, work unbalance, memory access latency or lack of task overlapping. We investigate how different software optimizations and porting to non general-purpose hardware architectures improve code scalability and execution times considering, as an example, the FALL3D volcanic ash transport model. To this purpose, we implement the FALL3D model equations in the WARIS framework, a software designed from scratch to solve in a parallel and efficient way different geoscience problems on a wide variety of architectures. In addition, we consider further improvements in WARIS such as hybrid MPI-OMP parallelization, spatial blocking, auto-tuning and thread affinity. Considering all these aspects together, the FALL3D execution times for a realistic test case running on general-purpose cluster architectures (Intel Sandy Bridge) decrease by a factor between 7 and 40 depending on the grid resolution. Finally, we port the application to Intel Xeon Phi (MIC) and NVIDIA GPUs (CUDA) accelerator-based architectures and compare performance, cost and power consumption on all the architectures. Implications on time-constrained operational model configurations are discussed.
Fast Edge Detection and Segmentation of Terrestrial Laser Scans Through Normal Variation Analysis
NASA Astrophysics Data System (ADS)
Che, E.; Olsen, M. J.
2017-09-01
Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and intersection edges are separated from the smooth surfaces. Then a modified region growing algorithm groups the points lying on the same smooth surface. The proposed method efficiently exploits the gridded scan pattern utilized during acquisition of TLS data from most sensors and takes advantage of parallel programming to process approximately 1 million points per second. Moreover, the proposed segmentation does not require estimation of the normal at each point, which limits the errors in normal estimation propagating to segmentation. Both an indoor and outdoor scene are used for an experiment to demonstrate and discuss the effectiveness and robustness of the proposed segmentation method.
Novel layered clustering-based approach for generating ensemble of classifiers.
Rahman, Ashfaqur; Verma, Brijesh
2011-05-01
This paper introduces a novel concept for creating an ensemble of classifiers. The concept is based on generating an ensemble of classifiers through clustering of data at multiple layers. The ensemble classifier model generates a set of alternative clustering of a dataset at different layers by randomly initializing the clustering parameters and trains a set of base classifiers on the patterns at different clusters in different layers. A test pattern is classified by first finding the appropriate cluster at each layer and then using the corresponding base classifier. The decisions obtained at different layers are fused into a final verdict using majority voting. As the base classifiers are trained on overlapping patterns at different layers, the proposed approach achieves diversity among the individual classifiers. Identification of difficult-to-classify patterns through clustering as well as achievement of diversity through layering leads to better classification results as evidenced from the experimental results.
Zou, Han; Lu, Xiaoxuan; Jiang, Hao; Xie, Lihua
2015-01-15
Nowadays, developing indoor positioning systems (IPSs) has become an attractive research topic due to the increasing demands on location-based service (LBS) in indoor environments. WiFi technology has been studied and explored to provide indoor positioning service for years in view of the wide deployment and availability of existing WiFi infrastructures in indoor environments. A large body of WiFi-based IPSs adopt fingerprinting approaches for localization. However, these IPSs suffer from two major problems: the intensive costs of manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on an online sequential extreme learning machine (OS-ELM) to address the above problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey. Meanwhile, its online sequential learning ability enables the proposed localization algorithm to adapt in a timely manner to environmental dynamics. Experiments under specific environmental changes, such as variations of occupancy distribution and events of opening or closing of doors, are conducted to evaluate the performance of OS-ELM. The simulation and experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches, due to its fast adaptation to various environmental dynamics.
Yim, Wen-Wai; Chien, Shu; Kusumoto, Yasuyuki; Date, Susumu; Haga, Jason
2010-01-01
Large-scale in-silico screening is a necessary part of drug discovery and Grid computing is one answer to this demand. A disadvantage of using Grid computing is the heterogeneous computational environments characteristic of a Grid. In our study, we have found that for the molecular docking simulation program DOCK, different clusters within a Grid organization can yield inconsistent results. Because DOCK in-silico virtual screening (VS) is currently used to help select chemical compounds to test with in-vitro experiments, such differences have little effect on the validity of using virtual screening before subsequent steps in the drug discovery process. However, it is difficult to predict whether the accumulation of these discrepancies over sequentially repeated VS experiments will significantly alter the results if VS is used as the primary means for identifying potential drugs. Moreover, such discrepancies may be unacceptable for other applications requiring more stringent thresholds. This highlights the need for establishing a more complete solution to provide the best scientific accuracy when executing an application across Grids. One possible solution to platform heterogeneity in DOCK performance explored in our study involved the use of virtual machines as a layer of abstraction. This study investigated the feasibility and practicality of using virtual machine and recent cloud computing technologies in a biological research application. We examined the differences and variations of DOCK VS variables, across a Grid environment composed of different clusters, with and without virtualization. The uniform computer environment provided by virtual machines eliminated inconsistent DOCK VS results caused by heterogeneous clusters, however, the execution time for the DOCK VS increased. In our particular experiments, overhead costs were found to be an average of 41% and 2% in execution time for two different clusters, while the actual magnitudes of the execution time costs were minimal. Despite the increase in overhead, virtual clusters are an ideal solution for Grid heterogeneity. With greater development of virtual cluster technology in Grid environments, the problem of platform heterogeneity may be eliminated through virtualization, allowing greater usage of VS, and will benefit all Grid applications in general.
Francoeur, Richard B
2015-01-01
Background The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors. Materials and methods Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients. Results Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain–fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain–fatigue/weakness–sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes. Conclusion By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial. PMID:25565865
Francoeur, Richard B
2015-01-01
The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors. Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients. Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain-fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain-fatigue/weakness-sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes. By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial.
Segmentation of remotely sensed data using parallel region growing
NASA Technical Reports Server (NTRS)
Tilton, J. C.; Cox, S. C.
1983-01-01
The improved spatial resolution of the new earth resources satellites will increase the need for effective utilization of spatial information in machine processing of remotely sensed data. One promising technique is scene segmentation by region growing. Region growing can use spatial information in two ways: only spatially adjacent regions merge together, and merging criteria can be based on region-wide spatial features. A simple region growing approach is described in which the similarity criterion is based on region mean and variance (a simple spatial feature). An effective way to implement region growing for remote sensing is as an iterative parallel process on a large parallel processor. A straightforward parallel pixel-based implementation of the algorithm is explored and its efficiency is compared with sequential pixel-based, sequential region-based, and parallel region-based implementations. Experimental results from on aircraft scanner data set are presented, as is a discussioon of proposed improvements to the segmentation algorithm.
Zhang, Jia-yu; Wang, Zi-jian; Li, Yun; Liu, Ying; Cai, Wei; Li, Chen; Lu, Jian-qiu; Qiao, Yan-jiang
2016-01-15
The analytical methodologies for evaluation of multi-component system in traditional Chinese medicines (TCMs) have been inadequate or unacceptable. As a result, the unclarity of multi-component hinders the sufficient interpretation of their bioactivities. In this paper, an ultra-high-performance liquid chromatography coupled with linear ion trap-Orbitrap (UPLC-LTQ-Orbitrap)-based strategy focused on the comprehensive identification of TCM sequential constituents was developed. The strategy was characterized by molecular design, multiple ion monitoring (MIM), targeted database hits and mass spectral trees similarity filter (MTSF), and even more isomerism discrimination. It was successfully applied in the HRMS data-acquisition and processing of chlorogenic acids (CGAs) in Flos Lonicerae Japonicae (FLJ), and a total of 115 chromatographic peaks attributed to 18 categories were characterized, allowing a comprehensive revelation of CGAs in FLJ for the first time. This demonstrated that MIM based on molecular design could improve the efficiency to trigger MS/MS fragmentation reactions. Targeted database hits and MTSF searching greatly facilitated the processing of extremely large information data. Besides, the introduction of diagnostic product ions (DPIs) discrimination, ClogP analysis, and molecular simulation, raised the efficiency and accuracy to characterize sequential constituents especially position and geometric isomers. In conclusion, the results expanded our understanding on CGAs in FLJ, and the strategy could be exemplary for future research on the comprehensive identification of sequential constituents in TCMs. Meanwhile, it may propose a novel idea for analyzing sequential constituents, and is promising for quality control and evaluation of TCMs. Copyright © 2015 Elsevier B.V. All rights reserved.
A cluster merging method for time series microarray with production values.
Chira, Camelia; Sedano, Javier; Camara, Monica; Prieto, Carlos; Villar, Jose R; Corchado, Emilio
2014-09-01
A challenging task in time-course microarray data analysis is to cluster genes meaningfully combining the information provided by multiple replicates covering the same key time points. This paper proposes a novel cluster merging method to accomplish this goal obtaining groups with highly correlated genes. The main idea behind the proposed method is to generate a clustering starting from groups created based on individual temporal series (representing different biological replicates measured in the same time points) and merging them by taking into account the frequency by which two genes are assembled together in each clustering. The gene groups at the level of individual time series are generated using several shape-based clustering methods. This study is focused on a real-world time series microarray task with the aim to find co-expressed genes related to the production and growth of a certain bacteria. The shape-based clustering methods used at the level of individual time series rely on identifying similar gene expression patterns over time which, in some models, are further matched to the pattern of production/growth. The proposed cluster merging method is able to produce meaningful gene groups which can be naturally ranked by the level of agreement on the clustering among individual time series. The list of clusters and genes is further sorted based on the information correlation coefficient and new problem-specific relevant measures. Computational experiments and results of the cluster merging method are analyzed from a biological perspective and further compared with the clustering generated based on the mean value of time series and the same shape-based algorithm.